2004 annual averages for national establishment data. Introdudiorl of new metropolitan areas and divisions. In ffi/s issue:

Transcription

1 In ffi/s issue: annual averages for national establishment data Introdudiorl of new metropolitan areas and divisions

2 U.S. DEPARTMENT OF LABOR Elaine L. Chao, Secretary U.S. BUREAU OF LABOR STATISTICS Kathleen R Utgoff, Commissioner Employment & Earnings (ISSN ; USPS ), is published monthly and prepared in the Office of Employment and Unemployment Statistics in collaboration with the Office of Publications. The data are collected by the U.S. Census Bureau (Department of Commerce) and State Employment Security Agencies, in cooperation with the Bureau of Labor Statistics. The State agencies are listed on the inside back cover. Employment & Earnings may be ordered from: New Orders, Superintendent of Documents, P.O. Box , Pittsburgh, PA Phone (202) Subscription price per year $53 domestic and $74,20 foreign. Single copy $27 domestic and $37.80 foreign. Prices are subject to change by the U.S. Government Printing Office. Correspondence concerning subscriptions, including address changes and missing issues, should be sent to the Superintendent of Documents, U.S. Government Printing Office, Washington, DC Phone (202) POSTMASTER: Send address changes to Employment & Earnings, U.S. Government Printing Office, Washington, DC Communications on material in this publication should be addressed to: Editors, Employment & Earnings, Bureau of Labor Statistics, Washington, DC Specific questions concerning the data in this publication, or their availability, should be directed as follows: Household data: Telephone: (202) CPSInfo@bls.gov Internet: http: //www. bis. gov/cps/ National establishment data: Telephone: (202) CESInfo@bls.gov Internet: http :// State and area establishment data: Telephone: (202) Internet: http :// Region, State, and area labor force data: Telephone: (202) LausInfo@bls.gov Internet: Periodicals postage paid at Washington, DC, and at additional mailing addresses. Information in this publication will be made available to sensory impaired individuals upon request. Voice phone (202) ; Federal Relay Service: Material in this publication is in the public domain and, with appropriate credit, may be reproduced without permission. March 2005 Vol. 52 No. 3 Calendar of Features In addition to the monthly data appearing regularly in Employment & Earnings, special features appear in most of the issues as shown below. Household data Revised seasonally adjusted series Annual averages Earnings by detailed occupation Union affiliation Minimum wage data Employee absences Quarterly averages: Seasonally adjusted data, persons of Hispanic or Latino ethnicity, and weekly earnings data Establishment data National annual averages: Industry sectors (preliminary) Industry detail Women employees National data revised to reflect new benchmarks and revised seasonally adjusted series State and area annual averages Area definitions Region, State, and area labor force data Annual averages, Apr., July, Oct. March March May May May Cover Design: Keith Tapscott

3 1 Tables B-l, B-2, B-12, B-13, and B-16 through B-18. Digitized for FRASER Employ men tfv Earnings Editor John R Stinson, Jr. Design and Layout Phyllis L. Lott Editor's Note This issue of Employment and Earnings introduces!h es new tables containing employment, unemployment, hours, and earnings data for metropolitan divisions, which are es ei V illy separately identifiable employment centers within some of the largest metropolitan areas. Table B-15 presents data or mmfarm payroll employment for 32 metropolitan divisions, while table B-20 presents data on average hours and earnings of pr >duction workers on manufacturing payrolls for the same 32 metropolitan divisions. Table C-4 presents civilian labor force and u ie nj loyment data for 34 metropolitan divisions. Existing B-tables in the publication have been renumbered to reflect the introd ic nn of these new tables. Effective with the publication of January 2005 date t >1 iblishment-based estimates for States and metropolitan areas (tables B-7, B-14, and B-19) have been revised to reflect 2 )C $ benchmark levels, updated seasonal adjustment factors, and new metropolitan area definitions. For most States, seasonall quoted data (table B-7) back to 2000 and not seasonally adjusted data (tables B-14 arid B-19) back to April 2003 are subject tc i vision. The metropolitan area data presented in tables B-14, B-15, B-19, and B-20 have been revised back to 1990 to incci p) itc new area definitions based on Office of Management and Budget Bulletin No , dated February 18,. The new r< a definitions are available on the BLS Web site at lau/lausmsa.htm and will appear in the May issue of 11 publication. In addition, regional (table C-l) and State and metropolitan area (tables C-2 and C-3) labor force estimates have been revised to incorporate updated Census 2000 population contra is md the implementation of a redesigned method for producing labor force estimates for census regions and divisions, States and selected substate areas. The historical series for census regions and divisions, States, the District of Columbia, New York City, and the Los Angeles-Long Beach-Glendale metropolitan division have been revised back to 1976, while the historical sen s f)r >ix newly modeled substate areas date back tol983. Also, the metropolitan area labor force estimates presented in al 1 s C-3 and C-4 have been revised back to 1990 to incorporate the new area definitions and new statewide controls. M re information on these changes is available on the BLS Web site at Revised State and area establishment-based estim te md regional, State, and area labor force estimates are available at and e p ctively. Contents Page List of statistical tables ii Contents of the explanatory notes and est mates of error v Employment and unemployment developments, February Summary tables and charts 3 Explanatory notes and estimates of error 184 Index to statistical tables 230 Statistical tables T1.., Seasonally Other Source Historical adjusted seasonally features adjusted Household data Establishment data: Employment: National State Area 96 Division 120 Hours and earnings: National State and area 156 Division 159 Local area labor force data: Region 161 State Area 168 Division 175 Not National establishment data: Annual averages 1 179

4 Monthly Household Data Historical A-l. Employment status of the civilian noninstitutional population 16 years and over, 1969 to date 5 A-2. Employment status of the civilian noninstitutional population 16 years and over by sex, 1992 to date 6 Seasonally Adjusted Data Employment Status A-3. Employment status of the civilian noninstitutional population by sex and age 7 A-4. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic or Latino ethnicity 8 A-5. Employment status of the civilian noninstitutional population 25 years and over by educational attainment 10 A-6. Employed and unemployed full- and part-time workers by sex and age 11 Characteristics of the Employed A-7. Employed persons by class of worker and part-time status 12 A-8. Employed persons by age, sex, and marital status 13 Characteristics of the Unemployed A-9. Unemployed persons by age, sex, and marital status 14 A-10. Unemployment rates by age, sex, and marital status 15 A-ll. Unemployed persons by reason for unemployment 16 A-12. Unemployed persons by duration of unemployment 16 Not Seasonally Adjusted Data Employment Status A-13. Employment status of the civilian noninstitutional population by age, sex, and race 17 A-14. Employment status of the Hispanic or Latino population by age and sex 21 A-15. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic or Latino ethnicity 22 A-l6. Employment status of the civilian noninstitutional population 16 to 24 years of age by school enrollment, educational attainment, sex, race, and Hispanic or Latino ethnicity 23 A-17. Employment status of the civilian noninstitutional population 25 years and over by educational attainment, sex, race, and Hispanic or Latino ethnicity 25 A-18. Employed and unemployed full- and part-time workers by age, sex, race, and Hispanic or Latino ethnicity 26 Characteristics of the Employed A-19. Employed persons by occupation, sex, and age 28 A-20. Employed persons by occupation, race, Hispanic or Latino ethnicity, and sex 29 A-21. Employed persons by industry and occupation 31 A-22. Employed persons in agriculture and related and in nonagricultural industries by age, sex, and class of worker 32 A-23. Employed persons in nonagricultural industries by sex and class of worker 33 A-24. Persons at work in agriculture and related and in nonagricultural industries by hours of work 35 A-25. Persons at work 1 to 34 hours in all and in nonagricultural industries by reason for working less than 35 hours and usual full- or part-time status 35 A-26. Persons at work in nonagricultural industries by class of worker and usual full- or part-time status 36 A-21. Persons at work in nonagricultural industries by age, sex, race, Hispanic or Latino ethnicity, marital status, and usual full- or part-time status 37 A-28. Persons at work by occupation, sex, and usual full- or part-time status 38 Characteristics of the Unemployed A-29. Unemployed persons by marital status, race, Hispanic or Latino ethnicity, age, and sex 39 A-30. Unemployed persons by occupation and sex 40 A-31. Unemployed persons by industry and sex 41 A-32. Unemployed persons by reason for unemployment, sex, and age 43 A-33. Unemployed persons by reason for unemployment, race, and Hispanic or Latino ethnicity 44 A-34. Unemployed persons by reason for unemployment, sex, age, and duration of unemployment 45 A-35. Unemployed total and full-time workers by duration of unemployment 45 A-36. Unemployed persons by age, sex, race, Hispanic or Latino ethnicity, marital status, and duration of unemployment 46 A-37. Unemployed persons by occupation, industry, and duration of unemployment 47 Persons Not in the Labor Force A-38. Persons not in the labor force by desire and availability for work, age, and sex 48 Multiple Jobholders A-39. Multiple jobholders by selected demographic and economic characteristics 49

5 Monthly Establishment Data B-l. Employees on nonfarm payrolls by major indistry sector, 1955 to date 50 B-2. Average hours and earnings of production or nonsupervisory workers on private nonfarm payrolls by major industry sector, 1964 to date 51 B-3. Employees on nonfarm payrolls by major industry sector and selected industry detail 55 B-4. Women employees on nonfarm payrolls by major industry sector and selected industry detail 59 B-5. Production or nonsupervisory workers on private nonfarm payrolls by major industry sector and selected industry detail 60 B-6. Diffusion indexes of employment change 61 B-7. Employees on nonfarm payrolls by State and major industry.. 62 Hours and Earnings National B-8. Average weekly hours of production or nonsupervisory workers on private nonfarm payrolls by major industry sector and selected industry detail. 71 B-9. Indexes of aggregate weekly hours of production or nonsupervisory workers on private nonfarm payrolls by major industry sector and selected industry detail 72 B-10. Hours of wage and salary workers on nonfarm payrolls by major industry.. 73 B-l 1. Average hourly and weekly earnings of production or nonsupervisory workers on private nonfarm payrolls by major industry sector and selected industry detail 74 B-l2. Employees on nonfarm payrolls by detailed industry 75 B-13. Women employees on nonfarm payrolls by major mdustry sector and selected industry detail 95 Hours and B-l4. Employees on nonfarm payrolls in States and selected areas by major industry 96 B-15. Employees on nonfarm payrolls by State, selected metropolitan area, and metropolitan division 120 B-l6. Average hours and earnings of production or payrolls by detailed industry 126 B-17. Average hourly earnings, excluding overtime, of production workers on manufacturing payrolls 154 B-l8. Average hourly and weekly earnings of production or ; nonfarm payrolls by major industry sector and selected industry detail, in i and constant (1982) dollars 155 B-l9. Average hours and earnings of production workers on manufacturing payrolls in :eas 156 B-20. Average hours and earnings of production workers on manufacturing payrolls in States, metropolitan areas, and metropolitan divisions 159 Digitized for FRASER ili

6 Monthly Regional, State, Area, and Division Labor Force Data Seasonally Adjusted Data C-l. Labor force status by census region and division 161 C-2. Labor force status by State 163 Not Seasonally Adjusted Data C-3. Labor force status by State and metropolitan area 168 C-4. Civilian labor force and unemployment by State, selected metropolitan area, and metropolitan division 175 Annual Averages Establishment Data Employment National 1. Employees on nonfarm payrolls by major industry sector and selected industry detail Production or nonsupervisory workers on private nonfarm payrolls by major industry sector and selected industry detail 182 Hours and Earnings National 3. Average hours and earnings of production or nonsupervisory workers on private nonfarn payrolls by major industry sector and selected industry detail 183

7

8 The National Compensation Survey's Wage Public Data Query System has dramatically simplified the process of obtaining wage data. Searching through many printed publications for wage data is a thing of the past. The Wage Query System accesses published occupational wage data as well as modeled estimates. Published estimates are those tabulated directly from the collected data. All published estimates have been reviewed and meet BLS publication standards. Modeled estimates are derived from linear regression techniques and use coefficients to obtain a modeled hourly wage estimate. These are provided in the event published estimates are not available. Wage Public Data Query How the Wage Query System works: Go to and under Create Customized Tables select Wages (NCS) from the menu (this program requires a Java-enabled browser and takes a few moments to load) ] Select how to view the data - occupations by area or areas by occupation ~ ""Z'3 Select an area - view metropolitan areas, census divisions, and the nation Select an occupation - up to 480 different occupations available Select a work level - users can select specific work levels (1-15) and overall averages (no work level) for many occupations OR Select "Get help choosing a work level" to view the 10 leveling factors used in producing work levels. For each factor, select the description that best describes the occupation; the system will then calculate a work level based on your answers. J~ Select "Get Data" for one query; limi.a mm! < e i ec t "Add to Your Selection" for additional queries Information you will receive on the data page includes: area, occupation, level, data source (published or modeled), mean hourly wage, and reference period (year and month). For more information on the Wage Query System please contact: Telephone: (202) ocltinfo@bls.gov

9 Employment and Unemployment Developments, February 2005 Nonfarm payroll employment increased by 262,000 in February and the unemployment rate edged up percent. Job growth occurred in both goodsproducing and service-providing industries. Unemployment In February, both the number of unemployed persons, 8 0 million, and the unemployment rate, 5.4 percent, returned to their December levels after dipping in January. The jobless rate had been either 5.4 or 5.5 percent during each of the last 6 months of. In February, the unemployment rates for the major worker groups adult men (4.9 percent), adult women (4.7 percent), teenagers (17.5 percent), whites (4 6 percent), blacks (10.9 percent), and Hispanics or Latinos (6 4 percent) showed little change. The unemployment rate for Asians was 4.5 percent in February, not seasonally adjusted. (See tables A-3,A-4, and A-13.) The number of long-term unemployed those unemployed for 27 weeks and over remained at 1.6 million in February. This group accounted for 1 in 5 unemployed persons. (See table A-12.) Total employment and the labor force In February, total employment was about unchanged at million, seasonally adjusted. The employment-population ratio the proportion of the population age 16 and over with jobs was little changed over the month at 62.3 percei t. The rate has fluctuated between 62.1 percent and 62.5 percent for the past 2 years. In February, the civilian labor force was essentially unchanged at million, and the participation rate held at 65.8 percent. (See table A-3.) Over the year, the number of persons who held more than one job increased by 432,000 to 7.7 million, not seasonally adjusted. These multiple jobholders represented 5.5 percent of total employment in February, up from 5.3 percent a year earlier. (See table A-39.) Persons not in the labor force There were 1.7 million persons who were marginally attached to the labor force in February, little changed over the year. (Data are not seasonally adjusted.) These individuals wanted and were available to work and had looked for ajob sometime in the prior 12 months. They were not counted as unemployed, however, because they did not actively search for work in the 4 weeks preceding the survey. Among the marginally attached, there were 485,000 discouraged workers in February, also about the same as a year earlier. Discouraged workers were not currently looking for work specifically because they believed no jobs were available for them. The other 1.2 million marginally attached had not searched for work for reasons such as school or family responsibilities. (See table A-38.) Industry payroll employment Total nonfarm payroll employment increased by 262,000 in February to million, seasonally adjusted, following smaller gains in the prior 3 months. Construction, manufacturing, and several service-providing industries added jobs. (See table B-3.) Construction employment rose by 30,000 in February. This followed no change in January, when unusually severe weather conditions in some areas of the country limited construction activity. Since its most recent low point in March 2003, the industry has added 458,000 jobs. Employment growth among residential specialty trade contractors (16,000) and residential builders (5,000) accounted for the bulk of February's gain. In February, manufacturing added 20,000jobs, with motor vehicles and parts accounting for about half of the job gain. The increase in motor vehicles employment (11,000) reflected the return of auto workers from larger-than-usual layoffs in January. While total manufacturing employment edged up over the year, it has shown little net change since mid-. Employment in a number of service-providing industries grew over the month. Professional and business services employment expanded by 81,000 in February. Within this sector, sizable increases occurred in employment services (38,000), services to buildings and dwellings (14,000), and architectural and engineering services (7,000). Within employment services, temporary help services added 30,000 jobs in February and 207,000 over the year. Retail trade employment increased by 30,000 in February, with small gains distributed throughout this industry. Over the year, retail trade has added 135,000 jobs. Wholesale trade employment was essentially flat in February; employment in the industry has been trending upward, however, and has grown by 94,000 since its most recent low in August Within the financial activities sector, employment growth continued in credit intermediation and related activities. The industry added 11,000 jobs in February, with commercial banks accounting for about 5,000 of the gain.

10 Health care employment rose by 23,000 over the month. Since February, this industry has gained 262,000jobs. Over the month, employment increased in ambulatory health care services (12,000) and in hospitals (6,000). In the leisure and hospitality sector, food services and drinking places added 27,000 jobs in February. Over the year, leisure and hospitality employment increased by 268,000, with strong gains in both food services and accommodations. Weekly hours The average workweek for production or nonsupervisory workers on private nonfarm payrolls was unchanged in February, at 33.7 hours, seasonally adjusted. The manufacturing workweek declined by 0.2 hour to 40.5 hours, the same level as in November and December. Manufacturing overtime edged up in February to 4.6 hours. (See table B-8.) The index of aggregate weekly hours of production or nonsupervisory workers on private nonfarm payrolls increased by 0.2 percent in February to (2002=100). The manufacturing index was down by 0.4 percent over the month to (See table B-9.) Hourly and weekly earnings Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls were unchanged over the month at $15.90, seasonally adjusted. This followed a 5-cent increase in January. Average weekly earnings also were unchanged in February at $ Overtheyear, average hourly earnings grew by 2.5 percent and average weekly earnings increased by 2.2 percent. (See table B-11.) Scheduled Release Dates Employment and unemployment data are scheduled for initial release on the following dates: Reference month Release date Reference month Release date March April 1 June July 8 April May 6 July August 5 May June 3 August September 2

11 Summary table A. Major labor force status categories, seasonall «cijusted (Numbers in thousands) Category 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. Labor force status Civilian noninstitutional population 222, , , , , , , , , , , , ,041 Civilian labor force 146, , , , , , , , , , , , ,132 Percent of population Employed 138, , , , , , , , , , , , ,144 Percent of population Unemployed 8,195 8,330 8,143 8,172 8,228 8,184 8,018 8,005 8,066 8,020 8,047 7,737 7,988 Not in labor force 75,828 75,812 75,969 75,950 75,809 75,599 76,001 76,410 76,299 76,109 76,437 76,858 76,909 Unemployment rates All workers Men, 20 years and over Women, 20 years and over Both sexes, 16 to 19 years White Black or African American Hispanic or Latino ethnicity NOTE: Beginning in January 2005, data reflect revised population controls used in the he 'srhold survey. Summary table B. Employment, hours, and earnings of employees on nonfarm payrolls, seasonally adjusted (Numbers in thousands) Industry 2005 ~ i Mar. Apr. May June July Aug. Sept. Oct. Nov. P P Employment Total nonfarm. Goods-producing 1 Construction Manufacturing Service-providing ' Retail trade Transportation and warehousing... Information Financial activities Professional and business services. Education and health services Leisure and hospitality Government 130, , , , , , , , , , , , ,843 21,699 21,773 21,825 21,888 21,890 21,902 21,946 21,947 21,982 21,996 22,022 22,005 22,060 6,841 6,897 6,913 6,949 6,955 6,965 6,985 6,998 7,043 7,060 7,086 7,086 7,116 14,281 14,291 14,323 14,347 14,344 14,341 14,366 14,352 14,344 14,337 14,334 14,314" 14, , , , , , , , , , , , , ,783" ,143 3,136 3,142 3,146 3,151 3,144 3,135 3,127 3,131 3,133 3,127 3,120 3,118 7,997 8,005 8,021 8,037 8,051 8,043 8,058 8,083 8,093 8,107 8,128 8,149 8,161 16,153 16,184 16,305 16,384 16,415 16,453 16,470 16,514 16,614 16,611 16,674 16,698 16,779 16,787 16,833 16,871 16,913 16,936 16,963 17,010 17,019 17,081 17,108 17,142 17,175 17,193 12,367 12,412 12,443 12,474 12,486 12,497 12,508 12,522 12,546 12,571 12,589 12,612 12,635 21,551 21,582 21,607 21,586 21,571 21,586 21,645 21,677 21,700 21,706 21,700 21,722 21,755 Over-the-month change Total nonfarm Goods-producing 1 Construction Manufacturing Sen/ice-providing I... Retail trade Transportation and warehousing... Information Financial activities Professional and business services. Education and health services Leisure and hospitality Government , IS Hours of work 2 Total private Manufacturing Overtime Indexes of aggregate weekly hours (2002=100) 2 Total private. Manufacturing Earnings 2 Average hourly earnings, total private: Current dollars Constants 982) dollars 3. Average weekly earnings, total private $ $ $ $15.62 $ $ $ $ $ $ $ $ $15.90 N.A includes other industries, not shown separately. 2 Data relate to production or nonsupervisory workers. 3 The Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W) is used to deflate this earnings series. N.A. = not available. p = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all seasonally adjusted data from January 2001 forward are subject to revision.

12 Chart 1. Nonfarm payroll employment, seasonally adjusted, Thousands 135,000 Thousands 135, , , , ,500 Chart 2. Unemployment rate, seasonally adjusted, Percent 7.0 Percent NOTE: Beginning in 2003, data reflect an upward adjustment to population controls and other changes to the survey. Beginning in January and January 2005, data incorporate revisions in the population controls. These changes affect comparability with data for prior periods.

13 A-1. Employment status of the civilian noninstitutionai population 16 years and over, 1969 to date (Numbers in thousands) Civilian labor force Year and month Civilian noninstitutionai population Number Percent of population Number Employed Percent of population Number Unemployed Percent of labor force Not in labor force Annual averages ,335 80, , , , ,085 82, , , , ,216 84, , , , ,126 87, , , , ,096 89, , , , ,120 91, , , , ,153 93, , , , ,150 96, , , , ,033 99, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , )9, , , , , :?, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,956 Monthly data, seasonally adjusted 2 : February.. 222, , , , ,828 March 222, , , , ,812 April 222, , , , ,969 May 222, , , , ,950 June 223, , , , ,809 July 223, , , , ,599 August 223, , , , ,001 September 223, , , , ,410 October 224, , , , ,299 November 224, , , , ,109 December , , , , , : January 3 224, , , , ,858 February 225, , , , ,909 1 Not strictly comparable with prior years. For an explanation, see "Historical Comparability" under the Household Data section of the Explanatory Notes and Estimates of Error. 2 The population figures are not adjusted for seasonal variation. 3 Beginning in January 2005, data are not strictly comparable with data for and earlier years because of the revisions in the population controls used in the household survey.

14 A-2. Employment status of the civilian noninstitutional population 16 years and over by sex, 1992 to date (Numbers in thousands) Civilian labor force Sex, year, and month Civilian noninstitutional population Number Percent of population Number Employed Percent of population Annual averages Number Unemployed Percent of labor force Not in labor force MEN ,270 69, , , , ,332 70, , , , ,354 70, , , , ,178 71, , , , ,206 72, , , , ,715 73, , , , ,758 73, , , , ,722 74, , , , ,964 76, , , , ,282 76, , , , ,585 77, , , , ,435 78, , , , ,710 78, , , ,730 Monthly data, seasonally adjusted 2 : February 107,177 78, , , ,787 March 107,281 78, , , ,691 April 107,392 78, , , , ,504 78, , , ,842 June 107,625 78, , , ,697 July 107,746 79, , , ,554 August 107,881 79, , , ,628 September 108,020 79, , , ,979 October 108,153 79, , , ,863 November 108,276 79, , , ,674 December 108,392 79, , , , : January 3 108,489 79, , , ,342 February 108,598 79, , , ,224 Annual averages WOMEN ,535 58, , , , ,506 58, , , , ,460 60, , , , ,406 60, , , , ,385 61, , , , ,418 63, , , , ,462 63, , , , ,031 64, , , , ,613 66, , , , ,811 66, , , , ,985 67, , , , ,733 68, , , , ,647 68, , , ,225 Monthly data, seasonally adjusted 2 : February 115,180 68, , , ,041 March 115,269 68, , , ,121 April 115,365 68, , , ,133 May 115,463 68, , , ,108 June 115,570 68, , , ,112 July 115,676 68, , , ,045 August 115,796 68, , , ,373 September 115,921 68, , , ,431 October 116,039 68, , , ,436 November 116,146 68, , , ,436 December 116,247 68, , , , : January 3 116,348 68, , , ,516 February 116,443 68, , , ,684 1 Not strictly comparable with prior years. For an explanation, see "Historical Comparability" under the Household Data section of the Explanatory Notes and Estimates of Error. 2 The population figures are not adjusted for seasonal variation. 3 Beginning in January 2005, data are not strictly comparable with data for and earlier years because of the revisions in the population controls used in the household survey.

15 A-3. Employment status of the civilian noninstitutional population by sex and age, seasonally adjusted (Numbers in thousands) Employment status, sex, and age 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. TOTAL Civilian noninstitutional population 1 222, , , , , , , , , , , , ,041 Civilian labor force 146, , , , , , , , , , , , ,132 Percent of population Employed 138, , , , , , , , , , , , ,144 Employment-population ratio Unemployed 8,195 8,330 8,143 8,172 8,2213 8,184 8,018 8,005 8,066 8,020 8,047 7,737 7,988 Unemployment rate Not in labor force 75,828 75,812 75,969 75,950 75,809 75,599 76,001 76,410 76,299 76,109 76,437 76,858 76,909 Persons who currently want a job 4,746 4,817 4,720 4,669 4,674 4,688 4,908 4,903 5,338 5,087 5,021 4,982 4,995 Men, 16 years and over Civilian noninstitutional population 1 107, , , , , , , , , , , , ,598 Civilian labor force 78,390 78,590 78,555 78,663 78,928 79,192 79,253 79,041 79,290 79,602 79,412 79,146 79,373 Percent of population , Employed 73,937 74,062 74,104 74,118 74,501 74,811 74,824 74,629 74,852 75,188 74,938 74,934 74,964 Employment-population ratio , Unemployed 4,454 4,527 4,451 4,545 4,427 4,381 4,429 4,413 4,438 4,414 4,474 4,212 4,410 Unemployment rate Not in labor force 28,787 28,691 28,836 28,842 7:8,697 28,554 28,628 28,979 28,863 28,674 28,981 29,342 29,224 Men, 20 years and over Civilian noninstitutional population 1 98,966 99,065 99,170 99,279 99,396 99,512 99,642 99,776 99, , , , ,321 Civilian labor force 74,854 75,035 74,908 75,095 75,361 75,567 75,615 75,462 75,632 75,866 75,754 75,594 75,816 Percent of population Employed 71,014 71,158 71,158 71,226 71,575 71,830 71,847 71,701 71,895 72,134 72,020 72,029 72,131 Employment-population ratio Unemployed 3,840 3,877 3,751 3,869 3,786 3,737 3,768 3,761 3,736 3,733 3,733 3,565 3,685 Unemployment rate Not in labor force 24,112 24,029 24,261 24,184 24,035 23,945 24,026 24,314 24,272 24,151 24,372 24,625 24,505 Women, 16 years and over Civilian noninstitutional population 1 115, , , ,463 1 '15, , , , , , , , ,443 Civilian labor force 68,138 68,148 68,233 68,355 68,458 68,631 68,423 68,490 68,603 68,711 68,791 68,832 68,759 Percent of population Employed 64,397 64,345 64,541 64,728 64,658 64,828 64,834 64,898 64,975 65,104 65,218 65,307 65,180 Employment-population ratio Unemployed 3,741 3,803 3,692 3,627 3,800 3,803 3,589 3,592 3,628 3,606 3,573 3,525 3,579 Unemployment rate Not in labor force 47,041 47,121 47,133 47,108 47,112 47,045 47,373 47,431 47,436 47,436 47,456 47,516 47,684 Women, 20 years and over Civilian noninstitutional population 1 107, , , , , , , , , , , , ,403 Civilian labor force 64,636 64,723 64,776 64,803 64,989 65,085 64,909 65,008 65,126 65,244 65,260 65,318 65,270 Percent of population Employed 61,456 61,424 61,591 61,723 61,731 61,902 61,877 61,939 62,024 62,145 62,208 62,295 62,202 Employment-population ratio Unemployed 3,179 3,299 3,185 3,080 3,259 3,183 3,032 3,069 3,102 3,099 3,051 3,023 3,068 Unemployment rate Not in labor force 42,580 42,576 42,613 42,680 42,597 42,603 42,892 42,912 42,906 42,885 42,961 42,998 43,133 Both sexes, 16 to 19 years Civilian noninstitutional population 1 16,175 16,186 16,198 16,205 16,214 16,222 16,234 16,246 16,257 16,275 16,293 16,302 16,317 Civilian labor force 7,039 6,979 7,104 7,120 7,036 7,172 7,152 7,062 7,135 7,202 7,189 7,066 7,046 Percent of population Employed 5,864 5,825 5,897 5,896 5,853 5,907 5,934 5,887 5,908 6,014 5,927 5,917 5,811 Employment-population ratio , Unemployed 1,175 1,154 1,207 1,223 1,184 1,265 1,217 1,175 1,227 1,188 1,262 1,150 1,235 Unemployment rate , Not in labor force 9,136 9,207 9,094 9,086 9,178 9,051 9,082 9,184 9,122 9,074 9,104 9,235 9,271 1 The population figures are not adjusted for seasonal variation. NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey.

16 A-4. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic or Latino ethnicity, seasonally adjusted (Numbers in thousands) Employment status, race, 2005 sex, age, and Hispanic or Latino ethnicity Mar. Apr. May June July Aug. Sept. Oct. Nov. WHITE Civilian noninstitutional population , , , , , , , , , , , , ,767 Civilian labor force 120, , , , , , , , , , , , ,621 Percent of population Employed 114, , , , , , , , , , , , ,022 Employment-population ratio Unemployed 5,975 6,098 5,934 5,991 6,013 5,773 5,752 5,677 5,655 5,640 5,600 5,395 5,598 Unemployment rate Not in labor force 61,411 61,522 61,539 61,387 61,319 61,293 61,568 62,027 61,915 61,735 61,973 62,088 62,146 Mien, 20 years and over Civilian labor force 62,633 62,691 62,688 62,771 62,965 63,153 63,115 62,859 63,092 63,225 63,199 63,259 63,390 Percent of population Employed 59,769 59,767 59,868 59,844 60,135 60,458 60,368 60,149 60,415 60,565 60,570 60,712 60,776 Employment-population ratio Unemployed 2,865 2,924 2,819 2,926 2,831 2,695 2,747 2,710 2,678 2,660 2,629 2,547 2,614 Unemployment rate Women, 20 years and over Civilian labor force 52,009 52,059 52,044 52,222 52,386 52,273 52,214 52,243 52,270 52,443 52,385 52,414 52,311 Percent of population Employed 49,810 49,751 49,865 50,096 50,070 50,082 50,126 50,141 50,186 50,318 50,344 50,392 50,246 Employment-population ratio Unemployed 2,199 2,307 2,178 2,125 2,316 2,192 2,088 2,102 2,084 2,125 2,040 2,022 2,066 Unemployment rate Both sexes, 16 to 19 years Civilian labor force 5,948 5,849 5,981 6,005 5,861 5,956 5,949 5,893 5,911 5,938 5,926 5,879 5,919 Percent of population Employed 5,036 4,982 5,045 5,065 4,994 5,070 5,032 5,028 5,017 5,083 4,995 5,054 5,001 Employment-population ratio Unemployed Unemployment rate BLACK OR AFRICAN AMERICAN Civilian noninstitutional population ,900 25,932 25,967 26,002 26,040 26,078 26,120 26,163 26,204 26,239 26,273 26,306 26,342 Civilian labor force 16,427 16,603 16,505 16,480 16,521 16,775 16,721 16,711 16,820 16,728 16,713 16,721 16,708 Percent of population Employed 14,829 14,917 14,893 14,837 14,825 14,937 14,972 14,981 15,012 14,913 14,907 14,946 14,890 Employment-population ratio Unemployed 1,598 1,685 1,612 1,642 1,696 1,838 1,749 1,730 1,808 1,814 1,806 1,775 1,818 Unemployment rate Not in labor force 9,473 9,330 9,462 9,523 9,520 9,303 9,399 9,452 9,384 9,512 9,559 9,585 9,634 Men, 20 years and over Civilian labor force 7,331 7,366 7,315 7,367 7,402 7,391 7,439 7,470 7,490 7,485 7,473 7,380 7,438 Percent of population Employed 6,647 6,689 6,633 6,671 6,701 6,629 6,665 6,707 6,722 6,697 6,677 6,612 6,630 Employment-population ratio Unemployed Unemployment rate Women, 20 years and over Civilian labor force 8,419 8,500 8,507 8,367 8,372 8,593 8,483 8,504 8,513 8,438 8,477 8,532 8,527 Percent of population Employed 7,675 7,713 7,772 7,662 7,622 7,811 7,743 7,747 7,756 7,675 7,702 7,770 7,751 Employment-population ratio Unemployed Unemployment rate

17 A-4. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic or Latino ethnicity, seasonally adjusted Continued (Numbers in thousands) Employment status, race, 2005 sex, age, ana Hispanic or Latino ethnicity Mar. Apr. May June July Aug. Sept. Oct. Nov. BLACK OR AFRICAN AMERICAN-Continued Both sexes, 16 to 19 years Civilian labor force Percent of population Employed Employment-population ratio Unemployed Unemployment rate HISPANIC OR LATINO ETHNICITY Civilian noninstitutional population ,705 27,791 27,879 27,968 28,059 28,150 28,243 28,338 28,431 28,520 28,608 28,642 28,729 Civilian labor force 18,702 19,036 19,081 19,297 19,302 19,432 19,463 19,444 19,524 19,552 19,544 19,379 19,458 Percent of population Employed 17,315 17,633 17,724 17,959 18,013 18,102 18,128 18,079 18,213 18,238 18,252 18,198 18,211 Employment-population ratio , Unemployed 1,387 1,403 1,358 1,338 1,289 1,330 1,335 1,366 1,311 1,313 1,292 1,181 1,248 Unemployment rate Not in labor force 9,003 8,755 8,797 8,671 8,756 8,718 8,780 8,894 8,907 8,968 9,064 9,263 9,270 1 The population figures are not adjusted for seasonal variation. NOTE: Estimates for the above race groups (white and black or African American) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey.

18 A-5. Employment status of the civilian noninstitutional population 25 years and over by educational attainment, seasonally adjusted (Numbers in thousands) Educational attainment 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. Less than a high school diploma Civilian labor force 12,474 12,356 12,025 12,275 12,399 12,449 12,554 12,742 12,502 12,722 12,814 12,575 12,581 Participation rate Employed 11,406 11,273 10,983 11,207 11,326 11,417 11,531 11,608 11,471 11,703 11,746 11,637 11,595 Employment-population ratio Unemployed 1,068 1,084 1,042 1,068 1,074 1,032 1,023 1,133 1,031 1,019 1, Unemployment rate High school graduates, no college 1 Civilian labor force 37,930 37,707 37,721 37,907 38,046 38,246 38,002 37,700 37,712 37,630 37,695 37,729 38,077 Participation rate Employed 36,025 35,727 35,754 36,007 36,106 36,318 36,129 35,894 35,874 35,788 35,846 35,943 36,223 Employment-population ratio Unemployed 1,906 1,980 1,967 1,900 1,940 1,928 1,873 1,806 1,838 1,842 1,849 1,786 1,854 Unemployment rate Some college or associate degree Civilian labor force 34,183 34,475 34,519 34,489 34,501 34,597 34,499 34,431 34,548 34,549 34,483 34,524 34,842 Participation rate Employed 32,704 32,861 33,100 33,109 33,064 33,141 33,096 33,037 33,112 33,051 32,995 33,117 33,387 Employment-population ratio Unemployed. 1,479 1,613 1,419 1,380 1,436 1,455 1,404 1,394 1,435 1,498 1,487 1,407 1,455 Unemployment rate Bachelor's degree and higher 2 Civilian labor force 39,888 40,309 40,144 40,084 40,130 40,145 40,219 40,471 40,772 41,131 41,026 40,907 40,534 Participation rate Employed 38,722 39,147 38,982 38,924 39,048 39,062 39,152 39,438 39,744 40,090 40,009 39,925 39,563 Employment-population ratio Unemployed 1,166 1,162 1,162 1,160 1,083 1,083 1,068 1,033 1,027 1,041 1, Unemployment rate Includes persons with a high school diploma or equivalent. 2 Includes persons with a bachelor's, master's, professional, and doctoral degrees. NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey.

19 A-6. Employed and unemployed full- and part-time workers by sex and age, seasonally adjusted (Numbers in thousands) Full- and part-time status, sex, and age 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. EMPLOYED Full-time workers 113, , , ,991 r v Oo 114, , , , , , , ,370 Men, 16 years and over 66,050 66,098 66,067 66, ,323 66,462 66,629 66,537 66,720 67,095 66,974 66,927 66,959 Men, 20 years and over 65,042 65,073 65,030 65,072 e 65,371 65,492 65,409 65,578 66,021 65,941 65,920 65,987 Women, 16 years and over 47,920 47,857 48,073 47,880 < nm 47,862 48,149 48,420 48,245 48,291 48,559 48,846 48,388 Women, 20 years and over 47,189 47,162 47,436 47,189 < /, 5 47,263 47,396 47,618 47,556 47,578 47,843 48,026 47,621 Both sexes, 16 to 19 years 1,754 1,722 1,681 1,729,,,11, 1,730 1,886 1,804 1,820 1,816 1,801 1,912 1,761 Part-time workers 24,161 24,361 24,480 24,827 <14,911 25,464 25,047 24,729 24,931 24,940 24,728 24,220 24,626 Men, 16 years and over 7,854 7,927 8,019 7,866 3,221 8,438 8,289 8,111 8,176 8,115 8,014 7,894 7,995 Men, 20 years and over 5,977 6,066 6,112 6,133 8,294 6,439 6,375 6,267 6,329 6,219 6,139 6,103 6,162 Women, 16 years and over 16,351 16,445 16,467 16,917 ' 3,643 17,069 16,721 16,623 16,765 16,813 16,691 16,294 16,690 Women, 20 years and over 14,098 14,220 14,192 14,539 ' 4,444 14,744 14,514 14,383 14,499 14,601 14,487 14,111 14,432 Both sexes, 16 to 19 years 4,085 4,075 4,176 4,155 4,172 4,281 4,158 4,080 4,103 4,120 4,102 4,006 4,033 UNEMPLOYED Looking for full-time work 6,841 6,961 6,762 6,882 6,764 6,791 6,639 6,733 6,611 6,570 6,637 6,400 6,569 Men, 16 years and over 3,925 3,926 3,871 3,919 3,737 3,786 3,840 3,853 3,818 3,784 3,798 3,647 3,743 Men, 20 years and over 3,590 3,583 3,487 3,617 3,473 3,480 3,472 3,520 3,459 3,445 3,444 3,324 3,378 Women, 16 years and over 2,955 3,050 2,931 2,922 2,961 2,992 2,821 2,881 2,802 2,803 2,837 2,743 2,821 Women, 20 years and over 2,705 2,834 2,688 2,671 2,747 2,684 2,547 2,622 2,557 2,552 2,598 2,512 2,552 Both sexes, 16 to 19 years Looking for part-time work 1,317 1,379 1,370 1,361 1,439 1,392 1,377 1,295 1,461 1,432 1,417 1,343 1,419 Men, 16 years and over Men, 20 years and over Women, 16 years and over Women, 20 years and over Both sexes, 16 to 19 years UNEMPLOYMENT RATES Full-time workers Men, 16 years and over Men, 20 years and over Women, 16 years and over Women, 20 years and over Both sexes, 16 to 19 years Part-time workers Men, 16 years and over Men, 20 years and over Women, 16 years and over Women, 20 years and over Both sexes, 16 to 19 years NOTE: Detail for the data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Beginning in January 2005, data reflect revised population controls used in the household survey,

20 A-7. Employed persons by class of worker and part-time status, seasonally adjusted (In thousands) Category 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. CLASS OF WORKER Agriculture and related industries 2,201 2,180 2,261 2,301 2,291 2,273 2,305 2,221 2,155 2,212 2,179 2,120 2,145 Wage and salary workers 1,256 1,268 1,284 1,293 1,267 1,241 1,265 1,213 1,194 1,204 1,185 1,181 1,208 Self-employed workers ,021 1,014 1, Nonagricultural industries 136, , , , , , , , , , , , ,005 Wage and salary workers 126, , , , , , , , , , , , ,184 Private industries 106, , , , , , , , , , , , ,978 Industries except private households 106, , , , , , , , , , , , ,162 Government 19,477 19,941 19,920 19,814 20,003 19,841 20,117 20,166 20,213 20,309 20,270 20,296 20,106 Self-employed workers 9,482 9,243 9,251 9,416 9,379 9,529 9,630 9,481 9,702 9,505 9,473 9,514 9,709 PERSONS AT WORK PART TIME 1 All industries: Part time for economic reasons 4,445 4,708 4,557 4,634 4,504 4,488 4,509 4,476 4,762 4,533 4,474 4,395 4,269 Slack work or business conditions 2,841 2,984 2,813 2,845 2,801 2,642 2,816 2,805 3,052 2,761 2,735 2,768 2,629 Could only find part-time work 1,363 1,430 1,431 1,449 1,400 1,472 1,403 1,312 1,385 1,420 1,440 1,329 1,296 Part time for noneconomic reasons 19,020 19,091 19,130 19,570 19,564 19,737 19,657 19,410 19,704 19,499 19,502 19,089 19,555 Nonagricultural industries: Part time for economic reasons 4,335 4,595 4,451 4,567 4,423 4,390 4,408 4,400 4,656 4,404 4,382 4,303 4,153 Slack work or business conditions 2,768 2,899 2,747 2,801 2,753 2,580 2,722 2,750 2,971 2,685 2,682 2,702 2,572 Could only find part-time work 1,350 1,415 1,425 1,458 1,382 1,484 1,388 1,320 1,363 1,396 1,397 1,309 1,268 Part time for noneconomic reasons 18,775 18,791 18,844 19,145 19,123 19,327 19,204 19,061 19,288 19,141 19,176 18,765 19,254 1 Persons at work excludes employed persons who were absent from their jobs during the entire reference week for reasons such as vacation, illness, or industrial dispute. Part time for noneconomic reasons excludes persons who usually work full time but worked only 1 to 34 hours during the reference week for reasons such as holidays, illness, and bad weather. NOTE: Detail for the data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Beginning in January 2005, data reflect revised population controls used in the household survey.

21 A-8. Employed persons by age, sex, and marital status, seasonal! / adjusted (In thousands) Age, sex, ana marital status 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. AGE AND SEX Total, 16 years and over 138, , , ,846 1:9, li\ 139, , , , , , , , to 19 years 5,864 5,825 5,897 5,896 j 5,907 5,934 5,887 5,908 6,014 5,927 5,917 5, to 17 years 2,282 2,189 2,230 2,141 2,088 2,149 2,121 2,149 2,189 2,240 2,261 2,267 2, to 19 years 3,600 3,629 3,660 3, ,758 3,875 3,730 3,711 3,739 3,691 3,634 3, years and over 132, , , ,949 i:3,:»06 133, , , , , , , , to 24 years 13,594 13,613 13,771 13, ,804 13,777 13,641 13,842 13,818 13,851 13,702 13, years and over 118, , , , ,!. i8 119, , , , , , , , to 54 years 97,016 96,988 97,235 97,399 <"7^8 97,694 97,610 97,667 97,700 97,885 97,701 98,049 97, to 34 years 30,189 30,300 30,351 30,420 ' 0,!i?6 30,496 30,496 30,508 30,432 30,495 30,504 30,683 30, to 44 years 34,505 34,470 34,475 34,623. 4,: 44 34,650 34,547 34,556 34,599 34,739 34,632 34,589 34, to 54 years 32,321 32,218 32,408 32,355 >/l>i 32,548 32,568 32,604 32,669 32,651 32,566 32,776 32, years and over 21,854 21,948 21,788 21,867 22,196 22,384 22,326 22,366 22,571 22,719 22,620 22,772 Men, 16 years and over 73,937 74,062 74,104 74,118 \ C 1 74,811 74,824 74,629 74,852 75,188 74,938 74,934 74, to 19 years 2,923 2,904 2,947 2, il 5 2,981 2,977 2,927 2,957 3,055 2,917 2,905 2, to 17 years 1,068 1,008 1, %3 1,002 1,018 1,040 1,072 1,117 1,049 1,068 1, to 19 years 1,865 1,887 1,901 1,910 1, )60 1,990 2,016 1,874 1,879 1,914 1,862 1,825 1, years and over 71,014 71,158 71,158 71,226 1, h 'i 71,830 71,847 71,701 71,895 72,134 72,020 72,029 72, to 24 years 7,159 7,200 7,230 7,169 7, I 7,355 7,284 7,151 7,307 7,295 7,354 7,181 7, years and over 63,881 63,932 63,922 64,010 4, M3 64,466 64,591 64,497 64,592 64,823 64,704 64,900 65, to 54 years 52,176 52,167 52,342 52,407 2, xi 1 52,610 52,564 52,553 52,582 52,695 52,563 52,840 52, to 34 years 16,612 16,719 16,719 16,784 I6,:K>6 16,887 16,946 16,917 16,900 16,851 16,818 16,902 16, to 44 years 18,681 18,652 18,671 18,730 8,M>3 18,736 18,641 18,639 18,649 18,799 18,719 18,769 18, to 54 years 16,883 16,795 16,951 16,893 6,406 16,986 16,977 16,998 17,033 17,045 17,026 17,169 17, years and over 11,705 11,765 11,581 11,603 1, '92 11,857 12,026 11,943 12,010 12,128 12,141 12,061 12,175 Women, 16 years and over 64,397 64,345 64,541 64,728 4,>!>3 64,828 64,834 64,898 64,975 65,104 65,218 65,307 65, to 19 years 2,941 2,921 2,950 3,005 2, )::r 2,926 2,957 2,959 2,951 2,959 3,010 3,012 2, to 17 years 1,214 1,181 1,197 1,168 i,i:>o 1,147 1,103 1,109 1,118 1,123 1,212 1,199 1, to 19 years 1,734 1,743 1,759 1,823 1,,( )9 1,768 1,859 1,856 1,831 1,826 1,830 1,809 1, years and over 61,456 61,424 61,591 61,723 1, f '$1 61,902 61,877 61,939 62,024 62,145 62,208 62,295 62, to 24 years 6,435 6,413 6,541 6,487 6,459 6,450 6,493 6,490 6,535 6,523 6,497 6,521 6, years and over 54,989 55,004 55,100 55,255 5, I "J 55,424 55,404 55,497 55,474 55,633 55,716 55,769 55, to 54 years 44,840 44,822 44,893 44,992 5 i)08 45,084 45,046 45,114 45,118 45,190 45,138 45,209 45, to 34 years 13,577 13,581 13,632 13,636 3 r<)0 13,609 13,550 13,591 13,532 13,644 13,686 13,782 13, to 44 years 15,825 15,818 15,804 15,894 i 5 B76 15,913 15,906 15,917 15,950 15,940 15,912 15,820 15, to 54 years 15,438 15,423 15,457 15,462 5 \?2 15,562 15,591 15,606 15,636 15,606 15,540 15,608 15, years and over 10,149 10,183 10,208 10,264 0' ,340 10,358 10,383 10,356 10,443 10,578 10,560 10,597 MARITAL STATUS Married men, spouse present 45,044 45,000 44,759 44,763 44,958 44,948 45,099 45,093 45,127 45,462 45,315 45,171 45,351 Married women, spouse present 34,481 34,283 34,375 34,536 34,487 34,607 34,494 34,704 34,808 34,961 34,878 34,739 34,601 NOTE: Detail for the data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Beginning in January 2005, data reflect revised population controls used in the household survey.

22 A-9. Unemployed persons by age, sex, and marital status, seasonally adjusted (In thousands) 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. AGE AND SEX Total, 16 years and over 8,195 8,330 8,143 8,172 8,228 8,184 8,018 8,005 8,066 8,020 8,047 7,737 7, to 19 years 1,175 1,154 1,207 1,223 1,184 1,265 1,217 1,175 1,227 1,188 1,262 1,150 1, to 17 years to 19 years years and over 7,020 7,176 6,936 6,949 7,044 6,920 6,801 6,830 6,838 6,832 6,785 6,588 6, to 24 years 1,430 1,440 1,397 1,464 1,478 1,404 1,369 1,433 1,505 1,398 1,360 1,440 1, years and over 5,602 5,741 5,556 5,484 5,571 5,521 5,427 5,395 5,349 5,409 5,391 5,141 5, to 54 years 4,723 4,934 4,661 4,620 4,638 4,685 4,545 4,506 4,456 4,545 4,597 4,326 4, to 34 years 1,793 1,885 1,753 1,798 1,674 1,842 1,732 1,677 1,761 1,811 1,813 1,629 1, to 44 years 1,633 1,709 1,592 1,525 1,647 1,574 1,585 1,607 1,469 1,457 1,456 1,479 1, to 54 years 1,297 1,340 1,316 1,297 1,317 1,270 1,228 1,222 1,226 1,276 1,328 1,217 1, years and over Men, 16 years and over 4,454 4,527 4,451 4,545 4,427 4,381 4,429 4,413 4,438 4,414 4,474 4,212 4, to 19 years to 17 years to 19 years years and over 3,840 3,877 3,751 3,869 3,786 3,737 3,768 3,761 3,736 3,733 3,733 3,565 3, to 24 years years and over 3,040 3,092 2,942 3,066 2,954 2,948 2,953 2,923 2,909 2,919 2,969 2,734 2, to 54 years 2,585 2,620 2,470 2,568 2,424 2,477 2,458 2,443 2,401 2,449 2,531 2,247 2, to 34 years 1,049 1, , , to 44 years to 54 years years and over Women, 16 years and over 3,741 3,803 3,692 3,627 3,800 3,803 3,589 3,592 3,628 3,606 3,573 3,525 3, to 19 years to 17 years to 19 years years and over 3,179 3,299 3,185 3,080 3,259 3,183 3,032 3,069 3,102 3,099 3,051 3,023 3, to 24 years years and over 2,562 2,649 2,614 2,418 2,616 2,573 2,473 2,472 2,441 2,490 2,422 2,407 2, to 54 years 2,138 2,314 2,191 2,052 2,213 2,209 2,087 2,064 2,055 2,096 2,066 2,078 2, to 34 years to 44 years to 54 years MARITAL STATUS Married men, spouse present 1,562 1,494 1,448 1,443 1,465 1,483 1,423 1,386 1,393 1,432 1,434 1,430 1,402 Married women, spouse present 1,287 1,304 1,310 1,178 1,334 1,249 1,235 1,120 1,121 1,236 1,227 1,157 1,140 NOTE: Detail for the data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Beginning in January 2005, data reflect revised population controls used in the household survey.

23 A-10. Unemployment rates by age, sex, and marital status, seasonally adjusted (Percent) age, sex, ana marital status 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. AGE AND SEX Total, 16 years and over to 19 years to 17 years to 19 years years and over to 24 years years and over to 54 years to 34 years to 44 years to 54 years years and over Men, 16 years and over to 19 years , to 17 years to 19 years years and over to 24 years years and over to 54 years to 34 years to 44 years to 54 years years and over Women, 16 years and over to 19 years to 17 years to 19 years years and over to 24 years years and over to 54 years to 34 years to 44 years to 54 years MARITAL STATUS Married men, spouse present Married women, spouse present NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey.

24 A-11. Unemployed persons by reason for unemployment, seasonally adjusted (Numbers in thousands) Reason 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. NUMBER OF UNEMPLOYED Job losers and persons who completed temporary jobs.. 4,284 4,475 4,322 4,190 4,117 4,228 3,978 4,014 4,074 4,066 4,108 4,048 3,980 On temporary layoff 1,060 1, ,009 1, Not on temporary layoff 3,224 3,440 3,329 3,270 3,108 3,160 3,007 3,094 3,127 3,124 3,144 3,082 3,015 Job leavers Reentrants 2,421 2,419 2,310 2,437 2,426 2,333 2,440 2,417 2,411 2,388 2,361 2,324 2,405 New entrants PERCENT DISTRIBUTION Total unemployed Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Job leavers Reentrants New entrants UNEMPLOYED AS A PERCENT OF THE CIVILIAN LABOR FORCE Job losers and persons who completed temporary jobs Job leavers Reentrants New entrants NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. A-12. Unemployed persons by duration of unemployment, seasonally adjusted (Numbers in thousands) Duration 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. NUMBER OF UNEMPLOYED Less than 5 weeks 2,449 2,623 2,772 2,731 2,715 2,803 2,605 2,796 2,753 2,611 2,865 2,599 2,755 5 to 14 weeks 2,418 2,417 2,370 2,376 2,397 2,458 2,521 2,251 2,290 2,361 2,264 2,343 2, weeks and over 3,252 3,321 2,956 3,059 3,051 2,885 2,924 2,971 3,032 3,012 2,961 2,824 2, to 26 weeks 1,382 1,330 1,165 1,277 1,294 1,198 1,243 1,227 1,261 1,294 1,325 1,201 1, weeks and over 1,870 1,991 1,791 1,783 1,757 1,686 1,681 1,744 1,771 1,718 1,636 1,623 1,633 Average (mean) duration, in weeks Median duration, in weeks PERCENT DISTRIBUTION Total unemployed Less than 5 weeks to 14 weeks weeks and over to 26 weeks weeks and over NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey.

25 A-13. Employment status of the civilian noninstitutional popul it jn by age, sex, and race (Numbers in thousands) February 2005 Civilian labor force Age, sex, and race Civilian noninstitutional population Total Percent of population Total Employed Percent of population Number Unemployed Percent of labor force Not in labor force 16 years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over.. 65 to 69 years 70 to 74 years 75 years and over TOTAL 225,041 16,317 8,866 7,451 20, ,813 38,977 19,239 19,738 43,072 20,468 22,604 41,764 22,100 19,664 29,717 16,957 12,760 34,933 9,947 8,326 16, ,649 6,598 2,636 3,962 14, ,437 32,170 15,734 16,436 36, ,990 34,198 18,545 15,653 18, ,556 5,117 2,711 1,400 1, ,100 5,395 2,098 3,297 13,275 97,598 30,359 14,807 15,553 34,404 16,221 18,183 32,835 17,764 15,070 17,940 11,626 6,314 4,891 2,591 1, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , years and over 16to 19years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over.. 65 to 69 years 70 to 74 years 75 years and over Men 108,598 78,950 8,277 3,309 4,536 1,277 3,740 2,033 10,166 7,937 61,013 55,058 19,390 17,714 9,615 8,686 9,776 9,028 21,200 19,497 10,099 9,330 11,101 10,168 20,423 17,846 10,838 9,666 9,585 8,181 14,284 9,848 8,189 6,330 6,095 3,518 14,858 2,798 4,626 1,440 3, , ,990 2, ,628 6,957 52,346 16,681 8,154 8,528 18,565 8,839 9,726 17,100 9,230 7,870 9,452 6,074 3,378 2,658 1, , , , , , , , , , , , , , , , , , , , , , years and over 16to 19years to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over to 69 years 70 to 74 years 75 years and over Women 116,443 68,699 8,040 3,289 4,330 1,359 3,711 1,930 10,094 6,923 62,801 47,380 19,587 14,456 9,625 7,048 9,962 7,408 21,872 16,572 10,369 7,750 11,503 8,823 21,342 16,352 11,262 8,879 10,080 7,472 15,433 8,790 8,768 5,752 6,666 3,038 20,074 2,319 5,321 1,270 4, , ,109 2,818 1,149 1,669 6,318 45,252 13,678 6,653 7,025 15,838 7,382 8,456 15,735 8,535 7,200 8,489 5,553 2,936 2,234 1, , , , , , , , , , , , , , , I 4, , , , , i 3, , , , ,721

26 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A-13. Employment status of the civilian noninstitutional population by age, sex, and race-continued (Numbers in thousands) February 2005 Civilian labor force Age, sex, and race Civilian noninstitutional population Total Percent of population Total Employed Percent of population Number Unemployed Percent of labor force Not labor force 16 years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over.. 65 to 69 years 70 to 74 years 75 years and over WHITE 183, ,293 12,646 5,559 6,852 2,240 5,794 3,319 15,862 11,905 99,614 83,278 30,558 25,446 15,075 12,461 15,483 12,984 34,651 29,237 16,332 13,685 18,319 15,552 34,405 28,596 18,111 15,409 16,294 13,187 25,186 16,002 14,278 10,286 10,908 5,716 30,459 4,548 8,458 2,392 7,236 1,244 14, ,188 4,624 1,827 2,797 10,856 79,887 24,248 11,887 12,361 28,053 13,077 14,976 27,585 14,818 12,767 15,465 9,944 5,521 4,357 2,298 1, , , , , , , , , , , , , , , , , , , , , , , , , , , , , years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over to 69 years 70 to 74 years 75 years and over Men 89,654 6,450 3,483 2,967 8,049 49,849 15,481 7,670 7,811 17,325 8,196 9,129 17,043 9,000 8,043 12,241 6,994 5,247 13,065 3,971 3,272 5,822 65,957 2,766 1,075 1,691 6,462 45,641 14,325 7,016 7,310 16,143 7,622 8,521 15,172 8,149 7,024 8,581 5,469 3,113 2,507 1, ,311 2, ,379 5,794 43,662 13,597 6,662 6,936 15,456 7,283 8,173 14,609 7,821 6,787 8,272 5,279 2,992 2,388 1, , , , , , , , , , , , , , , , , , , , years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over.. 65 to 69 years 70 to 74 years 75 years and over Women 94,113 6,196 3,369 2,827 7,813 49,765 15,077 7,404 7,672 17,327 8,136 9,190 17,362 9,111 8,251 12,945 7,284 5,662 17,394 4,486 3,964 8,944 55,335 2,793 1,165 1,627 5,443 37,637 11,120 5,446 5,674 13,094 6,062 7,031 13,423 7,260 6,163 7,421 4,818 2,603 2,041 1, , , , , , , , , , , , , , , , , i 4, , , , , , , , , , , , , , , , , , , , , , , , , , , ,555

27 A-13. Employment status of the civilian noninstitutional population by age, sex, and race Continued (Numbers in thousands) February 2005!, sex, and race Civilian noninstitutional population Total Percent of population Civilian labor force Total Employed Percent of population Number Unemployed Percent of labor force Not labor force BLACK OR AFRICAN AMERICAN 16 years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to44years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over.. 65 to 69 years 70 to 74 years 75 years and over 26,342 2,454 1,370 1,084 2,832 15,180 5,051 2,547 2,504 5,318 2,550 2,768 4,811 2,615 2,196 2,923 1,655 1,269 2, ,283 16, ,895 12,043 4, ,318 2,113 2,205 3,611 2,066 1,545 1,570 1, , , , , , , , , , , , , , , , ( 1 ) 9,804 1,787 1, , , , , , , years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over.. 65 to 69 years 70 to 74 years 75 years and over Men 11,794 1, ,337 6,819 2,262 1,151 1,110 2,375 1,133 1,242 2,182 1, , , , ,607 1, , , , , , , , ( T ) 4, , years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over to 69 years 70 to 74 years 75 years and over Women 14,548 8,788 1, , ,361 6,437 2,789 2,166 1,395 1,052 1,394 1,114 2,943 2,318 1,417 1,108 1,526 1,210 2,629 1,953 1,426 1,100 1, , , , , , , , , , , , , , , ( 1 ) 802

28 A-13 Employment status of the civilian noninstitutional population by age, sex, and race Continued (Numbers in thousands) February 2005 Civilian labor force Age, sex, and race Civilian noninstitutional population Total Percent of population Employed Unemployed Not in Total Percent Percent labor of of force Number population labor force ASIAN 16 years and over 9,659 6, , , to 19 years to 17 years ( 1 ) to 19 years to 24 years to 54 years 6,036 4, , , to 34 years 2,213 1, , to 29 years 1, to 34 years 1, to 44 years 2,111 1, , to 39 years 1, to 44 years 1, to 54 years 1,712 1, , to 49 years to 54 years to 64 years 1, to 59 years to 64 years years and over 1, to 69 years to 74 years years and over ( 1 ) Data not shown where base is less than 75,000. NOTE: Estimates for the above race groups do not sum to totals because data are not presented for all races. Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

29 A-14. Employment status of the Hispanic or Latino population by age and sex (Numbers in thousands) February 2005 Civilian labor force Age and sex Civilian noninstitutional population Total Percent of population Total Employed Percent of population Number Unemployed Percent of labor force labor force HISPANIC OR LATINO ETHNICITY 16 years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over.. 65 to 69 years 70 to 74 years 75 years and over 28,729 19,385 2, , , ,654 2,615 17,904 14,132 7,594 5,975 3,906 3,052 3,688 2,923 6,202 4,987 3,281 2,625 2,921 2,362 4,107 3,170 2,320 1,851 1,787 1,319 2,303 1,349 1, , , , , , , , , , , , , , , , ( 1 ) 9,344 1,677 1, ,039 3,772 1, , , years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over.. 65 to 69 years 70 to 74 years 75 years and over Men 14,745 11,679 1, ,965 1,616 9,391 8,599 4,100 3,776 2,137 1,963 1,963 1,812 3,231 3,014 1,726 1,608 1,506 1,407 2,060 1,809 1,177 1, , , , , , , , , , , , (1) ( 1 ) 3, years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 54 years 25 to 34 years 25 to 29 years 30 to 34 years 35 to 44 years 35 to 39 years 40 to 44 years 45 to 54 years 45 to 49 years 50 to 54 years 55 to 64 years 55 to 59 years 60 to 64 years 65 years and over to 69 years 70 to 74 years 75 years and over Women 13,983 7,706 1, , ,513 5,532 3,494 2,199 1,769 1,089 1,725 1,111 2,971 1,973 1,556 1,017 1, ,048 1,361 1, , , , , , , , , , <!> ( 1 ) 6, ,980 1, , Data not shown where base is less than 75,000. NOTE- Persons whose ethnicity is identified as Hispanic or Latino may be of any rac e survey. Dash indicates no data or data that do not meet publication criteria. Beginning in January 2005, data reflect revised population controls used in the household

30 A-15. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic or Latino ethnicity (Numbers in thousands) Employment status, race, and Hispanic or Latino ethnicity Total 2005 Men, 20 years and over 2005 Women, 20 years and over 2005 Both sexes, 16 to 19 years 2005 TOTAL Civilian noninstitutional population 222, ,041 98, , , ,403 16,175 16,317 Civilian labor force 146, ,649 74,719 75,640 64,832 65,411 6,603 6,598 Percent of population Employed 137, ,100 70,318 71,413 61,592 62,292 5,475 5,395 Unemployed 8,770 8,549 4,402 4,228 3,240 3,119 1,128 1,203 Unemployment rate Not in labor force 76,203 77,392 24,246 24,680 42,384 42,992 9,572 9,719 White Civilian noninstitutional population 182, ,767 82,269 83,204 87,155 87,917 12,577 12,646 Civilian labor force 120, ,293 62,494 63,192 52,281 52,543 5,561 5,559 Percent of population Employed 113, ,188 59,123 60,116 50,051 50,448 4,661 4,624 Unemployed 6,502 6,105 3,371 3,076 2,230 2, Unemployment rate Not in labor force 61,665 62,474 19,775 20,012 34,874 35,375 7,016 7,088 Black or African American Civilian noninstitutional population 25,900 26,342 10,385 10,584 13,108 13,303 2,406 2,454 Civilian labor force 16,274 16,538 7,284 7,394 8,369 8, Percent of population Employed 14,650 14,688 6,552 6,523 7,628 7, Unemployed 1,624 1, Unemployment rate Not in labor force 9,626 9,804 3,102 3,190 4,739 4,828 1,785 1,787 Asian Civilian noninstitutional population 9,334 9,659 4,121 4,283 4,627 4, Civilian labor force 6,190 6,378 3,240 3,362 2,772 2, Percent of population Employed 5,900 6,092 3,098 3,224 2,633 2, Unemployed Unemployment rate Not in labor force 3,144 3, ,855 1, Hispanic or Latino ethnicity Civilian noninstitutional population 27,705 28,729 12,878 13,387 12,247 12,688 2,580 2,653 Civilian labor force 18,682 19,385 10,709 11,143 7,036 7, Percent of population Employed 17,170 18,031 9,916 10,508 6,547 6, Unemployed 1,512 1, Unemployment rate Not in labor force 9,023 9,344 2,170 2,245 5,210 5,422 1,643 1,677 NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey.

31 A-16. Employment status of the civilian noninstitutional population 16 to 24 years of age by school enrollment, educational attainment, sex, race, and Hispanic or Latino ethnicity (Numbers in thousands) February 2005 Civilian labor force Enrollment status, educational attainment, race, and Hispanic or Latino ethnicity Total Civilian noninstitutional population Percent of population Total Employed Full time Part time Total Unemployed Looking for full-time work Looking for parttime work Percent of labor force TOTAL ENROLLED Total, 16 to 24 years 20,634 8, ,763 1,675 6,088 1, to 19 years 13,542 4, , , to 24 years 7,093 4, ,780 1,310 2, Men 10,161 4, , , Women 10,473 4, , , High school 10,692 3, , , College 9,942 5, ,074 1,503 3, Full-time students 8,446 4, , , Part-time students 1,496 1, , White Total, 16 to 24 years 16,039 7, ,552 1,347 5, to 19 years 10,499 4, , , to 24 years 5,540 3, ,124 1,055 2, Men 7,952 3, , , Women 8,087 3, , , High school 8,204 2, , , College 7,835 4, ,234 1,221 3, Full-time students 6,637 3, , , Part-time students 1,199 1, Black or African American Total, 16 to 24 years 2, to 19 years 2, to 24 years Men 1, Women 1, High school 1, College 1, Full-time students 1, Part-time students Asian Total, 16 to 24 years 1, _ to 19 years to 24 years , Men _ Women High school , _ College ! Full-time students ! _ Part-time students ; ( 1 ) Hispanic or Latino ethnicity Total, 16 to 24 years 2,795 1, to 19 years 1, to 24 years Men 1, Women 1, High school 1, College 1, Full-time students Part-time students See footnotes at end of table.

32 A-16. Employment status of the civilian noninstitutional population 16 to 24 years of age by school enrollment, educational attainment, sex, race, and Hispanic or Latino ethnicity Continued (Numbers in thousands) February 2005 Civilian labor force Enrollment status, educational attainment, race, and Hispanic or Latino ethnicity Civilian noninstitutional population Total Percent of population Total Employed Full time Part time Total Unemployed Looking for full-time work Looking for parttime work Percent of labor force TOTAL NOT ENROLLED Total, 16 to 24 years 15,943 12, ,907 8,914 1,994 1,765 1, to 19 years 2,775 1, , to 24 years 13,168 10, ,496 7,947 1,549 1,312 1, Men 8,282 7, ,011 5, ,125 1, Women 7,661 5, ,897 3,696 1, Less than a high school diploma 3,890 2, ,844 1, High school graduates, no college 2 6,660 5, ,663 3, Some college or associate degree 3,615 3, ,850 2, Bachelor's degree and higher 3 1,778 1, ,551 1, White Total, 16 to 24 years 12,469 10, ,928 7,264 1,664 1,231 1, to 19 years 2,147 1, , to 24 years 10,322 8, ,732 6,441 1, Men 6,547 5, ,018 4, Women 5,922 4, ,910 2, Less than a high school diploma 3,008 1, ,534 1, High school graduates, no college 2 5,100 4, ,755 2, Some college or associate degree 2,871 2, ,333 1, Bachelor's degree and higher 3 1,490 1, ,306 1, Black or African American Total, 16 to 24 years 2,388 1, ,266 1, to 19 years to 24 years 1,956 1, , Men 1, Women 1, Less than a high school diploma High school graduates, no college 2 1, Some college or associate degree Bachelor's degree and higher Asian Total, 16 to 24 years to 19 years ( 1 ) ( 1 ) 20 to 24 years Men _ 9.0 Women Less than a high school diploma ( 1 ) ( 1 ) High school graduates, no college Some college or associate degree Bachelor's degree and higher Hispanic or Latino ethnicity Total, 16 to 24 years 3,512 2, ,264 1, to 19 years to 24 years 2,849 2, ,938 1, Men 1,934 1, ,479 1, Women 1, Less than a high school diploma 1,598 1, High school graduates, no college 2 1,273 1, Some college or associate degree Bachelor's degree and higher ( 1 ) 1 Data not shown where base is less than 75, Includes persons with a high school diploma or equivalent. 3 Includes persons with a bachelor's, master's, professional, and doctoral degrees. NOTE: In the summer months, the educational attainment levels of youth not enrolled in school are increased by the temporary movement of high school and college students into that group. Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

33 A-17. Employment status of the civilian noninstitutional population 25 years and over by educational attainment, sex, race, and Hispanic or Latino ethnicity (Numbers in thousands) Sex, race, and Hispanic or Latino ethnicity Less than a high school diploma High school graduates, no college 1 Total Some college or associate degree Some college, no degree Associate degree Bachelor's degree and higher TOTAL Civilian labor force 12,191 12,269 37,985 38,230 34,357 35,071 22,449 22,456 11,909 12,616 40,148 40,621 Percent of population Employed 10,965 11,142 35,802 36,101 32,792 33,529 21,346 21,371 11,446 12,157 38,984 39,657 Employment-population ratio Unemployed 1,227 1,126 2,182 2,129 1,565 1,543 1,103 1, , Unemployment rate Men Civilian labor force 7,728 7,751 20,456 21,013 17,029 17,278 11,481 11,426 5,548 5,852 21,626 21,662 Percent of population Employed 6,960 7,077 19,162 19,764 16,202 16,474 10,901 10,855 5,301 5,618 20,987 21,140 Employment-population ratio Unemployed ,295 1, Unemployment rate Women Civilian labor force 4,463 4,518 17,528 17,218 17,328 17,793 10,967 11,029 6,361 6,764 18,522 18,959 Percent of population Employed 4,004 4,065 16,641 16,337 16,590 17,055 10,445 10,516 6,145 6,539 17,996 18,517 Employment-population ratio Unemployed Unemployment rate White Civilian labor force 9,778 9,851 30,997 31,187 28,455 29,014 18,448 18,432 10,008 10,582 33,548 33,776 Percent of population Employed 8,840 9,108 29,366 29,691! 27,293 27,856 17,650 17,645 9,643 10,211 32,674 33,054 Employment-population ratio i Unemployed ,631 1,497 1,162 1, Unemployment rate j Black or African American Civilian labor force 1,561 1,622 5,147 5,219 3,985 4,145 2,825 2,831 1,160 1,313 3,075 2,990 Percent of population Employed 1,377 1,294 4,704 4,703 3,683 3,854 2,585 2,608 1,097 1,246 2,924 2,885 Employment-population ratio Unemployed Unemployment rate Asian Civilian labor force ,056 1,058 1,046 1, ,975 3,222 Percent of population Employed ,005 1, ,862 3,096 Employment-population ratio Unemployed Unemployment rate Hispanic or Latino ethnicity Civilian labor force 5,338 5,492 4,401 4,746 3,311 3,433 2,331 2, ,018 2,057 2,123 Percent of population Employed 4,812 5,102 4,127 4,463 3,164 3,288 2,228 2, ,005 2,065 Employment-population ratio I Unemployed Unemployment rate Includes persons with a high school diploma or equivalent. 2 Includes persons with a bachelor's, master's, professional, and doctoral degrees. NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey.

34 A-18. Employed and unemployed full- and part-time workers by age, sex, race, and Hispanic or Latino ethnicity (In thousands) Employed February 2005 Unemployed Full-time workers Part-time workers Age, sex, race, and Hispanic or Latino ethnicity Total 35 hours or more At work 1 to 34 hours for economic or noneconomic reasons Not at work Total Part time for economic reasons At work 2 Part time for noneconomic reasons Not at work Looking for full-time work Looking for part-time work TOTAL Total, 16 years and over. 16 to 19 years 16 to 17 years 18 to 19 years 20 years and over 20 to 24 years 25 years and over 25 to 54 years 55 years and over Men, 16 years and over. 16 to 1-9 years 20 years and over 20 to 24 years 25 years and over 25 to 54 years 55 years and over Women, 16 years and over 16 to 19 years 20 years and over 20 to 24 years 25 years and over 25 to 54 years 55 years and over 114,022 1, , ,691 9, ,434 85,824 17,609 65, ,061 5,289 59,771 49,712 10,059 48, ,630 3,968 43,663 36,112 7, ,084 1, ,009 8,072 91,937 76,672 15,265 58, ,241 4,603 53,638 44,834 8,804 42, ,768 3,469 38,299 31,838 6,461 10, , ,873 7,148 1,724 5, , ,660 3, , , ,213 3, , , ,624 2, , , ,473 1, , , , ,078 4,064 1,956 2,108 21,014 4,018 16,996 11,773 5,222 8,169 1,817 6,352 1,668 4,684 2,634 2,050 16,909 2,248 14,661 2,350 12,311 9,140 3,172 2, , ,171 1, , , , , ,250 1, ,858 3,769 1,879 1,890 17,088 3,315 13,773 9,209 4,563 6,448 1, ,323 3,465 1,691 1,774 14,410 2,109 12,300 1,992 10,308 7, , , , , ,501 1,364 5,137 4, , , ,060 2, , , ,077 1, , White Men, 16 years and over. 16 to 19 years 20 years and over 20 to 24 years 25 years and over 25 to 54 years 55 years and over Women, 16 years and over 16 to 19 years 20 years and over 20 to 24 years 25 years and over 25 to 54 years 55 years and over 55, ,711 4,361 50,350 41,559 8,791 38, ,793 3,135 34,658 28,368 6,290 49, ,931 3,786 45,145 37,471 7,674 33, ,127 2,741 30,385 25,031 5,354 4, , ,972 3, , , ,370 2, , , , ,975 1,570 5,404 1,433 3,972 2,103 1,868 14,594 1,939 12,655 1,926 10,728 7,856 2,872 1, , , ,613 1,442 4,171 1,156 3,015 1,382 1,633 12,540 1,823 10,716 1,639 9,078 6,545 2, , , ,261 1, , , ,358 1, Black or African American Men, 16 years and over. 16 to 19 years 20 years arid over 20 to 24 years 25 years and over 25 to 54 years 55 years and over Women, 16 years and over 16 to 19 years 20 years and over 20 to 24 years 25 years and over 25 to 54 years 55 years and over 6, , ,421 4, , , ,915 5, , , ,849 4, , , ,151 4, , , ,

35 A-18. Employed and unemployed full- and part-time workers by ago, sex, race, and Hispanic or Latino ethnicity Continued (In thousands) February 2005 Employed 1 Unemployed Full-time workers Part-time workers Age, sex, race, and Hispanic or Latino ethnicity Total 35 hours or more At work 1 to 34 hours for economic or noneconomic reasons Not at work Total Part time for economic reasons At work 2 Part time for noneconomic reasons Not at work Looking for full-time work Looking for part-time work Asian Men, 16 years and over 2,955 2, to 19 years years and over 2,933 2, to 24 years years and over 2,757 2, to 54 years 2,328 2, years and over Women, 16 years and over 2,252 2, to 19 years 4 4 _ years and over 2,248 2, to 24 years years and over 2,118 1, to 54 years 1,759 1, years and over Hispanic or Latino ethnicity Men, 16 years and over 9,890 8, , to 19 years years and over 9,692 8, to 24 years 1,216 1, years and over 8,475 7, to 54 years 7,694 6, years and over Women, 16 years and over 5,448 4, , , to 19 years years and over 5,325 4, , , to 24 years years and over 4,707 4, , to 54 years 4,184 3, years and over Employed persons are classified as full- or part-time workers based on their usual weekly hours at all jobs regardless of the number of hours they were at work during the reference week. Persons absent from work also are classified according to their usual status. 2 Includes some persons at work 35 hours or more classified by their reason for working part time. NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

36 A-19. Employed persons by occupation, sex, and age (In thousands) Total Men Women 16 years 16 years 20 years 16 years 20 years Occupation and over and over and over and over and over Total 137, ,100 73,003 73,990 70,318 71,413 64,381 65,109 61,592 62,292 Management, professional, and related occupations 48,580 48,495 23,804 23,807 23,643 23,676 24,775 24,687 24,566 24,516 Management, business, and financial operations occupations 20,112 19,876 11,511 11,285 11,479 11,267 8,601 8,592 8,582 8,576 Management occupations 14,475 14,064 9,031 8,745 9,006 8,734 5,444 5,319 5,434 5,308 Business and financial operations occupations 5,637 5,813 2,480 2,540 2,473 2,533 3,157 3,273 3,148 3,268 Professional and related occupations 28,467 28,618 12,293 12,523 12,164 12,409 16,174 16,096 15,984 15,940 Computer and mathematical occupations 3,137 3,281 2,248 2,390 2,220 2, Architecture and engineering occupations 2,628 2,703 2,258 2,359 2,253 2, Life, physical, and social science occupations 1,314 1, Community and social services occupations 2,175 2, ,313 1,287 1,306 1,278 Legal occupations 1,617 1, Education, training, and library occupations 8,038 8,281 2,104 2,193 2,079 2,156 5,934 6,088 5,848 6,025 Arts, design, entertainment, sports, and media occupations 2,690 2,687 1,391 1,373 1,355 1,334 1,299 1,313 1,246 1,281 Healthcare practitioner and technical occupations 6,868 6,577 1,831 1,795 1,825 1,790 5,036 4,782 5,004 4,748 Service occupations 21,586 22,179 9,234 9,455 8,322 8,579 12,352 12,724 11,209 11,593 Healthcare support occupations 2,846 2, ,558 2,623 2,455 2,542 Protective service occupations 2,862 2,878 2,282 2,206 2,249 2, Food preparation and serving related occupations 6,976 7,154 3,096 3,158 2,493 2,512 3,880 3,996 3,164 3,268 Building and grounds cleaning and maintenance occupations 4,572 4,754 2,646 2,745 2,501 2,633 1,926 2,009 1,864 1,957 Personal care and service occupations 4,329 4, ,408 3,424 3,189 3,193 Sales and office occupations 35,358 35,687 12,814 12,966 12,015 12,206 22,544 22,721 21,224 21,347 Sales and related occupations 15,998 16,316 8,152 8,290 7,694 7,835 7,846 8,026 6,979 7,162 Office and administrative support occupations 19,360 19,371 4,662 4,676 4,321 4,370 14,698 14,695 14,245 14,185 Natural resources, construction, and maintenance occupations 13,960 14,542 13,359 13,874 12,976 13, Farming, fishing, and forestry occupations Construction and extraction occupations 7,941 8,570 7,719 8,296 7,509 8, Installation, maintenance, and repair occupations 5,144 5,134 4,931 4,898 4,833 4, Production, transportation, and material moving occupations 17,901 18,198 13,792 13,888 13,362 13,382 4,109 4,310 4,012 4,200 Production occupations 9,599 9,446 6,713 6,509 6,588 6,354 2,886 2,937 2,834 2,887 Transportation and material moving occupations 8,301 8,752 7,079 7,379 6,774 7,028 1,222 1,373 1,179 1,313 NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey.

37 A-20. Employed persons by occupation, race, Hispanic or Latino ethnicity, and sex (Percent distribution) Total Men Women Occupation, race, and Hispanic or Latino ethnicity TOTAL Total, 16 years and over (thousands). Percent Management, professional, and related occupations Management, business, and financial operations occupations Professional and related occupations Service occupations Sales and office occupations Sales and related occupations Office and administrative support occupations Natural resources, construction, and maintenance occupations. Farming, fishing, and forestry occupations Construction and extraction occupations Installation, maintenance, and repair occupations Production, transportation, and material moving occupations Production occupations Transportation and material moving occupations 137, ,100 73,003 73,990 64,381 65, White Total, 16 years and over (thousands), Percent Management, professional, and related occupations Management, business, and financial operations occupations Professional and related occupations Service occupations Sales and office occupations Sales and related occupations Office and administrative support occupations Natural resources, construction, and maintenance occupations. Farming, fishing, and forestry occupations Construction and extraction occupations Installation, maintenance, and repair occupations Production, transportation, and material moving occupations Production occupations Transportation and material moving occupations. 113, ,188 61,458 62,311 52,377 52, Black or African American Total, 16 years and over (thousands). Percent Management, professional, and related occupations Management, business, arid financial operations occupations Professional and related occupations Service occupations Sales and office occupations Sales and related occupations Office and administrative support occupations Natural resources, const'uction, and maintenance occupations. Farming, fishing, and forestry occupations Construction and extraction occupations Installation, maintenance, and repair occupations Production, transportation, and material moving occupations Production occupations Transportation and material moving occupations 14,650 14,688 6,740 6,758 7,910 7, See footnotes at end of table.

38 A-20. Employed persons by occupation, race, Hispanic or Latino ethnicity, and sex Continued (Percent distribution) Total Men Women Occupation, race, and Hispanic or Latino ethnicity Asian Total, 16 years and over (thousands) 5,900 6,092 3,182 3,281 2,718 2,811 Percent Management, professional, and related occupations Management, business, and financial operations occupations Professional and related occupations Service occupations Sales and office occupations Sales and related occupations Office and administrative support occupations Natural resources, construction, and maintenance occupations Farming, fishing, and forestry occupations Construction and extraction occupations Installation, maintenance, and repair occupations Production, transportation, and material moving occupations Production occupations Transportation and material moving occupations Hispanic or Latino ethnicity Total, 16 years and over (thousands) 17,170 18,031 10,288 10,916 6,882 7,114 Percent Management, professional, and related occupations Management, business, and financial operations occupations Professional and related occupations Service occupations Sales and office occupations Sales and related occupations Office and administrative support occupations Natural resources, construction, and maintenance occupations ' Farming, fishing, and forestry occupations Construction and extraction occupations Installation, maintenance, and repair occupations Production, transportation, and material moving occupations Production occupations Transportation and material moving occupations NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

39 A-21. Employed persons by industry and occupation (In thousands) February 2005 Management, professional, and related occupations Service occupation:; Sales and office occupations Natural resources, construction, and maintenance occupations Production, transportation, and material moving occupations Industry Total employed Management, business, and financial operations occupations Professional and related occupations Protective service occupations Se i yice occ jp I- ticns, ex,ept prot 'Ct v; Sales and related occupations Office and administrative support occupations Farming, fishing, and forestry occupations Construction and extraction occupations Installation, maintenance, and repair occupations Production occupations Transportation and material moving occupations Agriculture, forestry, fishing, and hunting Mining Construction Manufacturing Durable goods Nondurable goods Wholesale and retail trade Wholesale trade Retail trade Transportation and utilities Information Financial activities Professional and business services Education and health services Leisure and hospitality Other services Other services, except private households Private households Public administration 1, I ,520 1, , ,186 2,608 1, , ,858 1,297 10,228 1,683 1, , , , ,312 1,509 1, ,858 3, ,166 4, , , ,218 2, ,326 7, , ,194 3, , ,216 3, ,433 2, ,996 3,105 4, , ,942 2,390 15, , , ,365 1, , , , , , , ,642 1,166 1,543 1, , NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

40 A-22. Employed persons in agriculture and related and in nonagricultural industries by age, sex, and class of worker (In thousands) February 2005 Agriculture and related industries Nonagricultural industries Age and sex Wage and salary workers Unpaid family workers Total Total Wage and salary workers Private industries Private household workers Other private industries Government Selfemployed workers Selfemployed workers Unpaid family workers Total, 16 years and over 1, , , ,517 20,321 9, to 19 years ,257 5, , to 17 years ,021 1, , to 19 years ,236 3, , to 24 years ,896 11, ,734 1, to 34 years ,539 24, ,635 3,747 1, to 44 years ,482 26, ,157 5,182 2, to 54 years ,738 23, ,529 6,072 2, to 64 years ,803 12, ,166 3,533 1, years and over ,900 3, , Men, 16 years and over ,706 58, ,951 8,696 5, to 19 years ,498 2, , to 17 years to 19 years ,589 1,526-1, to 24 years ,691 6, , to 34 years ,511 13, ,846 1, _ 35 to 44 years ,739 14, ,526 2,196 1, to 54 years ,133 12, ,617 2,504 1, to 64 years ,120 6, ,565 1,549 1,107 _ 65 years and over ,015 1, , Women, 16 years and over ,909 49, ,566 11,626 3, to 19 years ,759 2, , to 17 years 5 2 1,113 1, , to 19 years 5 4-1,647 1, , to 24 years ,206 5, , to 34 years ,028 10, ,789 2, to 44 years ,744 11, ,630 2, to 54 years ,605 11, ,912 3, to 64 years ,683 5, ,602 1, years and over ,885 1, , NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

41 A-23. Employed persons in nonagricultural industries by sex and class of worker (In thousands) February 2005 Industry and sex Total employed 1 Total Wage and salary workers Private industries Government Selfemployed workers TOTAL Total, 16 years and over 137, , ,294 20,321 9,468 Mining Construction 10,520 8,706 8, ,791 Manufacturing 16,186 15,801 15, Durable goods 10,228 9,997 9, Nondurable qoods 5,958 5,804 5, Wholesale and retail trade 21,312 19,903 19, ,391 Wholesale trade... 4,438 4,176 4, Retail trade 16,875 15,727 15, ,135 Transportation and utilities 7,284 6,846 5,382 1, Transportation and warehousing 6,095 5,657 4,535 1, Utilities. 1,189 1, ,271 3,119 2, Financial activities. 10,216 9,441 9, Finance and insurance 7,012 6,759 6, Real estate and rental and leasing 3,204 2,683 2, Professional and business services 13,996 12,129 11, ,858 Professional and technical services 8,631 7,430 7, ,193 Management, administrative, and waste services 5,364 4,699 4, Education and health services 28,942 27,835 17,477 10,358 1,089 Educational services 12,418 12,197 3,483 8, Health care and social assistance 16,524 15,638 13,994 1, Hospitals 5,556 5,543 4, Health services, except hospitals 8,215 7,790 7, Social assistance 2,753 2,305 1, Leisure and hospitality 11,365 10,788 10, Arts, entertainment, and recreation 2,442 2,094 1, Accommodation and food services 8,922 8,694 8, Other services 6,857 5,797 5, ,037 Other services, except private households 6,080 5,020 4, ,037 Private households Public administration 6,642 6,642-6,642 Men Total, 16 years and over 72,563 66,706 58,011 8,696 5,822 Mining Construction 9,433 7,756 7, ,677 Manufacturing 11,181 10,953 10, Durable goods 7,483 7,330 7, Nondurable goods 3,698 3,624 3, Wholesale and retail trade 11,965 11,231 11, Wholesale trade 3,166 2,994 2, Retail trade 8,798 8,237 8, Transportation and utilities 5,598 5,211 4,196 1, Transportation and warehousing 4,665 4,278 3, Utilities ,782 1,671 1, Financial activities 4,586 4,146 4, Finance and insurance 2,867 2,693 2, Real estate and rental and leasing 1,719 1,452 1, Professional and business services 7,783 6,672 6, ,111 Professional and technical services 4,660 3,921 3, Management, administrative, and waste services 3,124 2,751 2, Education and health services 7,141 6,826 3,892 2, Educational services 3,740 3,665 1,186 2, Health care and social assistance 3,401 3,161 2, Hospitals 1,310 1,299 1, Health services, except hospitals. 1,708 1,491 1, Social assistance Leisure and hospitality 5,543 5,244 4, Arts, entertainment, and recreation 1,287 1, Accommodation and food services 4,257 4,140 4, Other services 3,430 2,885 2, Other services, except private households 3,371 2,825 2, Private households Public administration 3,576 3,576 3,576 See footnotes at end of table.

42 A-23. Employed persons in nonagricuitural industries by sex and class of worker Continued (In thousands) February 2005 Industry and sex Total employed 1 Total Wage and salary workers Private industries Government Selfemployed workers Women Total, 16 years and over 64,647 60,909 49,284 11,626 3,647 Mining Construction 1, Manufacturing 5,005 4,848 4, Durable goods 2,744 2,667 2, Nondurable goods 2,261 2,180 2, Wholesale and retail trade 9,348 8,672 8, Wholesale trade 1,271 1,182 1, Retail trade 8,076 7,490 7, Transportation and utilities 1,686 1,635 1, Transportation and warehousing 1,430 1,379 1, Utilities Information 1,489 1,448 1, Financial activities 5,631 5,296 5, Finance and insurance 4,145 4,065 3, Real estate and rental and leasing 1,485 1,230 1, Professional and business services 6,212 5,457 5, Professional and technical services 3,971 3,509 3, Management, administrative, and waste services 2,241 1,948 1, Education and health services 21,800 21,009 13,585 7, Educational services 8,678 8,532 2,298 6, Health care and social assistance 13,123 12,477 11,288 1, Hospitals 4,245 4,244 3, Health services, except hospitals 6,506 6,299 5, Social assistance 2,371 1,934 1, Leisure and hospitality 5,821 5,543 5, Arts, entertainment, and recreation 1, Accommodation and food services 4,665 4,553 4, Other sen/ices 3,427 2,912 2, Other services, except private households 2,709 2,195 2, Private households Public administration 3,066 3,066 3,066 1 Includes unpaid family workers, not shown separately. NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

43 A-24. Persons at work in agriculture and related and in nonagricultural industries by hours of work February 2005 Hours of work All industries Thousands of persons Agriculture and related industries Nonagricultural industries All industries Percent distribution Agriculture and related industries Nonagricultural industries Total, 16 years and over 134,943 1, , to 34 hours 32, , to 4 hours 1, , to 14 hours 5, , to 29 hours 16, , to 34 hours 9, , hours and over 101,973 1, , to 39 hours 9, , hours 54, , hours and over 37, , to 48 hours 13, , to 59 hours 14, , hours and over 9, , Average hours, total at work Average hours, persons who usually work full time NOTE: Beginning in January 2:005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria. A-25. Persons at work 1 to 34 hours in all and in nonagricultural industries by reason for working less than 35 hours and usual full- or part-time status (Numbers in thousands) February 2005 Reason for working less than 35 hours All industries Nonagricultural industries Usually Usually Usually Usually Total work work Total work work full time part time full time part time Total, 16 years and over 32,970 10,041 22,929 32,484 9,861 22,622 Economic reasons 4,487 1,703 2,784 4,380 1,623 2,757 Slack work or business conditions 2,820 1,411 1,409 2,761 1,362 1,399 Could only find part-time work 1,315-1,315 1,306 _ 1,306 Seasonal work Job started or ended during week Noneconomic reasons 28,483 8,338 20,145 28,104 8,238 19,865 Child-care problems Other family or personal obligations 6, ,429 6, ,357 Health or medical limitations In school or training 6, ,454 6, ,412 Retired or Social Security limit on earnings 2,054-2,054 1,967-1,967 Vacation or personal day 2,603 2,603-2,588 2,588 - Holiday, legal or religious Weather-related curtailment _ All other reasons 8,197 3,560 4,637 8,097 3,526 4,571 Average hours: Economic reasons Other reasons NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

44 A-26* Persons at work in nonagricultural industries by class of worker and usual full- or part-time status (Numbers in thousands) February 2005 Worked 1 to 34 hours Average hours Industry and class of worker Total at work Total For economic reasons For noneconomic reasons Usually work full time Usually work part time Worked 35 hours or more Total at work Persons who usually work full time Total, 16 years and over 133,201 32,484 4,380 8,238 19, , Wage and salary workers 124,205 29,368 3,804 7,571 17,993 94, Mining Construction 8,408 1, , Manufacturing 15,433 1, , Durable goods 9, , Nondurable goods 5, , Whotesale and retail trade 19,391 5, ,769 13, Transportation and utilities 6,615 1, , Information 3, , Financial activities 9,219 1, ,002 7, Professional and business services 11,769 2, ,293 9, Education and health services 27,124 7, ,760 5,254 19, Leisure and hospitality 10,511 4, ,314 6, Other services 5,626 1, ,193 3, Other services, except private households 4,886 1, , Private households Public administration 6,466 1, , Self-employed workers.. 8,869 3, ,807 5, Unpaid family workers ( 1 ) 1 Data not shown where base is less than 75,000. NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey.

45 A-27. Persons at work in nonagricultural industries by age, sex, race, Hispanic or Latino ethnicity, marital status, and usual full- or part-time status (Numbers in thousands) February 2005 Worked 1 to 34 hours Average hours Age, sex, race, Hispanic or Latino ethnicity, and marital status Total at work Total For economic reasons For noneconomic reasons Usually work full time Usually work part time Worked 35 hours or more Total at work Persons who usually work full time TOTAL Total, 16 years and over 133,201 32,484 4,380 8,238 19, , to 19 years 5,202 4, ,692 1, to 17 years 2,023 1, , to 19 years 3,179 2, , years and over 127,999 28,367 4,129 8,084 16,174 99, to 24 years 12,821 4, ,199 8, years and over 115,178 23,6: 9 3,343 7,382 12,974 91, to 54 years 93,854 17,513 2,794 6,005 8,714 76, years and over 21,323 6, ,377 4,260 15, Men, 16 years and over 70,633 12,4;!,12 2,324 4,075 6,053 58, to 19 years 2,460 1,8,! , to 17 years I ( 1 ) 18 to 19 years 1,549 9! years and over 68,173 10,631 2,186 4,000 4,445 57, to 24 years 6,685 2, ,259 4, years and over 61,488 8,560 1,757 3,618 3,185 52, to 54 years 50,273 5,997 1,445 2,971 1,581 44, years and over 11,215 2, ,605 8, Women, 16 years and over 62,568 20,032 2,056 4,163 13,813 42, to 19 years 2,742 2, , to 17 years 1,112 1, , ( 1 ) 18 to 19 years 1,630 1, , years and over 59,825 17,756 1,943 4,084 11,729 42, to 24 years 6,136 2, ,940 3, years and over 53,689 15,139 1,586 3,764 9,789 38, to 54 years 43,581 11,516 1,348 3,034 7,133 32, years and over 10,108 3, ,656 6, Race and Hispanic or Latino ethnicity White, 16 years and over 110,081 27,557 3,555 6,733 17,269 82, Men 59,378 10,634 1,945 3,415 5,274 48, Women 50,702 16, Si 22 1,609 3,318 11,995 33, Black or African American, 16 years and over 14,217 3, :."7fi 566 1,043 1,469 11, Men 6,528 1, , Women 7,689 1, ,060 5, Asian, 16 years and over 5,896 1, , Men 3, , Women 2,738 m , Hispanic or Latino, 16 years and over 17,222 3,,' ,958 13, Men 10,347 1,1* , Women 6,875 1/J ,310 4, Marital status Men, 16 years and over: Married, spouse present 43,036 5, ,505 1,975 37, Widowed, divorced, or separated 8,462 1, , Never married 19,135 5,564 1,019 1,015 3,530 13, Women, 16 years and over: Married, spouse present 33,192 10, ,247 7,264 22, Widowed, divorced, or separated 12,931 3, ,906 9, Never married 16,444 6, ,643 10, Data not shown where base is less than 75,000. NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey.

46 A-28. Persons at work by occupation, sex, and usual full- or part-time status (Numbers in thousands) February 2005 Worked 1 to 34 hours Average hours Occupation and sex Total at work Total For economic reasons For noneconomic reasons Usually work full time Usually work part time Worked 35 hours or more Total at work Persons who usually work full time Total, 16 years and over 134,943 32,970 4,487 8,338 20, , Management, professional, and related occupations 47,181 9, ,012 5,435 37, Management, business, and financial operations occupations 19,279 2, ,161 1,305 16, Professional and related occupations 27,902 6, ,851 4,130 21, Service occupations 21,454 8,273 1,326 1,165 5,782 13, Sales and office occupations 34,635 9, ,037 6,760 24, Sales and related occupations 15,782 4, ,382 11, Office and administrative support occupations 18,853 4, ,226 3,379 13, Natural resources, construction, and maintenance occupations 1 13,968 2, , , Construction and extraction occupations 8,197 1, , Installation, maintenance, and repair occupations 4, , Production, transportation, and material moving occupations 17,704 3, ,053 1,521 14, Production occupations 9,209 1, , Transportation and material moving occupations 8,496 1, ,023 6, Men, 16 years and over 71,962 12,766 2,410 4,152 6,204 59, Management, professional, and related occupations 23,267 3, ,245 1,414 20, Management, business, and financial operations occupations 10,981 1, , Professional and related occupations 12,287 1, , Service occupations 9,175 2, ,646 6, Sales and office occupations 12,631 2, ,643 10, Sales and related occupations 8,080 1, , Office and administrative support occupations 4,550 1, , Natural resources, construction, and maintenance occupations 1 13,331 2, , , Construction and extraction occupations 7,940 1, , Installation, maintenance, and repair occupations 4, , Production, transportation, and material moving occupations 13,558 2, , Production occupations 6, , Transportation and material moving occupations 7,188 1, , Women, 16 years and over 62,981 20,204 2,077 4,186 13,941 42, Management, professional, and related occupations 23,914 6, ,768 4,021 17, Management, business, and financial operations occupations 8,298 1, , Professional and related occupations 15,616 4, ,128 3,147 11, Service occupations 12,279 5, ,136 6, Sales and office occupations 22,004 7, ,446 5,117 14, Sales and related occupations 7,702 3, ,445 4, Office and administrative support occupations 14,302 3, ,672 10, Natural resources, construction, and maintenance occupations Construction and extraction occupations Installation, maintenance, and repair occupations Production, transportation, and material moving occupations 4,146 1, , Production occupations 2, , Transportation and material moving occupations 1, Includes farming, fishing, and forestry occupations, not shown separately. NOTE: EJeginning in January 2005, data reflect revised population controls used in the household survey.

47 A-29. Unemployed persons by marital status, race, Hispanic or Latino ethnicity, age, and sex Men Women Marital status, race, Hispanic or Latino ethnicity, and age Thousands of persons Unemployment rates Thousands of persons Unemployment rates Feb, Total, 16 years and over 5,012 4, ,758 3, Married, spouse present 1,860 1, ,318 1, Widowed, divorced, or separated ! Never married 2,513 2, ,589 1, White, 16 years and over 3,865 3, ,636 2, Married, spouse present 1,556 1, , Widowed, divorced, or separated Never married 1,798 1, Black or African American, 16 years and over 809 i? Married, spouse present Widowed, divorced, or separated ! Never married 527 6^ Asian, 16 years and over Married, spouse present Widowed, divorced, or separated Never married Hispanic or Latino, 16 years and over 941 7' Married, spouse present Widowed, divorced, or separated Never married Total, 25 years and over 3,529 3, ,610 2, Married, spouse present 1,773 1, ,191 1, Widowed, divorced, or separated '" Never married 1,144 1, White, 25 years and over 2,747 2, ,858 1, Married, spouse present 1,475 1, Widowed, divorced, or separated Never married Black or African American, 25 years and over Married, spouse present Widowed, divorced, or separated 93 ' Never married Asian, 25 years and over Married, spouse present Widowed, divorced, or separated Never married Hispanic or Latino, 25 years and over Married, spouse present Widowed, divorced, or separated Never married 196 "i NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey.

48 A-30. Unemployed persons by occupation and sex Thousands of persons Unemployment rates Occupation Total Total Men Women Total, 16 years and over 1 8,770 8, Management, professional, and related occupations 1,367 1, Management, business, and financial operations occupations Management occupations Business and financial operations occupations Professional and related occupations Computer and mathematical occupations Architecture and engineering occupations Life, physical, and social science occupations Community and social services occupations Legal occupations Education, training, and library occupations Arts, design, entertainment, sports, and media occupations Healthcare practitioner and technical occupations Service occupations 1,742 1, Healthcare support occupations Protective service occupations Food preparation and serving related occupations Building and grounds cleaning and maintenance occupations Personal care and service occupations Sales and office occupations 2,051 1, Sales and related occupations 1, Office and administrative support occupations 1,001 1, Natural resources, construction, and maintenance occupations 1,433 1, Farming, fishing, and forestry occupations Construction and extraction occupations 1,015 1, Installation, maintenance, and repair occupations Production, transportation, and material moving occupations 1,591 1, Production occupations Transportation and material moving occupations No previous work experience to 19 years to 24 years years and over Includes a small number of persons whose last job was in the Armed Forces. NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

49 Thousands of persons Unemployment rates Industry Total Total Men Women F< 20 A Total, 16 years and over 8,"' 7(3 8, Nonagricultural private wage and salary workers 7/ 01 6, Mining Construction 1, 139 1, Manufacturing i,:i Durable goods," Nonmetallic mineral products Primary and fabricated metal products f Machinery manufacturing 8" Computer and electronic products ' Electrical equipment and appliances Transportation equipment Wood products Furniture and fixtures Miscellaneous manufacturing Nondurable goods Food manufacturing Beverage and tobacco products Textile, apparel, and leather Paper and printing Petroleum and coal products ( 1 ) ( 1 ) Chemicals Plastics and rubber products Wholesale and retail trade , Wholesale trade Retail trade 1,121 1, Transportation and utilities Transportation and warehousing Utilities Information Publishing, except Internet Motion picture and sound recording industries Broadcasting, except Internet Telecommunications Internet service providers and data processing services ( 1 ) Other information services 3 _ Financial activities Finance and insurance Finance Insurance Real estate and rental and leasing Real estate Rental and leasing services Professional and business services Professional and technical services Management, administrative, and waste services Administrative and support services Waste management and remediation services ( 1 ) ( 1 ) Education and health services Educational services Health care and social assistance Hospitals Health services, except hospitals Social assistance

50 A-31. Unemployed persons by industry and sex Continued Thousands of persons Unemployment rates Industry Total Total Men Women Leisure and hospitality 987 1, Arts, entertainment, and recreation Accomodation and food services Accomodation Food services and drinking places Other services Other services, except private households Repair and maintenance Personal and laundry services Membership associations and organizations Private households ( 1 ) ( 1 ) Agricultural and related private wage and salary workers Government workers Self-employed and unpaid family workers No previous work experience J Data not shown where base is less than 75, Includes other industries, not shown separately. NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

51

52 A-33. Unemployed persons by reason for unemployment, race, and Hispanic or Latino ethnicity (Numbers in thousands) Reason Black or Hispanic White African Asian or Latino American ethnicity NUMBER OF UNEMPLOYED Total unemployed 6,502 6,105 1,624 1, ,512 1,354 Job losers and persons who completed temporary jobs 3,813 3, On temporary layoff 1,237 1, Not on temporary layoff 2,576 2, Permanent job losers 1,980 1, Persons who completed temporary jobs Job leavers Reentrants 1,700 1, New entrants PERCENT DISTRIBUTION Total unemployed Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Job leavers Reentrants New entrants UNEMPLOYED AS A PERCENT OF THE CIVILIAN LABOR FORCE Job losers and persons who completed temporary jobs Job leavers Reentrants New entrants NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey.

53 A-34. Unemployed persons by reason for unemployment, sex, age, and duration of unemployment (Percent distribution) Reason, sex, and age Total unemployed Thousands of persons i i Percent Less than 5 weeks February to 14 weeks Duration of unemployment Total 15 weeks and over 15 to 26 weeks 27 weeks and over Total, 16 years and over 8, Job losers and persons who completed temporary jobs 4, On temporary layoff 1,330 ioo.o Not on temporary layoff 3,130 ioo.o Permanent job losers 2, Persons who completed temporary jobs Job leavers Reentrants 2, New entrants Men, 20 years and over 4, Job losers and persons who completed temporary jobs 2, On temporary layoff Not on temporary layoff 1, Permanent job losers 1, Persons who completed temporary jobs Job leavers Reentrants New entrants Women, 20 years and over 3, Job losers and persons who completed temporary jobs 1, On temporary layoff Not on temporary layoff 1, Permanent job losers Persons who completed temporary jobs Job leavers Reentrants 1,089 'IOO.O , New entrants Both sexes, 16 to 19 years 1, Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Permanent job losers O O <l> O Persons who completed temporary jobs ( l> 1 ) ( 1 ) ( 1 ) ( 1 ) ( 1 ) Job leavers Reentrants New entrants Data not shown where base is less than 75,000. NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. A-35. Unemployed total and full-time workers by duration of unemployment TcM Full-time workers Duration of unemployment Thousands of persons Percent distribution Thousands of persons Percent distribution Total, 16 years and over 8,770 8, ,346 7, Less than 5 weeks 2,318 2, ,719 1, to 14 weeks 2,912 2, ,467 2, to 10 weeks 1,982 1, ,630 1, to 14 weeks weeks and over 3,540 3, ,160 2, to 26 weeks 1,605 1, ,403 1, weeks and over 1,935 1, ,757 1, to 51 weeks weeks and over 1,088 1, Average (mean) duration, in weeks _ Median duration, in weeks NOTE: Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

54 A-36. Unemployed persons by age, sex, race, Hispanic or Latino ethnicity, marital status, and duration of unemployment February 2005 Sex, age, race, Hispanic or Latino ethnicity, and marital status Total Less than 5 weeks Thousands of persons unemployed 5 to 14 weeks Total 15 weeks and over 15 to 26 weeks 27 weeks and over Weeks of unemployment Average Median (mean) duration duration TOTAL Total, 16 years and over 8,549 2,629 2,789 3,132 1,445 1, to 19 years... 1, to 24 years 1, to 34 years 1, to 44 years 1, to 54 years 1, to 64 years years and over Men, 16 years and over 4,959 1,497 1,739 1, to 19 years to 24 years to 34 years 1, to 44 years to 54 years to 64 years years and over Women, 16 years and over 3,590 1,132 1,050 1, to 19 years to 24 years to 34- years to 44 years to 54 years to 64 years years and over Race and Hispanic or Latino ethnicity White, 16 years and over 6,105 2,024 2,066 2, , Men 3,646 1,211 1,297 1, Women 2, Black or African American, 16 years and over 1, Men Women Asian, 16 years and over Men Women Hispanic or Latino ethnicity, 16 years and over 1, Men Women Marital status Men, 16 years and over: Married, spouse present 1, Widowed, divorced, or separated Never married 2, Women, 16 years and over: Married, spouse present 1, Widowed, divorced, or separated Never married 1, NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented for all races. In addition, persons whose ethnicity is identified as "Hispanic or Latino" may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey.

55

56 A-38. Persons not in the labor force by desire and availability for work, age, and sex ((n thousands) Total Age Sex Category to 24 years to 54 years years and over 2005 Men 2005 Women 2005 Total not in the labor force 76,203 77,392 14,841 15,120 21,300 21,376 40,062 40,896 29,163 29,648 47,040 47,744 Do not want a job now 1 71,580 72,547 13,329 13,466 19,177 19,276 39,074 39,805 27,049 27,520 44,531 45,027 Want a job 1 4,622 4,844 1,512 1,654 2,123 2, ,091 2,113 2,128 2,509 2,716 Did not search for work in previous year 2,483 2, ,048 1, ,050 1,112 1,433 1,589 Searched for work in previous year 2 2,139 2, , ,063 1,016 1,076 1,127 Not available to work now Available to work now 1,691 1, Reason not currently looking: Discouragement over job prospects Reasons other than discouragement 1,206 1, Family responsibilities In school or training Ill health or disability Other Includes some persons who are not asked if they want a job. 2 Persons who had a job in the prior 12 months must have searched since the end of that job. 3 Includes believes no work available, could not find work, lacks necessary schooling or training, employer thinks too young or old, and other types of discrimination. 4 Includes those who did not actively look for work in the prior 4 weeks for such reasons as child-care and transportation problems, as well as a small number for which reason for nonparticipation was not ascertained.

57 A-39. Multiple jobholders by selected demographic and economic characteristics (Numbers in thousands) Both sexes Men Women Characteristic Number Rate 1 Number Rate 1 Number Rate AGE Total, 16 years and over 2 7,235 7, ,606 3, ,629 3, to 19 years years and over 6,998 7,452 :l> ,509 3, ,489 3, to 24 years a years and over 6,156 6, ,130 3, ,026 3, to 54 years 5,116 5, ,616 2, ,500 2, years and over 1,040 1, to 64 years years and over RACE AND HISPANIC OR LATINO ETHNICITY White 6,172 6, ,115 3, ,058 3, Black or African American Asian Hispanic or Latino ethnicity MARITAL STATUS Married, spouse present 4,087 4, ,330 2, ,758 1, Widowed, divorced, or separated 1,233 1, Never married 1,915 1, ,043 1, FULL- OR PART-TIME STATUS Primary job full time, secondary job part time 3,713 3,882 - _ 2,055 2, ,658 1, Primary and secondary jobs both part time 1,753 1, ,176 1, Primary and secondary jobs both full time Hours vary on primary or secondary job 1,458 1, Multiple jobholders as a percent of all employed persons in specifiec group. 2 Includes a small number of persons who work part time on their primary job and full time on their secondary jobs(s), not shown separately. NOTE: Estimates for the above race groups (white, black or African American, and Asian) do not sum to totals because data are not presented foal! races. In addition, persons whose ethnicity is identified as Hispanic or Latino may be of any race and, therefore, are classified by ethnicity as well as by race. Beginning in January 2005, data reflect revised population controls used in the household survey. Dash indicates no data or data that do not meet publication criteria.

58 B-1. Employees on nonfarm payrolls by major industry sector, 1955 to date (In thousands) Goods-p iroducing Service-providing Year and month Total Total private Total Natural resources Construction and mining Manufacturing Total Trade, transportation and utilities Financial activities Information Professional and business services Education and health services Leisure and hospitality Other services Government Annual averages ,744 43,722 19, ,881 15,524 31, ,473 45,087 19, ,082 15,858 32, ,959 45,235 19, ,007 15,798 33, ,426 43,480 18, ,862 14,656 33, ,374 45,182 19, ,050 15,325 34, ,296 45,832 19, ,973 15,438 35,114 10,612 10,921 10,942 10,656 10,960 11,147 1,735 1,778 1,780 1,674 1,718 1,728 2,212 2,299 2,348 2,386 2,454 2,532 3,320 3,437 3,504 3,449 3,591 3,694 2,491 2,593 2,676 2,695 2,822 2,937 3, , ,365 3, ,018 1,050 1,058 1,107 1, ,105 45,399 18, ,908 15,011 35, ,659 46,655 19, ,997 15,498 36, ,764 47,423 19, ,060 15,631 37, ,391 48,680 19, ,148 15,888 38, ,874 50,683 20, ,284 16,617 40, ,020 53,110 21, ,371 17,680 42, ,931 54,406 21, ,305 17,897 44, ,023 56,050 22, ,410 18,211 45, ,512 58,181 22, ,637 18,573 47, ,006 58,318 22, ,654 17,848 48,827 11,040 11,215 11,367 11,677 12,139 12,611 12,950 13,334 13,853 14,144 1,693 1,723 1,735 1,766 1,824 1,908 1,955 1,991 2,048 2,041 2,590 2,656 2,731 2,811 2,878 2,961 3,087 3,234 3,404 3,532 3,744 3,885 3,990 4,137 4,306 4,517 4,720 4,918 5,156 5,267 3,030 3,172 3,288 3,438 3,587 3,770 3,986 4,191 4,428 4,577 3,468 3,557 3,639 3,772 3,951 4,127 4,269 4,453 4,670 4,789 1, ,288 1,346 1,404 1,475 1,558 1,638 1,731 1, ,335 58,323 21, ,770 17,174 49, ,798 60,333 22, ,957 17,669 51, ,912 63,050 23, ,167 18,589 53, ,389 64,086 23, ,095 18,514 55, ,069 62,250 21, ,608 16,909 55, ,502 64,501 22, ,662 17,531 57, ,593 67,334 22, ,940 18,167 59, ,826 71,014 24, ,322 18,932 62, ,932 73,864 24,997 1,008 4,562 19,426 64, ,528 74,154 24,263 1,077 4,454 18,733 66,265 14,318 14,788 15,349 15,693 15,606 16,128 16,765 17,658 18,303 18,413 2,009 2,056 2,135 2,160 2,061 2,111 2,185 2,287 2,375 2,361 3,651 3,784 3,920 4,023 4,047 4,155 4,348 4,599 4,843 5,025 5,328 5,523 5,774 5,974 6,034 6,287 6,587 6,972 7,312 7,544 4,675 4,863 5,092 5,322 5,497 5,756 6,052 6,427 6,767 7,072 4,914 5,121 5,341 5,471 5,544 5,794 6,065 6,411 6,631 6,721 1,827 1,900 1,990 2,078 2, ,359 2,505 2,637 2, ,289 75,109 24,118 1,180 4,304 18,634 67, ,677 73,695 22,550 1,163 4,024 17,363 67, ,280 74,269 22, ,065 17,048 68, ,530 78,371 23,435 1,014 4,501 17,920 71, ,511 80,978 23, ,793 17,819 73, ,474 82,636 23, ,937 17,552 76, ,088 84,932 23, ,090 17,609 78, ,345 87,806 23, ,233 17,906 81, ,014 90,087 24, ,309 17,985 83, ,487 91,072 23, ,263 17,695 85,764 18,604 18,457 18,668 19,653 20,379 20,795 21,302 21,974 22,510 22,666 2,382 2,317 2,253 2,398 2,437 2,445 2,507 2,585 2,622 2,688 5,163 5,209 5,334 5,553 5,815 6,128 6,385 6,500 6,562 6,614 7,782 7,848 8,039 8,464 8,871 9,211 9,608 10,090 10,555 10,848 7,357 7,515 7,766 8,193 8,657 9,061 9,515 10,063 10,616 10,984 6,840 6,874 7,078 7,489 7,869 8,156 8,446 8,778 9,062 9,288 2,865 2,924 3,021 3,186 3,366 3,523 3,699 3,907 4,116 4, ,374 89,829 22, ,780 17,068 85, ,726 89,940 22, ,608 16,799 86, ,844 91,855 22, ,779 16,774 88, ,291 95,016 22, ,095 17,021 91, ,298 97,866 23, ,274 17,241 94, , ,169 23, ,536 17,237 96, , ,113 23, ,813 17,419 98, , ,021 24, ,149 17, , , ,686 24, ,545 17, , , ,996 24, ,787 17, ,136 22,281 22,125 22,378 23,128 23,834 24,239 24,700 25,186 25,771 26,225 2,677 2,641 2,668 2,738 2,843 2,940 3,084 3,218 3,419 3,631 6,558 6,540 6,709 6,867 6,827 6,969 7,178 7,462 7,648 7,687 10,714 10,970 11,495 12,174 12,844 13,462 14,335 15,147 15,957 16,666 11,506 11,891 12,303 12,807 13,289 13,683 14,087 14,446 14,798 15,109 9,256 9,437 9,732 10,100 10,501 10,777 11,018 11,232 11,543 11,862 4,249 4,240 4,350 4,428 4,572 4,690 4,825 4,976 5,087 5, , ,707 23, ,826 16, , , ,828 22, ,716 15, , , ,416 21, ,735 14, , , ,862 21, ,964 14, ,596 25,983 25,497 25,287 25,510 3,629 3,395 3,188 3,138 7,807 7,847 7,977 8,052 16,476 15,976 15,987 16,414 15,645 16,199 16,588 16,954 12,036 11,986 12,173 12,479 5,258 5,372 5,401 5,431 Monthly data, seasonally adjusted, 130, ,915 21, ,841 14, , , ,204 21, ,897 14, , , ,516 21, ,913 14, , , ,787 21, ,949 14, , , ,908 21, ,955 14, , , ,976 21, ,965 14, , , ,105 21, ,985 14, , , ,203 21, ,998 14, , , ,462 21, ,043 14, , , ,588 21, ,060 14, , , ,749 22, ,086 14, ,427 25,367 25,441 25,481 25,511 25, ,555 25,581 25,621 25, ,136 3,142 3,146 3, ,135 3,127 3,131 3,133 3,127 7,997 8,005 8,021 8,037 8,051 8,043 8,058 8,083 8,093 8,107 8,128 16,153 16,184 16,305 16,384 16,415 16,453 16,470 16,514 16,614 16,611 16,674 16,787 16,833 16,871 16,913 16,936 16,963 17,010 17,019 17,081 17,108 17,142 12,367 12,412 12,443 12,474 12,486 12,497 12,508 12,522 12,546 12,571 12,589 5,402 5,420 5,428 5,434 5,443 5,438 5,441 5,436 5,434 5,441 5, , ,859 22, ,086 14, , , ,088 22, ,116 14, ,783 25,647 25,686 3,120 3,118 8,149 8,161 16,698 16,779 17,175 17,193 12,612 12,635 5,453 5,456 1 Data include Alaska and Hawaii beginning in This inclusion resulted in an increase of 212,000 (0.4 percent) in the nonfarm total for the March 1959 benchmark month. p = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, a unadjusted data (beginning April ) and all seasonally adjusted data (beginning January 2001) are subject to revision.

59 B-2. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry sector, 1964 to date Total private Goods-producing Natural resources and mining Construction Year and month Weekly hours Hourly earnings Weekly earnings Weekly hours Hourly earnings Weekly earnings Weekly hours Hourly earnings Weekly earnings Weekly hours Hourly earnings Weekly earnings Annual averages $2.53 $ $2.53 $ $2.76 $ $3.08 $ J ! , i I ! ! J ] H J Monthly data, not : seasonally adjusted : February March April May June July August.j September October November December : January p February p See footnotes at end of table,.

60 B-2 Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industrv J sector, 1964 to date Continued Manufc icturing Durable goods Nondurable goods Year and month Weekly hours Hourly earnings Hourly earnings, excluding overtime Weekly earnings Weekly hours Hourly earnings Hourly earnings, excluding overtime Weekly earnings Weekly hours Hourly earnings Hourly earnings, excluding overtime Weekly earnings Annual averages $2.41 $2.32 $ $2.65 $2.55 $ $2.06 $1.99 $ Monthly data, not seasonally adjusted : February March April May June July August September October November December : January p February* See footnotes at end of table.

61 B-2. Average hours and earnings»f production or nonsupervisory workers 1 on private nonfarm payrolls by major industry sector, 1964 to date Continued Year and month Private service-providing Trade, transportation, and utilities Information Financial activities Weekly Hourly Weekly Weekly Hourly Weekly Weekly Hourly Weekly Weekly Hourly Weekly hours earnings earnings hours earnings earnings hours earnings earnings hours earnings earnings Annual averages $2.53 $ $2.85 $ $4.35 $ $2.29 $ J J , j J I ! I i ! ! Mi i nt ilv data, not seasonally adjusted : February March April May June July August September October November December : January February p See footnotes at end of table.

62 B-2. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industrv 7 sector, 1964 to date Continued Professional and business services Education and health services Leisure and hospitality Other services Weekly hours Hourly earnings Weekly earnings Weekly hours Hourly earnings Weekly earnings Weekly hours Hourly earnings Weekly earnings Weekly hours Hourly earnings Annual averages 37.4 $3.17 $ $2.01 $ $1.06 $ $1.14 $ , Monthly data, not seasonally adjusted Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. p = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all unadjusted data from April forward are subject to revision.

63 (In thousands) Industry 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P P Total nonfarm 130, , ,123 " 131, , , , , , , , ,843 Total private 108, , , , , , , , , , , ,088 Goods-producing 21,699 21,773 21,825 21,888? 11,890 21,902 21,946 21,947 21,982 21,996 22,022 22,005 22,060 Natural resources and mining Logging Mining Oil and gas extraction , Mining, except oil and gas Coal mining Support activities for mining Construction 6,841 6,897 6,913 6,949 6,955 6,965 6,985 6,998 7,043 7,060 7,086 7,086 7,116 Construction of buildings 1, , , , , , , , , , , , ,693.3 Residential building Nonresidential building Heavy and civil engineering construction (J Specialty trade contractors 4, , , ,423.o 4,, , , , , , , , ,515.4 Residential specialty trade contractors 2, , , , , , , , , , , ,140.2 Nonresidential specialty trade contractors... 2, , , , , , , , , , , , ,375.2 Manufacturing 14,281 14,291 14,323 14,34' ' 4,344 14,341 14,366 14,352 14,344 14,337 14,334 14,314 14,334 Durable goods 8,864 8,873 8,902 8,92 3,931 8,926 8,965 8,957 8,960 8,954 8,957 8,945 8,968 Wood products > Nonmetallic mineral products , Primary metals Fabricated metal products 1, , , ,496.. > 1, , , , , , , , ,517.5 Machinery 1, , , ,140.; 1, , , , , , , , ,147.0 Computer and electronic products 1 1, , , , , , , , , , , , ,328.3 Computer and peripheral equipment Communications equipment Semiconductors and electronic components , Electronic instruments Electrical equipment and appliances Transportation equipment 1, , , ,763, , , , , , , , ,776.8 Motor vehicles and parts , , , , , , , , , , , , ,104.5 Furniture and related products , Miscellaneous manufacturing Nondurable goods 5,417 5,418 5,421 5,42:2 5,413 5,415 5,401 5,395 5,384 5,383 5,377 5,369 5,366 Food manufacturing 1, , , ,501,8 1, , , , , , , , ,505.8 Beverages and tobacco products Textile mills Textile product mills Apparel Leather and allied products Paper and paper products Printing and related support activities Petroleum and coal products Chemicals , Plastics and rubber products Service-providing 108, , , , , , , , , , , , ,783 Private service-providing... 87,216 87,431 87,691 87,899 88,018 88,074 88,159 88,256 88,480 88,592 88,727 88,854 89,028

64 (In thousands) Industry 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P P Trade, transportation, and utilities 25,367 25,441 25,481 25,511 25,536 25,536 25,537 25,555 25,581 25,621 25,620 25,647 25,686 Wholesale trade 5, , , , , , , , , , , , ,682.2 Durable goods 2, , , , , , , , , , , , ,967.9 Nondurable goods 2, , , , , , , , , , , , ,004.8 Electronic markets and agents and brokers Retail trade 14, , , , , , , , , , , , ,112.4 Motor vehicle and parts dealers 1 1, , , , , , , , , , , , ,911.0 Automobile dealers 1, , , , , , , , , , , , ,249.4 Furniture and home furnishings stores Electronics and appliance stores Building material and garden supply stores 1, , , , , , , , , , , , ,250.3 Food and beverage stores 2, , , , , , , , , , , , ,826.2 Health and personal care stores Gasoline stations Clothing and clothing accessories stores 1, , , , , , , , , , , , ,383.1 Sporting goods, hobby, book, and music stores General merchandise stores 1 2, , , , , , , , , , , , ,867.0 Department stores 1, , , , , , , , , , , , ,622.4 Miscellaneous store retailers Nonstore retailers Transportation and warehousing 4, , , , , , , , , , , , ,314.8 Air transportation Rail transportation Water transportation Truck transportation 1, , , , , , , , , , , , ,378.5 Transit and ground passenger transportation Pipeline transportation Scenic and sightseeing transportation Support activities for transportation Couriers and messengers Warehousing and storage Utilities information 3,143 3,136 3,142 3,146 3,151 3,144 3,135 3,127 3,131 3,133 3,127 3,120 3,118 Publishing industries, except Internet Motion picture and sound recording industries Broadcasting, except Internet Internet publishing and broadcasting Telecommunications 1, , , , , , , , , , , , ,027.7 ISPs, search portals, and data processing Other information services Financial activities 7,997 8,005 8,021 8,037 8,051 8,043 8,058 8,083 8,093 8,107 8,128 8,149 8,161 Finance and insurance 5, , , , , , , , , , , , ,036.1 Monetary authorities - central bank Credit intermediation and related activities? 2, , , , , , , , , , , , ,896.4 Depository credit intermediation 1 1, , , , , , , , , , , , ,793.5 Commercial banking 1, , , , , , , , , , , , ,307.4

65 (In thousands) Industry 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P P Financial activities-continued Securities, commodity contracts, investments S Insurance carriers and related activities 2, , , , , , , , , , , , ,252.3 Funds, trusts, and other financial vehicles ! Real estate and rental and leasing 2, , , , , , , , , , , , ,125.2 Real estate 1, , , ,413.8 "1, , , , , , , , ,444.6 Rental and leasing services Lessors of nonfmancial intargibie assets Professional and business services 16,153 16,184 16,305 16,384 16,415 16,453 16,470 16,514 16,614 16,611 16,674 16,698 16,779 Professional and technical services 1 6, , , , , ,765.1 ; 6, , , , , , ,895.5 Legal services 1, , , ,160.(1 1, , , , , , , , ,161.0 Accounting and bookkeeping services Architectural and engineering services 1, , , , , , , , , , , , ,294.7 Computer systems design and related services 1, , , , , , , , , , , , ,171.5 Management and technical consulting services Management of companies and enterprises... 1, , , , , , , , , , , , ,728.6 Administrative and waste services 7, , , , , , , , , , , , ,154.4 Administrative and support services , , , ,609.'. 7, , , , , , , , ,825.5 Employment services 1 3, , , ,461.;:! 3, , , , , , , , ,637.8 Temporary help services 2, , , ,385.!) 2, , , , , , , ,514.2 Business support services Services to buildings and dwellings 1, , , , , , , , , , , , ,718.3 Waste management and remediation services Education and health services 16,787 16,833 16,871 16,91, 16,936 16,963 17,010 17,019 17,081 17,108 17,142 17,175 17,193 Educational services 2, , , ,754 ' , , , , , , , ,814.0 Health care and social assistance 14, , , ,158 M , , , , , , , ,379.4 Health care , , , ,031» 1/ , , , , , , , ,203.9 Ambulatory health care services 1 4, , , ,929 ) 4, , , , , , , , ,036.0 Offices of physicians 2, , , ,046 1 :: , , , , , , , ,090.6 Outpatient care centers Home health care services f Hospitals 4, , , ,290 '» 1, , , , , , , , ,334.8 Nursing and residential care facilities , , , , , , , , , , , , ,833.1 Nursing care facilities 1, , , ,575,8 1, , , , , , , , ,572.4 Social assistance 1 2, , , ,12f -T " , , , , , , , ,175.5 Child day care services : ) Leisure and hospitality 12,367 12,412 12,443 12, ,497 12,508 12,522 12,546 12,571 12,589 12,612 12,635 Arts, entertainment, and recreation 1, , , ,831. 1, , , , , , , , ,798.5 Performing arts and spectator sports Museums, historical sites, zoos, and parks Amusements, gambling, and recreation. 1, , , ,356,0 1, , , , , , , , ,333.9 Accommodations and food services 10, , , , , , , , , , , , ,836.2 Accommodations 1, , , ,792 2 I 1, , , , , , , , ,828.0 Food services and drinking places 8, , , ,844,9 8, , , , , , , , ,008.2 Other services 5,402 5,420 5,428 5,434 5,443 5,438 5,441 5,436 5,434 5,441 5,447 5,453 5,456 Repair and maintenance 1, , , , , , , , , , , , ,233.9

66 (In thousands) Industry 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P P Other services-continued Personal and laundry services 1, , , , , , , , , , , , ,278.8 Membership associations and organizations 2, , , , , , , , , , , , ,943.1 Government 21,551 21,582 21,607 21,586 21,571 21,586 21,645 21,677 21,700 21,706 21,700 21,722 21,755 Federal 2,731 2,730 2,745 2,729 2,731 2,726 2,730 2,730 2,723 2,728 2,706 2,717 2,719 Federal, except U.S. Postal Service... 1, , , , , , , , , , , , ,940.2 U.S. Postal Service State government 4,971 4,974 4,975 4,967 4,963 4,976 4,987 5,000 5,007 5,015 5,020 5,028 5,038 State government education 2, , , , , , , , , , , , ,295.5 State government, excluding education 2, , , , , , , , , , , , ,742.6 Local government 13,849 13,878 13,887 13,890 13,877 13,884 13,928 13,947 13,970 13,963 13,974 13,977 13,998 Local government education 7, , , , , , , , , , , , ,833.9 Local government, excluding education 6, , , , , , , , , , , , , ncludes other industries, not shown separately. 2 Includes motor vehicles, motor vehicle bodies and trailers, and motor vehicle parts. 3 Includes ambulatory health care services, hospitals, and nursing and residential care facilities. p = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all seasonally adjusted data from January 2001 forward are subject to revision.

67 (In thousands) Industry 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Total nonfarm... 63,378 63,403 63,484 63,621 6 s?y 63,766 63,675 63,894 63,901 64,026 64,112 64,195 64,298 Total private... 51,039 51,062 51,138 51,258 5 i s 71 51,452 51,467 51,550 51,530 51,651 51,744 51,814 51,905 Goods-producing... 5,103 5,104 5,109 5, ,126 5,130 5,133 5,125 5,123 5,124 5,123 5,123 Natural resources and mfninq.!,,, Mining Construction Manufacturing 4,198 4,197 4,198 4,203 4,208 4,206 4,209 4,210 4,203 4,196 4,195 4,193 4,190 Durable goods 2,262 2,262 2,263 2,266 2,270 2,271 2,273 2,278 2,276 2,272 2,270 2,267 2,268 Nondurable goods 1,936 1,935 1,935 1,937 1,938 1,935 1,936 1,932 1,927 1,924 1,925 1,926 1,922 Service-providing 58,275 58,299 58,375 58,503 58,594 58,640 58,545 58,761 58,776 58,903 58,988 59,072 59,175 Private service-providing 45,936 45,958 46,029 46,140 46,251 46,326 46,337 46,417 46,405 46,528 46,620 46,691 46,782 Trade, transportation, and utilities 10,295 10,298 10,319 10,331 10,347 10,367 10,348 10,358 10,355 10,375 10,413 10,395 10,401 Wholesale trade 1, , , , , , , , , , , , ,715.8 Retail trade 7, , , , , , , , , , , , ,406.4 Transportation and warehousing 1, , , , , , , , , , , , ,129.1 Utilities Information 1,388 1,386 1,379 1,380 1,382 1,382 1,375 1,367 1,362 1,360 1,363 1,372 1,369 Financial activities 4,823 4,824 4,823 4,824 4,829 4,840 4,830 4,838 4,854 4,857 4,870 4,874 4,884 Finance and insurance 3, , , , , , , , , , , , ,904.2 Real estate and rental and leasing Professional and business services 7,299 7,295 7,295 7,335 7,368 7,367 7,383 7,390 7,397 7,425 7,421 7,447 7,470 Professional and technical services. 3, , , , , , , , , , , , ,263.0 Management of companies and enterprises Administrative and waste services 3, , , , , , , , , , , , ,333.4 Education and health services... 12,927 12,942 12,975 13,002 13,033 13,062 13,086 13,141 13,110 13,172 13,193 13,218 13,247 Educational services 1, , , , , , , , , , , , ,704.4 Health care and social assistance 11, , , , , , , , , , , , ,542.9 Leisure and hospitality 6,433 6,437 6,459 6,481 6,503 6,513 6,527 6,526 6,536 6,548 6,568 6,589 6,611 Arts, entertainment, and recreation Accommodations and food services 5, , , , ,671 J 5, , , , , , , ,780.5 Other services 2,771 2,776 2,779 2,787 2,789 2,795 2,788 2,797 2,791 2,791 2,792 2,796 2,800 Government 12,339 12,341 12,346 12,363 12,343 12,314 12,208 12,344 12,371 12,375 12,368 12,381 12,393 Federal 1,172 1,169 1,166 1,173 1,165 1,164 1,167 1,170 1,171 1,165 1,167 1,164 1,164 State government 2,568 2,571 2,569 2,571 2,558 2,541 2,547 2,554 2,565 2,571 2,573 2,574 2,578 Local government 8,599 8,601 8,611 8,619 8,620 8,609 8,494 8,620 8,635 8,639 8,628 8,643 8,651 1 Includes other industries, not shown separately. p = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all seasonally adjusted data from January 2001 forward are subject to revision.

68 B-5. Production or nonsupervisory workers 1 on private nonfarm payrolls by major industry sector and selected industry detail, seasonally adjusted (in thousands) Industry Mar. Apr. May June July Aug. Sept. Oct. Nov. P P 2005 Total private Goods-producing Natural resources and mining... Construction Manufacturing 87,976 88,216 88,565 88,817 88,978 89,087 89,262 89,371 89,648 89,781 89,921 90,072 90,254 15,649 15,699 15,767 15,818 15,822 15,848 15,891 15,887 15,939 15,933 15,957 15,939 15, ,211 5,237 5,264 5,283 5,287 5,303 5,314 5,322 5,383 5,379 5,408 5,399 5,445 10,013 10,028 10,064 10,093 10,095 10,102 10,131 10,117 10,111 10,104 10,097 10,085 10,096 Durable goods Wood products Nonmetallic mineral products... Primary metals Fabricated metal products Machinery Computer and electronic products Electrical equipment and appliances Transportation equipment Motor vehicles and parts?. Furniture and related products Miscellaneous manufacturing.. Nondurable goods Food manufacturing Beverages and tobacco products Textile mills Textile product mills Apparel Leather and allied products... Paper and paper products Printing and related support activities Petroleum and coal products Chemicals Plastics and rubber products... Private service-providing. Trade, transportation, and utilities Wholesale trade.. Retail trade Transportation and warehousing Utilities Informations Financial activities.. Professional and business services Education and health services.. Leisure and hospitality Other seivices 6, , , , , , , , , , , , , , , , , , , , , , , , , , , ,938 1, , ,943 1, , ,950 1, , ,955 1, , ,948 1, , ,958 1, , ,951 1, , ,945 1, , ,939 1, , ,938 1, , ,927 1, , ,922 1, , ,921 1, ,327 72,517 72,798 72,999 73,156 73,239 73,371 73,484 73,709 73,848 73,964 74,133 74, ,133 21,203 21,232 21,277 21,313 21,317 21,331 21,365 21,402 21,453 21,443 21,504 21,540 4, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,341 2,342 2,367 2,381 2,393 2,400 2,407 2,412 2,421 2,421 2,439 2,439 2, ,956 5,958 5,966 5,981 6,002 5,998 6,010 6,027 6,038 6,049 6,065 6,078 6,089 13,020 13,066 13,193 13,266 13,294 13,346 13,378 13,432 13,521 13,525 13,557 13,574 13,626 14,639 14,659 14,699 14,728 14,753 14,775 14,821 14,815 14,871 14,895 14,929 14,966 14,975 10,831 10,867 10,910 10,928 10,949 10,959 10,967 10,981 11,006 11,044 11,060 11,095 11,106 4,407 4,422 4,431 4,438 4,452 4,444 4,457 4,452 4,450 4,461 4,471 4,477 4,481 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing Industries. includes motor vehicles, motor vehicle bodies and trailers, and motor vehicle parts. P = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all seasonally adjusted data from January 2001 forward are subject to revision.

69 (Percent) Time Span Mar. Apr, May June July Aug. Sept. Oct. Nov. Private nonfarm payrolls, 278 industries 1 Over 1-month span: P 57.4 Over 3-month span: , , P 56.7 Over 6-month span: P 61.7 Over 12-month span: , p 60.4 P 64.0 Manufacturing payrolls, 84 industries 1 Over 1-month span: P 43.5 Over 3-month span: , P 44.0 Over 6-month span: P 43.5 Over 12-month span: P Based on seasonally adjusted data for 1-, 3-, 6-month spans and unadjusted data for the 12-month span. p = preliminary. NOTE: Figures are the percent of industries with employment increasing plus one-half of the industries with unchanged employment, where 50 percent indicates an equal balance between industries with increasing and decreasing employment. Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all unadjusted data (beginning April ) and all seasonally adjusted data (beginning January 2001) are subject to revision.

70 (In thousands) State 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Alabama 1, , , , , , , , , , , , ,918.5 Alaska Arizona 2, , , , , , , , , , , , ,424.0 Arkansas 1, , , , , , , , , , , , ,166.0 California 14, , , , , , , , , , , , ,665.5 Colorado 2, , , , , , , , , , , , ,203.1 Connecticut 1, , , , , , , , , , , , ,661.2 Delaware District of Columbia Florida 7, , , , , , , , , , , , ,647.4 Georgia 3, , , , , , , , , , , , ,894.8 Hawaii Idaho Illinois 5, , , , , , , , , , , , ,805.3 Indiana 2, , , , , , , , , , , , ,958.9 Iowa 1, , , , , , , , , , , , ,458.2 Kansas 1, , , , , , , , , , , , ,321.6 Kentucky 1, , , , , , , , , , , , ,806.3 Louisiana 1, , , , , , , , , , , , ,927.6 Maine Maryland 2, , , , , , , , , , , , ,538.6 Massachusetts 3, , , , , , , , , , , , ,191.2 Michigan 4, , , , , , , , , , , , ,381.0 Minnesota 2, , , , , , , , , , , , ,691.4 Mississippi 1, , , , , , , , , , , , ,132.4 Missouri 2, , , , , , , , , , , , ,698.1 Montana Nebraska Nevada 1, , , , , , , , , , , , ,190.4 New Hampshire New Jersey 3, , , , , , , , , , , , ,030.0 New Mexico New York 8, , , , , , , , , , , , ,481.5 North Carolina 3, , , , , , , , , , , , ,857.4 North Dakota Ohio 5, , , , , , , , , , , , ,406.4 Oklahoma 1, , , , , , , , , , , , ,483.5 Oregon 1, , , , , , , , , , , , ,620.6 Pennsylvania 5, , , , , , , , , , , , ,676.7 Rhode Island South Carolina 1, , , , , , , , , , , , ,823.9 South Dakota Tennessee 2, , , , , , , , , , , , ,710.2 Texas 9, , , , , , , , , , , , ,552.5 Utah 1, , , , , , , , , , , , ,119.8 Vermont Virginia 3, , , , , , , , , , , , ,628.3 Washington 2, , , , , , , , , , , , ,723.9 West Virginia Wisconsin 2, , , , , , , , , , , , ,816.7 Wyoming Total 1 See footnotes at end of table.

71 (In thousands) State 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Construction Alabama Alaska / Arizona Arkansas California Colorado Connecticut B Delaware District of Columbia Florida I Georgia Hawaii Idaho , Illinois Indiana Iowa , Kansas , Kentucky Louisiana , Maine , Maryland , Massachusetts , Michigan , Minnesota Mississippi Missouri Montana Nebraska Nevada < New Hampshire <l New Jersey ! New Mexico < New York North Carolina ' i North Dakota mi Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington : West Virginia Wisconsin Wyoming See footnotes at end of table.

72 (In thousands) 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Manufacturing Alabama Alaska ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Arizona Arkansas California 1, , , , , , , , , , , , ,538.3 Colorado Connecticut Delaware ( 3 ) ( 3 ) ( 3 > ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) District of Columbia ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) < 3 ) ( 3 ) < 3 > ( 3 ) ( 3 ) ( 3 ) Florida Georgia ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) (3) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) < 3 ) New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Oregon Pennsylvania Rhode Island , South Carolina ( 3 ) 3 3 ( 3 ) ( 3 ) ( 3 ) South Dakota Tennessee ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) See footnotes at end of table.

73 (In thousands) 2005 btate r Mar. Apr. May June July Aug. Sept. Oct. Nov. Jan P Trade, transportation, and utilities Alabama ! Alaska il! Arizona ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Arkansas ,;;: California 2, , , ,741 i 2, , , , , , , , ,773.4 Colorado ::! Connecticut Delaware o District of Columbia ( 3 ) ( 3 ) ( 3 ) ( 3 ) (3) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Florida 1, , , ,497.!:! 1, , , , , , , , ,518.9 Georgia Hawaii Idaho Illinois 1, , , , , , , , , , , , ,172.9 Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts , Michigan Minnesota , Mississippi , Missouri Montana Nebraska Nevada , New Hampshire , New Jersey New Mexico , New York 1, , , , , , , , , , , ,483.1 North Carolina North Dakota Ohio 1, , , , , , , , , , , ,034.2 Oklahoma , Oregon , Pennsylvania 1, , , U 2 1, , , , , , , , ,127.0 Rhode Island ! I South Carolina ; South Dakota Tennessee Texas 1, , , , , , , , , , , , ,958.5 Utah Vermont < 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Virginia Washington West Virginia Wisconsin S Wyoming See footnotes at end of table.

74 (In thousands) 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Financial activities Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Florida Georgia Hawaii ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Idaho ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) < 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Illinois Indiana Iowa Kansas ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi ( 3 ) ( 3 ) < 3 ) ( 3 ) < 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Vermont ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Virginia Washington West Virginia Wisconsin Wyoming ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) < 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) See footnotes at end of table.

75 (In thousands) otate 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Professional and business services Alabama ( 3 ) ( 3 ) ( 3 ) ( 3 ) < 3 > ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Alaska Arizona Arkansas California 2, , , , , , , , , , , , ,131.9 Colorado Connecticut Delaware District of Columbia Florida 1, , , ,279,4 1, , , , , , , , ,338.5 Georgia Hawaii ( 3 ) ( 3 ) ( 3 ) ( 3 ) (3) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) < 3 ) ( 3 ) ( 3 ) Idaho S Illinois Indiana Iowa ) Kansas ( 3 ) ( 3 ) ( 3 ) ( 3 ) (3) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi ( 3 ) ( 3 ) ( 3 ) ( 3 ) (3) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Missouri Montana Nebraska Nevada New Hampshire New Jersey , New Mexico , New York 1, , , , , , , , , , , , ,056.9 North Carolina , North Dakota , Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina 3 3 > 3 3 ( 3 ) ( 3 ) 3 3 South Dakota ( 3 ) ( 3 ) ( 3 ) ( 3 ) < 3 > ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Tennessee ( Texas 1, , , , , , , , , , , , ,094.2 Utah " Vermont Virginia Washington West Virginia Wisconsin Wyoming See footnotes at end of table.

76 (In thousands) 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Education and health services Alabama ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Alaska Arizona Arkansas California 1, , , , , , , , , , , , ,574.8 Colorado Connecticut ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Delaware District of Columbia ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Florida Georgia ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Hawaii Idaho ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Illinois Indiana Iowa Kansas ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Missouri Montana Nebraska Nevada New Hampshire ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) New Jersey New Mexico New York 1, , , , , , , , , , , , ,537.7 North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania , , , ,009.5 Rhode Island South Carolina South Dakota Tennessee ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Texas 1, , , , , , , , , , , , ,159.0 Utah Vermont ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) Virginia Washington West Virginia Wisconsin Wyoming ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) See footnotes at end of table.

77 (In thousands) btate 2005 Mar. Apr. I May June July Aug. Sept. Oct. Nov. P Leisure and hospitality Alabama ] Alaska Arizona ' Arkansas " California 1, , , ,4330 1, , , , , , , , ,468.8 Colorado Connecticut Delaware District of Columbia Florida ! 848, Georgia Hawaii Idaho Illinois Indiana Iowa ( 3 ) ( 3 ) ( 3 ) ( 3 ) < 3 > ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) (3) Kansas Kentucky Louisiana Maine Maryland : !:! Massachusetts ' Michigan Minnesota Mississippi Missouri i > Montana ! Nebraska ':l Nevada New Hampshire New Jersey IS New Mexico New York North Carolina i North Dakota Ohio Oklahoma , Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas , Utah Vermont ( 3 ) (3) ( 3 ) ( 3 ) (3) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 3 > ( 3 ) Virginia , Washington West Virginia Wisconsin Wyoming See footnotes at end of table.

78 (In thousands) State 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Government Alabama Alaska Arizona Arkansas California 2, , , , , , , , , , , , ,383.2 Colorado Connecticut Delaware District of Columbia Florida 1, , , , , , , , , , , , ,079.5 Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine ; Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York 1, , , , , , , , , , , , ,484.9 North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas 1, , , , , , , , , , , , ,666.3 Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming Includes natural resources and mining, information, and other services, not shown separately. 2 Natural resources and mining is combined with construction. 3 This series is not published seasonally adjusted because the seasonal component, which is small relative to the trend-cycle and irregular components, cannot be separated with sufficient precision. P = preliminary. NOTE: Data have been revised to reflect benchmarks and updated seasonal adjustment factors. Seasonally adjusted data from January 2000 for most states are subject to revision.

79 B-8. Average weekly hours of production or nonsupervisory w jrkers 1 on private nonfarm payrolls by major industry sector and selected Industry detail, seasonally adjusted Industry 2005 Mar. Apr. Way June July Aug. Sept. Oct. Nov. P P Total private i Goods-producing Natural resources and mining , Construction manufacturing Overtime hours Durable goods Overtime hours Wood products Nonmetalhc mineral products Primary metals '43, Fabricated metal products Machinery , Computer and electronic products Electrical equipment and appliances Transportation equipment , Motor vehicles and parts Furniture and related products , Miscellaneous manufacturing Nondurable goods Overtime hours ,A Food manufacturing , Beverages and tobacco products , Textile mills Textile product mills Apparel Leather and allied products Paper and paper products Printing and related support activities Petroleum and coal products I Chemicals Plastics and rubber products Private service-providing , Trade, transportation, and utilities Wholesale trade Retail trade Transportation and warehousing Utilities Information Financial activities Professional and business services Education and health services Leisure and hospitality Other services Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. includes motor vehicles, motor vehicle bodies and trailers, and motor vehicle parts. p = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introducted with the release of January 2006 estimates, all seasonally adjusted data from January 2001 forward are subject to revision.

80 B-9. Indexes of aggregate weekly hours of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry sector and selected industry detail, seasonally adjusted (2002=100) Industry 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. " 3 P Total private Goods-producing Natural resources and mining Construction Manufacturing Durable goods Wood products Nonrnetallic mineral products Primary metals Fabricated metal products Machinery Computer and electronic products Electrical equipment and appliances Transportation equipment Motor vehicles and parts Furniture and related products Miscellaneous manufacturing Nondurable goods Food manufacturing Beverages and tobacco products Textile mills Textile product mills Apparel Leather and allied products Paper and paper products Printing and related support activities Petroleum and coal products Chemicals Plastics and rubber products Private service-providing Trade, transportation, and utilities Wholesale trade Retail trade Transportation and warehousing Utilities Information Financial activities Professional and business services Education and health services Leisure and hospitality Other services I 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. includes motor vehicles, motor vehicle bodies and trailers, and motor vehicle parts. p = preliminary. NOTE: The indexes of aggregate weekly hours are calculated by dividing the current month's estimates of aggregate hours by the corresponding 2002 annual average levels. Aggregate hours estimates are the product of estimates of average weekly hours and production or nonsupervisory work employment. Data are currently projected from March benchmark levels. When more recent benchmark data are introducted with the release of January 2006 estimates, all seasonally adjusted data from January 2001 forward are subject to revision.

81 B-10. Hours of wage and salary workers on nonfarm payrolls by major industry, quarterly, seasonally adjusted Millions of hoy ~s (a nnual rate) 1 Percent change (annual rate) Industry I V 2005 I I to 2005 I IV to 2005 I Total 225, , , Private sector 184,594 1* , Natural resources and mining 1, , Construction 13, , Manufacturing 28,058 2 o: 27, Durable goods 17,606 1 f,49:< 17, Nondurable qoods 10,452 1 ),c.09 10, Trade, transportation, and utilities... 42,593 ^ , Information.. 5,620 >,( 3:. 5, Financial activities 13,645 1 V>65 14, Professional and business services 27,363 2 J,031 28, Education and health services 27,216 5 r',l 3; 28, Leisure and hospitality 16,392 1,( 4-16, Other services 8,473 U 5E 8, Government 40,989 ^ 7 r J 41, Total hours at work for 1 week in the month, seasonally adjusted, multiplied by 52. r = revised. p = preliminary. NOTE: Data refer to hours of all employees production workers, nonsupervisory workers, and salaried workers and are based largely on establishment data. See 3LS Handbook of Methods, BLS Bulletin 2490, chapter 10, "Productivity Measures: Business Sector and Major Subsectors." Beginning with the August issue of Employment and Earnings, these hours measures are presented on a quarterly basis, and incorporate both a shift from hours paid to hours at work and new estimates of the hours worked by supervisory and nonproduction workers. These changes are described in "Alternative measures of supervisory employee hours and productivity growth" in the April issue of the Monthly Labor Review, available on the Internet at http ://www. bls.gov/opub/m 1 r//04/ art2fu H.pdf SOURCE: Office of Productivity and Technology ( ). Historical data for these series also are available on the Internet at the following address: ftp://ftp.bls.gov/pub/special.requests/opt/tableb10.txt

82 B-11. Average hourly and weekly earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry sector and selected industry detail, seasonally adjusted Industry 2005 Mar. Apr. May J June July Aug. Sept. Oct. Nov. P P Average hourly earnings Total private (in current dollars) $15.51 $15.54 $15.58 $15.62 $15.64 $15.70 $15.74 $15.77 $15.81 $15.82 $15.85 $15.90 $15.90 Goods-producing Natural resources and mining Construction Manufacturing Excluding overtime Durable goods Nondurable goods Private service-providing Trade, transportation, and utilities Wholesale trade Retail trade Transportation and warehousing Utilities Information Financial activities Professional and business services Education and health services Leisure and hospitality Other services Total private (in constant (1982) dollars) Goods-producing Private service-providing O ( 4 ) Average weekly earnings Total private (in current dollars) $ $ $ $ $ $ $ $ $ $ $ $ $ Goods-producing Natural resources and mining Construction Manufacturing Durable goods Nondurable goods Private service-providing Trade, transportation, and utilities Wholesale trade Retail trade Transportation and warehousing Utilities 1, , , , , , , , , , , , , Information Financial activities Professional and business services Education and health services Leisure and hospitality Other services Total private (in constant (1982) dollars) Goods-producing ( 4 ) Private service-providing ( 4 ) Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 2 Derived by asssuming that overtime hours are paid at the rate of time and one-half. 3 The Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W) is used to deflate these series. Data not available. p = preliminary NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all seasonally adjusted data from January 2001 forward are subject to revision.

83 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Total nonfarm 131, , , , ,330 Total private 109, , , , ,270 88,976 86,141 90,367 88,203 88,556 Goods-producing 21,884 21,161 21,924 21,426 21,479 15,823 15,138 15,872 15,417 15,458 Natural resources and mining Logging Mining Oil and gas extraction Mining, except oil and gas Coal mining Bituminous coal and lignite surface mining Bituminous coal underground mining and anthracite mining Metal ore mining , Nonmetallic mineral mining and quarrying Stone mining and quarrying Crushed and broken limestone mining Other stone mining and quarrying ,3, Sand, gravel, clay, and refractory mining Construction sand and gravel mining Other nonmetallic mineral mining Support activities for mining Support activities for oil and gas operations Construction 6,964 6,431 5,984 6,654 6,657 5,300 4,804 5,319 5,003 5,003 Construction of buildings 236 1, , , , , , , , , Residential building New single-family general contractors C New multifamily general contractors Residential remodelers Nonresidential building Industrial building Commercial building Heavy and civil engineering construction Utility system construction Water and sewer system construction Oil and gas pipeline construction ' Power and communication system construction Land subdivision Highway, street, and bridge construction Other heavy construction Specialty trade contractors 238 4, , , , , , , , , Residential specialty trade contractors... part 238 2, , , , , Nonresidential specialty trade contractors.. part 238 2, , , , , Building foundation and ex.erior contractors , ,003.9 Residential building foundation and exterior contractors part Nonresidential specialty trade contractors part Poured concrete structure contractors Steel and precast concrete contractors Framing contractors

84 NOT SEASONALLY ADJUSTED B-12. Employees on nonfarm payrolls by detailed industry Continued (in thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Construction-Continued Masonry contractors Glass and glazing contractors Roofing contractors Siding contractors Other building exterior contractors Building equipment contractors , , , , , , , ,410.7 Residential building equipment contractors part Nonresidential building equipment contractors part , , , ,083.0 Electrical contractors Plumbing and HVAC contractors Other building equipment contractors Building finishing contractors Residential building finishing contractors part Nonresidential building finishing contractors part Drywall and insulation contractors Fainting and wall covering contractors Flooring contractors Tile and terrazzo contractors Finish carpentry contractors Other building finishing contractors Other specialty trade contractors Other residential trade contractors part Other nonresidential trade contractors.. part Site preparation contractors All other specialty trade contractors Manufacturing 14,329 14,171 14,338 14,181 14,227 10,083 9,925 10,102 9,971 10,012 Durable goods 8,923 8,797 8,968 8,881 8,916 6,137 6,025 6,180 6,110 6,138 Wood products Sawmills and wood preservation Plywood and engineered wood products Hardwood and softwood veneer and plywood , Engineered wood members and trusses , Other wood products Millwork Wood windows and doors Cut stock, resawing lumber, planing, and other millwork, including flooring , Wood containers and pallets All other wood products , Manufactured and mobile homes Nonmetallic mineral products Clay products and refractories Pottery, ceramics, and plumbing fixtures , Clay building material and refractories Glass and glass products Flat glass and other pressed and blown glass and glassware , Glass containers > - - Glass products made of purchased glass Cement and concrete products Fteady-mix concrete Other cement and concrete products ,3, Lime, gypsum, and other nonmetallic - - mineral products 3274, Primary metals Iron and steel mills and ferroalloy production

85 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Durable goods-continued Steel products from purchased steel Iron, steel pipe, and tube from purchase steel Rolling and drawing of purchased steel Rolled steel shapes Alumina and aluminum production Other nonferrous metal production Rolled, drawn, extruded, and alloyed copper Nonferrous metal, except CU and AL, Foundries Ferrous metal foundries Iron foundries i) Steel foundries , Nonferrous metal foundries shaping Fabricated metal products 332 1, , , , , , , , , ,120.9 Forging and stamping , Iron and steel forging Metal stamping Cutlery and hand tools Hand and edge tools Architectural and structural metals ,5 379, Plate work and fabricated structural products , Prefabricated metal buildings and components i Fabricated structural metal products J Plate work , Ornamental and architectural metal products , Metal windows and doors , Sheet metal work , Ornamental and architectural metal work " Boilers, tanks, and shipping containers Hardware Spring and wire products Machine shops and threaded products Machine shops ! Turned products and screws, nuts, - and bolts. Precision turned products C Bolts, nuts, screws, rivets, and washers ; metals Coating, engraving, and heat treating Metal heat treating and coating and nonprecious engraving , Electroplating, anodizing, and coloring metals , Other fabricated metal products...: Metal valves Fluid power valves and hose fittings ,8 I Plumbing fixture fittings and trims Industrial valves and other meial valves and pipe fittings , All other fabricated metal products Ball and roller bearinqs Small arms,, ammunition, and other ordnance and accessories ,3,4, Miscellaneous fabricated metal products ,7,8, Machinery 333 1, ,126.,3 1, , , Agricultural, construction, and mining machinery

86 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg p Durable goods-continued Agricultural implements Farm machinery and equipment Mining and oil and gas field Industrial machinery Commercial and service industry machinery Office machinery Photographic and photocopying equipment Miscellaneous commercial and service industry machinery HVAC and commercial refrigeration ,2,4, equipment AC, refrigeration, and forced air , heating Metalworking machinery Industrial molds Metal cutting and forming machine tools , Special tools, dies, jigs, and fixtures Miscellaneous metalworking machinery ,6, Turbine and power transmission equipment Turbine and turbine generator set units Power transmission and miscellaneous engine equipment ,3, Other general purpose machinery Pumps and compressors Air and gas compressors Pumps and pumping equipment, including measuring and dispensing , Material handling equipment Conveyor and conveying equipment All other general purpose machinery Computer and electronic products 334 1, , , , , Computer and peripheral equipment Electronic computers Computer storage devices Computer terminals and other computer peripheral equipment , Communications equipment Telephone apparatus Broadcast and wireless Semiconductors and electronic communications equipment Audio and video equipment components Electron tubes Bare printed circuit boards Semiconductors and related devices Electronic capacitors Printed circuit assemblies Electronic connectors and misc Electromedical apparatus Search, detection, and navigation electronic components Electronic instruments ,6,7, instruments Automatic environmental controls Industrial process variable instruments instruments Electricity and signal testing

87 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Durable goods-continued Irradiation apparatus Miscellaneous electronic instruments Magnetic media manufacturing and ,6,8, reproduction , Electrical equipment and appliances Electric lighting equipment f (» Electric lamp bulbs and parts Lighting fixtures Household appliances Small electrical appliances I Electric housewares and household fans Major appliances Household refrigerators and home freezers Electrical equipment Electric power and specialty transformers Motors and generators Switchgear and switchboard apparatus Relays and industrial controls Other electrical equipment and components Batteries Communication and energy wires and cables Wiring devices Current-carrying wiring devices All other electrical equipment and components * Transportation equipment 336 1, ,749. i 1, , , , , , , ,268.7 Motor vehicles and parts 3361,2,3 1, , , , , Motor vehicles Automobiles and light trucks Automobiles Light trucks and utility vehicles Heavy duty trucks Motor vehicle bodies and trailers Motor vehicle bodies , Truck trailers Travel trailers and campers Motor vehicle parts Motor vehicle gasoline engine and parts , Carburetors, pistons, rings, and valves Gasoline engine and engine parts Motor vehicle electric equipment Vehicular lighting equipment Other motor vehicle electric equipment , Motor vehicle steering and suspension parts Motor vehicle brake systems Motor vehicle power train components Motor vehicle seating and interior trim Motor vehicle metal stamping Other motor vehicle parts All other motor vehicle parts Aerospace products and parts Aircraft Aircraft engines and engine parts Other aircraft parts and equipment , Guided missiles, space vehicles, and parts ,5, ,

88 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Durable goods-continued Railroad rolling stock Ship and boat building Ship building and repairing Boat building Other transportation equipment Furniture and related products Household and institutional furniture Wood kitchen cabinets and countertops Other household and institutional furniture Upholstered household furniture Nonupholstered wood household furniture Miscellaneous household and institutional furniture ,5,7, Office furniture and fixtures Wood office furniture and custom architectural woodwork and millwork , Office furniture, except wood Showcases, partitions, shelving, and lockers Other furniture-related products Miscellaneous manufacturing Medical equipment and supplies Surgical and medical instruments Surgical appliances and supplies Dental laboratories Other miscellaneous manufacturing Jewelry and silverware Sporting and athletic goods Dolls, toys, and games Office supplies, except paper Signs All other miscellaneous manufacturing Nondurable goods 5,406 5,374 5,370 5,300 5,311 3,945 3,900 3,922 3,861 3,874 Food manufacturing 311 1, , , , , , , , , ,173.1 Animal food Grain and oilseed milling Flour milling, malt, starch, and vegetable oil 31121, Breakfast cereal Sugar and confectionery products Sugar Chocolate confectioneries 31132, Fruit and vegetable preserving and specialty Frozen food Frozen fruits and vegetables Frozen specialty food Fruit and vegetable canning and drying Fruit and vegetable canning Specialty canning Dried and dehydrated food Dairy products Dairy products, except frozen Fluid milk Ice cream and frozen desserts Animal slaughtering and processing Animal, except poultry, slaughtering Meat processed from carcasses, and rendering and meat byproduct processing , Poultry processing Seafood product preparation and packaging

89 (in thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Nondurable goods-continued Bakeries and tortilla manufacturing !'! Bread ana oakery proaucts : Retail bakeries , Commercial bakeries and frozen cakes and other pastry products , ; Cookies, crackers, pasta, and tortillas , A Other food products ,: Snack food :: Miscellaneous food products ,3,4, ; Beverages and tobacco products Beverages 'I Soft drinks and ice : Soft drinks Breweries, wineries, and distilleries ,3, ! Tobacco and tobacco products 'I: Textile mills Fiber, yarn, and thread mills :! Fabric mills ::! Broadwoven fabric mills ;: Textile and fabric finishing mills ii Broadwoven fabric finishing mills il Textile product mills » Textile furnishings mills Carpet and rug mills Curtain and linen mills ; Other textile product mills '! Textile bag and canvas mills All other textile product mills * Apparel Apparel knitting mills Hosiery and sock mills ' Sheer hosiery mills Other hosien/ and sock mills ' Cut and sew apparel J: Cut and sew apparel contractors ! I Men's cut and sew apparel: contractors Women's cut and sew apparel j contractors...j Men's cut and sew apparel Women's cut and sew apparel Other cut and sew apparel Accessories and other apparel Leather and allied products Footwear Leather and hide tanning and finishing 22 J - -- and other leather products 3161, Paper and paper products Pulp, paper, and paperboard mills , Pulp mills and paper mills 32211, , Paperboard mills , Converted paper products Paperboard containers Corrugated and solid fiber boxes i Folding paperboard boxes ' Miscellaneous paperboard containers ,4, paper Paper bags and coated and treated :J Coated and laminated package materials and paper , ii Miscellaneous coated and treated paper and paper bags ,4,5, ? Stationery products Other converted paper products

90 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Nondurable goods-continued Printing and related support activities Commercial lithograph printing Commercial flexographic printing Commercial screen printing Quick printing Manifold business forms printing Commercial gravure and misc ,5,7,8, 25.0 commercial printing Support activities for printing Petroleum and coal products Petroleum refineries Asphalt paving and roofing materials and other petroleum and coal products , Chemicals Basic chemicals Petrochemicals and industrial gases , Synthetic dyes and pigments Other basic inorganic chemicals Other basic organic chemicals Resin, rubber, and artificial fibers Resin and synthetic rubber Plastics material and resin Synthetic rubber Agricultural chemicals Pharmaceuticals and medicines < Pharmaceutical preparations Miscellaneous medicinal and biological products ,3, Paints, coatings, and adhesives Paints and coatings Soaps, cleaning compounds, and toiletries Soaps and cleaning compounds Polishes and other sanitation goods and surface active agents , Toilet preparations Other chemical products and preparations Plastics and rubber products Plastics products Plastics packaging materials, film, and sheet Nonpackaging plastics film and sheet Plastics pipe, fittings, and profile shapes Unlaminated plastics profile shapes Plastics pipe and pipe fittings Foam products 32614, Plastics bottles and laminated plastics plate, sheet, and shapes 32613, Other plastics products Rubber products Tires Rubber and plastics hose and belting Other rubber products Rubber products for mechanical use All other rubber products Service-providing 109, , , , , Private service-providing 87,978 85,761 89,219 87,421 87,791 73,152 71,003 74,495 72,786 73,098 Trade, transportation, and utilities 25,510 25,165 26,250 25,461 25,311 21,298 20,933 22,080 21,327 21,179 Wholesale trade 42 5, , , , , , , , , ,457.8 Durable goods 423 2, , , , , , , , ,339.3 Motor vehicles and parts

91 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Wholesale trade-continued Motor vehicles New motor vehicle parts , Furniture and furnishings Furniture Home furnishings Lumber and construction supplies Lumber and wood , Masonry materials Roofing, siding, and other construction materials 42333, Commercial equipment > Office equipment i Computer and software > Medical equipment Miscellaneous professional and commercial equipment ,4,6, Metals and minerals Electric goods T Electrical equipment and wiring Electric appliances and other electronic parts 42362, Hardware and plumbing o Hardware Plumbing equipment HVAC and refrigeration equipment 42373, : Machinery and supplies Construction equipment ' Farm and garden equipment ; Industrial machinery Industrial supplies Service establishment equipment Other transportation goods Miscellaneous durable goods 'I Sporting goods , Recyclable materials ! 94, Jewelry , Toy, hobby, and other durable goods , , Nondurable goods 424 2, ,9767 2, , , , , , ,570.8 Paper and paper products , Printing and writing paper and office supplies 42411, Industrial paper Druggists' goods , Apparel and piece goods , Men's and boys' clothing Women's and children's clothing Grocery and related products S General line grocery C Packaged frozen food , Fruits and vegetables Farm product raw materials Grains and field beans Chemicals Other chemicals Petroleum Alcoholic beverages Beer and ale Wine and spirits Misc. nondurable goods Farm supplies Books and periodicals Nursery stock and florists' supplies , Tobacco and tobacco products Paint, painting supplies, and other nondurable goods 42495, Electronic markets and agents and brokers

92 (in thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Wholesale trade-continued Business to business electronic markets Wholesale trade agents and brokers Retail trade 44,45 15, , , , , , , , , ,591.0 Motor vehicle and parts dealers 441 1, , , , , , , , ,544.0 Automobile dealers , , , , , , , , ,030.3 Mew car dealers , , , , Used car dealers Other motor vehicle dealers Recreational vehicle dealers Motorcycle, boat, and other vehicle dealers Auto parts, accessories, and tire stores Automotive parts and accessories stores Tire dealers Furniture and home furnishings stores Furniture stores Home furnishings stores Floor covering stores Other home furnishings stores Electronics and appliance stores Appliance, TV, and other electronics stores Household appliance stores Radio, TV, and other electronics stores Computer, software, camera, and photography supply stores 44312, Building material and garden supply stores 444 1, , , , , , , Building material and supplies dealers , , , , Home centers Paint and wallpaper stores Hardware stores Other building material dealers Lav/n and garden equipment and supplies stores Outdoor power equipment stores Nursery, garden, and farm supply stores Food and beverage stores 445 2, , , , , , , , ,480.8 Grocery stores , , , , , , , ,180.7 Supermarkets and other grocery stores , , , , , , , ,066.7 Convenience stores Specialty food stores Meat markets and fish and seafood markets 44521, Firuit and vegetable markets Other specialty food stores >> Beer, wine, and liquor stores Health and personal care stores Pharmacies and drug stores Cosmetic and beauty supply stores > -... Optical goods stores Other health and personal care stores Food (health) supplement stores All other health and personal care stores Gasoline stations Gasoline stations with convenience stores Other gasoline stations

93 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Retail trade-continued Clothing and clothing accessories stores , ,333. 1, , , , , , ,113.2 Clothing stores , ,4 1, , Men's clothinq stores Women's clothing stores , Children's and infants' clothing stores J) Family clothing stores , Clothing accessories stores , Other clothing stores Shoe stores Jewelry, luggage, and leather goods stores , Sporting goods, hobby, book, and music stores " Sporting goods and musical instrument stores I Sporting goods stores r Hobby, toy, and game stores '->> _ Sewing, needlework, and piece goods stores ; Musical instrument and supplies stores..., Book, periodical, and music stores : Book stores and news dealers ' Prerecorded tape, CD, and record stores, General merchandise stores , , , , , , , , ,638.6 Department stores , , , , , , , , , Department stores, except discount Discount department stores Other general merchandise stores , ,213 1, , , , , ,122.1 Warehouse clubs and supercenters All other general merchandise stores i Miscellaneous store retailers... Florists 906 I 104 /, Office supplies, stationery, and gift 406, stationery stores , stores Office. supplies. and Gift, novelty, and souvenir stores Used merchandise stores , Other miscellaneous store retailers , Pet and pet supplies stores Art dealers Manufactured and mobile home dealers All other miscellaneous store retailers c Nonstore retailers ^ Electronic shopping and mail-order houses , Electronic shopping and electronic auctions , Mail-order houses Vending machine operators Direct selling establishments Fuel dealers , Heating oil dealers Liquefied petroleum gas, bottled gas, and other fuel dealers , Other direct selling establishments Transportation arid warehousing... 48,49 4, ,166,2 4, , , , , , , ,672.7 Air transportation Scheduled air transportation Nonscheduled air transportation t Rail transportation Water transportation

94 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Transportation and warehousing-continued Sea, coastal, and Great Lakes 4831 transportation ~ Truck transportation 484 1, , , , , , , , ,178.5 General freight trucking General freight trucking, local General freight trucking, long-distance General freight trucking, long-distance TL General freight trucking, long-distance LTL Specialized freight trucking Used household and office goods moving Other specialized trucking, local Other specialized trucking, long-distance Transit and ground passenger transportation Urban transit systems Interurban and rural bus transportation Taxi and limousine service Taxi service Limousine service School and employee bus transportation Charter bus industry Other ground passenger transportation Pipeline transportation Scenic and sightseeing transportation Support activities for transportation Support activities for air transportation Airport operations Support activities for water transportation Port and harbor operations Marine cargo handling Navigational services and other water transportation support activities 48833, Support activities for road transportation Motor vehicle towing Freight transportation arrangement Support activities for other transportation, including rail 4882, Couriers and messengers Couriers Local messengers and local delivery Warehousing and storage General warehousing and storage Refrigerated warehousing and storage Miscellaneous warehousing and storage 49313, Utilities Power generation and supply Electric power generation Hydroelectric power generation Fossil fuel electric power generation Nuclear and other electric power generation , Electric power transmission and distribution Electric bulk power transmission and control

95 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Utilities-Continued Electric power distribution Natural gas distribution Water, sewage and other systems Information J 3,138 3,125 3,139 3,105 3,099 2,389 2,327 2,456 2,431 2,428 Publishing industries, except Internet Newspaper, book, and directory publishers ' Newspaper publishers Periodical publishers Book publishers Directory and mailing list publishers Other publishers Software publishers < Motion picture and sound recording industries Motion picture and video industries S Motion picture and video production ;:: Motion picture and video exhibition Miscellaneous motion picture and video industries 51212, Sound recording industries Broadcasting, except Internet Radio and television broadcasting Radio broadcasting Television broadcasting Cable and other subscription programming Internet publishing and broadcasting Telecommunications , , , , , Wired telecommunications carriers Wireless telecommunications carriers Cellular and other wireless carriers Telecommunications resellers ) Cable and other program distribution ISPs, search portals, and data processing , i ISPs and web search portals , Data process!nq and related services , Other information services , Financial activities?... 8,052 7,932 8,124 8,088 8,109 6,001 5,912 6,059 6,030 6,043 Finance and insurance 52 5, , , , , , , , , Monetary authorities - central bank Credit intermediation and related activities , , , , , , , , ,094.7 Depository credit intermediation , , , , , , , , , Commercial banking , , , , , Savings institutions Credit unions and other depository credit intermediation , Nondepository credit intermediation Credit card issuing Sales financing Other nondepository credit intermediation , Consumer lending «Real estate credit Miscellaneous nondepository credit intermediation ,4, Activities related to credit intermediation Mortgage and nonmortgage loan brokers Financial transaction processing and clearing

96 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Financial activities-continued Other credit intermediation activities Securities, commodity contracts, investments Securities brokerage Securities and commodity contracts brokerage and exchanges 5231, Other financial investment activities Miscellaneous intermediation Portfolio management Investment advice All other financial investment activities Insurance carriers and related activities 524 2, , , , , , , , ,758.8 Insurance carriers , , , , , , , ,093.0 Direct life and health insurance carriers Direct life insurance carriers Direct health and medical insurance carriers Direct insurers, except life and health Direct property and casualty insurers Direct title insurance and other direct insurance carriers , Reinsurance carriers Insurance agencies, brokerages, and related services Insurance agencies and brokerages Other insurance-related activities Claims adjusting Third-party administration of insurance funds All other insurance-related activities Funds, trusts, and other financial vehicles Insurance and employee benefit funds Other investment pools and funds Real estate and rental and leasing 53 2, , , , , , , , , Real estate 531 1, , , , , , , , , Lessors of real estate Lessors of residential buildings Lessors of nonresidential buildings Miniwarehouse and self-storage unit operators Lessors of other real estate property Offices of real estate agents and brokers Activities related to real estate Real estate property managers Residential property managers Nonresidential property managers Offices of real estate appraisers Other activities related to real estate Rental and leasing services Automotive equipment rental and leasing Passenger car rental and leasing Truck, trailer, and RV rental and leasing Consumer goods rental Video tape and disc rental Miscellaneous consumer goods rental ,2, Home health equipment rental General rental centers Machinery and equipment rental and leasing Heavy machinery rental and leasing

97 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Financial activities-continued Office equipment and other 53242,9 machinery rental and leasinq 53242, Lessors of nonfinancia! intangible assets _ - Professional and business services.. 16,414 15,773 16,660 16,302 16,450 13,306 12,678 13,568 13,201 13,341 Professional and technical seivices 54 6, , , , , , , , , Legal services , , , , , Offices of lawyers , , , , Other legal services Title abstract and settlement offices , Accounting and bookkeeping services , Offices of certified public accountants Tax preparation services Payroll services Other accounting services Architectural and engineering services , , , , , , Architectural services , Landscape architectural services Engineering and drafting services 54133, Building inspection, surveying, and mapping services 54135,6, , Specialized design services > «Interior design services J -- Graphic design services Testing laboratories Computer systems design and related services , , , , Custom computer programming, «j services Computer systems design services , J Computer facilities management services I Other computer-related services Management and technical consulting services Management consulting services Administrative management. Marketing consulting services , consulting services... Human resource consulting services Process and logistics consulting services , services Environmental consulting services G Other technical consulting services , Other management consulting Scientific research and development services , Physical, engineering, and biological research , Advertising and related services Advertising agencies Public relations agencies Social science and humanities research Media buying agencies and media - representatives Direct mail advertising , Advertising material distribution and other advertising services 54187, Other professional and technical services Marketing research and public opinion polling Photographic services , Veterinary services ,

98 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Professional and business services-continued Miscellaneous professional and 54193,9 technical services 54193, Management of companies and enterprises. 55 1, , , , , , , , ,192.1 Offices of bank holding companies and of other holding companies , Managing offices , , , , , , , ,140.4 Administrative and waste services 56 7, , , , , , , , , Administrative and support services 561 7, , , , , , , , ,489.3 Office administrative services Facilities support services Employment services , , , , , , , , ,144.8 Employment placement agencies Temporary help services , , , , , , , , ,225.9 Professional employer organizations Business support services Document preparation services Telephone call centers Telephone answering services Telemarketing bureaus Business service centers Collection agencies Credit bureaus Other business support services Travel arrangement and reservation services Travel agencies Tour operators Other travel arrangement services Investigation and security services Security and armored car services Investigation services Security guards and patrols and armored car services , Security systems services Services to buildings and dwellings , , , , , , , , ,309.4 Exterminating and pest control services Janitorial services Landscaping services Carpet and upholstery cleaning services Other services to buildings and dwellings Other support services Packaging and labeling services » Convention and trade show organizers All other support services Waste management and remediation Waste treatment and disposal Hazardous waste treatment and services Waste collection disposal Nonhazardous waste treatment and disposal ,3, Remediation and other waste services Remediation services Materials recovery facilities and other waste management services 56292, Education and health services 16,954 16,665 17,310 17,057 17,300 14,771 14,538 15,083 14,868 15,066 Educational services 61 2, , , , , Elementary and secondary schools

99 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Education and health services-continued Junior colleges Colleges and universities , , , ,325.1 Business, computer, and management training Business and secretariai schools and computer training 61141, i Management training * Technical and trade schools Other schools and instruction Fine arts schools B ; Sports and recreation instruction Miscellaneous schools and instruction , ,9 ; Educational support services Health care and social assistance 62 14, , , , , , , , ,532.8 Health care 621,2,3 12, ,902,5 12, , , , , , ,660.1 Ambulatory health care services 621 4, ,852 0 I 5, , , , , , ,207.6 Offices of physicians , , , , , , , , ,686.9 Offices of physicians, except mental health , , , , , , , ,652.7 Offices of mental health physicians Offices of dentists , Offices of other health practitioners , Offices of chiropractors , Offices of optometrists Offices of mental health practitioners Offices of specialty therapists Offices of all other health practitioners Offices of podiatrists Offices of miscellaneous health practitioners , » Outpatient care centers , centers Outpatient mental health , Outpatient care centers except mental health C HMO medical centers 67.8 Kidney dialysis centers C Freestanding emergency medical centers ,4 : centers Miscellaneous outpatient care , , Medical and diagnostic laboratories Medical laboratories Diagnostic imaging centers Home health care services Other ambulatory health care services ,0 Ambulance services All other ambulatory health care 811,4 55,5 services Blood and organ banks Miscellaneous ambulatory health care services Hospitals 622 4, , , , , , , , ,958.8 General medical and surgical hospitals , , , , , , , , Psychiatric and substance abuse hospitals Other hospitals Nursing and residential care facilities 623 2, , , , , , , , , Nursing care facilities , , , , , , , , ,408.2 Residential mental health facilities Residential mental retardation facilities Residential mental and substance abuse care Community care facilities for the elderly Continuing care retirement communities

100 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. Education and health services-continued Homes for the elderly Other residential care facilities Social assistance 624 2, , , , , , , , ,872.7 Individual and family services Child and youth services Services for the elderly and disabled Other individual and family services Emergency Community and food other services relief services Community housing, emergency, and 23.4 relief services 62422, Vocational rehabilitation services Child day care services Leisure and hospitality. 12,479 11,760 12,303 12,022 12,107 10,945 10,258 10,787 10,511 10,594 Arts, entertainment, and recreation 71 1, , , , , , , , ,339.2 Performing arts and spectator sports Performing arts companies Musical groups and artists Theater, dance, and other performing arts companies 71111,2, Spectator sports Sports teams and clubs Racetracks Other spectator sports Arts and sports promoters and agents and managers for public figures 7113, Independent artists, writers, and performers Museums, historical sites, zoos, and parks Museums Historical sites Zoos, botanical gardens, nature parks, and similar institutions 71213, Amusements, gambling, and recreation , , , , , , , , Amusement parks and arcades Amusement and theme parks Amusement arcades Gambling industries Casinos, except casino hotels Other gambling industries Other amusement and recreation industries , Golf courses and country clubs Skiing facilities Marinas Fitness and recreational sports centers Bowling centers All other amusement and recreation industries Accommodations and food services 72 10, , , , , , , , , Accommodations 721 1, , , , , , , , ,485.2 Traveler accommodations and other lonqer-term accommodations , , , , , , , ,462.9 Hotels and motels, except casino hotels , , , , , , , ,192.9 Casino hotels Miscellaneous traveler accommodations Bed-and-breakfast inns All other traveler accommodations and rooming and boarding houses , RV parks and recreational camps

101 (In thousands) Industry 2002 NAICS code Avg. /ill employees Production workers 1 Avg. Leisure and hospitality-continued RV parks and campgrounds Recreational and vacation camps Food services and drinking places 722 8, , , , , , , , ,686.7 Full-service restaurants , ,033/ 4, , , , , ,766.7 Limited-service eating places , ,551.d , , , , ,178.7 Limited-service restaurants , ,100/ 3 S , , , , ,784.4 Cafeterias : Snack and nonalcoholic beverage bars Special food services Food service contractors Caterers and mobile food services 72232, Drinking places, alcoholic beverages Other services 5,431 5,341 5,433 5,386 5,415 4,442 4,357 4,462 4,418 4,447 Repair and maintenance 811 1, , , , , Automotive repair and maintenance Automotive mechanical and electrical repair General automotive repair Automotive exhaust system repair Automotive transmission repair Other automotive mechanical and elec. repair Automotive body, interior, and glass repair ' Automotive body and interior repair Automotive glass replacement shops Other automotive repair and maintenance Car washes Auto oil change shops and all other auto repair and maintenance Electronic equipment repair and maintenance Computer and office machine repair Miscellaneous electronic equipment repair and maintenance ,3, Commercial machinery repair and maintenance Household goods repair and maintenance Personal and laundry services 812 1, , , , , , , , ,057.8 Personal care services « Hair, nail, and skin care services Barber shops and beauty salons , _ Nail salons Other personal care services Death care services Funeral homes and funeral services Cemeteries and crematories Dry-cleaning and laundry services Coin-operated laundries and dry cleaners Dry-cleaning and laundry services, except coin-operated «Linen and uniform supply Linen supply Industrial launderers Other personal services Pet care services, except veterinary Photofinishing..J Parking lots and garages All other personal services i Membership associations and organizations 813 2, , , , , , , , ,386.6

102 (In thousands) Industry 2002 NAICS code Avg. All employees Production workers 1 Avg. i 2005P Other services-continued Grantmaking and giving services Grantmaking foundations Voluntary health organizations Other grantmaking and giving services Social advocacy organizations Human rights organizations Environment, conservation, and other social advocacy organizations , Civic and social organizations Professional and similar organizations Business associations Professional organizations Labor unions and similar labor organizations Miscellaneous professional and similar organizations 81394, Government 21,618 21,443 22,044 21,627 22, Federal 2,728 2,707 2,723 2,700 2, Federal, except U.S. Postal Service 1, , , , ,925.4 Federal hospitals Department of Defense U.S. Postal Service Other Federal government 1, , , , State qovernment 4,985 4,885 5,110 4,935 5,148 State government education 2, , , , ,420.0 State government, excluding education,.,, 2, , , , ,727.6 State hospitals State government general administration 1, , , ,843.4 Other State government Local qovernment 13,905 13,851 14,211 13,992 14,209 Local government education 7, , , , ,143.8 Local government, excluding education 6, , , , , Local government utilities Local government transportation Local hospitals Local government general administration 3, , , ,895.6 Other local government 1, , , Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 2 Excludes nonoffice commissioned real estate sales agents. 3 Includes rural mail carriers. - Data not available. p = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all unadjusted data from April forward are subject to revision.

103 (In thousands) Industry Avg. Nov. Total nonfarm 63,762 62,805 64,872 64,936 63,681 Total private 51,426 I 50,421 52,118 52,245 51,231 Goods-producing 5,121 5,046 5,141 5,114 5,048 Natural resources and mining 1. : Mining Construction Manufacturing. 4,202 4,165 4,207 4,193 4,139 Durable goods 2,269 2,254 2,274 2,270 2,254 Nondurable goods 1,933 1,911 1,933 1,923 1,885 Service-providing 58,641 57,759 59,731 59,822 58,633 Private service-providing 46,305 45,375 46,977 47,131 46,183 Trade, transportation, and utilities 10,350 10,254 10,705 10,820 10,363 Wholesale trade 1, , , , ,704.9 Retail trade 7, , , , ,382.8 Transportation and warehousing 1, , , , ,126.1 Utilities Information 1,375 1,381 1,364 1,381 1,361 Financial activities 4,841 4,801 4,862 4,874 4,860 Finance and insurance 3, , , , ,893.4 Real estate and rental and leasing Professional and business services 7,369 7,218 7,456 7,484 7,378 Professional and technical services 3, , , , ,295.3 Management of companies and enterprises Administrative and waste services 3, , , , ,214.2 Education and health services 13,073 12,865 13,342 13,331 13,174 Educational services 1, , , , ,666.4 Health care and social assistance 11, , , , ,507.3 Leisure and hospitality * 6,510 6,111 6,455 6,449 6,279 Arts, entertainment, and recreation Accommodations and food services 5, , , , ,534.2 Other services 2,788 2,745 2,793 2,792 2,768 Government 12,336 12,384 12,754 12,691 12,450 Federal 1,167 1,158 1,164 1,168 1,160 State government 2,564 2,537 2,662 2,633 2,539 Local government 8,605 8,689 8,928 8,890 8,751 1 Includes other industries, not shown separately. levels. When more recent benchmark data are introduced with the p = preliminary. release of January 2006 estimates, all unadjusted data from April NOTE: Data are currently projected from March benchmark forward are subject to revision.

104 (In thousands) State and area Total Natural resources and mining Construction 2005P 2005P 2005P Alabama 1, , , Anniston-Oxford Auburn-Opelika ( 1 ) ( 1 ) ( 1 ) Birmingham-Hoover Decatur ) Dothan > Florence-Muscle Shoals Gadsden Huntsville ( 1 ) Mobile o ( 1 ) ( 1 ) Montgomery ( > Tuscaloosa < > 91.5 ( 1 ) ( 1 ) ( 1 ) Alaska Anchorage Fairbanks Arizona 2, , , Flagstaff ( 1 ) ( 1 ) ( 1 ) Phoenix-Mesa-Scottsdale 1, , , Prescott ( 1 ) ( 1 ) ( 1 ) Tucson Yuma ( 1 ) ( 1 ) ( 1 ) Arkansas 1, , , Fayetteville-Springdale-Rogers O ( l> Fort Smith ( 1 ) ( 1 ) ( 1 ) Hot Springs ( 1 ) ( 1 ) Jonesboro ( 1 ) ( 1 ) ( 1 ) Little Rock-North Little Rock ( 1 ) ( 1 ) ( 1 ) Pine Bluff ( 1 ) ( 1 ) ( 1 ) California 14, , , Bakersfield Chico El Centra ( 1 ) ( 1 ) ( 1 ) Fresno Hanford-Corcoran ( 1 ) ( 1 ) ( 1 ) Los Angeles-Long Beach-Santa Ana 5, , , Madera ( 1 ) Merced O Modesto Napa ( 1 ) ( 1 ) ( 1 ) Oxnard-Thousand Oaks-Ventura Redding ( 1 ) ( 1 ) ( 1 ) Riverside-San Bernardino-Ontario 1, , , Sacramento Arden-Arcade Roseville Salinas San Diego-Carlsbad-San Marcos 1, , , San Francisco-Oakland-Fremont 1, , , San Jose-Sunnyvale-Santa Clara San Luis Obispo-Paso Robles ( 1 ) ( 1 ) ( 1 ) Santa Barbara-Santa Maria-Goleta Santa Cruz-Watsonville ( 1 ) ( 1 ) ( 1 ) Santa Rosa-Petaluma Stockton Vallejo-Fairfield Visalia-Porterville Yuba City ( 1 ) ( 1 ) ( 1 ) Colorado 2, , , Boulder ( 1 ) ( 1 ) ( 1 ) Colorado Springs O Denver-Aurora 1, , ,162.1 ( 1 ) Fort Collins-Loveland ( 1 ) Grand Junction o ( 1 ) ( 1 ) Greeley o < > < > Pueblo ( 1 ) ( 1 ) ( 1 ) Connecticut 1, , , Bridgeport-Stamford-Norwalk o O O Danbury ( 2 > ( 2 ) ( 2 ) Hartford-West Hartford-East Hartford ( 1 ) ( 1 ) ( 1 ) New Haven < > o ( 1 ) Norwich-New London ( 1 ) ( 1 ) ( 1 ) Waterbury ( 1 ) ( 1 ) ( 1 ) Delaware ( 1 ) ( 1 ) ( 1 ) Dover ( 1 ) ( 1 ) ( 1 ) District of Columbia o o o Washington-Arlington-Alexandria 2, , ,849.9 ( 1 ) ( 1 ) ( 1 )

105 2005P ( 2 ) ( 2 ) ( 2 ) , , , , , , , Hartford-West a ( 2 ) ( 2 ) ( 2 ) ( 2 )

106 (In thousands) State and area Financial activities Professional and business services Education and health services 2005P 2005P 2005P Alabama Anniston-Oxford Aubum-Opelika Birmingham-Hoover Decatur Dothan Florence-Muscle Shoals Gadsden Huntsville Mobile Montgomery Tuscaloosa Alaska Anchorage Fairbanks Arizona Flagstaff Phoenix-Mesa-Scottsdale Prescott Tucson Yuma Arkansas Fayetteville-Springdale-Rogers Fort Smith Hot Springs ( 2 ) ( 2 ) ( 2 ) Jonesboro Little Rock-North Little Rock Pine Bluff California , , , , , ,562.0 Bakersfield Chico El Centra Fresno Hanford-Corcoran Los Angeles-Long Beach-Santa Ana Madera Merced Modesto Napa Oxnard-Thousand Oaks-Ventura Redding Riverside-San Bernardino-Ontario Sacramento Arden-Arcade Roseville Salinas San Diego-Carlsbad-San Marcos San Francisco-Oakland-Fremont San Jose-Sunnyvale-Santa Clara San Luis Obispo-Paso Robles Santa Barbara-Santa Maria-Goleta Santa Cruz-Watsonville Santa Rosa-Petaluma Stockton Vallejo-Fairfield Visalia-Porterville Yuba City Colorado Boulder Colorado Springs Denver-Aurora Fort Collins-Loveland Grand Junction Greeley Pueblo Connecticut Bridgeport-Stamford-Norwalk Danbury ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) < 2 ) Hartford-West Hartford-East Hartford New Haven Norwich-New London Waterbury Delaware Dover District of Columbia Washington-Arlington-Alexandria

107 (In thousands) State and area Leisure and hospitality Other services Government 2005P 2005P 2005P Alabama Anniston-Oxford Auburn-Opelika Birmingham-Hoover Decatur Dothan Florence-Muscle Shoals Gadsden Huntsville Mobile Montgomery Tuscaloosa Alaska Anchorage Fairbanks Arizona Flagstaff Phoenix-Mesa-Scottsdale Prescott Tucson Yuma Arkansas Fayetteville-Springdale-Rogers Fort Smith Hot Springs ( 2 ) ( 2 ) ( 2 ) Jonesboro Little Rock-North Little Rock Pine Bluff California 1, , , , , ,384.4 Bakersfield Chico El Centra Fresno Hanford-Corcoran Los Angeles-Long Beach-Santa Ana Madera Merced Modesto Napa Oxnard-Thousand Oaks-Ventura Redding Riverside-San Bernardino-Ontario Sacramento Arden-Arcade Roseville Salinas San Diego-Carlsbad-San Marcos San Francisco-Oakland-Fremont S San Jose-Sunnyvale-Santa Clara San Luis Obispo-Paso Robles Santa Barbara-Santa Maria-Goleta Santa Cruz-Watsonville Santa Rosa-Petaluma Stockton Vallejo-Fairfield Visalia-Porterville Yuba City Colorado Boulder Colorado Springs Denver-Aurora Fort Collins-Loveland Grand Junction Greeley Pueblo Connecticut Bridgeport-Stamford-Norwalk Danbury ( 2 ) ( 2 ) ( 2 ) Hartford-West Hartford-East Hartford New Haven Norwich-New London Waterbury Delaware Dover District of Columbia Washington-Arlington-Alexandria

108 (In thousands) State and area Total Natural resources and mining Construction 2005P 2005P 2005P Florida 7, , , Cape Coral-Fort Myers ( 1 ) ( 1 ) ( 1 ) Deltona-Dayton a Beach-Ormond Beach ( 1 ) ( 1 ) ( 1 ) Fort Walton Beach-Crestview-Destin ( 1 ) ( 1 ) ( 1 ) Gainesville ( 1 ) ( 1 ) ( 1 ) Jacksonville Lakeland ( 1 ) ( 1 ) ( 1 ) Miami-Fort Lauderdale-Miami Beach 2, , , Naples-Marco Island ( 1 ) ( 1 ) ( 1 ) Ocala ( 1 ) < 1 ) ( 1 ) Orlando , Palm Bay-Melbourne-Titusville ( 1 ) ( 1 ) ( 1 ) Panama City-Lynn Haven ( 1 ) ( 1 > ( 1 ) Pensacola-Ferry Pass-Brent ( 1 ) ( 1 ) ( 1 ) Port St. Lucie-Fort Pierce ( 1 ) ( 1 ) ( 1 ) Punta Gorda ( 1 ) ( 1 ) ( 1 ) Sarasota-Bradenton-Venice ( 1 ) ( 1 ) ( 1 ) Tallahassee ( 1 ) ( 1 ) ( 1 ) Tampa-St. Petersburg-Clearwater 1, , , Vera Beach ( 1 ) ( 1 ) ( 1 ) Georgia 3, , , Albany ( 1 ) ( 1 ) ( 1 ) Athens-Clarke County ( 1 ) ( 1 ) ( 1 ) Atlanta-Sandy Springs-Marietta 2, , , Augusta-Richmond County ( 1 ) ( 1 ) ( 1 ) Brunswick ( 1 ) ( 1 ) ( 1 ) Columbus ( 1 ) ( 1 ) ( 1 ) Dalton ( 1 ) ( 1 ) ( 1 ) Gainesville ( 1 ) ( 1 ) ( 1 ) Hinesville-Fort Stewart ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Macon ( 1 ) ( 1 ) ( 1 ) Rome ( 1 ) ( 1 ) ( 1 ) Savannah ( 1 ) ( 1 ) ( 1 ) Valdosta ( 1 ) ( 1 ) ( 1 ) Warner Robins ( 1 > ( 1 ) ( 1 ) Hawaii ( Honolulu ( 1 1 ) < 1 ) ( 1 ) Idaho Boise City-Nampa ( 1 ) ( 1 ) ( 1 ) Coeur d'alene Idaho Falls ( 1 ) ( 1 ) Lewiston Pocatello ( 1 ) ( 1 ) ( 1 > Illinois 5, , , Bloomington-Normal ( 1 ) ( 1 ) ( 1 ) Champaign-Urbana ( 1 ) ( j ) ( 1 ) Chicago-Naperville-Joliet 4, , ,326.7 ( 1 ) ( 1 ) ( 1 ) ( 2 ) ( 2 ) ( 2 ) Danville ( 1 ) ( 1 ) (1) Davenport-Moline-Rock Island ( 1 ) ( 1 ) ( 1 ) Decatur ( 1 ) ( 1 ) ( 1 ) Kankakee-Bradley ( 1 ) o ( 1 ) Peoria ( 1 ) ( 1 ) ( 1 ) Rockford ( 1 ) < 1 ) ( 1 ) Springfield ( 1 ) ( 1 ) ( 1 ) Indiana 2, , , Anderson Bloomington Columbus Elkhart-Goshen ( 1 ) Evansville ( 1 ) ( Fort Wayne < > (1 ) Indianapolis ) 1 > Kokomo ( 1 ) Lafayette ( 1 ) ( 1 ) Michigan City-La Porte O Muncie ( South Bend-Mishawaka < Terre Haute ( 1 ) ( 1 ) ( 1 ) , , , Ames ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) < 2 ) Cedar Rapids ( 1 ) o ( 1 ) Des Moines ( 1 ) ( 1 ) ( 1 ) Dubuque ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Iowa City ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) < 2 ) Sioux City ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 > Waterloo-Cedar Falls ( 1 ) ( 1 ) ( 1 ) ( 2 ) ( 2 ) ( 2 )

109 Trade, transportation, and utilities 2005P Cape Coral-Fort Myers KnsToK : Port St. Lucie-Fort F , , , ' ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Coeur d'a Fort \ 1 City-La Porte , , , OU4.D cn/i K aoo.o 7.9 QQ7 tsy /.d O 7.4 a yo.u n ,9 302, (2) ( 2 ) ( ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) (2) (2) (2) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) M ( 2 ) ( 2 ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 )

110 (In thousands) State and area Financial activities Professional and business services Education and health services 2005P 2005P 2005P Florida , , , Cape Coral-Fort Myers Deltona-Daytona Beach-Ormond Beach Fort Walton Beach-Crestview-Destin Gainesville Jacksonville Lakeland Miami-Fort Lauderdale-Miami Beach Naples-Marco Island Ocala Orlando Palm Bay-Melbourne-Titusville Panama City-Lynn Haven Pensacola-Ferry Pass-Brent Port St. Lucie-Fort Pierce PuntaGorda Sarasota-Bradenton-Venice Tallahassee Tampa-St. Petersburg-Clearwater Vero Beach Georgia Albany Athens-Clarke County Atlanta-Sandy Springs-Marietta Augusta-Richmond County Brunswick Columbus Dalton Gainesville Hinesville-Fort Stewart ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Macon Rome Savannah Valdosta Warner Robins Hawaii Honolulu Idaho Boise City-Nampa Coeur d'alene Idaho Falls Lewiston Pocatello Illinois Bloomington-Normal Champaign-Urbana Chicago-Naperville-Joliet Danville Davenport-Moline-Rock Island Decatur Kankakee-Bradley Peoria Rockford Springfield Indiana Anderson Bloomington Columbus Elkhart-Goshen Evansville Fort Wayne Indianapolis Kokomo Lafayette Michigan City-La Porte Muncie South Bend-Mishawaka Terre Haute Iowa Ames ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Cedar Rapids Des Moines Dubuque O ( 2 ) ( 2 ) ( 2 ) O O Iowa City O O Sioux City <o> Waterloo-Cedar Falls ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 )

111 (In thousands) State ard area Leisure and hospi. ality Other services Government 2005P 2005P 2005P Florida , , ,085.4 Cape Coral-Fort Myers Deltona-Daytona Beach-Ormond Beach Fort Walton Beach-Crestview-Destin Gainesville Jacksonville Lakeland Miami-Fort Lauderdale-MiaTii Beach Naples-Marco Island Ocala Orlando Palm Bay-Melbourne-Titus'/ille Panama City-Lynn Haven Pensacola-Ferry Pass-Brent Port St. Lucie-Fort Pierce Punta Gorda Sarasota-Bradenton-Venice Tallahassee Tampa-St. Petersburg-Clearwater Vero Beach Georgia Albany Athens-Clarke County Atlanta-Sandy Springs-Marietta Augusta-Richmond County Brunswick Columbus Dalton Gainesville Hinesville-Fort Stewart ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Macon Rome Savannah Valdosta Warner Robins Hawaii C Honolulu Idaho Boise City-Nampa Coeur d'alene Idaho Falls Lewiston Pocatello Illinois f! Bloomington-Normal ;' Champaign-Urbana : Chicago-Naperville-Joliet i Danville 'i Davenport-Moline-Rock Island ' Decatur Kankakee-Bradley Peoria Rockford i Springfield Indiana > Anderson 4.7 4/i Bloomington Columbus Elkhart-Goshen Evansville ; Fort Wayne ' Indianapolis IS Kokomo B Lafayette j Michigan City-La Porte Muncie South Bend-Mishawaka J Terre Haute 6.9 1,' Iowa ) Ames ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Cedar Rapids Des Moines Dubuque ( 2 ) ( 2 ) ( 2 ) ( 2 ) < 2 > ( 2 ) Iowa City ( 2 ) ( 2 ) ( 2 ) Sioux City ( 2 ) ( 2 > ( 2 ) Waterloo-Cedar Falls ( 2 ) ( 2 ) ( 2 )

112 (In thousands) State and area Total Natural resources and mining Construction 2005P 2005P 2005P Kansas 1, , , Lawrence ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Topeka ( 1 ) ( 1 ) ( 1 ) Wichita ( 1 ) ( 1 ) ( 1 ) Kentucky 1, , , Bowling Green ( 1 ) ( 1 ) ( 1 ) Elizabethtown ( 1 ) ( 1 ) ( 1 ) Lexington-Fayette ) ( 1 ) ( 1 ) Louisville ( 1 ) < 1 ) ( 1 ) Owensboro ( 1 ) ( 1 ) ( 1 ) Louisiana 1, , , Alexandria ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Baton Rouge ( 1 ) ( 1 ) ( 1 ) Houma-Bayou Cane-Thibodaux < > ( 1 ) ( 1 ) Lafayette ( 1 ) ( 1 ) ( 1 ) Lake Charles ( 1 ) ( 1 ) ( j ) Monroe ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) New Orleans-Metairie-Kenner ( 1 ) ( 1 ) ( 1 ) Shreveport-Bossier City ( 1 ) ( 1 ) ( 1 ) Maine Bangor Lewiston-Auburn ( 1 ) ( 1 ) ( 1 ) Portland-South Portland-Biddeford ( 1 ) ( 1 ) ( 1 ) Maryland 2, , ,490.1 < 1 ) < 1 ) ( 1 ) Baltimore-Towson 1, , ,245.4 ( 1 ) ( 1 ) Cumberland ( 1 ) ( 1 ) ( 1 ) Hagerstown-Martinsburg o ( 1 ) ( 1 ) Salisbury ( 1 ) ( 1 ) ( 1 ) Massachusetts 3, , , Barnstable Town ( 1 ) < 1 ) ( 1 ) Boston-Cambridge-Quincy 2, , , Leominster-Fitchburg-Gardner O ( 1 ) New Bedford ( 1 ) ( 1 > Pittsfield ( 1 ) ( 1 > ) ( 1 ) Springfield ( 1 ) o ( 1 ) Worcester ( 1 ) ( 1 > ( 1 ) Michigan 4, , , Ann Arbor O ( 1 ) ( 1 ) Battle Creek ( 1 ) ( 1 ) ( 1 ) Bay City O o ( 1 ) Detroit-Warren-Livonia 2, , ,994.5 ( 1 ) 0) ( 1 ) Flint ( 1 ) ( 1 ) < 1 > Grand Rapids-Wyoming O O ( 1 ) Holland-Grand Haven ( 1 ) ( 1 > C) Jackson ( 1 ) ( 1 ) C) Kalamazoo-Portage o < > < 1 ) Lansing-East Lansing < > o ( ') Monroe ) 1 ) ( 1 ) Muskegon-Norton Shores < > ( > C) < 1 > Niles-Benton Harbor ( 1 ) ( Saginaw-Saginaw Township North > ( 1 ) ( 1 ) 0) Minnesota 2, , , Duluth < 1 ) ( 1 ) Minneapolis-St. Paul-Bloomington 1, , ,723.1 ( 1 ) ( > O Rochester ( 1 ) ( 1 ) ( 1 ) St. Cloud ( 1 ) ( 1 ) ( 1 ) Mississippi 1, , , Gulfport-Biloxi ( 1 ) ( 1 ) ( 1 ) Hattiesburg ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Jackson Pascagoula ( 1 ) ( 1 ) ( 1 ) Missouri 2, , , Columbia ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Jefferson City ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Joplin ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Kansas City O O ( 1 ) St. Joseph ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) St. Louis 3 1, , ,306.6 ( 1 ) ( 1 ) ( 1 ) Springfield ( 1 ) ( 1 ) ( 1 )

113 (In thousands) State ar d area Manufacturing Trade, transportation, and utilities Information 2005P 2005P 2005P Kansas Lawrence ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Topeka Wichita Kentucky Bowling Green Elizabethtown ( 2 ) ( 2 ) ( 2 ) Lexington-Fayette Louisville Owensboro Louisiana Alexandria ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Baton Rouge Houma-Bayou Cane-Thibodaux ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Lafayette Lake Charles ( 2 > ( 2 ) ( o> Monroe ( 2 ) ( 2 ) ( 2 ) New Orleans-Metairie-Kenner Shreveport-Bossier City Maine [ Bangor Lewiston-Auburn Portland-South Portland-Biddeford Maryland Baltimore-Towson Cumberland ( 2 ) ( 2 ) ( 2 ) Hagerstown-Martinsburg Salisbury ( 2 ) ( 2 ) ( 2 ) Massachusetts E Barnstable Town Boston-C ambr idge-qunc\ Leominster-Filchburg-Gardner New Bedford Pittsfield Springfield Worcester v! Michigan ?! Ann Arbor S Battle Creek ( ( 2 ) ( 2 ) Bay City ( Detroit-Warren-Livonia : Flint Grand Rapids-Wyommg Holland-Grand Haven Jackson Kalamazoo-Portage Lansing-East Lansing Monroe ( 2 ) ( 2 ) ( 2 ) Muskegon-Norton Shores , Niles-Benton Harbor i Saginaw-Saginaw Township North Minnesota Duluth Minneapolis-St. Paul-Bloomington '! Rochester !? St. Cloud Mississippi Gulfport-Biloxi Hattiesburg ( 2 ) ( 2 ) ( 2 ) Jackson Pascagoula ( 2 ) ( 2 ) ( 2 > Missouri Columbia ( 2 ) 2 2 Jefferson City (2} ( 2 ) 2 Joplin ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 > ( 2 ) Kansas City St. Joseph ( 2 ) C 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 > St. Louis Springfield

114 (In thousands) State and area Financial activities Professional and business services Education and health services 2005P 2005P 2G05P Kansas Lawrence ( 2 ) ( 2 ) ( 2 ) Topeka Wichita Kentucky Bowling Green > Elizabethtown ( 2 ) ( 2 ) ( 2 ) Lexington-Fayette Louisville Owensboro Louisiana Alexandria ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Baton Rouge Houma-Bayou Cane-Thibodaux ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Lafayette Lake Charles Monroe ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) New Orleans-Metairie-Kenner Shreveport-Bossier City Maine Bangor Lewiston-Auburn Portland-South Portland-Biddeford Maryland Baltimore-Towson Cumberland ( 2 ) ( 2 ) ( 2 ) Hagerstown-Martinsburg Salisbury ( 2 ) ( 2 ) ( 2 ) Massachusetts Barnstable Town Boston-Cambridge-Quincy Leominster-Fitchburg-Gardner New Bedford Pittsfield Springfield Worcester Michigan Ann Arbor Battle Creek Bay City Detroit-Warren-Livonia Flint Grand Rapids-Wyoming Holland-Grand Haven Jackson Kalamazoo-Portage Lansing-East Lansing Monroe Muskegon-Norton Shores Niles-Benton Harbor Saginaw-Saginaw Township North Minnesota Duluth Minneapolis-St. Paul-Bloomington Rochester St. Cloud Mississippi Gulfport-Biloxi O O 2 2 <o> ) Hattiesburg ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 > Jackson Pascagoula ( 2 ) ( 2 ) ( 2 ) ( 2 ) < 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Missouri Columbia Jefferson City Joplin ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Kansas City St. Joseph ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) St. Louis Springfield

115 STATE AND AREA Leisure and hospitality Other services.an. 2005P 2005P ! 6.2 ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) cm.d. OQ ( 2 \ i 2 \ 2 \ ( ( ( k ko K ) \ ) ( ; ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) <o> (2 ko (2 k <2 La a. a ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) St. Cloud S ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) , ( 2 f ( 2 120, ) ( 2 ) / 2 \ ( 2 ) ( 2 ) ( 2 ) ( lko a, (, ki '

116 (In thousands) State and area Total Natural resources and mining Construction 2005P 2.005P 2005P Montana Billings ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Great Falls ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Missoula ( 2 ) ( 2 > ( 2 ) ( 2 ) ( 2 ) ( 2 ) Nebraska ( 1 ) ( 1 ) ( 1 ) Lincoln ( 1 ) ( 1 ) ( 1 ) Omaha-Council Bluffs ( 1 ) ( 1 ) ( 1 ) Nevada 1, , , Carson City ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Las Vegas-Paradise Reno-Sparks New Hampshire Manchester ( 1 ) ( 1 ) ( 1 ) Portsmouth ( 1 ) ( 1 ) ( 1 ) Rochester-Dover ( 1 ) ( 1 ) ( 1 ) New Jersey 3, , , Atlantic City ( 1 ) ( 1 ) ( 1 ) Ocean City <?> ( 2 ) ( 2 ) ( 2 ) ( 2 ) Trenton-Ewing ( 1 ) ( 1 ) ( 1 ) Vineland-Millville-Bridgeton ( 1 ) ( 1 > ( 1 ) New Mexico Albuquerque ( 1 ) ( 1 ) ( 1 ) Farmington ( 1 ) ( 1 ) ( 1 ) Las Cruces ( 1 ) ( 1 ) Santa Fe ( 1 ) ( 1 ) ( 1 ) New York 8, , , Albany-Schenectady-Troy Binghamton O O ( 1 ) ( 1 > ( 1 ) Buffalo-Niagara Falls ( 1 ) ( 1 ) ( 1 ) Elmira ( 1 ) ( 1 ) ( 1 ) Glens Falls ( 1 ) ( 1 ) ( 1 ) Ithaca ( 1 ) ( 1 ) ( 1 ) Kingston ( 1 ) ( 1 ) ( 1 ) New York-Northern New Jersey-Long Island 8, , , Poughkeepsie-Newburgh-Middletown o o o ( 1 ) ( 1 ) ( 1 ) Rochester Syracuse ( 1 ) ( 1 ) ( 1 ) Utica-Rome ( 1 ) ( 1 ) ( 1 ) North Carolina 3, , , Asheville ( 1 ) ( 1 ) ( 1 ) Burlington o ( 1 ) ( 1 ) Charlotte-Gastonia-Concord ( 1 ) ( 1 ) ( 1 ) Durham ( 1 ) ( 1 ) ( 1 ) Fayetteville ( 1 ) ( 1 ) ( 1 ) Goldsboro ( 1 ) ( 1 ) ( 1 > Greensboro-High Point ( 1 ) ( 1 ) ( 1 ) Greenville ( 1 ) ( 1 ) ( 1 ) Hickory-Lenoir-Morganton Jacksonville <!> o ( 1 ) ( 1 ) 1 ) Raleigh-Cary < > < > > Rocky Mount O o ( 1 ) Wilmington ( 1 ) ( 1 ) ( 1 ) Winston-Salem ( 1 ) ( 1 ) ( 1 ) North Dakota Bismarck O ( 1 ) O Fargo ( 1 ) ( 1 ) ( 1 ) Grand Forks ( 1 ) ( 1 ) ( 1 ) Ohio 5, , , Akron ( 1 ) ( 1 ) ( 1 ) Canton-Massillon ( 1 ) ( 1 ) ( 1 ) Cincinnati-Middletown , ,006.4 ( 1 ) ( 1 ) ( 1 ) Cleveland-Elyria-Mentor 1, , , Columbus ( 1 ) ( 1 ) ( 1 ) Dayton o o <!> Lima ( 1 ) ( 1 ) ( 1 ) Mansfield o o ( 1 ) Sandusky o o Springfield O o < > o Toledo o o ( 1 ) Weirton-Steubenville o 0) ( 1 ) Youngstown-Warren-Boardman ( 1 ) 0) ( 1 )

117 (In thousands) Manufacturing Trade, transportation, and utilities Information State and area 20Q5P 2005P 2005P Montana Billings ( 2 ) O o ( 2 ) ( 2 ) ( 2 ) Great Falls ( 2 ) ( 2 ) ( 2 ) Missoula ( 2 ) ( 2 ) < 2 > ( 2 ) ( 2 ) ( 2 ) Nebraska Lincoln Omaha-Council Bluffs Nevada Carson City ( 2 ) ( 2 ) ( 2 ) Las Vegas-Paradise Reno-Sparks New Hampshire Manchester Portsmouth Rochester-Dover New Jersey Atlantic City Ocean City ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Trenton-Ewing Vineland-Millville-Bridgeton New Mexico Albuquerque Farmington ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Las Cruces Santa Fe New York , , , Albany-Schenectady-Troy Binghamton Buffalo-Niagara Falls Elmira Glens Falls Ithaca S Kingston New York-Northern New Jersey-Long Island , , , Poughkeepsie-Newburgh-fVliddletown Rochester Syracuse Utica-Rome North Carolina Asheville Burlington Charlotte-Gastonia-Concord Durham Fayetteville Goldsboro Greensboro-High Point Greenville Hickory-Lenoir-Morganton Jacksonville Raleigh-Cary Rocky Mount Wilmington Winston-Salem North Dakota Bismarck Fargo Grand Forks Ohio , , , Akron , Canton-Massillon Cincinnati-Middletown Cleveland-Elyria-Mentor Columbus Dayton Lima Mansfield ( 2 ) ( 2 ) ( 2 ) Sandusky Springfield (?) ( 2 ) ( 2 ) ( O ) Weirton-Steubenville i ( 2 ) ( 2 ) ( 2 ) Toledo ! Youngstown-Warren-Boardman

118 (In thousands) State and area Financial activities Professional and business services Education and health services 2005P 2005P 2005P Montana Billings ( 2 ) ( 2 ) ( 2 ) Great Falls ( 2 ) ( 2 ) ( 2 ) Missoula ( 2 ) ( 2 ) ( 2 ) Nebraska Lincoln Omaha-Council Bluffs Nevada Carson City ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Las Vegas-Paradise Reno-Sparks New Hampshire Manchester Portsmouth Rochester-Dover New Jersey Atlantic City Ocean City ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Trenton-Ewing Vineland-Millville-Bridgeton New Mexico Albuquerque Farmington ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) LasCruces Santa Fe New York , , , , , ,522.0 Albany-Schenectady-Troy Binghamton Buffalo-Niagara Falls Elmira Glens Falls Ithaca Kingston New York-Northern New Jersey-Long Island , , , , , ,362.2 Poughkeepsie-Newburgh-Middletown Rochester Syracuse Utica-Rome North Carolina Asheville Burlington Charlotte-Gastonia-Concord Durham Fayetteville Goldsboro Greensboro-High Point Greenville Hickory-Lenoir-Morganton Jacksonville Raleigh-Cary Rocky Mount Wilmington Winston-Salem North Dakota ESismarck Fargo Grand Forks Ohio Akron Canton-Massillon Cincinnati-Middletown Cleveland-Elyria-Mentor Columbus Dayton Lima ( 2 ) ( 2 ) ( 2 ) Mansfield Sandusky ( 2 ) ( 2 ) ( 2 ) Springfield Toledo Weirton-Steubenville ( 2 ) ( 2 ) ( 2 ) Youngstown-Warren-Boardman

119 (In thousands) State and area Leisure and hospitality Other services Government 2005P 2005P 2005P Montana Billings O O Great Falls < > o> Missoula ( 2 ) ( 2 ) ( 2 ) Nebraska C Lincoln Omaha-Council Bluffs Nevada Carson City ( 2 ) ( 2 ) ( 2 ) Las Vegas-Paradise Reno-Sparks New Hampshire Manchester Portsmouth Rochester-Dover New Jersey Atlantic City Ocean City ( 2 ) ( 2 ) ( 2 ) Trenton-Ewing Vineland-Millville-Bridgeton New Mexico Albuquerque i Farmington ') 4.6 ( 2 ) ( 2 ) ( 2 ) Las Cruces Santa Fe New York i , , ,474.2 Albany-Schenectady-Troy ' Binghamton 8.5 9, Buffalo-Niagara Falls Elmira r Glens Falls I Ithaca 3.3 3, Kingston New York-Northern New Jersey-Long Island , , ,268.0 Poughkeepsie-Newburgh-Middletown , Rochester , Syracuse j Utica-Rome North Carolina Asheville Burlington Charlotte-Gastonia-Concord Durham , Fayetteville , Goldsboro ; Greensboro-High Point Greenville Hickory-Lenoir-Morganton Jacksonville Raleigh-Cary Rocky Mount Wilmington Winston-Salem North Dakota Bismarck Fargo Grand Forks Ohio Akron Canton-Massillon Cincinnati-Middletown Cleveland-Elyria-Mentor Columbus Dayton Lima ( 2 ) ( 2 ) ( 2 ) Mansfield Sandusky ( 2 ) ( 2 ) ( 2 ) Springfield Toledo Weirton-Steubenville ( 2 ) ( 2 ) ( 2 ) Youngstown-Warren-Boardman

120 (In thousands) State and area Total Natural resources and mining Construction 2005P 2005P 2005P Oklahoma 1, , , Lawton ( 1 ) ( 1 ) ( 1 ) Oklahoma City ( 1 ) ( 1 ) ( 1 ) Tulsa Oregon 1, , , Bend ( 1 ) ( 1 ) ( 1 ) Corvallis ( 1 ) ( 1 ) ( 1 ) Eugene-Springfield Medford Portland-Vancouver-Beaverton Salem Pennsylvania 5, , , Allentown-Bethlehem-Easton ( 1 ) ( 1 ) ( 1 ) Altoona ( 2 ( 2 ( 2 ) ( 2 ) ( 2 ) ( 2 ) Erie < 1 ) < 1 ) ( 1 ) Harrisburg-Carlisle ( 1 ) ( 1 ) ( 1 ) Johnstown ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Lancaster ( 1 ) ( 1 ) ( 1 ) Lebanon ( 2 ) ( 2 ) ( 2 ) ( 2 > ( 2 ) ( 2 ) Philadelphia-Camden-Wilmington 2, , , Pittsburgh 1,110.6 O O 1, ,116.6 O ( 1 ) Reading o O ( 1 ) Scranton Wilkes-Barre ( 1 ) ( 1 ) ( 1 ) State College ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Williamsport ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) York-Hanover ( 1 ) ( 1 ) ( 1 ) Rhode Island Providence-Fall River-Warwick South Carolina 1, , , Anderson ( 1 ) ( 1 ) ( 1 ) Charleston-North Charleston ( 1 ) ( 1 ) ( 1 ) Columbia ( 1 ) ( 1 ) ( 1 ) Florence ( 1 ) ( 1 ) ( 1 ) Greenville ( 1 ) ( 1 ) ( 1 ) Myrtle Beach-Conway-North Myrtle Beach ( 1 ) ( 1 ) ( 1 ) Spartanburg ( 1 ) ( 1 ) ( 1 ) Sumter ( 1 ) ( 1 ) ( 1 ) South Dakota Rapid City Sioux Falls O O O ( 1 ) ( 1 ) ( 1 ) Tennessee 2, , , Chattanooga ( 1 ) ( 1 ) ( 1 ) Clarksville ( 1 ) ( 1 ) ( 1 ) Cleveland ( 1 ) ( 1 ) ( 1 ) Jackson ( 1 ) ( 1 ) ( 1 ) Johnson City ( 1 ) ( 1 ) ( 1 ) Kingsport-Bristol-Bristol ( 1 ) ( 1 ) ( 1 ) Knoxville ( 1 ) ( 1 ) ( 1 ) Memphis O ( 1 ) Morristown O ) ( 1 ) ( 1 ) Nashville-Davidson Murfreesboro ( 1 ) ( 1 ) ( 1 ) Texas 9, , , Abilene ( 1 ) ( 1 ) ( 1 ) Amarillo ( 1 ) ( 1 ( 1 ) Austin-Round Rock ( 1 ) < 1 ) ( 1 ) Beaumont-Port Arthur ( 1 ) ( 1 ) ( 1 ) Brownsville-Harlingen O ( l> College Station-Bryan < > (1 ) Corpus Christi O ( 1 ) Dallas-Fort Worth-Arlington 2, , ,699.1 O ( 1 ) o El Paso ( 1 ) ( 1 ) ( 1 ) Houston-Baytown-Sugar Land 2, , ,278.4 ( 1 ) ( 1 ) ( 1 ) Killeen-Temple-Fort Hood ( 1 ) ( 1 ) ( 1 ) Laredo ( 1 ) ( 1 ) ( 1 ) Longview ( ) ( 1 ) < > Lubbock ( 1 ) ( 1 ) ( 1 ) McAllen-Edinburg-Pharr ( 1 ) ( 1 ) ( 1 ) Midland ( 1 ) ( 1 ) C) Odessa ( 1 ) ( 1 ) ( 1 ) San Angelo San Antonio o o o ( 1 ( 1 ) ( 1 ) Sherman-Denison < 1 ) ( 1 ) ( 1 ) Texarkana ( 1 ) ( 1 ) 0) Tyler o ( 1 ) ( 1 ) Victoria ( 1 ) ( 1 ) ( 1 > Waco ( 1 ) ( 1 ) Wichita Falls 60.2 o ( 1 ) ( 1 ) 0)

121 (in thousands) State arid area Manufacturing Trade, transportation, and utilities Information 2J05P 2005P 2005P Oklahoma Lawton Oklahoma City Tulsa Oregon Bend Corvallis Eugene-Springfield Medford Portland-Vancouver-Beave ton Salem Pennsylvania , , , Allentown-Bethlehem-Easton Altoona ( 2 ) ( 2 ) ( 2 ) Erie Harrisburg-Cariisle Johnstown ( 2 ) ( 2 ) ( 2 ) Lancaster Lebanon ( 2 ) ( 2 ) ( 2 ) Philadelphia-Camden-Wilrriington Pittsburgh Reading Scranton Wilkes-Barre I State College j Williamsport ( 2 ) <*> ( 2 ) ( 2 ) York-Hanover j Rhode Island Providence-Fall River-Warwick South Carolina Anderson Charleston-North Charleston Columbia Florence Greenville Myrtle Beach-Conway-North Myrtle Beach Spartanburg Sumter ( 2 ) ( 2 ) ( 2 ) South Dakota Rapid City Sioux Falls Tennessee Chattanooga : I Clarksville ( Cleveland ! Jackson ; Johnson City ' Kingsport-Bristol-Bnstol ( Knoxville ; Memphis Morristown Nashville- Davidson Murireesboro Texas , , , Abilene Amarillo Austin-Round Rock i Beaumont-Port Arthur , Brownsville-Harlingen College Station-Bryan 5.7 5JS Corpus Chnsti Dallas-Fort Worth-Arlington S El Paso Ii Houston-Baytown-Sugar Land il Killeen-Temple-Fort Hooc Laredo ' Longview i) Lubbock McAllen-Edinburg-Pharr Midland ! Odessa , San Angelo San Antonio J Sherman-Demson Texarkana Tyler i Victoria j Waco , Wichita Falls

122 (In thousands) State and area Financial activities Professional and business services Education and health services 2005P 2005P 2005P Oklahoma Lawton Oklahoma City Tulsa Oregon Bend Corvallis Eugene-Springfield Medford Portland-Vancouver-Beaverton Salem Pennsylvania , Allentown-Bethlehem-Easton Altoona ( 2 ) ( 2 ) ( 2 ) Erie Harrisburg-Carlisle Johnstown ( 2 ) ( 2 ) ( 2 ) Lancaster Lebanon ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Philadelphia-Camden-Wilmington Pittsburgh Reading Scranton Wilkes-Barre State College Williamsport ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) York-Hanover Rhode Island Providence-Fall River-Warwick South Carolina Anderson Charleston-North Charleston Columbia Florence Greenville Myrtle Beach-Conway-North Myrtle Beach Spartanburg Sumter South Dakota Rapid City Sioux Falls Tennessee Chattanooga Clarksville Cleveland Jackson Johnson City Kingsport-Bristol-Bristol Knoxville Memphis Morristown Nashville-Davidson Murfreesboro Texas , , , , , ,151.9 Abilene Amarillo Austin-Round Rock Beaumont-Port Arthur Brownsville-Harlingen College Station-Bryan Corpus Christi Dallas-Fort Worth-Arlington El Paso Houston-Baytown-Sugar Land Killeen-Temple-Fort Hood Laredo Longview Lubbock McAllen-Edinburg-Pharr Midland Odessa San Angelo San Antonio Sherman-Denison Texarkana Tyler Victoria Waco Wichita Falls

123 -14. on Leisure and hospitality Other services 2005P 2005P ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 > : ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 > ( 2 ) S 2.9 ( 2 ) ( 2 ) ( 2 ) W i; ! ; , , ,.S , , , I o4.u OQ R: Do.O , , , I V.yJ Q Q Q O

124 (In thousands) State and area Total Natural resources and mining Construction 2005P 2005P 2005P Utah 1, , , Logan ( 1 ) ( 1 ) ( 1 ) Ogden-Clearfield ( 1 ) ( 1 ) ( 1 ) Provo-Orem ( 1 ) C) ( 1 ) St. George ( 1 ) ( 1 ) ( 1 ) Salt Lake City ( 1 ) ( 1 ) ( 1 ) Vermont Burlington-South Burlington ( 1 ) ( 1 ) ( 1 ) Virginia 3, , , Blacksburg-Christiansburg-Radford ( 2 ) ( 2 ) ( 2 ) ( ) ( ) ( ) Charlottesville ( 2 ) ( 2 ) ( 2 ) Danville ( 2 ) ( 2 ) ( 2 ) Harrisonburg ( 2 ) ( 2 ) ( 2 ) Lynchburg ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Richmond ( 1 ) ( 1 ) ( 1 ) Roanoke ( 1 ) ( 1 ) ( 1 ) Virginia Beach-Norfolk-Newport News ( 1 ) ( 1 ) ( 1 ) Winchester ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Washington 2, , , Bellingham ( 1 ) ( 1 ) ( 1 ) Bremerton-Silverdale ( 1 ) ( 1 ) ( 1 ) Kennewick-Richland-Pasco ( 1 ) ( 1 ) ( 1 ) Longview ( 1 ) ( 1 ) ( 1 ) Mount Vemon-Anacortes C 1 ) < 1 ) Olympia ( 1 <1 ) 1) ( 1 ) ( 1 ) Seattle-Tacoma-Bellevue 1, , , Spokane ( 1 ) ( 1 ) ( 1 ) Wenatchee ( 1 ) ( 1 ) ( 1 ) Yakima ( 1 ) ( 1 ) ( 1 ) West Virginia Charleston ( 1 ) ( 1 ) ( 1 ) Huntington-Ashland ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( ) ( ) Morgantown ( 2 > ( 2 ) ( 2 ) ( 2 Parkersburg-Marietta ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) 2 ) Wheeling ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Wisconsin 2, , , Appleton ( 1 ) ( 1 ) ( 1 ) Eau Claire ( 1 ) ( 1 ) ( 1 ) Fond du Lac ( 1 ) ( 1 ) ( 1 ) Green Bay ( 1 ) ( 1 ) ( 1 ) Janesville ( 1 ) ( 1 ) ( 1 ) LaCrosse ( 1 ) ( 1 ) Madison ( 1 ) < ( 1 ) ( 1! ) ) Milwaukee-Waukesha-West Allis Oshkosh-Neenah ( 1 ) ( 1 ) ( 1 ) Racine ( 1 ) ( 1 ) ( 1 ) Sheboygan ( 1 ) ( 1 ) ( 1 ) Wausau ( 1 ) ( 1 ) ( 1 ) Wyoming Casper Cheyenne ( 1 ) ( 1 ) ( 1 ) Puerto Rico 1, , ,035.4 ( 1 ) < 1 ) ( 1 ) Aguadilla-lsabela-San Sebastian ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Fajardo ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) < 2 Guayama ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 2 ) Mayaguez ( 2 ) ( 2 ) ( 2 ) ( 2 ) Ponce (?> 1 ) ( 1 ) ( 1 ) San German-Cabo Rojo ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) San Juan-Caguas-Guaynabo ( 1 ) ( 1 ) ( 1 ) Yauco ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Virgin islands ( 1 ) ( 1 ) ( 1 )

125 (Int Trade, tra nsportation, and utilities 20G5P 2005P t Lake City ' , ) , ( 2 ) ( 2 ) ( 2 ) : , ( 2 ) ( 2 ) III , B ,9 9.9 ( 2 ) ( 2 ) ,7 3.7 / 2 \ ,9 9.9 ( 2 ) ( 2 ) ( 2 ) / 2 \ ( 2 ) ( 2 ) i C , , , , , , S , ( 2 ) ( 2 ) ( 2 ) , , I ( 2 ) ( 2 ) ( 2 ) ( 2 ) 19.4 ( 2 ) lii.6 (2 k 5 8 ( 2 )

126 (In thousands) State and area Financial activities Professional and business services Education and health services 2005P 2005P 2005P Utah Logan Ogden-Clearfield Provo-Orem St. George Salt Lake City Vermont Burlington-South Burlington Virginia Blacksburg-Christiansburg-Radford ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Charlottesville 2 2 ( 2 ) ( ) Danville 2 ( ) Harrisonburg ( ( 2 ) ( 2 ) ( ) Lynchburg < 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) < 2 > Richmond Roanoke Virginia Beach-Norfolk-Newport News Winchester ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Washington Bellingham Bremerton-Silverdale ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Kennewick-Richland-Pasco Longview 2 ( Mount Vemon-Anacortes ( 2 ) < 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Olympia ( 2 ) ( 2 ) ( 2 ) Seattle-Tacoma-Bellevue Spokane Wenatchee O 2 2 ( 2 ) ( 2 ) ( 2 ) Yakima ( 2 ) ( 2 ) ( 2 ) West Virginia Charleston Huntington-Ashland ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Morgantown ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Parkersburg-Marietta ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Wheeling ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Wisconsin Appleton Eau Claire Fond du Lac Green Bay Janesville La Crosse Madison Milwaukee-Waukesha-West Allis Oshkosh-Neenah Racine Sheboygan Wausau Wyoming Casper Cheyenne Puerto Rico Aguadilla-lsabela-San Sebastian ( 2 2 ( 2 ) Fajardo ( Guayama ( 2 ) ( 2 ) ( 2 ) Mayaguez ( 2 ) ( 2 ) ( 2 ) Ponce San German-Cabo Rojo ( 2 ) ( 2 ) < 2 > ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) San Juan-Caguas-Guaynabo Yauco ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Virgin Islands

127 (In thousands) State and area Leisure and hosp all y Other services Government in. 005P 2005P 2005P Utah Logan Ogden-Clearfield Provo-Orem St. George Salt Lake City Vermont Burlington-South Burlington Virginia Blacksburg-Christiansburg-Radford ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Charlottesville ( 2 ) ( 2 ) ( 2 ) Danville ( 2 ) ( 2 ) ( 2 ) Harrisonburg ( 2 ) ( 2 ) (2) <V O o> Lynchburg ( 2 ) ( 2 ) ( 2 ) Richmond Roanoke Virginia Beach-Norfolk-Newport News Winchester ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Washington Bellingham ( 2 ) ( 2 ) ( 2 ) Bremerton-Silverdale ( 2 ) ( 2 ) ( 2 ) Kennewick-Richland-Pasco ( 2 ) ( 2 ) ( 2 ) Longview ( 2 ) ( 2 ) ( 2 ) Mount Vemon-Anacortes ( 2 ) ( 2 ) ( 2 ) Olympia ( 2 ) ( 2 ) ( 2 ) Seattle-Tacoma-Bellevue i Spokane Wenatchee ( 2 ) ( 2 ) ( 2 ) Yakima ( 2 ) ( 2 ) ( 2 ) West Virginia ( Charleston Huntington-Ashland ( 2 ) ( 2 ) ( 2 ) Morgantown (1 4.7 ( 2 ) ( 2 ) ( 2 ) Parkersburg-Marietta ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Wheeling ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Wisconsin Appleton Eau Claire Fond du Lac Green Bay Janesville La Crosse ? Madison ! Milwaukee-Waukesha-West A!lis Oshkosh-Neenah Racine Sheboygan :> Wausau Wyoming Casper Cheyenne Puerto Rico Aguadilla-lsabela-San Sebastian ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 > ( 2 ) Fajardo ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Guayama <o> ( 2 ) ( 2 ) ( 2 ) ( 2 ) Mayaguez ( 2 ) ( 2 ) ( 2 ) ( ) ( 2 ) Ponce 3.2 <?> ( 2 ) ( 2 ) ( 2 ) San German-Cabo Rojo ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) San Juan-Caguas-Guaynabo Yauco ( 2 ) ( 2 ) ( 2 > ( 2 ) ( 2 ) ( 2 ) Virgin Islands Natural resources and mining is combined with construction. 2 Data not available. 3 Area boundaries do not reflect official OMB definitions. P = preliminary. NOTE: Data are counts of jobs by place of work. Data have been revised to reflect benchmark levels. Metropolitan area data have been revised back to 1990 to incorporate new area definitions. Area definitions are based on Office of Management and Budget Bulletin No , dated February 18,, and are available at and in the May issue of Employment and Earnings. Areas in the six New England states are Metropolitan New England City and Town Areas (NECTAs), while areas in other states are county-based. Some metropolitan areas lie in two or more states. They are listed under the state that appears first in their titles. Davenport-Moline-Rock Island, Iowa-Ill., and Weirton-Steubenville, W. Va.-Ohio, are the exceptions in that they are listed under Illinois and Ohio, respectively, for operational reasons.

128 (Numbers in thousands) Total Natural resources and mining State, area, and division California 14, , , Los Angeles-Long Beach-Santa Ana 5, , , Los Angeles-Long Beach-Glendale 3, , , Santa Ana-Anaheim-Irvine 1, , , San Francisco-Oakland-Fremont 1, , , Oakland-Fremont-Hayward 1, , , San Francisco-San Mateo-Redwood City District of Columbia < 1 > Washington-Arlington-Alexandria 2, , , Bethesda-Frederick-Gaithersburg (!> 1 Washington-Arlington-Alexandria 2, , ,295.1 ( 1 ) ( 1 ) ( 1 ) Florida 7, , , Miami-Fort Lauderdale-Miami Beach 2, , , Fort Lauderdale-Pompano Beach-Deerfield Beach ( 2 ) ( 2 ) ( 2 ) Miami-Miami Beach-Kendall 1, , , West Palm Beach-Boca Raton-Boynton Beach ( 2 ) ( 2 ) ( 2 ) Illinois 5, , , Chicago-Naperville-Joliet 4, , ,326.7 ( 1 ) ( 1 ) < 1 ) Chicago-Naperville-Joliet 3, , , Gary ( 1 ) ( 1 ) < 1 ) Lake County-Kenosha County Massachusetts 3, , , Boston-Cambridge-Quincy 2, , , Boston-Cambridge-Quincy 1, , , Brockton-Bridgewater-Easton > Framingham Haverhill-North Andover-Amesbury Lowell-Billerica-Chelmsford Lynn-Peabody-Salem Nashua ( 1 ) ( 1 ) ( 1 ) Michigan 4, , , Detroit-Warren-Livonia 2, , , ( 1 ) Detroit-Livonia-Dearborn ( 1 1 Warren-Farmington Hills-Troy 1, , ,169.9 < 1 ) ( 1 ) ( 1 ) New York 8, , , New York-Northern New Jersey-Long Island 8, , , Edison , Nassau-Suffolk 1, , , New York-Wayne-White Plains 4, , , Newark-Union 1, , ,010.8 ( 1 ) ( 1 ) ( 1 ) Pennsylvania 5, , , Philadelphia-Camden-Wilmington 2, , , Camden Philadelphia 1, , , ( 1 ) 1 Wilmington ( 1 ) < 1 > ( 1 ) Texas 9, , , Dallas-Fort Worth-Arlington 2, , , Dallas-Plano-lrving 1, , , Fort Worth-Arlington ( 1 ) ( 1 ) ( 1 ) Washington 2, , , Seattle-Tacoma-Bellevue 1, , , Seattle-Bellevue-Everett 1, , , Tacoma See footnotes at end of table.

129 (Numbers in thousands) State, area, and division Construction Manufacturing California , , ,519.4 Los Angeles-Long Beach-Santa Ana Los Angeles-Long Beach-Glendale Santa Ana-Anaheim-Irvine San Francisco-Oakland-Fremont Oakland-Fremont-Hayward San Francisco-San Mateo-Redwood City District of Columbia Washington-Arlington-Alexandria Bethesda-Frederick-Gai.hersburg Washington-Arlington-Aiexaridria Florida Miami-Fort Lauderdale-Miami Beach Fort Lauderdale-Pompano Beach-Deerfield Beach Miami-Miami Beach-Kendall West Palm Beach-Boca Raton-Boynton Beach Illinois Chicago-Naperville-Joliet Chicago-Naperville-Joliet Gary Lake County-Kenosha County Massachusetts Boston-Cambridge-Quincy Boston-Cambridge-Quiricy Brockton-Bridgewater-Easton Framingham Haverhill-North Andover-Amesbury Lowell-Billerica-Chelmsford Lynn-Peabody-Salem Nashua Michigan Detroit-Warren-Livonia Detroit-Livonia-Dearborn Warren-Farmington Hills-Troy New York New York-Northern New Jersey-Long Island Edison Nassau-Suffolk New York-Wayne-White Plains Newark-Union Pennsylvania Philadelphia-Camden-Wilmington Camden Philadelphia Wilmington Texas Dallas-Fort Worth-Arlington Dallas-Plano-lrving Fort Worth-Arlington Washington Seattle-Tacoma-Bellevue Seattle-Bellevue-Everett Tacoma See footnotes at end of table.

130 (Numbers in thousands) State, area, and division Trade, transportation, and utilities Information California 2, , , Los Angeles-Long Beach-Santa Ana 1, , , Los Angeles-Long Beach-Glendale Santa Ana-Anaheim-Irvine San Francisco-Oakland-Fremont Oakland-Fremont-Hayward San Francisco-San Mateo-Redwood City District of Columbia Washington-Ariington-Alexandria Bethesda-Frederick-Gaithersburg Washington-Arlington-Alexandria Florida 1, , , Miami-Fort Lauderdale-Miami Beach Fort Lauderdale-Pompano Beach-Deerfield Beach Miami-Miami Beach-Kendall West Palm Beach-Boca Raton-Boynton Beach Illinois 1, , , Chicago-Naperville-Joliet Chicago-Naperville-Joliet Gary Lake County-Kenosha County Massachusetts Boston-Cambridge-Quincy Boston-Cambridge-Quincy Brockton-Bridgewater-Easton Framingham Haverhill-North Andover-Amesbury Lowell-Billerica-Chelmsford Lynn-Peabody-Salem Nashua Michigan Detroit-Warren-Livonia Detroit-Livonia-Dearborn Warren-Farmington Hills-Troy New York 1, , , New York-Northern New Jersey-Long Island 1, , , Edison Nassau-Suffolk New York-Wayne-White Plains Newark-Union Pennsylvania 1, , , Philadelphia-Camden-Wilmington Camden Philadelphia Wilmington Texas 1, , , Dallas-Fort Worth-Arlington Dallas-Plano-lrving Fort Worth-Arlington Washington Seattle-Tacoma-Bellevue Seattle-Bellevue-Everett Tacoma See footnotes at end of table.

131 (Numbers in thousands) Financial activities Professional and business services State, area, arid division California , , ,103.5 Los Angeles-Long Beach-Santa Ana Los Angeles-Long Beach-Glendale Santa Ana-Anaheim-Irvine San Francisco-Oakland-Fremont Oakland-Fremont-Hayward San Francisco-San Maieo-Redwood City District of Columbia Washington-Arlington-Alexandria Bethesda-Frederick-Gaithersburg Washington-Arlington-Alexandria Florida , , ,322.2 Miami-Fort Lauderdale-Miami Beach Fort Lauderdale-Pompano Beach-Deerfield Beach Miami-Miami Beach-Kendall West Palm Beach-Boca Ralon-Boynton Beach Illinois Chicago-Naperville-Joliet Chicago-Naperville-Joliet Gary Lake County-Kenosha County Massachusetts Boston-Cambridge-Quincy Boston-Cambridge-Quincy Brockton-Bridgewater-Faston Framingham Haverhill-North Andover-Amesbury Lowell-Billerica-Chelmsford Lynn-Peabody-Salem Nashua Michigan Detroit-Warren-Livonia Detroit-Livonia-Dearborn Warren-Farmington Hills-Troy New York , , ,033.8 New York-Northern New Jersey-Long Island , , ,193.7 Edison Nassau-Suffolk New York-Wayne-White Plains Newark-Union Pennsylvania Philadelphia-Camden-Wilmington Camden Philadelphia Wilmington Texas , , ,076.8 Dallas-Fort Worth-Arlington Dallas-Plano-lrving Fort Worth-Arlington Washington Seattle-Tacoma-Bellevue Seattle-Bellevue-Everett Tacoma See footnotes at end of table.

132 (Numbers in thousands) State, area, and division Education and health services Leisure and hospitality California 1, , , , , ,430.2 Los Angeles-Long Beach-Santa Ana Los Angeles-Long Beach-Glendale Santa Ana-Anaheim-Irvine San Francisco-Oakland-Fremont Oakland-Fremont-Hayward CI San Francisco-San Mateo-Redwood City District of Columbia CI Washington-Arlington-Alexandria Bethesda-Frederick-Gaithersburg Washington-Arlington-Alexandria Florida Miami-Fort Lauderdale-Miami Beach Fort Lauderdale-Pompano Beach-Deerfield Beach Miami-Miami Beach-Kendall West Palm Beach-Boca Raton-Boynton Beach Illinois Chicago-Naperville-Joliet Chicago-Naperville-Joliet Gary ! Lake County-Kenosha County Massachusetts Boston-Cambridge-Quincy Boston-Cambridge-Quincy Brockton-Bridgewater-Easton Framingham Haverhill-North Andover-Amesbury Lowell-Billerica-Chelmsford Lynn-Peabody-Salem Nashua Michigan Detroit-Warren-Livonia Detroit-Livonia-Dearborn Warren-Farmington Hills-Troy New York 1, , , New York-Northern New Jersey-Long Island 1, , , Edison Nassau-Suffolk New York-Wayne-White Plains Newark-Union Pennsylvania , Philadelphia-Camden-Wilmington Camden Philadelphia Wilmington Texas 1, , , Dallas-Fort Worth-Arlington Dallas-Plano-lrving Fort Worth-Arlington Washington Seattle-Tacoma-Bellevue Seattle-Bellevue-Everett Tacoma See footnotes at end of table.

133 (Numbers in thousands) Other services Government State, area, and division California , , ,384.4 Los Angeles-Long Beach-Santa Ana Los Angeles-Long Beach-Glendale Santa Ana-Anaheim-Irvine San Francisco-Oakland-Fremont Oakland-Fremoni-Hayward San Francisco-San Mateo-Redwood City District of Columbia Washington-Arlington-Alexandria Bethesda-Frederick-Gaithersburg Washington-Arlington-Alexandria Florida , , ,085.4 Miami-Fort Lauderdale-Miami Beach Fort Lauderdale-Pompano Eieach-Deerfield Beach Miami-Miami Beach-Kendall West Palm Beach-Boca Raton-Boynton Beach Illinois Chicago-Naperville-Joliet Chicago-Naperville-Joliet Gary Lake County-Kenosha County Massachusetts Boston-Cambridge-Quincy Boston-Cambridge-Quincy Brockton-Bridgewater-Faston Framingham Haverhill-North Andover-Amesbury Lowell-Billerica-Chelmsford Lynn-Peabody-Salem Nashua Michigan Detroit-Warren-Livonia Detroit-Livonia-Dearborn Warren-Farmington Hiils-Troy New York , , ,474.2 New York-Northern New Jersey-Long Island , , ,268.0 Edison Nassau-Suffolk New York-Wayne-White Plains Newark-Union Pennsylvania Philadelphia-Camden-Wilmirigton Camden Philadelphia Wilmington Texas , , ,662.0 Dallas-Fort Worth-Arlinoton Dallas-Plano-lrving Fort Worth-Arlington Washington Seattle-Tacoma-Bellevue Seattle-Bellevue-Everett Tacoma Natural resources and mining is combined with construction. 2 Data not available. P = preliminary. NOTE: Data are counts of jobs by place of work. Data have been revised to reflect benchmark levels. Metropolitan area data have been revised back to 1990 to incorporate new area definitions. Area definitions are based on Office of Management and Budget Bulletin No , dated February 18,, and are available at and in the May issue of Employment and Earnings. Areas in the six New England states are Metropolitan New England City and Town Areas (NECTAs), while areas in other states are county-based. Some metropolitan areas lie in two or more states. They are listed under the state that appears first in their titles. Some divisions lie in more than one state, and some, like Camden, N.J., are totally outside the states under which their metropolitan areas are listed. This table introduces data for metropolitan divisions.

134 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Total private Goods-producing Natural resources and mining _ Logging Mining Oil and gas extraction Mining, except oil and gas Coal mining Bituminous coal and lignite surface mining Bituminous coal underground mining and anthracite mining , Metal ore mining Nonmetallic mineral mining and quarrying Stone mining and quarrying Crushed and broken limestone mining Other stone mining and quarrying ,3, Sand, gravel, clay, and refractory mining Construction sand and gravel mining Other nonmetallic mineral mining Support activities for mining Support activities for oil and gas operations Construction Construction of buildings Residential building New single-family general contractors Residential remodelers Nonresidential building Industrial building Commercial building Heavy and civil engineering construction Utility system construction Water and sewer system construction Oil and gas pipeline construction Power and communication system construction Land subdivision Highway, street, and bridge construction Other heavy construction Specialty trade contractors Building foundation and exterior contractors F'oured concrete structure contractors Steel and precast concrete contractors Framing contractors Masonry contractors Glass and glazing contractors Ftoofing contractors Building equipment contractors » Electrical contractors FMumbing and HVAC contractors Other building equipment contractors Building finishing contractors Drywall and insulation contractors Fainting and wall covering contractors Flooring contractors Tile and terrazzo contractors Finish carpentry contractors Other building finishing contractors Other specialty trade contractors _ Site preparation contractors All other specialty trade contractors Manufacturing Durable goods Wood products Sawmills and wood preservation _

135 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Total private $ $15.88 $16.01 $15.93 $ $ $ $ $ Goods-producing Natural resources and mining Logging Mining Oil and gas extraction , Mining, except oil and gas Coal mining , , , , Bituminous coal and lignite surface mining , , , , Bituminous coal underground mining and anthracite mining , , , , , Metal ore mininq , , , , Nonmetallic mineral mining and quarrying Stone mining and quarrying Crushed and broken limestone mining Other stone mining and quarrying ,3, Sand, gravel, clay, and refractory mining Construction sand and gravel mining Other nonmetallic mineral mining Support activities for mining Support activities for oil and gas operations Construction Construction of buildings Residential building New single-family general contractors Residential remodelers Nonresidential building Industrial building Commercial building Heavy and civil engineering construction Utility system construction Water and sewer system construction Oil and gas pipeline construction Power and communication system construction Land subdivision Highway, street, and bridge construction Other heavy construction Specialty trade contractors Building foundation and exterior contractors Poured concrete structure contractors Steel and precast concrete contractors Framing contractors Masonry contractors Glass and glazing contractors Roofing contractors Building equipment contractors Electrical contractors Plumbing and HVAC contractors Other building equipment contractors Building finishing contractors Drywall and insulation contractors Painting and wall covering contractors Flooring contractors Tile and terrazzo contractors Finish carpentry contractors Other building finishing contractors Other specialty trade contractors Site preparation contractors All other specialty trade contractors Manufacturing Durable goods Wood products Sawmills and wood preservation

136 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours 2005 p Durable goods-continued Plywood and engineered wood products Hardwood and softwood veneer and plywood , Engineered wood members and trusses , Other wood products Millwork Wood windows and doors Cut stock, resawing lumber, planing, and other millwork, including flooring , Wood containers and pallets Ail other wood products Manufactured and mobile homes Nonmetallic mineral products Clay products and refractories Pottery, ceramics, and plumbing fixtures Clay building material and refractories Glass and glass products Flat glass and other pressed and blown glass and glassware , Glass products made of purchased glass Cement and concrete products Ready-mix concrete Other cement and concrete products 32731,3, Lime, gypsum, and other nonmetallic mineral products 3274, Primary metals Iron and steel mills and ferroalloy production Steel products from purchased steel » Iron, steel pipe, and tube from purchase steel Rolling and drawing of purchased steel Alumina and aluminum production Other nonferrous metal production Rolled, drawn, extruded, and alloyed copper,, Nonferrous metal, except CU and AL, shaping Foundries Ferrous metal foundries Iron foundries Steel foundries , _ Nonferrous metal foundries Fabricated metal products Forging and stamping Iron and steel forging Metal stamping Cutlery and hand tools Hand and edge tools Architectural and structural metals Plate work and fabricated structural products Prefabricated metal buildings and components ~ Fabricated structural metal products Plate work Ornamental and architectural metal products Metal windows and doors Sheet metal work Ornamental and architectural metal work Boilers, tanks, and shipping containers Hardware Spring and wire products Machine shops and threaded products Machine shops Turned products and screws, nuts, and bolts Precision turned products «Bolts, nuts, screws, rivets, and washers Coating, engraving, and heat treating metals Metal heat treating and coating and nonprecious engraving , Electroplating, anodizing, and coloring metals Other fabricated metal products

137 Industry 2002 NAICS code Avg. I Average hourly earnings Avg. Average weekly earnings Durable goods-continued Plywood and engineered wood products 3212 $13.23 $-:;.04 $13.21 $ $ $ $ $ Hardwood and softwood veneer and plywood , Engineered wood members and trusses , Other wood products ' Millwork ' Wood windows and doors i Cut stock, resawing lumber, planing, and other millwork, including flooring , Wood containers and pallets ! All other wood products Manufactured and mobile homes Nonmetallic mineral products $ $ Clay products and refractories Pottery, ceramics, and plumbing fixtures Clay building material and refractories Glass and glass products Flat glass and other pressed and blown glass and glassware , Glass products made of purchased glass Cement and concrete products Ready-mix concrete Other cement and concrete products ,3, Lime, gypsum, and other nonmetallic mineral products 3274, Primary metals Iron and steel mills and ferroalloy production , , , , Steel products from purchased steel Iron, steel pipe, and tube from purchase steel Rolling and drawing of purchased steel Alumina and aluminum production _ Other nonferrous metal production Rolled, drawn, extruded, and alloyed copper Nonferrous metal, except CU and AL, shaping Foundries Ferrous metal foundries d Iron foundries Steel foundries , Nonferrous metal foundries Fabricated metal products Forging and stamping Iron and steel forging Metal stamping Cutlery and hand tools Hand and edge tools Architectural and structural metals Plate work and fabricated structural products Prefabricated metal buildings and components Fabricated structural metal products Plate work , Ornamental and architectural metal products Metal windows and doors Sheet metal work Ornamental and architectural metal work Boilers, tanks, and shipping containers Hardware Spring and wire products Machine shops and threaded products Machine shops Turned products and screws, nuts, and bolts Precision turned products Bolts, nuts, screws, rivets, and washers Coating, engraving, and heat treating metals Metal heat treating and coating and nonprecious engraving , Electroplating, anodizing, and coloring metals Other fabricated metal products

138 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Durable goods-continued Metal valves Fluid power valves and hose fittings Industrial valves and other metal valves and 5.3 pipe fittings , All other fabricated metal products Ball and roller bearings Small arms, ammunition, and other ordnance 6.3 and accessories ,3,4, Miscellaneous fabricated metal products ,7,8, Machinery Agricultural, construction, and mining machinery Agricultural implements Farm machinery and equipment Construction machinery Industrial machinery Commercial and service industry machinery Photographic and photocopying equipment Miscellaneous commercial and service industry machinery ,2,4, HVAC and commercial refrigeration equipment AC, refrigeration, and forced air heating Metalworking machinery Industrial molds Metal cutting and forming machine tools , Special tools, dies, jigs, and fixtures Miscellaneous metalworking machinery ,6, Turbine and power transmission equipment Power transmission and miscellaneous engine equipment ,3, Other general purpose machinery Pumps and compressors Pumps and pumping equipment, including measuring and dispensing , Material handling equipment Conveyor and conveying equipment All other general purpose machinery Computer and electronic products Computer and peripheral equipment Communications equipment Broadcast and wireless communications equipment Audio and video equipment Semiconductors and electronic components Bare printed circuit boards Semiconductors and related devices Printed circuit assemblies Electronic connectors and misc. electronic components ,6,7, Electronic instruments Electromedical apparatus Search, detection, and navigation instruments Industrial process variable instruments Electricity and signal testing instruments Irradiation apparatus » Miscellaneous electronic instruments ,6,8, Electrical equipment and appliances Electric lighting equipment Electric lamp bulbs and parts Lighting fixtures Household appliances Electrical equipment Motors and generators Switchgear and switchboard apparatus Relays and industrial controls Other electrical equipment and components Wiring devices

139 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Durable goods-continued Metal valves $16.06 $15,84 $16.42 $16.41 $ $ $ $ Fluid power valves and hose fittings , Industrial valves and other metal valves and pipe fittings , , All other fabricated metal products Ball and roller bearings Small arms, ammunition, and other ordnance and accessories ,3,4, Miscellaneous fabricated metal products ,7,8, , Machinery $ $ Agricultural, construction, and mining machinery Agricultural implements Farm machinery and equipment » Construction machinery Industrial machinery Commercial and service industry machinery Photographic and photocopying equipment , , Miscellaneous commercial and service industry machinery ,2,4, HVAC and commercial refrigeration equipment AC, refrigeration, and forced air heating Metalworking machinery Industrial molds Metal cutting and forming machine tools , Special tools, dies, jigs, and fixtures Miscellaneous metalworking machinery ,6, Turbine and power transmission equipment Power transmission and miscellaneous engine equipment ,3, Other general purpose machinery Pumps and compressors Pumps and pumping equipment, including measuring and dispensing , Material handling equipment Conveyor and conveying equipment All other general purpose machinery Computer and electronic products Computer and peripheral equipment Communications equipment Broadcast and wireless communications equipment Audio and video equipment Semiconductors and electronic components Bare printed circuit boards Semiconductors and related devices » » Printed circuit assemblies Electronic connectors and misc. electronic components ,6,7, Electronic instruments Electromedical apparatus Search, detection, and navigation instruments Industrial process variable instruments Electricity and signal testing instruments Irradiation apparatus Miscellaneous electronic instruments ,6,8, Electrical equipment and appliances Electric lighting equipment Electric lamp bulbs and parts Lighting fixtures Household appliances Electrical equipment Motors and generators Switchgear and switchboard apparatus Relays and industrial controls Other electrical equipment and components Wiring devices

140 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Durable goods-continued Current-carrying wiring devices All other electrical equipment and components Transportation equipment Motor vehicles and parts 3361,2, Motor vehicles Automobiles and light trucks Automobiles Light trucks and utility vehicles Heavy duty trucks Motor vehicle bodies and trailers Motor vehicle bodies Truck trailers Travel trailers and campers Motor vehicle parts Motor vehicle gasoline engine and parts Gasoline engine and engine parts Motor vehicle electric equipment Other motor vehicle electric equipment Motor vehicle steering and suspension parts Motor vehicle power train components Motor vehicle seating and interior trim Motor vehicle metal stamping Other motor vehicle parts All other motor vehicle parts Aerospace products and parts Aircraft Aircraft engines and engine parts Other aircraft parts and equipment Ship and boat building Ship building and repairing Boat building Furniture and related products Household and institutional furniture Wood kitchen cabinets and countertops Other household and institutional furniture Upholstered household furniture Nonupholstered wood household furniture Miscellaneous household and institutional furniture ,5,7, Office furniture and fixtures Wood office furniture and custom architectural woodwork and millwork , Showcases, partitions, shelving, and lockers Other furniture-related products Miscellaneous manufacturing Medical equipment and supplies Surgical and medical instruments » Surgical appliances and supplies Dental laboratories _ Other miscellaneous manufacturing Jewelry and silverware » Sporting and athletic goods Office supplies, except paper Signs All other miscellaneous manufacturing Nondurable goods Food manufacturing _ Animal food Grain and oilseed milling Flour milling, malt, starch, and vegetable oil 31121, _ Sugar and confectionery products Sugar Chocolate confectioneries 31132, ~ Fruit and vegetable preserving and specialty Frozen food Frozen fruits and vegetables

141 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Durable goods-continued Current-carrying wiring devices $14.22 $14.15 $14.10 $14.19 $ $ $ $ All other electrical equipment and components Transportation equipment $ $ Motor vehicles and parts 3361,2, , Motor vehicles , , , , , Automobiles and light trucks , , , , , Automobiles , , , , Light trucks and utility vehicles , , , , Heavy duty trucks , Motor vehicle bodies and trailers , Motor vehicle bodies , Truck trailers , Travel trailers and campers Motor vehicle parts , Motor vehicle gasoline engine and parts , , Gasoline engine and engine parts , , , , , Motor vehicle electric equipment , Other motor vehicle electric equipment , Motor vehicle steering and suspension parts , , , , Motor vehicle power train components , , , , Motor vehicle seating and interior trim Motor vehicle metal stamping , , Other motor vehicle parts , «All other motor vehicle parts Aerospace products and parts , , , , Aircraft , , , , Aircraft engines and engine parts , , , , Other aircraft parts and equipment Ship and boat building Ship building and repairing Boat building Furniture and related products Household and institutional furniture Wood kitchen cabinets and countertops Other household and institutional furniture Upholstered household furniture Nonupholstered wood household furniture Miscellaneous household and institutional furniture ,5,7, Office furniture and fixtures Wood office furniture and custom architectural woodwork and millwork , Showcases, partitions, shelving, and lockers Other furniture-related products , Miscellaneous manufacturing , Medical equipment and supplies , Surgical and medical instruments Surgical appliances and supplies Dental laboratories Other miscellaneous manufacturing Jewelry and silverware Sporting and athletic goods Office supplies, except paper Signs All other miscellaneous manufacturing ~ Nondurable goods Food manufacturing Animal food Grain and oilseed milling Flour milling, malt, starch, and vegetable oil 31121, , Sugar and confectionery products Sugar Chocolate confectioneries 31132, Fruit and vegetable preserving and specialty Frozen food Frozen fruits and vegetables

142 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Nondurable goods-continued Frozen specialty food Fruit and vegetable canning and drying Fruit and vegetable canning Dried and dehydrated food _ Dairy products Dairy products, except frozen Fluid milk Animal slaughtering and processing Animal, except poultry, slaughtering Meat processed from carcasses, and rendering and meat byproduct processing , Poultry processing Seafood product preparation and packaging Bakeries and tortilla manufacturing Bread and bakery products Retail bakeries _ Commercial bakeries and frozen cakes and other pastry products , Cookies, crackers, pasta, and tortillas 31182, Other food products Snack food Miscellaneous food products 31192,3,4, Beverages and tobacco products Beverages Soft drinks and ice Soft drinks Breweries, wineries, and distilleries 31212,3, Textile mills Fiber, yarn, and thread mills Fabric mills Broadwoven fabric mills Textile and fabric finishing mills Broadwoven fabric finishing mills Textile product mills Textile furnishings mills Curtain and linen mills Other textile product mills Textile bag and canvas mills AH other textile product mills Apparel Apparel knitting mills Hosiery and sock mills Sheer hosiery mills ~ Other hosiery and sock mills Cut and sew apparel Cut and sew apparel contractors Men's cut and sew apparel contractors ~ Women's cut and sew apparel contractors Men's cut and sew apparel Women's cut and sew apparel » Accessories and other apparel Leather and allied products Footwear Leather and hide tanning and finishing and other leather products 3161, Paper and paper products Pulp, paper, and paperboard mills Pulp mills and paper mills 32211, _ Paperboard mills Converted paper products Paperboard containers Corrugated and solid fiber boxes Folding paperboard boxes Miscellaneous paperboard containers ,4, Paper bags and coated and treated paper Coated and laminated package materials and paper ,

143 industry 2002 NAiCS code Avg. Average hourly earnings Avg. Average weekly earnings Nondurable goods-continued Frozen specialty food $11.54 $1108 $12.08 $11.91 $ $ $ $ Fruit and vegetable canning and drying , Fruit and vegetable canning , Dried and dehydrated food Dairy products Dairy products, except frozen Fluid milk Animal slaughtering and processing Animal, except poultry, slaughtering Meat processed from carcasses, and rendering and meat byproduct processing , i no Poultry processing ') Seafood product preparation and packaging Bakeries and tortilla manufacturing h>.c Bread and bakery products ,> Retail bakeries Commercial bakeries and frozen cakes and other pastry products , Cookies, crackers, pasta, and tortillas 31182, > = Other food products I > Snack food ).fc Miscellaneous food products 31192,3,4, i Beverages and tobacco products H $ $ Beverages l. s G Soft drinks and ice i ; >.C Soft drinks I i i Breweries, wineries, and distilleries 31212,3, I J Textile mills ' ' Fiber, yarn, and thread mills 'i Fabric mills » Broadwoven fabric mills \ _ Textile and fabric finishing mills » ] Broadwoven fabric finishing mills » Textile product mills I Textile furnishings mills I Curtain and linen mills U Other textile product mills $ Textile bag and canvas mills All other textile product mills : Apparel 'i? Apparel knitting mills In Hosiery and sock mills ' -~ Sheer hosiery mills * i -, Other hosiery and sock mills MJ Cut and sew apparel M Cut and sew apparel contractors MJ Men's cut and sew apparel contractors ' i Women's cut and sew apparel contractors , Men's cut and sew apparel ' i Women's cut and sew apparel f > Accessories and other apparel ') Leather and allied products ! Footwear Leather and hide tanning and finishing and other leather products 3161, ' Paper and paper products Pulp, paper, and paperboard mills , , Pulp mills and paper mills , , , Paperboard mills , , , , Converted paper products Paperboard containers Corrugated and solid fiber boxes Folding paperboard boxes Miscellaneous paperboard containers ,4, Paper bags and coated and treated paper _ Coated and laminated package materials and paper ,

144 Industry 2002 NAICS code Avg. Average weekly hours 2005 p Avg. Average overtime hours Nondurable goods-continued Miscellaneous coated and treated paper and paper bags ,4,5, Stationery products Other converted paper products Printing and related support activities Commercial lithograph printing Commercial flexographic printing Commercial screen printing Quick printing Manifold business forms printing _ Commercial gravure and misc. commercial ,5,7,8 printing Support activities for printing Petroleum and coal products Petroleum refineries Asphalt paving and roofing materials and other petroleum and coal products 32412, Chemicals Basic chemicals Other basic inorganic chemicals Resin, rubber, and artificial fibers Resin and synthetic rubber Plastics material and resin Agricultural chemicals Pharmaceuticals and medicines Pharmaceutical preparations Miscellaneous medicinal and biological products ,3, Paints, coatings, and adhesives Paints and coatings Soaps, cleaning compounds, and toiletries Soaps and cleaning compounds Polishes and other sanitation goods and surface active agents , Toilet preparations Other chemical products and preparations Plastics and rubber products Plastics products Plastics packaging materials, film, and sheet Nonpackaging plastics film and sheet Plastics pipe, fittings, and profile shapes Unlaminated plastics profile shapes Plastics pipe and pipe fittings Foam products 32614, Plastics bottles and laminated plastics plate, sheet, and shapes 32613, Other plastics products Rubber products » Tires Other rubber products Rubber products for mechanical use All other rubber products Private service-providing Trade, transportation, and utilities Wholesale trade Durable goods Motor vehicles and parts Motor vehicles » - - New motor vehicle parts Furniture and furnishings Home furnishings Lumber and construction supplies » Lumber and wood Masonry materials Roofing, siding, and other construction materials 42333,

145 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Nondurable goods-continued Miscellaneous coated and treated paper $14,03 Stationery products Other converted paper products , and paper bags ,4,5,6 $ $ $ $ $ $ $ Printing and related support activities ' 5, $ $ Commercial lithograph printing Commercial flexographic printing ' Commercial screen printing ' Quick printing ' Manifold business forms printing ' Commercial gravure and misc. commercial ,5,7,8 printing J Support activities for printing _ Petroleum and coal products , , , , , Petroleum refineries , , , , Asphalt paving and roofing materials and other petroleum and coal products 32412, Chemicals , Basic chemicals , , , ,82 Other basic inorganic chemicals , , Resin, rubber, and artificial fibers ! Resin and synthetic rubber , Plastics material and resin , ; Agricultural chemicals , Pharmaceuticals and medicines , Pharmaceutical preparations , _ Miscellaneous medicinal and biological products ,3, , _ Paints, coatings, and adhesives , Paints and coatings , Soaps, cleaning compounds, and toiletries , Soaps and cleaning compounds , Polishes and other sanitation goods and surface active agents , P Toilet preparations Ibi Other chemical products and preparations Plastics and rubber products ' Plastics products FfS ! Plastics packaging materials, film, and sheet i ) ' Nonpackaging plastics film and sheet i 3, , Plastics pipe, fittings, and profile shapes i "' Unlaminated plastics profile shapes ? M ! Plastics pipe and pipe fittings i 2 ' Foam products , Plastics bottles and laminated plastics plate, sheet, and shapes 32613, I ) S Other plastics products J'H Rubber products i> Tires ' i Other rubber products _ i Rubber products for mechanical use ; All other rubber products Private service-providing, JOO.SO Trade, transportation, and utilities m.m Wholesale trade >7C Durable goods ' Motor vehicles and parts " i ; Motor vehicles j New motor vehicle parts C I Furniture and furnishings 4232 ; r Home furnishings I Lumber and construction supplies ' Lumber and wood S Masonry materials Roofing, siding, and other construction materials ,

146 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Wholesale trade-continued Commercial equipment Office equipment Computer and software Medical equipment Miscellaneous professional and commercial equipment 42341,4,6, Metals and minerals Electric goods Electrical equipment and wiring Electric appliances and other electronic parts 42362, Hardware and plumbing Hardware Plumbing equipment HVAC and refrigeration equipment 42373, Machinery and supplies Construction equipment Farm and garden equipment Industrial machinery Industrial supplies Service establishment equipment Miscellaneous durable goods Recyclable materials Toy, hobby, and other durable goods 42392, Nondurable goods Paper and paper products _ Printing and writing paper and office supplies 42411, Industrial paper Druggists' goods Apparel and piece goods Grocery and related products General line grocery Fruits and vegetables Farm product raw materials Grains and field beans Chemicals Other chemicals Petroleum Alcoholic beverages Beer and ale Misc. nondurable goods Farm supplies Paint, painting supplies, and other nondurable goods 42495, Electronic markets and agents and brokers Business to business electronic markets Wholesale trade agents and brokers Retail trade 44, Motor vehicle and parts dealers Automobile dealers New car dealers Used car dealers «_ Other motor vehicle dealers Motorcycle, boat, and other vehicle dealers Auto parts, accessories, and tire stores » - Automotive parts and accessories stores » Tire dealers Furniture and home furnishings stores Furniture stores » Home furnishings stores Floor covering stores _ Other home furnishings stores Electronics and appliance stores Appliance, TV, and other electronics stores » Household appliance stores Radio, TV, and other electronics stores » - Computer, software, camera, and photography supply stores 44312,

147 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Wholesale trade-continued Commercial equipment 4234 $22.88 $2:2.63 $23.11 $23.52 $ $ $ $ Office equipment Computer and software , , , , Medical equipment Miscellaneous professional and commercial equipment ,4,6, Metals and minerals Electric goods Electrical equipment and wiring Electric appliances and other electronic parts 42362, Hardware and plumbing Hardware Plumbing equipment HVAC and refrigeration equipment 42373, Machinery and supplies Construction equipment Farm and garden equipment Industrial machinery Industrial supplies! Service establishment equipment Miscellaneous durable goods , Recyclable materials Toy, hobby, and other durable goods 42392, Nondurable goods Paper and paper products Printing and writing paper and office supplies 42411, Industrial paper Druggists' goods Apparel and piece goods Grocery and related products General line grocery Fruits and vegetables , Farm product raw materials Grains and field beans Chemicals Other chemicals Petroleum Alcoholic beverages Beer and ale Misc. nondurable goods Farm supplies Paint, painting supplies, and other nondurable goods 42495, Electronic markets and agents and brokers Business to business electronic markets Wholesale trade agents and brokers Retail trade 44, $ $ Motor vehicle and parts dealers _ Automobile dealers New car dealers Used car dealers Other motor vehicle dealers , Motorcycle, boat, and other vehicle dealers , Auto parts, accessories, and tire stores Automotive parts and accessories stores Tire dealers Furniture and home furnishings stores Furniture stores Home furnishings stores Floor covering stores Other home furnishings stores Electronics and appliance stores Appliance, TV, and other electronics stores Household appliance stores Radio, TV, and other electronics stores Computer, software, camera, and photography supply stores 44312,

148 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Retail trade-continued Building material and garden supply stores Building material and supplies dealers Home centers Paint and wallpaper stores Hardware stores Other building material dealers Lawn and garden equipment and supplies stores Outdoor power equipment stores Nursery, garden, and farm supply stores Food and beverage stores Grocery stores Supermarkets and other grocery stores Convenience stores Specialty food stores Meat markets and fish and seafood markets 44521, Fruit and vegetable markets Other specialty food stores Beer, wine, and liquor stores Health and personal care stores Pharmacies and drug stores Optical goods stores Other health and personal care stores All other health and personal care stores Gasoline stations Gasoline stations with convenience stores Other gasoline stations » Clothing and clothing accessories stores Clothing stores Men's clothing stores Women's clothing stores Family clothing stores Clothing accessories stores Other clothing stores Shoe stores Jewelry, luggage, and leather goods stores Sporting goods, hobby, book, and music stores Sporting goods and musical instrument stores Sporting goods stores Hobby, toy, and game stores Sewing, needlework, and piece goods stores Book, periodical, and music stores Book stores and news dealers Prerecorded tape, CD, and record stores General merchandise stores Department stores Department stores, except discount Discount department stores Other general merchandise stores Warehouse clubs and supercenters All other general merchandise stores Miscellaneous store retailers Florists _ Office supplies, stationery, and gift stores Office supplies and stationery stores Gift, novelty, and souvenir stores Used merchandise stores Other miscellaneous store retailers Pet and pet supplies stores All other miscellaneous store retailers Nonstore retailers Electronic shopping and mail-order houses Mail-order houses Direct selling establishments Fuel dealers Heating oil dealers

149 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Retail trade-continued Building material and garden supply stores $12.80 $12.79 $12.97 $13.05 $ $ $ $ Building material and supplies dealers Home centers " _ Paint and wallpaper stores Hardware stores ' Other building material dealers Lawn and garden equipment and supplies stores ' Outdoor power equipment stores Nursery, garden, and farm supply stores Food and beveraqe stores Grocery stores '') Supermarkets and other grocery stores Convenience stores , Specialty food stores » Meat markets and fish and seafood markets 44521, Fruit and vegetable markets , Other specialty food stores «Beer, wine, and liquor stores , Health and personal care stores Pharmacies and drug stores Optical goods stores Other health and personal care stores All other health and personal care stores , Gasoline stations Gasoline stations with convenience stores , Other gasoline stations :) Clothing and clothing accessories stores Clothing stores Men's clothing stores Women's clothing stores Family clothing stores Clothing accessories stores Other clothing stores Shoe stores Jewelry, luggage, and leather goods stores Sporting goods, hobby, book, arid music stores Sporting goods and musical instrument stores ' Sporting goods stores '> Hobby, toy, and game stores ) Sewing, needlework, and piece goods stores Book, periodical, and music stores Book stores and news dealers , Prerecorded tape, CD, and record stores General merchandise stores , Department stores , » Department stores, except discount _ Discount department stores Other general merchandise stores Warehouse clubs and supercenters All other general merchandise stores Miscellaneous store retailers Florists , Office supplies, stationery, and gift stores Office supplies and stationery stores Gift, novelty, and souvenir stores Used merchandise stores Other miscellaneous store retailers Pet and pet supplies stores , All other miscellaneous store retailers Nonstore retailers Electronic shopping and mail-order houses Mail-order houses Direct selling establishments Fuel dealers Heating oil dealers

150 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Retail trade-continued Liquefied petroleum gas, bottled gas, and other fuel dealers , Transportation and warehousing 48, Truck transportation General freight trucking General freight trucking, local General freight trucking, long-distance General freight trucking, long-distance TL General freight trucking, long-distance LTL Specialized freight trucking Used household and office goods moving Other specialized trucking, local Other specialized trucking, long-distance Transit and ground passenger transportation Urban transit systems School and employee bus transportation Other ground passenger transportation Pipeline transportation Scenic and sightseeing transportation Support activities for transportation Support activities for air transportation Airport operations Support activities for water transportation Port and harbor operations Marine cargo handling Support activities for road transportation Freight transportation arrangement Support activities for other transportation, including rail 4882, Couriers and messengers Couriers Warehousing and storage General warehousing and storage Refrigerated warehousing and storage Miscellaneous warehousing and storage 49313, Utilities Power generation and supply Electric power generation Fossil fuel electric power generation Electric power transmission and distribution _ - Electric bulk power transmission and control Electric power distribution Natural gas distribution Water, sewage and other systems Information » - - Publishing industries, except Internet Newspaper, book, and directory publishers Newspaper publishers Periodical publishers Book publishers Software publishers Motion picture and sound recording industries Motion picture and video industries Motion picture and video production Motion picture and video exhibition Broadcasting, except Internet Radio and television broadcasting Radio broadcasting Television broadcasting Telecommunications Wired telecommunications carriers Wireless telecommunications carriers

151 industry 2002 NAICS code Avg. Average hourly earnings >004 Avg. Average weekly earnings Retail trade-continued Liquefied petroleum gas, bottled gas, and other fuel dealers ,9 $13.49 ' $13.89 $13.54 $ $ $ $ $ Transportation and warehousing 48, ! 1 o $ $ Truck transportation General freight trucking ' General freight trucking, local i General freight trucking, long-distance General freight trucking, long-distance TL General freight trucking, long-distance LTL Specialized freight trucking Used household and office goods moving s Other specialized trucking, local ! Other specialized trucking, long-distance Transit and ground passenger transportation Urban transit systems School and employee bus transportation Other ground passenger transportation Pipeline transportation , , , , Scenic and sightseeing transportation Support activities for transportation Support activities for air transportation Airport operations Support activities for water transportation ! Port and harbor operations , , , , Marine cargo handling I , , , Support activities for road transportation Freight transportation arrangement Support activities for other transportation, including rail 4882, Couriers and messengers I Couriers Warehousing and storage General warehousing and storage Refrigerated warehousing and storage Miscellaneous warehousing and storage , Utilities , , , , , Power generation and supply : , , , , Electric power generation , , , , Fossil fuel electric power generation i , , , , Electric power transmission and distribution ! , , , Electric bulk power transmission and control , , , , Electric power distribution , , Natural gas distribution , , , , , Water, sewage and other systems Information Publishing industries, except Internet Newspaper, book, and directory publishers ! Newspaper publishers Periodical publishers Book publishers Software publishers , , , , Motion picture and sound recording industries Motion picture and video industries Motion picture and video production , Motion picture and video exhibition Broadcasting, except Internet _ Radio and television broadcasting _ Radio broadcasting Television broadcasting Telecommunications i Wired telecommunications carriers i Wireless telecommunications carriers I

152 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Information-Continued Cellular and other wireless carriers Teiecommunications resellers Cable and other program distribution ISPs, search portals, and data processing ISPs and web search portals Data processing and related services Other information services Financial activities? Finance and insurance _ Credit intermediation and related activities Depository credit intermediation Commercial banking Savings institutions Credit unions and other depository credit intermediation 52213, Nondepository credit intermediation Credit card issuing Sales financing Other nondepository credit intermediation Consumer lending Real estate credit Miscellaneous nondepository credit intermediation ,4, Activities related to credit intermediation Mortgage and nonmortgage loan brokers Other credit intermediation activities «- Securities, commodity contracts, investments Securities brokerage Securities and commodity contracts brokerage and exchanges 5231, Other financial investment activities Portfolio management Investment advice Insurance carriers and related activities Insurance carriers Direct life and health insurance carriers Direct life insurance carriers Direct health and medical insurance carriers Direct insurers, except life and health Direct property and casualty insurers Direct title insurance and other direct insurance carriers , Reinsurance carriers Insurance agencies, brokerages, and related services Insurance agencies and brokerages Other insurance-related activities Claims adjusting Third-party administration of insurance funds » Funds, trusts, and other financial vehicles Other investment pools and funds » Real estate and rental and leasing Real estate Lessors of real estate Lessors of residential buildings Lessors of nonresidential buildings Lessors of other real estate property Offices of real estate agents and brokers Activities related to real estate Real estate property managers Residential property managers Nonresidential property managers Rental and leasing services

153 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Information-Continued Cellular and other wireless carriers $18.55 $18.92 $17.91 $18.13 $ $ $ $ Telecommunications resellers , Cable and other program distribution ie ISPs, search portals, and data processing ' ISPs and web search portals Data processing and related services Other information services Financial activities? $ $ Finance and insurance , Credit intermediation and related activities , Depository credit intermediation , Commercial banking Savings institutions Credit unions and other depository credit intermediation 52213, Nondepository credit intermediation Credit card issuing , Sales financing Other nondepository credit intermediation Consumer lending Real estate credit Miscellaneous nondepository credit 17, _ Mortgage and nonmortqage loan brokers Other credit intermediation activities intermediation.. Activities related to credit intermediation ,4, Securities, commodity contracts, Investments ^ , Securities brokerage ( fv , Securities and commodity contracts brokerage and exchanges 5231, :X , , Other financial investment activities :/.i Portfolio management ?e , Investment advice / Insurance carriers and related activities JO Insurance carriers Direct life and health insurance carriers Direct life insurance carriers ! Direct health and medical insurance carriers P Direct insurers, except life and health I v ; Direct property and casualty insurers ; Direct title insurance and other direct i insurance carriers , ; 'H Reinsurance carriers , Insurance agencies, brokerages, and related services i Si,02, Insurance agencies and brokerages , j; Other insurance-related activities i Claims adjusting Third-party administration of insurance funds Funds, trusts, and other financial vehicles Other investment pools and funds Real estate and rental and leasing Real estate Lessors of real estate « Lessors of residential buildings Lessors of nonresidential buildings Lessors of other real estate property , Offices of real estate agents and brokers Activities related to real estate , Real estate property managers Residential property managers i:;, Nonresidential property managers I Rental and leasing services "I

154 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Financial activities-continued Automotive equipment rental and leasing Passenger car rental and leasing Consumer goods rental Video tape and disc rental Miscellaneous consumer goods rental 53221,2, General rental centers Machinery and equipment rental and leasing Professional and business services _ Professional and technical services Legal services Offices of lawyers Other legal services Accounting and bookkeeping services Offices of certified public accountants Tax preparation services Payroll services Other accounting services Architectural and engineering services Architectural services Landscape architectural services Engineering and drafting services 54133, _... Building inspection, surveying, and mapping services 54135,6, _ Testing laboratories _... Specialized design services Interior design services Graphic design services Computer systems design and related services Custom computer programming services Computer systems design services Other computer-related services Management and technical consulting services Management consulting services Administrative management consulting services _ Human resource consulting services Marketing consulting services Process and logistics consulting services Other management consulting services Environmental consulting services Other technical consulting services Scientific research and development services Physical, engineering, and biological research Social science and humanities research Advertising and related services Advertising agencies Public relations agencies Direct mail advertising Advertising material distribution and other advertising services 54187, _ Other professional and technical services Marketing research and public opinion polling, Photographic services Veterinary services Miscellaneous professional and technical services 54193, Management of companies and enterprises Offices of bank holding companies and of other holding companies , Managing offices Administrative and waste services Administrative and support services Office administrative services Facilities support services Employment services Employment placement agencies _

155 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Financial activities-continued Automotive equipment rental and leasing 5321 $12.57 $13.19 $ $ $ $ $ Passenger car rental and leasing ? ) Consumer goods rental $ Video tape and disc rental Miscellaneous consumer goods rental 53221,2, ? > General rental centers ' Machinery and equipment rental and leasing Professional and business services $ $ Professional and technical services ?f > Legal services Offices of lawyers Other legal services >/ Accounting and bookkeeping services Offices of certified public accountants Tax preparation services Payroll services Other accounting services Architectural and engineering services Architectural services Landscape architectural services Engineering and draftinq services 54133, Building inspection, surveying, and mapping services 54135,6, Testing laboratories Specialized design services Interior design services Graphic design services Computer systems design and related services , , , , Custom computer programming services , , , , Computer systems design services , , , , Other computer-related services , , , , Management and technical consulting services , Management consulting services , Administrative management consulting services Human resource consulting services Marketing consulting services Process and logistics consulting services Other management consulting services Environmental consulting services Other technical consulting services Scientific research and development services , , , Physical, engineering, and biological research , , , Social science and humanities research Advertising and related services Advertising agencies , Public relations agencies , Direct mail advertising , Advertising material distribution and other advertising services 54187, , Other professional and technical services Marketing research and public opinion polling Photographic services Veterinary services Miscellaneous professional and technical services 54193, Management of companies and enterprises Offices of bank holding companies and of other holding companies , Managing offices Administrative and waste services Administrative and support services Office administrative services Facilities support services Employment services Employment placement agencies

156 industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Professional and business services-continued Temporary help services Professional employer organizations _ Business support services Telephone call centers Telephone answering services Telemarketing bureaus Business service centers Collection agencies Other business support services Travel arrangement and reservation services Travel agencies Other travel arrangement services Investigation and security services Security and armored car services Security guards and patrols and armored car services , Security systems services Services to buildings and dwellings Exterminating and pest control services Janitorial services Landscaping services Carpet and upholstery cleaning services Other services to buildings and dwellings Other support services Packaging and labeling services Convention and trade show organizers All other support services Waste management and remediation services Waste collection Waste treatment and disposal Nonhazardous waste treatment and disposal ,3, Remediation and other waste services Remediation services Education and health services Health care and social assistance _ Health care 621,2, Ambulatory health care services Offices of physicians _ Offices of physicians, except mental health Offices of mental health physicians Offices of dentists Offices of other health practitioners Offices of chiropractors » Offices of optometrists Offices of mental health practitioners Offices of specialty therapists _ Offices of all other health practitioners Outpatient care centers Outpatient mental health centers Outpatient care centers, except mental health,, Miscellaneous outpatient care centers , Medical and diagnostic laboratories Medical laboratories Home health care services Other ambulatory health care services Ambulance services All other ambulatory health care services Blood and organ banks Hospitals General medical and surgical hospitals Psychiatric and substance abuse hospitals Other hospitals Nursing and residential care facilities Nursing care facilities Residential mental health facilities

157 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings 2005 p Professional and business services-continued Temporary help services $12.07 $12.62 $11.91 $12.08 $ $ $ $ Professional employer organizations Business support services Telephone call centers Telephone answering services Telemarketing bureaus Business service centers Collection aqencies Other business support services Travel arrangement and reservation services Travel agencies Other travel arrangement services Investigation and security services Security and armored car services Security guards and patrols and armored car services , Security systems services Services to buildings and dwellings Exterminating and pest control services Janitorial services Landscaping services Carpet and upholstery cleaning services Other services to buildings and dwellings Other support services Packaging and labeling services Convention and trade show organizers » All other support services Waste management and remediation services Waste collection Waste treatment and disposal Nonhazardous waste treatment and disposal ,3, Remediation and other waste services Remediation services Education and health services 16.16! $ $ Health care and social assistance ! Health care 621,2, Ambulatory health care services ; Offices of physicians Offices of physicians, except mental health Offices of mental health physicians Offices of dentists Offices of other health practitioners Offices of chiropractors Offices of optometrists Offices of mental health practitioners Offices of specialty therapists Offices of all other health practitioners Outpatient care centers Outpatient mental health centers Outpatient care centers, except mental health Miscellaneous outpatient care centers , Medical and diagnostic laboratories Medical laboratories Home health care services Other ambulatory health care services Ambulance services All other ambulatory health care services Blood and organ banks Hospitals General medical and surgical hospitals Psychiatric and substance abuse hospitals Other hospitals Nursing and residential care facilities Nursing care facilities Residential mental health facilities

158 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Education and health services-continued Residential mental retardation facilities Residential mental and substance abuse care Community care facilities for the elderly Continuing care retirement communities Homes for the elderly Other residential care facilities Social assistance Individual and family services Child and youth services Services for the elderly and disabled Other individual and family services Emergency and other relief services Community food services Community housing, emergency, and relief services 62422, Vocational rehabilitation services Child day care services Leisure and hospitality Arts, entertainment, and recreation Performing arts and spectator sports Performing arts companies Musical groups and artists Theater, dance, and other performing arts companies 71111,2, Spectator sports Racetracks Arts and sports promoters and agents and managers for public figures 7113, _ - Independent artists, writers, and performers Museums, historical sites, zoos, and parks Museums Zoos, botanical gardens, nature parks, and similar institutions 71213, Amusements, gambling, and recreation Amusement parks and arcades Amusement and theme parks Gambling industries Casinos, except casino hotels Other gambling industries Other amusement and recreation industries Golf courses and country clubs Skiing facilities Marinas Fitness and recreational sports centers Bowling centers All other amusement and recreation industries Accommodations and food services? Accommodations Traveler accommodations and other longer-term accommodations Hotels and motels, except casino hotels Miscellaneous traveler accommodations RV parks and recreational camps RV parks and campgrounds Recreational and vacation camps Food services and drinking places Full-service restaurants Limited-service eating places Limited-service restaurants Cafeterias Snack and nonalcoholic beverage bars Special food services » Food service contractors _ Caterers and mobile food services 72232,

159 Industry 2002 NAICS code Avg. Average hourly earnings Avg. Average weekly earnings Education and health services-continued Residential mental retardation facilities $10.73 $10,54 $10.86 $10.93 _ $ $ $ $ Residential mental and substance abuse care , Community care facilities for the elderly i 10., Continuing care retirement communities Homes for the elderly Other residential care facilities , Social assistance , Individual and family services , Child and youth services , Services for the elderly and disabled , Other individual and family services Emergency and other relief services » Community food services Community housing, emergency, and relief services 62422, Vocational rehabilitation services Child day care services Leisure and hospitality $ $ Arts, entertainment, and recreation Performing arts and spectator sports Performing arts companies Musical groups and artists Theater, dance, and other performing arts companies ,2, Spectator sports :3, _ Racetracks ! Arts and sports promoters and agents and managers for public figures 7113, Independent artists, writers, and performers Museums, historical sites, zoos, and parks Museums Zoos, botanical gardens, nature parks, and similar institutions 71213, Amusements, gambling, and recreation Amusement parks and arcades Amusement and theme parks Gambling industries Casinos, except casino hotels Other gambling industries T Other amusement and recreation industries i Golf courses and country ciubs I Skiing facilities Marinas Fitness and recreational sports centers Bowling centers All other amusement and recreation industries Accommodations and food services? Accommodations Traveler accommodations and other longer-term accommodations Hotels and motels, except casino hotels Miscellaneous traveler accommodations RV parks and recreational camps RV parks and campgrounds Recreational and vacation camps Food services and drinking places Full-service restaurants Limited-service eating places ! Limited-service restaurants ! Cafeterias Snack and nonalcoholic beverage bars Special food services Food service contractors Caterers and mobile food services 72232,

160 Industry 2002 NAICS code Avg. Average weekly hours Avg. Average overtime hours Leisure and hospitality-continued Drinking places, alcoholic beverages Other services Repair and maintenance Automotive repair and maintenance Automotive mechanical and electrical repair General automotive repair Automotive exhaust system repair Other automotive mechanical and elec. repair Automotive body, interior, and glass repair Automotive body and interior repair Automotive glass replacement shops Other automotive repair and maintenance Car washes Auto oil change shops and all other auto repair and maintenance Electronic equipment repair and maintenance Computer and office machine repair Miscellaneous electronic equipment repair and maintenance ,3, Commercial machinery repair and maintenance., Household goods repair and maintenance Personal and laundry services Personal care services Hair, nail, and skin care services? Barber shops and beauty salons , Other personal care services Death care services Funeral homes and funeral services Cemeteries and crematories Dry-cleaning and laundry services Coin-operated laundries and dry cleaners Dry-cleaning and laundry services, except coin-operated Linen and uniform supply Linen supply Industrial launderers _ Other personal services Fhotofinishing Parkinq lots and garages Membership associations and organizations Grantmaking and giving services Grantmaking foundations Other grantmaking and giving services Social advocacy organizations «- - Human rights organizations Environment, conservation, and other social advocacy organizations , Civic and social organizations Professional and similar organizations «- - Business associations Professional organizations Labor unions and similar labor organizations Miscellaneous professional and similar organizations 81394, See footnotes at end of table.

161 Industry 2002 NAICS code Avg. i Average hourly earnings Avg. Average weekly earnings Leisure and hospitality-continued Drinking places, alcoholic beverages 7224 $7.77 % T 67 $7.87 $ $ $ $ $ Other services IT $ $ Repair and maintenance k Automotive repair and maintenance W Automotive mechanical and electrical repair General automotive repair Automotive exhaust system repair Other automotive mechanical and elec. repair Automotive body, interior, and glass repair Automotive body and interior repair ,'i _ Automotive glass replacement shops ! _ Other automotive repair and maintenance Car washes , Auto oil change shops and all other auto repair and maintenance , Electronic equipment repair and maintenance in Computer and office machine repair II » Miscellaneous electronic equipment repair and maintenance ,3, I Commercial machinery repair and maintenance It) Household goods repair and maintenance I'! Personal and laundry services I I Personal care services «Hair, nail, and skin care services? Barber shops and beauty salons , i Other personal care services IH Death care services Funeral homes and funeral services I Cemeteries and crematories Dry-cleaning and laundry services > Coin-operated laundries and dry cleaners , C! Dry-cleaning and laundry services, except coin-operated I Linen and uniform supply i Linen supply Industrial launderers _ Other personal services Photofinishing Parking lots and garages Membership associations and organizations i k6n Grantmaking and giving services > Grantmaking foundations Other grantmaking and giving services " Social advocacy organizations ^ Human rights organizations i i Environment, conservation, and other social advocacy organizations , Civic and social organizations Professional and similar organizations Business associations < Professional organizations Labor unions and similar labor organizations Miscellaneous professional and similar i organizations 81394,9 11.8/ 1>? Data relate to production workers in natural resources and mining and p = preliminary. manufacturing, construction workers in construction, and nonsupervisory NOTE: Data are currently projected from March benchmark levels, workers in the service-providing industries. When more recent benchmark data are introduced with the release of 2 Excludes nonoffice commissioned real estate sales agents. January 2006 estimates, all unadjusted data from April forward Wage and salary payments; tips excluded. are subject to revision. ~ Data not available.

162 Industry Avg p Manufacturing $15.29 $15.15 $15.54 $15.56 Durable goods Wood products Nonmetallic mineral products Primary metals Fabricated metal products Machinery Computer and electronic products Electrical equipment and appliances Transportation equipment Furniture and related products Miscellaneous manufacturing Nondurable goods Food manufacturing Beverages and tobacco products Textile mills Textile product mills Apparel Leather and allied products Paper and paper products Printing and related support activities Petroleum and coal products Chemicals Plastics and rubber products Derived by asssuming that overtime hours are paid at the rate of time and one-half. 2 Data not available. p = preliminary. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, all unadjusted data from April forward are subject to revision

163 Average hourly earnings Average weekly earnings Industry Avg., Avg p 2005 p 2005 p 2005 p Total private: Current dollars Constant (1982) dollars $ $ $ $ $15.93 ( 2 ) $ $ $ $ $ ( 2 ) Goods-producing: Current dollars Constant (1982) dollars i 9.08 J ( 2 ) ( 2 ) Natural resources and mining: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Construction: Current dollars Constant (1982) dollars :: ( 2 ) ( 2 ) Manufacturing: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Private service-providing: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Trade, transportation, and utilities: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Wholesale trade: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Retail trade: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Transportation and warehousing: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) utilities uurrent d illars constant (1982) dollars ( 2 ) 1, , , , , ( 2 ) Information: Current dollars Con tant (1982) dollars ( 2 ) ( 2 ) Financial activities: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Professional and bu _ mess services: ( u rent dollar Constant (1982) dollars ( 2 ) ( 2 ) Education and health services: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Leisure and hospitality: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) Other services: Current dollars Constant (1982) dollars ( 2 ) ( 2 ) 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 2 Data not available. p = preliminary. NOTE: The Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W) is used to deflate the earnings series. Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, ail unadjusted data from April forward are subject to revision.

164 State and area Average weekly hours Average hourly earnings Average weekly earnings Alabama $13.61 $14.99 $14.73 $ $ $ Birmingham-Hoover Mobile Alaska Arizona Phoenix-Mesa-Scottsdale Tucson Arkansas Fayetteville-Springdale-Rogers Fort Smith Little Rock-North Little Rock California Bakersfield Los Angeles-Long Beach-Santa Ana Modesto Oxnard-Thousand Oaks-Ventura Riverside-San Bernardino-Ontario Sacramento Arden-Arcade Roseville Salinas San Diego-Carlsbad-San Marcos San Francisco-Oakland-Fremont San Jose-Sunnyvale-Santa Clara Santa Barbara-Santa Maria-Goleta Santa Rosa-Petaluma Stockton Colorado Denver-Aurora Connecticut Bridgeport-Stamford-Norwalk Hartford-West Hartford-East Hartford New Haven Norwich-New London Waterbury Delaware Florida Georgia Atlanta-Sandy Springs-Marietta Hawaii Honolulu Idaho Illinois Chicago-Naperville-Joliet Davenport-Moline-Rock Island Peoria Rockford Indiana Elkhart-Goshen Evansville Fort Wayne Indianapolis Iowa Des Moines Kansas Wichita Kentucky Lexington-Fayette Louisville Louisiana Maine Portland-South Portland-Biddeford Maryland

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166 State and area Average weekly hours Average hourly earnings Average weekly earnings Pennsylvania $15.04 $15.24 $15.19 $ $ $ Allentown-Bethlehem-Easton Erie Harrisburg-Carlisle Lancaster Pittsburgh Reading Scranton Wilkes-Barre York-Hanover Rhode Island Providence-Fall River-Warwick South Carolina South Dakota Tennessee Chattanooga Knoxville Memphis Nashville-Davidson Murfreesboro Texas Dallas-Fort Worth-Arlington Houston-Baytown-Sugar Land San Antonio Utah Ogden-Clearfield Provo-Orem Salt Lake City Vermont Burlington-South Burlington Virginia Lynchburg Richmond Virginia Beach-Norfolk-Newport News Washington West Virginia Hunington-Ashland Wisconsin Milwaukee-Waukesha-West Allis Wyoming Puerto Rico Virgin Islands , , Area boundaries do not reflect official OMB definitions. P = preliminary. NOTE: Data have been revised to reflect benchmark levels. Data from 2001 forward are subject to revision. Area definitions are based on Office of Management and Budget Bulletin No , dated February 18,, and are available at and in the May issue of Employment and Earnings. Areas in the six New England states are Metropolitan New England City and Town Areas (NECTAs), while areas in other states are county-based. Some metropolitan areas lie in two or more states. They are listed under the state that appears first in their titles. Davenport-Moline-Rock Island, Iowa-Ill., and Weirton-Steubenville, W.Va-Ohio, are the exceptions in that they are listed under Illinois and Ohio, respectively, for operational reasons.

167 B-20. Average hours and earnings of production workers an manufacturing payrolls in selected states, metropolitan areas, and metropolitan divisions (Numbers in thousands) State, area, and division Average weekly hours Average hourly earnings Average weekly earnings 200'-- California , $15.25 $15.60 $15.59 $ $ $ Los Angeles-Long Beach-Santa Ana Los Angeles-Long Beach-Glendale Santa Ana-Anaheim-Irvine J;} San Francisco-Oakland-Fremont Oakland-Fremont-Hayward San Francisco-San Mateo-Redwood City , District of Columbia: Washington-Arlington-Alexandria Illinois Chicago-Naperville-Joliet Chicago-Naperville-Joliet ? Gary , , , Lake County-Kenosha County Massachusetts '!) Boston-Cambridge-Quincy ) Boston-Cambridge-Quincy Nashua! Michigan Detroit-Warren-Livonia , , , Detroit- Livon ia- Dearborn , , , Warren-Farmington Hills-Troy ! , , , Pennsylvania Philadelphia ; Wilmington Texas Dallas-Fort Worth-Arlington Dallas-Plano-lrving , Fort Worth-Arlington Part of the area is in one or more adjacent states. 2 All of the area is in one or more adjacent states. P = preliminary. NOTE: Data are counts of jobs by place of work. Data have been revised to reflect benchmark levels. Metropolitan area data have been revised back to 1990 to incorporate new area definitions. Area definitions are based on Office of Management and Budget Bulletin No , dated February 18,, and a f 5 available at and in the May issue of Employment and Earnings. Areas in the six New England states are Metropolitan New England City and Town Areas (NECTAs), while areas in other states are county-based. Some metropolitan areas lie in two or more states. They are listed under the state that appears first in their titles. Some divisions lie in more than one state, and some, like Camden, N.J., are totally outside the states under which their metropolitan areas are listed. This table introduces data for metropolitan divisions.

168 Obtain the latest NCS national data on occupational wages. National Compensation Survey: Occupational Wages in the United States, July 2002 BLS Bulletin 2561 This bulletin contains occupational hourly earnings and weekly hours for selected worker characteristics, establishment characteristics, and geographical areas. National Compensation Survey: Occupational Wages in the Nine Census Divisions, 2002 BLS Bulletin , New England BLS Bulletin , Middle Atlantic BLS Bulletin , East North Central BLS Bulletin , West North Central BLS Bulletin , South Atlantic BLS Bulletin , East South Central BLS Bulletin , West South Central BLS Bulletin , Mountain BLS Bulletin , Pacific Electronic files of these surveys are available on the Internet at: For more information on available National Compensation Surveys please contact: Bureau of Labor Statistics Division of Compensation Data Analysis and Planning 2 Massachusetts Avenue, NE, Room 4175 Washington, DC Telephone: (202) ocltinfo@bls.gov To purchase the latest BLS national wage data bulletins, write to: New Orders Superintendent of Documents P.O. Box Pittsburgh, PA Telephone: (412)

169 Census region and division 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P NORTHEAST Civilian labor force... Employed Unemployed Unemployment rate. 27, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , New England Civilian labor force Employed Unemployed Unemployment rate. 7, , , , , , , , , , , , , , , , , , , , , , , , Middle Atlantic Civilian labor force Employed Unemployed Unemployment rate. 19, ,722.3 ', , , , , , , , , ,857. 1, , , , , , , , , , , , , , , , , , , , , , SOUTH Civilian labor force Employed Unemployed Unemployment rate. 51, , , , , , , , , , , , ,688 ' 48,960. 2, , !), , , , , , , , , , , , , , , , , , , , , South Atlantic Civilian labor force Employed Unemployed Unemployment rate. 27, , , , , , , , , , ,252.' 25,927.;: 1, , , , , , , , , , , , , , , , , , , , , , , East South Central Civilian labor force Employed Unemployed Unemployment rate. 8, , , , , , , , , , :: 8, , , , , , , , , , , , , , West South Central Civilian labor force Employed Unemployed Unemployment rate. MIDWEST Civilian labor force Employed Unemployed Unemployment rate. 16, , , , , ! 16, , , , , , , , , , , , , , , " , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , East North Central Civilian labor force Employed Unemployed Unemployment rate. 23, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , West North Central Civilian labor force Employed Unemployed Unemployment rate. 10, , , , , , , , , , , , , , , , , , , , , , , ,

170 (Numbers in thousands) census region and division 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P WEST Civilian labor force 33, , , , , , , , , , , , ,844.6 Employed 31, , , , , , , , , , , , ,025.3 Unemployed 2, , , , , , , , , , , , ,819.2 Unemployment rate Mountain Civilian labor force 9, , , , , , , , , , , , ,154.0 Employed 9, , , , , , , , , , , , ,698.4 Unemployed Unemployment rate Pacific Civilian labor force 23, , , , , , , , , , , , ,690.5 Employed 21, , , , , , , , , , , , ,327.0 Unemployed 1, , , , , , , , , , , , ,363.6 Unemployment rate Census region estimates are derived by summing the Census division model-based estimates. P = preliminary. NOTE: Data refer to place of residence. The States (including the District of Columbia) that compose the various census divisions are: New England: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont; Middle Atlantic: New Jersey, New York, and Pennsylvania; South Atlantic: Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, and West Virginia; East South Central: Alabama, Kentucky, Mississippi, and Tennessee; West South Central: Arkansas, Louisiana, Oklahoma, and Texas; East North Central: Illinois, Indiana, Michigan, Ohio, and Wisconsin; West North Central: Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota; Mountain: Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and Wyoming; and Pacific: Alaska, California, Hawaii, Oregon, and Washington. Data have been revised to incorporate new estimation methods and updated Census-2000 population controls.

171 C-2. Labor force status by State, seasonally adjusted (Numbers in thousands) State 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Civilian labor force Employed Unemployed Unemployment rate. 2, , , , , , , , I 5 3 2, , , , , , , , , , , , , , Civilian labor force Employed Unemployed Unemployment rate Civilian labor force Employed Unemployed Unemployment rate. 2, , , , , , , , , , , , , , , , , , , , , , , , , , Arkansas Civilian labor force Employed Unemployed Unemployment rate. 1, , , , , , !) 5 ; 1, , , , , , , , , , , , , , , , , , California Civilian labor force Employed Unemployed Unemployment rate , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , Colorado Civilian labor force Employed Unemployed Unemployment rate. 2, , , , , , , , , , , , , , , , , , , , , , , , , , Connecticut Civilian labor force Employed Unemployed Unemployment rate. 1, , , , , , , , , , , , , , , , , , , , , , , , Delaware Civilian labor force Employed Unemployed Unemployment rate , District of Columbia Civilian labor force Employed Unemployed Unemployment rate Florida Civilian labor force Employed Unemployed Unemployment rate. 8, , , , , , , , , , , , , , , , , , j 8, , , , , , Georgia Civilian labor force Employed Unemployed Unemployment rate. 4, , , , , , , , , , , , , , , , , , , , , , , ,

172 (Numbers in thousands) State 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Hawaii Civilian labor force Employed Unemployed Unemployment rate Idaho Civilian labor force Employed Unemployed Unemployment rate Illinois Civilian labor force 6, , , , , , , , , , , , ,454.3 Employed 5, , , , , , , , , , , , ,093.8 Unemployed Unemployment rate Indiana Civilian labor force 3, , , , , , , , , , , , ,184.6 Employed 3, , , , , , , , , , , , ,011.4 Unemployed Unemployment rate Iowa Civilian labor force 1, , , , , , , , , , , , ,624.3 Employed 1, , , , , , , , , , , , ,541.8 Unemployed Unemployment rate Kansas Civilian labor force 1, , , , , , , , , , , , ,464.9 Employed 1, , , , , , , , , , , , ,388.2 Unemployed Unemployment rate Kentucky Civilian labor force 1, , , , , , , , , , , , ,972.4 Employed 1, , , , , , , , , , , , ,875.1 Unemployed Unemployment rate Louisiana Civilian labor force 2, , , , , , , , , , , , ,089.1 Employed 1, , , , , , , , , , , , ,972.2 Unemployed Unemployment rate Maine Civilian labor force Employed Unemployed Unemployment rate Maryland Civilian labor force 2, , , , , , , , , , , , ,893.4 Employed 2, , , , , , , , , , , , ,773.3 Unemployed Unemployment rate Massachusetts Civilian labor force 3, , , , , , , , , , , , ,371.8 Employed 3, , , , , , , , , , , , ,210.8 Unemployed Unemployment rate

173 (Numbers in thousands) State 2005 Mar. Apr. v ay June July Aug. Sept. Oct. NOV. P Michigan Civilian labor force 5, , , , , , , , , , , , ,089.2 Employed 4, , , , , , , , , , , , ,729.8 Unemployed Unemployment rate Minnesota Civilian labor force 2, , , , , , , , , , , , ,962.6 Employed 2, , , , , , , , , , , , ,833.6 Unemployed Unemployment rate Mississippi Civilian labor force 1, , , , , , , , , , , , ,345.1 Employed 1, , , , , , , , , , , , ,250.3 Unemployed Unemployment rate Missouri Civilian labor force 3, , , , , , , , , , , , ,025.2 Employed 2, , , , , , , , , , , , ,843.0 Unemployed Unemployment rate Montana Civilian labor force Employed Unemployed Unemployment rate Nebraska Civilian labor force Employed Unemployed Unemployment rate Nevada Civilian labor force 1, , , , , , , , , , , , ,194.3 Employed 1, , , ,120.3 I 1, , , , , , , , ,147.6 Unemployed ! Unemployment rate New Hampshire Civilian labor force Employed Unemployed Unemployment rate New Jersey Civilian labor force 4, , , , , , , , , , , , ,391.5 Employed 4, , , , , , , , , , , , ,218.4 Unemployed Unemployment rate New Mexico Civilian labor force Employed Unemployed Unemployment rate New York Civilian labor force 9, , , , , , , , , , , , ,353.8 Employed 8, , , , , , , , , , , , ,886.3 Unemployed Unemployment rate

174 (Numbers in thousands) State 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P North Carolina Civilian labor force Employed Unemployed Unemployment rate. 4, , , , , , , , , , , , , , , , , , , , , , North Dakota Civilian labor force Employed Unemployed Unemployment rate Ohio Civilian labor force Employed Unemployed Unemployment rate. 5, , , , , , , , , , , , , , , , , , , , , , , , Oklahoma Civilian labor force Employed Unemployed Unemployment rate. 1, , , , , , , , , , , , , , , , , , , , , , , , Oregon Civilian labor force Employed Unemployed Unemployment rate. 1, , , , , , , , , , , , , , , , , , , , , , , , , , Pennsylvania Civilian labor force Employed Unemployed Unemployment rate. 6, , , , , , , , , , , , , , , , , , , , , , , , , , Rhode Island Civilian labor force. Employed. Unemployed Unemployment rate South Carolina Civilian labor force Employed Unemployed Unemployment rate South Dakota 2, , , , , , , , , , , , , , , , , , , , , , , , , , Civilian labor force Employed Unemployed Unemployment rate Tennessee Civilian labor force Employed Unemployed Unemployment rate 2, , , , , , , , , , , , , , , , , , , , Texas Civilian labor force Employed Unemployed Unemployment rate , , , , , , , , , , , , , , , , , , , , , , , ,

175 (Numbers in thousands) State 2005 Mar. Apr. May June July Aug. Sept. Oct. Nov. P Utah Civilian labor force Employed Unemployed Unemployment rate 1, , , , , , ,199. 1, , , , , , , , , , , , , , , , , , Vermont Civilian labor force Employed Unemployed Unemployment rate Virginia Civilian labor force Employed Unemployed Unemployment rate 3, , , , , , , , , , , , , , , , , , , , , , , , , , Washington Civilian labor force Employed Unemployed Unemployment rate 3, , , , , , ,228.3! 3, C 6.2 3, , , , , , , , , , , , , , , , , , West Virginia Civilian labor force Employed Unemployed Unemployment rate T' Wisconsin Civilian labor force Employed Unemployed Unemployment rate 3, , , , , , , , , , , , , , , , , , , , , , , , , , Wyoming Civilian labor force Employed Unemployed Unemployment rate Puerto Rico Civilian labor force Employed Unemployed Unemployment rate 1, , , , , , , , S , , , , , , , , , , , , , , , P = preliminary. NOTE: Data refer to place of residence. Data for Puerto Rico are derived from a monthly household survey similar to the Current Population Survey. Estimates for the latest month are revised the following month, and at least 3 years of estimates are subject to revision at the end of the year, to incorporate updated inputs and reestimation. Data have been revised to incorporate new estimation methods and updated Census-2000 population controls.

176 C-3. Labor force status by State and metropolitan area (Numbers in thousands) State and area Civilian labor force 2005P Number Unemployed 2005P Percent of labor force 2005P Alabama 2, , , Anniston-Oxford Auburn-Opelika Birmingham-Hoover Decatur Dothan Florence-Muscle Shoals Gadsden Huntsville Mobile Montgomery Tuscaloosa Alaska Anchorage Fairbanks :6 7.6 Arizona 2, , , Flagstaff Phoenix-Mesa-Scottsdale 1, , , Prescott Tucson Yuma Arkansas 1, , , Fayetteville-Springdale-Rogers Fort Smith Hot Springs Jonesboro Little Rock-North Little Rock Pine Bluff California 17, , , , , Bakersfield Chico El Centra Fresno Hanford-Corcoran Los Angeles-Long Beach-Santa Ana 6, , , Madera Merced Modesto Napa Oxnard-Thousand Oaks-Ventura Redding Riverside-San Bernardino-Ontario 1, , , Sacramento-Arden-Arcade-Rosevi lie , , Salinas San Diego-Carlsbad-San Marcos 1, , , San Francisco-Oakland-Fremont 2, , , San Jose-Sunnyvale-Santa Clara San Luis Obispo-Paso Robles Santa Barbara-Santa Maria-Goleta Santa Cruz-Watsonville Santa Rosa-Petaluma Stockton Vallejo-Fairfield Visalia-Porterville Yuba City Colorado 2, , , Boulder Colorado Springs Denver-Aurora 1, , , Fort Collins-Loveland Grand Junction Greeley Pueblo Connecticut 1, , , Bridgeport-Stamford-Norwalk Danbury Hartford-West Hartford-East Hartford New Haven Norwich-New London Waterbury

177 (Numbers in thousands) State and area Civilian labor force Dec: 2005P Number Unemployed 2005P Percent of labor force 2005P Delaware Dover District of Columbia Washington-Arlington-Alexandria 2, , , Florida., 8, , , Cape Coral-Fort Myers Deltona-Daytona Beach-Ormond Beach Fort Walton Beach-Crestview-Destin Gainesville Jacksonville Lakeland Miami-Fort Lauderdale-Miami Beach 2, , , Naples-Marco Island Ocala Orlando Palm Bay-Melbourne-Titusville , Panama City-Lynn Haven ' Pensacola-Ferry Pass-Bient Port St. Lucie-Fort Pierce Punta Gorda Sarasota-Bradenton-Venice Tallahassee Tampa-St. Petersburg-Clearwater 1, , , Vero Beach Georgia 4, , , Albany Athens-Clarke County Atlanta-Sandy Springs-Marietta 2, , , Augusta-Richmond County Brunswick , Columbus Dalton Gainesville Hinesville-Fort Stewart Macon Rome Savannah Valdosta Warner Robins Hawaii Honolulu Idaho Boise City-Nampa Coeur d'alene Idaho Falls , Lewiston Pocatello Illinois.. 6, , , Bloomington-Normal Champaign-Urbana Chicago-Naperville-Joliet i 4, , , Danville f Davenport-Moline-Rock Island t Decatur Kankakee-Bradley Peoria Rockford Springfield Indiana. 3, , , Anderson Bloomington , Columbus Elkhart-Goshen Evansville Fort Wayne Indianapolis Kokomo Lafayette , Michigan City-La Porte ,

178 C-3. Labor force status by State and metropolitan area Continued (Numbers in thousands) State and area Civilian labor force 2005P Number Unemployed 2005P Percent of labor force 2005P Indiana Continued Muncie South Bend-Mishawaka Terre Haute Iowa 1, , , Ames Cedar Rapids Des Moines Dubuque Iowa City Sioux City Waterloo-Cedar Falls Kansas 1, , , Lawrence Topeka Wichita Kentucky 1, , , Bowling Green Elizabethtown Lexington-Fayette Louisville Owensboro Louisiana 2, , , Alexandria Baton Rouge Houma-Bayou Cane-Thibodaux Lafayette Lake Charles Monroe New Orleans-Metairie-Kenner Shreveport-Bossier City Maine Bangor Lewiston-Auburn Portland-South Portland-Biddeford Maryland 2, , , Baltimore-Towson 1, , , Cumberland Hagerstown-Martinsburg Salisbury Massachusetts 3, , , Barnstable Town Boston-Cambridge-Quincy 2, , , Leominster-Fitchburg-Gardner New Bedford Pittsfield Springfield Worcester Michigan 5, , , Ann Arbor Battle Creek Bay City Detroit-Warren-Livonia 2, , , Flint Grand Rapids-Wyoming Holland-Grand Haven Jackson Kalamazoo-Portage Lansing-East Lansing Monroe Muskegon-Norton Shores Niles-Benton Harbor Saginaw-Saginaw Township North Minnesota 2, , , Duluth Minneapolis-St. Paul-Bloomington 1, , , Rochester

179 (Numbers in thousands) State and area Civilian labor force 2005P Number Unemployed 2005P Percent of labor force 2005P Minnesota Continued St- Cloud Mississippi 1, , , Gulfport-Biloxi Hattiesburg Jackson Pascagoula Missouri 3, , , Columbia Jefferson City Joplin Kansas City 1, , , St. Joseph St. Louis 1 1, , , Springfield Montana : Billings Great Falls Missoula Nebraska Lincoln Omaha-Council Bluffs Nevada 1, , , Carson City Las Vegas-Paradise : Reno-Sparks : New Hampshire Manchester Portsmouth : Rochester-Dover New Jersey 4, , , Atlantic City Ocean City Trenton-Ewing Vineland-Millville-Bridgeton New Mexico Albuquerque Farmington Las Cruces Santa Fe New York 9, , , Albany-Schenectady-Troy : Binghamton Buffalo-Niagara Falls Elmira Glens Falls Ithaca Kingston New York-Northern New Jersey-Long Island 9, , , Poughkeepsie-Newburgh-Middletown Rochester Syracuse Utica-Rome North Carolina 4, , , Asheville Burlington Charlotte-Gastonia-Concord Durham Fayetteville Goldsboro Greensboro-High Point Greenville Hickory-Lenoir-Morganton Jacksonville Raleigh-Cary Rocky Mount

180 C-3. Labor force status by State and metropolitan area Continued (Numbers in thousands) State and area Civilian labor force 2005P Number Unemployed 2005P Percent of labor force 2005P North Carolina Continued Wilmington Winston-Salem North Dakota Bismarck Fargo Grand Forks Ohio 5, , , Akron Canton-Massillon Cincinnati-Middletown 1, , , Cleveland-Elyria-Mentor 1, , , Columbus Dayton Mansfield Sandusky Springfield Toledo Weirton-Steubenville Youngstown-Warren-Boardman Oklahoma 1, , , Lawton Oklahoma City Tulsa Oregon 1, , , Bend Corvallis Eugene-Springfield Medford Portland-Vancouver-Beaverton 1, , , Salem Pennsylvania 6, , , Allentown-Bethlehem-Easton Altoona Erie Harrisburg-Carlisle Johnstown Lancaster Lebanon Philadelphia-Camden-Wilmington 2, , , Pittsburgh 1, , , Reading Scranton-Wilkes-Barre State College Williamsport York-Hanover Rhode Island Providence-Fall River-Warwick South Carolina 2, , , Anderson Charleston-North Charleston Columbia Florence Greenville Myrtle Beach-Conway-North Myrtle Beach Spartanburg Sumter South Dakota Rapid City Sioux Falls Tennessee 2, , , Chattanooga Clarksville Cleveland Jackson Johnson City

181 (Numbers in thousands) State and area Civilian labc h roe 2005P Number Unemployed 2005P Percent of labor force 2005P Tennessee Continued Kingsport-Bristol-Bristol i Knoxville Memphis Morristown Nashville-Davidson-Murfreesboro , ,128 I 11, Abilene Amarillo Austin-Round Rock Beaumont-Port Arthur Brownsville-Harhngen College Station-Bryan Corpus Christi ' Dallas-Fort Worth-Arlington 2, , , El Paso Houston-Baytown-Sugar Land 2, ,651 2, Killeen-Temple-Fort Hood Laredo Longview Lubbock McAllen-Edinburg-Pharr Midland Odessa » San Angelo ! San Antonio ) Sherman-Denison ,:) Texarkana Tyler Victoria > Waco ,lj Wichita Falls Utah 1, , , Logan ) Ogden-Clearfield Provo-Orem St. George > Salt Lake City , Vermont Burlington-South Burlington I Virginia 3, ,816 3, Blacksburg-Christiansburg-Radford } Charlottesville Danville : Harrisonburg ^ Lynchburg Richmond Roanoke s Virginia Beach-Norfolk-Newport News 'J Winchester ) Washington 3, ,276.> 3, Bellingham ) Bremerton-Silverdale Kennewick-Richland-Pasco Longview ) Mount Vernon-Anacortes Olympia ) Seattle-Tacoma-Bellevue 1, ,731.; 1, Spokane Wenatchee Yakima West Virginia Charleston ? Huntington-Ashland * Morgantown Parkersburg-Marietta Wheeling Wisconsin 3, , , Appleton (

182 C-3. Labor force status by State and metropolitan area Continued (Numbers in thousands) State and area Civilian labor force 2005P Number Unemployed 2005P Percent of labor force 2005P Wisconsin Continued Eau Claire Fond du Lac Green Bay Janesville LaCrosse Madison Milwaukee-Waukesha-West Allis Oshkosh-Neenah Racine Sheboygan Wausau Wyoming Casper Cheyenne Puerto Rico 1, , , Aguadilla-lsabela-San Sebastian Fajardo Guayama Mayaguez ' Ponce San German-Cabo Rojo San Juan-Caguas-Guaynabo Yauco Area boundaries do not reflect official OMB definitions. P = preliminary. NOTE: Data refer to place of residence. Data for Puerto Rico are derived from a monthly household survey similiar to the Current Population Survey. Area definitions are based on Office of Management and Budget Bulletin No , dated February 18,, and are available at and in the May issue of Employment and Earnings. Areas in the six New England states are Metropolitan New England City and Town Areas (NECTAs), while areas in other states are county-based. Some metropolitan areas lie in two or more states. They are listed under the state that appears first in their titles. Davenport-Moline-Rock Island, Iowa-Ill., and Weirton-Steubenville, W.Va-Ohio, are the exceptions in that they are listed under Illinois and Ohio, respectively, for operational reasons. Estimates for the latest month are revised the following month, and at least 3 years of estimates are subject to revision at the end of the year, to incorporate updated inputs and reestimation. Data have been revised to incorporate new estimation methods and updated Census-2000 population controls.

183 C-4. Civilian labor force and unemployment by state, selected meti -p c iitan area, and metropolitan division 1 (Numbers in thousands) State, area, and division Civilian labor force De< P Number Unemployed 2005P Percent of labor force 2005P California 17, , , , , Los Angeles-Long Beach-Santa Ana 6, ,46 i.7 6, Los Angeles-Long Beach-Glendale 4, ,85 ).1 4, Santa Ana-Anaheim-Irvine 1, ,6C 1.6, 1, San Francisco-Oakland-Fremont 2, , , Oakland-Fremont-Hayward 1, , , San Francisco-San Mateo-Redwood City District of Columbia C Washington-Arlington-Alexandria 2 2, , , Bethesda-Frederick-Gaithersburg Washington-Arlington-Alexandria 2 2, ,2C j.2 2, Florida 8, , , Miami-Fort Lauderdale-Miami Beach 2, , , Fort Lauderdale-Pompano Beach-Deerfield Beach Miami-Miami Beach-Kendall 1, , , West Palm Beach-Boca Raton-Boynton Beach Illinois 6, , , Chicago-Naperville-Joliet 2 4, , , Chicago-Naperville-Joliet 3, , , Gary Lake County-Kenosha County Massachusetts 3, ,37X8 3, Boston-Cambridge-Quincy 2 2, , , Boston-Cambridge-Quincy 1, , , Brockton-Bridgewater-Easton Framingham Haverhill-North Andover-Amesburv Lawrence-Methuen-Salem Lowell-Billerica-Chelmsford Lynn-Peabody-Salem Nashua Taunton-Norton-Raynham Michigan 5, , , Detroit-Warren-Livonia 2, , , Detroit-Livonia-Dearbom Warren-Farmington Hills-Troy 1, , , New York 9, ,3< :.1 9, New York-Northern New Jersey-Long Island 2 9, ,2C i.2 9, Edison 3 1, ,U >.C 1, Nassau-Suffolk 1, ,4 r.1 1, New York-Wayne-White Plains 2 5, , , Newark-Union 3 1, , , Pennsylvania 6, ,3c 12 6, Philadelphia-Camden-Wilmington 2 2, ,9' 5.7 2, Camden i.s Philadelphia 1, , , Wilmington ' Texas 10, , , Dallas-Fort Worth-Arlington 2, , , Dallas-Plano-lrving 1, , , Fort Worth-Arlington Washington 3, , , Seattle-Tacoma-Bellevue 1, , , Seattle-Bellevue-Everett 1, , , Tacoma These 11 areas contain all oi the 34 metropolitan divisions. 2 Part of the area (or division) is in one or more adjacent states. 3 All of the division is in one or more adjacent states. P = preliminary. NOTE: Data refer to place of residence. Area definitions are based on Office of Management and Budget Bulletin No , dated February 18,, and are available at and in the May issue of Employment and Earnings. Areas in the six New England states are Metropolitan New England City and Town Areas (NECTAs), while areas in other states are county-based. Some metropolitan areas lie in two or more states. They are listed under the state that corresponds to the first city in their title. Metropolitan divisions are listed under their metropolitan areas. Some divisions lie in more than one state, and some, like Camden, N.J., are totally outside the states under which their metropolitan areas are listed. Estimates for the latest month are revised the following month, and at least 3 years of estimates are subject to revision at the end of the year, to incorporate updated inputs and reestimation. Two sets of metropolitan areas and divisions have similar or identical titles. For Washington-Arlington-Alexandria, D.C.-Va.-Md.-W.Va., the titles are identical. For the Chicago-Naperville-Joliet, lll.-lnd.-/wis. metropolitan area, the division title includes only Illinois. Data have been revised to incorporate new estimation methods and updated Census-2000 population controls.

184 ILabor Statistics vft U.S. Department of Labor Bureau of Labor Statistics Free from BLS, to keep you informed The Bureau's series of issues papers provides you with succinct, up-to-the-minute background data in a readily digestible form. They're convenient, current, easy to read, and available free from BLS. To be added to the Issues in Labor Statistics mailing list (No. J336), write to: Bureau of Labor Statistics, Office of Publications and Special Studies, Room 2850, 2 Massachusetts Ave., NE., Washington, DC , or fax the coupon below to (202) Issues in Labor Statistics also are available in PDF format on the BLS Web site: Here are some recent Issues Twenty-first century moonlighters Declining teen labor force participation Consumer Spending Patterns Differ by Region Housing expenditures Certification Can Count: The Case of Aircraft Mechanics 2001 New and emerging occupations Who was affected as the economy started to slow? Characteristics and spending patterns of consumer units in the lowest 10 percent of the expenditure distribution 2000 Unemployed Job Leavers: A Meaningful Gauge of Confidence in the Job Market? Spending Patterns By Age When one job is not enough A comparison of the characteristics and spending patterns of Food Stamp recipients and nonrecipients Labor Supply in a Tight Labor Market Are Managers and Professionals Really Working More? 1999 Occupational Stress Expenditures on Public Transportation Consumer Spending on Traveling for Pleasure What the Nation Spends on Health Care: A Regional Comparison What Women Earned in 1998 Computer Ownership Up Sharply in the 1990s The Southeast is Maintaining Its Share of Textile Plant Employment Auto Dealers are Fewer, Bigger, and Employ More Workers 1998 Labor-Market Outcomes for City Dwellers and Suburbanites Spending Patterns of High-income Households New Occupations Emerging Across Industry Lines Yes, please add my name to mailing list J336, Issues in Labor Statistics. Name Organization Street City State _ Zip

185 Establishment Data Annual Averages

186

187 Industry Total nonfarm. 131,82(3 130, , ,480 Total private. 110, , , ,862 Good produciny 23,873 22,557 21,816 21,884 Natural re ource nd mining. Logging Mining Oil and gas extraction Mining, except oil and gas Goal mining Support activities for mining. 3C ( > i'3.!5 5 >2!> 11!3 f i 4. \ 1 >0 I Construction Construction of buildings Residential building Nonresidential building Heavy and civil engineering construction Specialty trade contractors Residential specialty trade contractors Nonresidential specialty trade contractors ( > 1,5't [ 8 17 '5 9 >3,0 4, ,8 8 I 2,4 i5 8 6, , , , , , ,964 1, , , Manufacturing I 15,259 14,510 14,329 Durable goods Wood products Nonmetallic mineral products Primary metals Fabricated metal products Machinery Computer and electronic products 1 Computer and peripheral equipment Communications equipment Semiconductors and electronic components. Electronic instruments Electrical equipment and appliances Transportation equipment 1. Motor vehicles and parts 2 Furniture and related products Miscellaneous manufacturing , ' :> 5, 'O.J 1,6 '6 4 1,3 >8 3 1, '5. I 5 «8.9 1, , A , , , , , , , , , , , Nondurable goods Food manufacturing Beverages and tobacco products Textile mills Textile product mills Apparel Leather and allied products Paper and paper products Printing and related support activities. Petroleum and coal products Chemicals Plastics and rubber products 6 107,5!«1.2 2( ', i!6.5 > J8.4 1;:1.1 9?: >9.0 8U7.4 5, , ,406 1, See footnotes at end of table.

188 Industry Service-providing 107, , , ,596 Private service-providing... 86,834 86,271 86,599 87,978 Trade, transportation, and utilities. 25,983 25,497 25,287 25,510 Wholesale trade Durable goods Nondurable goods Electronic markets and agents and brokers , , , , , , Retail trade Motor vehicle and parts dealers 1 Automobile dealers Furniture and home furnishings stores Electronics and appliance stores Building material and garden supply stores Food and beverage stores Health and personal care stores Gasoline stations Clothing and clothing accessories stores Sporting goods, hobby, book, and music stores. General merchandise stores 1 Department stores Miscellaneous store retailers Nonstore retailers 15, , , , , , , , , , , , , , , , Transportation and warehousing Air transportation Rail transportation Water transportation Truck transportation Transit and ground passenger transportation. Pipeline transportation Scenic and sightseeing transportation Support activities for transportation Couriers and messengers Warehousing and storage , , , , , , Utilities Information Publishing industries, except Internet Motion picture and sound recording industries. Broadcasting, except Internet internet publishing and broadcasting Telecommunications ISPs, search portals, and data processing Other information services 3, , , , Financial activities Finance and insurance Monetary authorities - central bank Credit intermediation and related activities 1 Depository credit intermediation 1 Commercial banking Securities, commodity contracts, investments. Insurance carriers and related activities Funds, trusts, and other financial vehicles Real estate and rental and leasing Real estate Rental and leasing services Lessors of nonfinancial intangible assets 7, , , , ,847 5, , , ,977 5, , , , , , , , ,

189 Industry Professional and business sen/ices 16,476 15,976 15,987 16,414 Professional and technical services 1.. 6, , , ,762.0 Legal services 1, , , ,161.8 Accounting and bookkeeping services Architectural and engineering services 1, , , ,260.8 Computer systems design and related services 1, , , ,147.4 Management and technical consulting services Management of companies and enterprises , , ,718.0 Administrative and waste services 7 u 9 7, , ,934.0 Administrative and support services , , ,608.7 Employment services , , ,470.3 Temporary help services : , , ,393.2 Business support services 7i' Services to buildings and dwellings 6i i6 2 1, , ,694.2 Waste management and remediation services Education and health services ,199 16,588 16,954 Educational services :, , , ,766.4 Health care and social assistance 1: , , ,187.3 Health care E 1 11, , ,054.8 Ambulatory health care services 1 < 4' 1 5 4, , ,946.4 Offices of physicians , , ,053.9 Outpatient care centers 3' S Home health care services 6) Hospitals <,0 I' 9 4, , ,293.6 Nursing and residential care facilities 1 2,6i 8 2, , ,814.8 Nursing care facilities ', , , ,575.3 '»9'S 9 2, , ,132.5 Child day care services Leisure and hospitality 2 )J6 11,986 12,173 12,479 Arts, entertainment, and recreation,8 1, , ,833.0 Performing arts and spectator sports 3i! Museums, historical sites, zoos, and parks 1, Amusements, gambling, and recreation 1, , , ,351.1 Accommodations and food services 10, , , ,646.0 i, , , ,795.9 Food services and drinking places 8, , , ,850.1 Other services.... 5,258 5,372 5,401 5,431 Repair and maintenance ', , , ,227.6 Personal and laundry services ', , , ,274.1 Membership associations and organizations 2, , , ,929.1 i!1,118 21,513 21,583 21,618 2,764 2,766 2,761 2,728 Federal except U S Postal Service ', , , ,943.4 U.S. Postal Service State government 4,905 5,029 5,002 4,985 State government education 2, , , ,249.2 State government excluding education 2, , , ,736.2 Local government 13,449 13,718 13,820 13,905 Local government education 7, , , ,762.5 Local government, excluding education 5, , , , Includes other industries, not shown separately. 2 Includes motor vehicles, motor vehicle bodies and motor vehicle parts. 3 includes ambulatory health care service hospitals, and nursing and care facilities. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, data from April forward are subject to revision.

190 (In thousands) Industry Total private 89,983 88,393 87,658 88,976 Goods-producing 17,466 16,400 15,732 15,823 Natural resources and mining Construction 5,332 5,196 5,123 5,300 Manufacturing 11,677 10,768 10,190 10,083 Durable goods Wood products Nonmetallic mineral products Primary metals Fabricated metal products Machinery Computer and electronic products Electrical equipment and appliances., Transportation equipment Motor vehicles and parts?. Furniture and related products Miscellaneous manufacturing 7, , , , , , , , , , , , Nondurable goods Food manufacturing Beverages and tobacco products Textile mills Textile product mills Apparel Leather and allied products Paper and paper products Printing and related support activities- Petroleum and coal products Chemicals Plastics and rubber products Private service-providing 4,514 1, ,517 4,239 1, ,993 4,038 1, ,926 3,945 1, ,152 Trade, transportation, and utilities 21,709 21,337 21,078 21,298 Wholesale trade , , Retail trade 12, , , ,766,4 Transportation and warehousing , , Utilities Information 2,530 2,398 2,347 2,389 Financial activities 5,810 5,872 5,967 6,001 Professional and business services.. 13,588 13,049 12,910 13,306 Education and health services 13,846 14,311 14,532 14,771 Leisure and hospitality 10,662 10,576 10,666 10,945 Other services 4,373 4,449 4,426 4,442 1 Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 2 Includes motor vehicles, motor vehicle bodies and motor vehicle parts. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, data from April forward are subject to revision.

191 Industry Average weekly hours Average hourly earnings Average weekly earnings Total private $14.53 $14.95 $15.35 $15.67 $ $ $ $ Goods-producing : Natural resources and mining Construction Manufacturing Overtime hours ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Durable goods Overtime hours ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) Wood products Nonmetallic mineral products Primary metals Fabricated metal products Machinery Computer and electronic products Electrical equipment and appliances ( Transportation equipment Motor vehicles and parts? Furniture and related products Miscellaneous manufacturing B Nondurable goods :\9.a Overtime hours ( 2 ) ( 2 ) ( 2 ) ( 2 ) : (2) ( 2 ) ( 2 ) ( 2 ) Food manufacturing Beverages and tobacco products Textile mills Textile product mills Apparel Leather and allied products Paper and paper products " Printing and related support activities ;? Petroleum and coal products < 4.: : Chemicals Plastics and rubber products Private service-providing , Trade, transportation, and utilities Wholesale trade :,! Retail trade Transportation and warehousing Utilities < Information Financial activities Professional and business services Education and health services Leisure and hospitality Other services Data relate to production workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory workers in the service-providing industries. 2 Data not available. 3 Includes motor vehicles, motor vehicle bodies and motor vehicle parts. NOTE: Data are currently projected from March benchmark levels. When more recent benchmark data are introduced with the release of January 2006 estimates, data from April forward are subject to revision.

192 Explanatory Notes and Estimates of Error Introduction The statistics in this periodical are compiled from two major sources: (1) household interviews, and (2) reports from employers. Data based on household interviews are obtained from the Current Population Survey (CPS), a sample survey of the population 16 years of age and over. The survey is conducted each month by the U.S. Census Bureau for the Bureau of Labor Statistics and provides comprehensive data on the labor force, the employed, and the unemployed, classified by such characteristics as age, sex, race, family relationship, marital status, occupation, and industry attachment. The survey also provides data on the characteristics and past work experience of those not in the labor force. The information is collected by trained interviewers from a sample of about 60,000 households (beginning with July 2001 data) located in 754 sample areas. These areas are chosen to represent all counties and independent cities in the United States, with coverage in 50 States and the District of Columbia. The data collected are based on the activity or status reported for the calendar week including the 12th of the month. Data based on establishment records are compiled each month through the use of touchtone data entry, computerassisted telephone interviewing, and electronic data interchange, or by mail or fax, or on magnetic tape or computer diskette. The Current Employment Statistics (CES) survey is designed to provide industry information on nonfarm wage and salary employment, average weekly hours, average hourly earnings, and average weekly earnings for the Naition, States, and metropolitan areas. The employment, hours, and earnings series are based on payroll reports from a sample that includes about 160,000 businesses and government agencies covering approximately 400,000 individual worksites. The sample is drawn from a sampling frame of over 8 million unemployment insurance tax accounts. The active CES sample includes approximately one-third of all nonfarm payroll workers. The data relate to all workers, full or part time, who receive pay during the payroll period that includes the 12th of the month. RELATIONSHIP BETWEENTHE HOUSEHOLD AND ESTABLISHMENT SERIES The household and establishment data complement one another, each providing significant types of information that the other cannot suitably supply. Population characteristics, for example, are obtained only from the household survey, whereas detailed industrial classifications are much more reliably derived from establishment reports. Data from these two sources differ from each other because of variations in definitions and coverage, source of information, methods of collection, and estimating procedures. Sampling variability and response errors are additional reasons for discrepancies. The major factors that have a differential effect on the levels and trends of the two data series are as follows. Employment Coverage. The household survey definition of employment comprises wage and salary workers (including domestics and other private household workers), self-employed persons, and unpaid workers who worked 15 hours or more during the reference week in family-operated enterprises. Employment in both agricultural and nonagricultural industries is included. The payroll survey covers only wage and salary employees on the payrolls of nonfarm establishments. Multiple jobholding. The household survey provides information on the work status of the population without duplication, because each person is classified as employed, unemployed, or not in the labor force. Employed persons holding more than one job are counted only once. In the figures based on establishment reports, persons who worked in more than one establishment during the reporting period are counted each time their names appear on payrolls. Unpaid absences from jobs. The household survey includes among the employed all civilians who had jobs but were not at work during the reference week that is, were not working but had jobs from which they were temporarily absent because of illness, vacation, bad weather, childcare problems, or labor-management disputes, or because they were taking time off for various other reasons, even if they were not paid by their employers for the time off. In the figures based on payroll reports, persons on leave paid for by the company are included, but those on leave without pay for the entire payroll period are not. Hours of work The household survey measures hours worked for all workers, whereas the payroll survey measures hours for

193 private production or nonsupervisory workers paid for by employers. In the household survey, all persons with a job but not at work are excluded from the hours distributions and the computations of average hours at work. In the payroll survey, production or nonsupervisory employees on paid vacation, paid holiday, or paid sick leave are included and assigned the number of hours for which they were pai I during the reporting period. Earnings The household survey measures the earnings of wage and salary workers in all. occupations and industries in both the private and public sectors. Data refer to the usual earnings received from the worker's sole or primary job. Data froi i the establishment survey generally refer to average earnings of production and related workers in natural resources and mining and manufacturing; construction workers in construction; and nonsupervisory employees in private service-providing industries. For a comprehensive discussion of the various earnings series available from the household and establishment surveys, see BLS Measures of Compensation, Bulletin 2239 (Bureau of Labor Statistics, 1986). COMPARABILITY OF HOUSEHOLD DATA WITH OTHER SERIES Unemployment insurance data. The unemployed total from the household survey includes all persons who did not have a job during the reference week, were currently available for a job, and were looking for work or were waiting to be called back to a job from which they had been laid oft, whether or not they were eligible for unemployment insurance. Figures on unemployment insurance claims, prepared by the Employment and Training Administration of the U.S. Department of Labor, exclude, in addition to otherwise ineligible persons who do not file claims for benefits, persons who have exhausted their benefit rights, new workers who have not earned rights to unemployment insurance, and persons losing jobs not covered by unemployment insurance systems (some workers in agriculture, domestic services, and religious organizations, and self-employed and unpaid family workers). In addition, the qualifications for drawing unemployment compensation differ from the definition of unemployment used in the household survey. For example, persons with a job but not at work and persons working only a few hours during the week are sometimes eligible for unemployment compensation but are classified as employed, rather than unemployed, in the household survey. Agricultural employment estimates of the U.S. Department of Agriculture. The principal differences in coverage are the inclusion of persons under 16 in the National Agricultural Statistics Service series and the treatment of dual jobholders, who are counted more than once if they work on more than one farm during the reporting period. There also are wide differences in sampling techniques and data collecting and estimating methods, which cannot be readily measured in terms of their impact on differences in the levels and trends of the two series. COMPARABILITY OF PAYROLL EMPLOYMENT DATA WITH OTHER SERIES Statistics on manufacturers and business, U.S. Census Bureau. BLS establishment statistics on employment differ from employment counts derived by the U.S. Census Bureau from its censuses or sample surveys of manufacturing and business establishments. The major reasons for noncomparability are different treatment of business units considered parts of an establishment, such as central administrative offices and auxiliary units; the industrial classification of establishments; and different reporting patterns by multiunit companies. There also are differences in the scope of the industries covered for example, the Census of Business excludes professional services, public utilities, and financial establishments, whereas these are included in the BLS statistics. County Business Patterns, U.S. Census Bureau. Data in County Business Patterns (CBP) differ from BLS establishment statistics in the treatment of central administrative offices and auxiliary units. Differences also may arise because of industrial classification and reporting practices. In addition, CBP excludes interstate railroads and most of government, and coverage is incomplete for some of the nonprofit agencies. Employment covered by State unemployment insurance programs. Most nonfarm wage and salary workers are covered by the unemployment insurance programs. However, some employees, such as those working in parochial schools and churches, are not covered by unemployment insurance, whereas they are included in the BLS establishment statistics.

194 Household Data ("A" tables, monthly; "D" tables, quarterly) COLLECTION AND COVERAGE Statistics on the employment status of the population and related data are compiled by BLS using data from the Current Population Survey (CPS). This monthly survey of households is conducted for BLS by the U.S. Census Bureau through a scientifically selected sample designed to represent the civilian noninstitutional population. Respondents are interviewed to obtain information about the employment status of each member of the household 16 years of age and older. The inquiry relates to activity or status during the calendar week, Sunday through Saturday, that includes the 12th day of the month. This is known as the "reference week." Actual field interviewing is conducted in the following week, referred to as the "survey week." Each month, about 60,000 occupied units are eligible for interview. Some 4,500 of these households are contacted but interviews are not obtained because the occupants are not at home after repeated calls or are unavailable for other reasons. This represents a noninterview rate for the survey that ranges between 7 and 8 percent. In addition to the 60,000 occupied units, there are about 12,000 sample units in an average month that are visited but found to be vacant or otherwise not eligible for enumeration. Part of the sample is changed each month. The rotation plan, as will be explained later, provides for three-fourths of the sample to be common from one month to the next, and one-half to be common with the same month a year earlier. CONCEPTS AND DEFINITIONS The concepts and definitions underlying labor force data have been modified, but not substantially altered, since the inception of the survey in 1940; those in use as of January 1994 are as follows: Civilian noninstitutional population. Included are persons 16 years of age and older residing in the 50 States and the District of Columbia who are not inmates of institutions (for example, penal and mental facilities, homes for the aged), and who are not on active duty in the Armed Forces. Employed persons. All persons who, during the reference week, (a) did any work at all (at least 1 hour) as paid employees, worked in their own business, profession, or on their own farm, or worked 15 hours or more as unpaid workers in an enterprise operated by a member of the family, and (b) all those who were not working but who had jobs or businesses from which they were temporarily absent because of vacation, illness, bad weather, childcare problems, maternity or paternity leave, labor-management dispute, job training, or other family or personal reasons, whether or not they were paid for the time off or were seeking other jobs. Each employed person is counted only once, even if he or she holds more than one job. For purposes of occupation and industry classification, multiple jobholders are counted in the job at which they worked the greatest number of hours during the reference week. Included in the total are employed citizens of foreign countries who are temporarily in the United States but not living on the premises of an embassy. Excluded are persons whose only activity consisted of work around their own house (painting, repairing, or own home housework) or volunteer work for religious, charitable, and other organizations. Unemployed persons. All persons who had no employment during the reference week, were available for work, except for temporary illness, and had made specific efforts to find employment sometime during the 4-week period ending with the reference week. Persons who were waiting to be recalled to a job from which they had been laid off need not have been looking for work to be classified as unemployed. Duration of unemployment This represents the length of time (through the current reference week) that persons classified as unemployed had been looking for work. For persons on layoff, duration of unemployment represents the number of full weeks they had been on layoff. Mean duration is the arithmetic average computed from single weeks of unemployment; median duration is the midpoint of a distribution of weeks of unemployment. Reason for unemployment Unemployment also is categorized according to the status of individuals at the time they began to look for work. The reasons for unemployment are divided into five major groups: (1) Job losers, comprising (a) persons on temporary layoff \ who have been given a date to return to work or who expect to return within 6 months (persons on layoff need not be looking for work to qualify as unemployed), and (b) permanent job losers, whose employment ended involuntarily and who began looking for work; (2) Job leavers, persons who quit or otherwise terminated their employment voluntarily and immediately began looking for work; (3) Persons who completed temporary jobs, who began looking for work after the jobs ended; (4) Reentrants, persons who previously worked but who were out: of the labor force prior to beginning their job search; and (5) New entrants, persons who had never worked. Each of these five categories of the unemployed can be expressed as a proportion of the entire civilian labor force; the sum of the four rates thus equals the unemployment rate for all civilian workers. (For statistical presentation purposes, "job losers" and "persons who completed temporary jobs" are combined into a single category until seasonal adjustments can be developed for the separate categories.)

195 Jobseekers= All unemployed persons who made specific: efforts to find a job sometime during the 4-week period pre ceding the survey week are classified as jobseekers. Job seekers do not include persons classified as on temporary layoff, who, although often looking for work, are not required to do so to be classified as unemployed. Jobseekers are grouped by the methods used to seek work. Only active: methods which have the potential to result in a job offer without further action on the part of the jobseeker qualify as job search. Examples include going to an employe; directly or to a public or private employment agency, seek ing assistance from triends or relatives, placing or answering ads, or using some other active method. Examples of the "other" category include being on a union or professional register, obtaining assistance from a community organization, or waiting at a designated labor pickup point, Passive methods, which do not qualify as job search, include: reading (as opposed 1u answering or placing) "help wanted' ads and taking a job training course. Labor force. This group comprises all persons classified as employed or unemployed in accordance with the criteria described above. Unemployment rate. The unemployment rate represents the number unemployed as a percent of the labor force. Participation rate. This represents the proportion of the popu lation that is in the labor force. Employment-population ratio. This represents the propor tion of the population that is employed. Not m the labor force. Included, in this group are all persons m the civilian noninstitutional population who are neither employed nor unemployed. Information is collected on their desire tor and availability to take a job at the time of the CPS interview, job search activity in the prior year, and reason for not looking in the 4-week period prior to the survey week. This group includes discouraged workers, defined as persons not in the labor force who want and are available for a job and who have looked for work sometime in the past 12: months (or since the end of their last job if they held one within the past 12 months), but who are not currently look ing because they believe there are no jobs available or there are none for which they would qualify. Persons classified as not in the labor force who are in the sample for either their fourth or eighth month are asked additional questions relating to job history and workseeking intentions. These latter data are available on a quarterly basis. Occupation, industry, and class of worker. This information for the employed applies to the job held in the reference week. Persons with two or more jobs are classified in the job at which they worked the greatest number of hours. The unemployed are classified according to their last job. Beginning in 2003, the occupational and industrial classification of CPS data is based on the 2002 Census Bureau occupational and industrial classification systems which are derived from the 2000 Standard Occupational Classification (SOC) and the 2002 North American Industry Classification System (NAICS). (See the following section on historical comparability for a discussion of previous classification systems used in the CPS.) The class-of-worker breakdown assigns workers to the following categories: Private and government wage and salary workers, self-employed workers, and unpaid family workers. Wage and salary workers receive wages, salary, commissions, tips, or pay in kind from a private employer or from a government unit. Self-employed persons are those who work for profit or fees in their own business, profession, trade, or farm. Only the unincorporated self-employed are included in the self-employed category in the classof-worker typology. Self-employed persons who respond that their businesses are incorporated are included among wage and salary workers because, technically, they are paid employees of a corporation. Unpaid family workers are persons working without pay for 15 hours a week or more on a farm or in a business operated by a member of the household to whom they are related by birth or marriage. Multiple jobholders. These are employed persons who, during the reference week, either had two or more jobs as a wage and salary worker, were self-employed and also held a wage and salary job, or worked as an unpaid family worker and also held a wage and salary job. Excluded are self-employed persons with multiple businesses and persons with multiple jobs as unpaid family workers. Hours of work. These statistics relate to the actual number of hours worked during the reference week. For example, persons who normally work 40 hours a week but were off on the Columbus Day holiday would be reported as working 32 hours, even though they were paid for the holiday. For persons working in more than one job, the published figures relate to the number of hours worked in all jobs during the week; all the hours are credited to the major job. Unpublished data are available for the hours worked in each job and for usual hours. At work part time for economic reasons. Sometimes referred to as involuntary part time, this category refers to individuals who gave an economic reason for working 1 to 34 hours during the reference week. Economic reasons include slack work or unfavorable business conditions, inability to find full-time work, and seasonal declines in demand. Those who usually work part time must also indicate that they want and are available for full-time work to be classified as on part time for economic reasons. At work part time for noneconomic reasons. This group includes those persons who usually work part time and were at work 1 to 34 hours during the reference week for a noneconomic reason. Noneconomic reasons include, for example: Illness or other medical limitations, childcare problems or other family or personal obligations, school or training, retirement or Social Security limits on earnings, and being in a

196 job where full-time work is less than 35 hours. The group also includes those who gave an economic reason for usually working 1 to 34 hours but said they do not want to work full time or are unavailable for such work. Usual full- or part-time status. Data on persons "at work" exclude persons who were temporarily absent from a job and therefore classified in the zero-hours-worked category, "with a job but not at work." These are persons who were absent from their jobs for the entire week for such reasons as bad weather, vacation, illness, or involvement in a labor dispute. In order to differentiate a person's normal schedule from his or her activity during the reference week, persons also are classified according to their usual full- or part-time status. In this context, full-time workers are those who usually worked 35 hours or more (at all jobs combined). This group will include some individuals who worked less than 35 hours in the reference week for either economic or noneconomic reasons and those who are temporarily absent from work. Similarly, part-time workers are those who usually work less than 35 hours per week (at all jobs), regardless of the number of hours worked in the reference week. This may include some individuals who actually worked more than 34 hours in the reference week, as well as those who are temporarily absent from work. The full-time labor force includes all employed persons who usually work full time and unemployed persons who are either looking for full-time work or are on layoff from full-time jobs. The part-time labor force consists of employed persons who usually work part time and unemployed persons who are seeking or are on layoff from parttime jobs. Unemployment rates for full- and part-time workers are calculated using the concepts of the full- and parttime labor force. White, black or African American, and Asian. These are terms used to describe the race of persons. Persons in these categories are those who selected that race group only. Persons in the remaining race categories American Indian or Alaska Native, Native Hawaiian or Other Pacific Islanders, and persons who selected more than one race category are included in the estimates of total employment and unemployment but are not shown separately because the number of survey respondents is too small to develop estimates of sufficient quality for monthly publication. In the enumeration process, race is determined by the household respondent. (See the following section on historical comparability for a discussion of changes beginning in 2003 that affected how people are classified by race.) Hispanic or Latino ethnicity. This refers to persons who identified themselves in the enumeration process as being Spanish, Hispanic, or Latino. Persons whose ethnicity is identified as Hispanic or Latino may be of any race. (See the following section on historical comparability for a discussion of changes beginning in 2003 that affected how people are classified by Hispanic or Latino ethnicity.) Usual weekly earnings. Data represent earnings before taxes and other deductions, and include any overtime pay, commissions, or tips usually received (at the main job, in the case of multiple jobholders). Earnings reported on a basis other than weekly (for example, annual, monthly, hourly) are converted to weekly. The term "usual" is as perceived by the respondent. If the respondent asks for a definition of usual, interviewers are instructed to define the term as more than half the weeks worked during the past 4 or 5 months. Data refer to wage and salary workers (excluding all self-employed persons regardless of whether their businesses were incorporated) who usually work full time on their sole or primary job. Median earnings. These figures indicate the value that divides the earnings distribution into two equal parts, one part having values above the median and the other having values below the median. The medians shown in this publication are calculated by linear interpolation of the $50 centered interval within which each median falls. Data expressed in constant dollars are deflated by the Consumer Price Index for All Urban Consumers (CPI-U). Never married; married, spouse present; and other marital status. These are the terms used to define the marital status of individuals at the time of interview. Married, spouse present, applies to husband and wife if both were living in the same household, even though one may be temporarily absent on business, on vacation, on a visit, in a hospital, etc. Other marital status applies to persons who are married, spouse absent; widowed; or divorced. Married, spouse absent relates to persons who are separated due to marital problems, as well as to husbands and wives who are living apart because one or the other was employed elsewhere or was on duty with the Armed Forces, or for any other reasons. Household. A household consists of all persons related family members and all unrelated persons who occupy a housing unit and have no other usual address. A house, an apartment, a group of rooms, or a single room is regarded as a housing unit when occupied or intended for occupancy as separate living quarters. A householder is the person (or one of the persons) in whose name the housing unit is owned or rented. The term is never applied to either husbands or wives in married-couple families but relates only to persons in families maintained by either men or women without a spouse. Family. A family is defined as a group of two or more persons residing together who are related by birth, marriage, or adoption; all such persons are considered as members of one family. Families are classified either as married-couple families or as families maintained by women or men without spouses. A family maintained by a woman or a man is one in which the householder is either single, widowed, divorced, or married, spouse absent. HISTORICAL COMPARABILITY Changes in concepts and methods While current survey concepts and methods are very similar

197 to those introduced at the inception of the survey in 1940, a number of changes have been made over the years to improve the accuracy and usefulness of the data. Some of the most important changes include: In 1945, the questionnaire was radically changed with the introduction of four basic employment questions. Prior to that time, the survey did not contain specific question wording, but, rather, relied on a complicated scheme of activity prioritization. In 1953, the current rotation system was adopted, whereby households are interviewed for 4 consecutive months, leave the sample for 8 months, and then return to the sample for the same 4 months of the following year. Befo e this system was introduced, households were interviewed for 6 consecutive months and then replaced. The new system provided some year-to-year overlap in the sample, thereby improving measurement over time. In 1955, the survey reference week was changed to the calendar week including the 12th day of the month, for great;* consistency with the reference period used for other labor-rolated statistics. Previously, the calendar week containing the 8th day of the month, had been used as the reference week. In 1957, the employment definition was modified slightly as a result of a comprehensive interagency review of labor force concepts and methods. Two relatively small groups of persons classified as employed, under "with a job but not at work," were assigned to different classifications. Persons on layoff with definite instructions to return to work within 30 days of the layoff date, and persons volunteering that they were waiting to start a new wage and salary job within 30 days of interview, were, for the most part, reassigned to the unemployed classification. Title only exception was the small subgroup m school during the reference week but waiting to start new jobs, which was transferred to not m the labor force. In 1967, more substantive changes were made as a result of the recommendations oi the Presidents Committee to Appraise Employment and Unemployment Statistics (the Gordon Committee). The principal improvements were as follows: a) A 4-week job search period and specific questions on jobseeking activity were introduced. Previously, the questionnaire was ambiguous as to the period for jobseeking, and there were no specific questions concerning job search methods. b) An availability test was introduced whereby a person must be currently available for work in order to be classified as unemployed. Previously, there was no such requirement. This revision to me concept mainly affected students, who, for example, may begin to look for summer jobs in the sprin g although they will not be available until June or July. Such persons, until 1967, had been classified as unemployed bi t since have been assigned to the "not in the labor force" category. c) Persons "with a job but not at work" because of strikes, bad weather, etc., who volunteered that they were looking for work were shifted from unemployed status to employed. d) The lower age limit for official statistics on employment, unemployment, and other labor force concepts was raised from 14 to 16 years. Historical data for most major series have been revised to provide consistent information based on the new minimum age limit. e) New questions were added to obtain additional information on persons not in the labor force, including those referred to as "discouraged workers," defined as persons who indicate that they want a job but are not currently looking because they believe there are no jobs available or none for which they would qualify. f) New "probing" questions were added to the questionnaire in order to increase the reliability of information on hours of work, duration of unemployment, and self-employment. In 1994, major changes to the Current Population Survey (CPS) were introduced, which included a complete redesign of the questionnaire and the use of computer- as si sted interviewing for the entire survey. In addition, there were revisions to some of the labor force concepts and definitions, including the implementation of some changes recommended in 1979 by the National Commission on Employment and Unemployment Statistics (NCEUS, also known as the Levitan Commission). Some of the major changes to the survey were: a) The introduction of a redesigned and automated questionnaire. The CPS questionnaire was totally redesigned in order to obtain more accurate, comprehensive, and relevant information, and to take advantage of state-of-the-art computer interviewing techniques. b) The addition of two, more objective, criteria to the definition of discouraged workers. Prior to 1994, to be classified as a discouraged worker, a person must have wanted a job and been reported as not currently looking because of a belief that no jobs were available or that there were none for which he or she would qualify. Beginning in 1994, persons classified as discouraged must also have looked for a job within the past year (or since their last job, if they worked during the year), and must have been available for work during the reference week (a direct question on availability was added in 1994; prior to 1994, availability had been inferred from responses to other questions). These changes were made because the NCEUS and others felt that the previous definition of discouraged workers was too subjective, relying mainly on an individual's stated desire for a job and not on prior testing of the labor market. c) Similarly, the identification of persons employed part time for economic reasons (working less than 35 hours in the reference week because of poor business conditions or because of an inability to find full-time work) was tightened

198 by adding two new criteria for persons who usually work part time: They must want and be available for full-time work. Previously, such information was inferred. (Persons who usually work full time but worked part time for an economic reason during the reference week are assumed to meet these criteria.) d) Specific questions were added about the expectation of recall for persons who indicate that they are on layoff. To be classified as "on temporary layoff," persons must expect to be recalled to their jobs. Previously, the questionnaire did not include explicit questions about the expectation of recall. e) Persons volunteering that they were waiting to start a new job within 30 days must have looked for work in the 4 weeks prior to the survey in order to be classified as unemployed. Previously, such persons did not have to meet the job search requirement in order to be included among the unemployed. For additional information on changes in CPS concepts and methods, see "The Current Population Survey: Design and Methodology," Technical Paper 63RV (Washington, U.S. Census Bureau and Bureau of Labor Statistics, March 2002), available on the Internet at tp63.htm; "Overhauling the Current Population Survey Why is it Necessary to Change?," "Redesigning the Questionnaire," and "Evaluating Changes in the Estimates," Monthly Labor Review, September 1993; and "Revisions in the Current Population Survey Effective January 1994," in the February 1994 issue of this publication. Noncomparability of labor force levels In addition to the refinements in concepts, definitions, and methods made over the years, other changes also have affected the comparability of the labor force data. Beginning in 1953, as a result of introducing data from the 1950 census into the estimating procedures, population levels were raised by about 600,000; labor force, total employment, and agricultural employment were increased by about 350,000, primarily affecting the figures for totals and for men; other categories were relatively unaffected. Beginning in 1960, the inclusion of Alaska and Hawaii resulted in increases of about 500,000 in the population and about 300,000 in the labor force. Four-fifths of the labor force increase was in nonagricultural employment; other labor force categories were not appreciably affected. Beginning in 1962, the introduction of data from the 1960 census reduced the population by about 50,000 and labor force and employment by about 200,000; unemployment totals were virtually unchanged. Beginning in 1972, information from the 1970 census was introduced into the estimation procedures, increasing the population by about 800,000; labor force and employment totals were raised by a little more than 300,000; unemployment levels and rates were essentially unchanged. In March 1973, a subsequent population adjustment based on the 1970 census was introduced. This adjustment, which affected the white and black-and-other groups but had little effect on totals, resulted in the reduction of nearly 300,000 in the white population and an increase of the same magnitude in the black-and-other population. Civilian labor force and total employment figures were affected to a lesser degree; the white labor force was reduced by 150,000, and the blackand-other labor force rose by about 210,000. Unemployment levels and rates were not significantly affected. Beginning in January 1974, the method used to prepare independent estimates of the civilian noninstitutional population was modified to an "inflation-deflation" approach. This change in the derivation of the estimates had its greatest impact on estimates of 20- to 24-year-old men particularly those in the black-and-other population but had little effect on estimates of the total population 16 years and over. Additional information on the adjustment procedure appears in "CPS Population Controls Derived from Inflation-Deflation Method of Estimation," in the February 1974 issue of this publication. Effective in July 1975, as a result of the large inflow of Vietnamese refugees to the United States, the total and blackand-other independent population controls for persons 16 years and over were adjusted upward by 76,000 30,000 men and 46,000 women. The addition of the refugees increased the black-and-other population by less than 1 percent in any age-sex group, with all of the changes being confined to the "other" component of the population. Beginning in January 1978, the introduction of an expansion in the sample and revisions in the estimation procedures resulted in an increase of about 250,000 in the civilian labor force and employment totals; unemployment levels and rates were essentially unchanged. An explanation of the procedural changes and an indication of the differences appear in "Revisions in the Current Population Survey in January 1978" in the February 1978 issue of this publication. Beginning in October 1978, the race of the individual was determined by the household respondent for the incoming rotation group households, rather than by the interviewer as before. The purpose of this change was to provide more accurate estimates of characteristics by race. Thus, in October 1978, one-eighth of the sample households had race determined by the household respondent and seveneighths of the sample households had race determined by interviewer observation. It was not until January 1980 that the entire sample had race determined by the household respondent. The new procedure had no significant effect on the estimates. Beginning in January 1979, the first-stage ratio adjustment method was changed in the CPS estimation procedure. Differences between the old and new procedures existed only for metropolitan and nonmetropolitan area estimates, not for the total United States. The reasoning behind the change

199 and an indication of the differences appear in "Revisions in the Current Population Survey in January 1979" in the Feb - ruary 1979 issue of this publication. Beginning in January 1982, the second-stage ratio ad - justment method was changed. The rationale for the change and an indication of its effect on national estimates of labor force characteristics appear in "Revisions in the Current Popu - lation Survey Beginning in January 1982" in the February 1982 issue of this publication. In addition, current popula tion estimates used in the second-stage estimation proce dure were derived from information obtained from the 1980 census, rather than the 1970 census. This change caused substantial increases in the total population and in the esti - mates of persons in all labor force categories. Rates for labor force characteristics, however, remained virtually unchanged. Some 30,000 labor force series were adjusted back to 1970 to avoid major breaks in series. The adjustment procedure used also is described in the February 1982 article cited above. The revisions did not, however, smooth out the breaks in series occurring between 1972 and 1979 (described above), and data users should consider them when comparing estimates from different periods. Beginning in January 1983, the first-stage ratio adjust ment method was updated to incorporate data from the 1980 census. The rationale for the change and an indication of it effect on national estimates for labor force characteristic appear in "Revisions in the Current Population Survey Beginning in January 1983" in the February 1983 issue of this publication. There were only slight differences betweer the old and new procedures in estimates of levels for the various labor force characteristics and virtually no differ ences in estimates of participation rates. Beginning in January 1985, most of the steps of the CPS estimation procedure the noninterview adjustment the first- and second-stage ratio adjustments, and the com posite estimator were revised. These procedures are described in the Estimating Methods section. A description of the changes and an indication of their effect on national estimates of labor force characteristics appear in "Change: in the Estimation Procedure in the Current Population Survey Beginning m January 1^85" in the February 1985 issue of this publication. Overall, the revisions had only a slight effect on most estimates. The greatest impact was on estimates ot persons ol Hispanic origin. Major estimates were revised back to January Beginning in January 1986, the population controls used in the second-stage ratio adjustment method were revised to reflect an explicit estimate of the number of undocumented immigrants (largely Hispanic) since 1980 and an improved estimate of the number of emigrants among legal foreign-bom residents for the same period. As a result, the total civilian population and labor force estimates were raised by nearly 400,000; civilian employment was increased by about 350,000. The Hispanic-origin population and labor force estimates were raised by about 425,000 and 305,000, respectively. and Hispanic employment was increased by 270,000. Overall and subgroup unemployment levels and rates were not significantly affected. Because of the magnitude of the adjustments for Hispanics, data were revised back to January 1980 to the extent possible. An explanation of the changes and an indication of their effect on estimates of labor force characteristics appear in "Changes in the Estimation Procedure in the Current Population Survey Beginning in January 1986" in the February 1986 issue of this publication. Beginning in August 1989, the second-stage ratio estimation procedures were changed slightly to decrease the chance of very small cells occurring and to be more consistent with published age, sex, race cells. This change had virtually no effect on national estimates. Beginning in January 1994, 1990 census-based population controls, adjusted for the estimated undercount, were introduced into the second-stage estimation procedure. This change resulted in substantial increases in total population and in all major labor force categories. Effective February 1996, these controls were introduced into the estimates for Under the new population controls, the civilian noninstitutional population for 1990 increased by about 1.1 million, employment by about 880,000, and unemployment by approximately 175,000. The overall unemployment rate rose by about 0.1 percentage point. For further information, see "Revisions in the Current Population Survey Effective January 1994," and "Revisions in Household Survey Data Effective February 1996" in the February 1994 and March 1996 issues, respectively, of this publication. Additionally, for the period January through May 1994, the composite estimation procedure was suspended for technical and logistical reasons. Beginning in January 1997, the population controls used in the second-stage ratio adjustment method were revised to reflect updated information on the demographic characteristics of immigrants to, and emigrants from, the United States. As a result, the civilian noninstitutional population 16 years and over was raised by about 470,000. The labor force and employment levels were increased by about 320,000 and 290,000, respectively. The Hispanic-origin population and labor force estimates were raised by about 450,000 and 250,000, respectively, and Hispanic employment was increased by 325,000. Overall and subgroup unemployment rates and other percentages of labor market participation were not affected. An explanation of the changes and an indication of their effect on national labor force estimates appear in "Revisions in the Current Population Survey Effective January 1997" in the February 1997 issue of this publication. Beginning in January 1998, new composite estimation procedures and minor revisions in the population controls were introduced into the household survey. The new composite estimation procedures simplify processing of the monthly labor force data at BLS, allow users of the survey

200 microdata to more easily replicate the official estimates released by BLS, and increase the reliability of the employment and labor force estimates. The new procedures also produce somewhat lower estimates of the civilian labor force and employment and slightly higher estimates of unemployment. For example, based on 1997 annual average data, the differences resulting from the use of old and new composite weights were as follows: Civilian labor force (-229,000), total employed (-256,000), and total unemployed (+27,000). Unemployment rates were not significantly affected. Also beginning in January 1998, the population controls used! in the survey were revised to reflect new estimates of legal immigration to the United States and a change in the method for projecting the emigration of foreign-born legal residents. As a result, the Hispanic-origin population was raised by about 57,000; however, the total civilian noninstitutional population 16 years and over was essentially unchanged. More detailed information on these changes and their effect on the estimates of labor force change and composition appear in "Revisions in the Current Population Survey Effective January 1998," in the February 1998 issue of this publication. Beginning in January 1999, the population controls used in the survey were revised to reflect newly updated information on immigration. As a result, the civilian noninstitutional population 16 years and over was raised by about 310,000. The impact of the changes varied for different demographic groups. The civilian noninstitutional population for men 16 years and over was lowered by about 185,000, while that for women was increased by about 490,000. The Hispanicorigin population was lowered by about 165,000 while that of persons of non-hispanic origin was raised by about 470,000. Overall labor force and employment levels were increased by about 60,000 each, while the Hispanic labor force and employment estimates were reduced by about 225,000 and 215,000, respectively. The changes had only a small impact on overall and subgroup unemployment rates and other percentages of labor market participation. An explanation of the changes and an indication of their effect on national labor force estimates appear in "Revisions in the Current Population Survey Effective January 1999" in the February 1999 issue of this publication. Beginning in January 2003, several major changes were introduced into the CPS. These changes included: a) Population controls that reflected the results of Census 2000 were introduced into the monthly CPS estimation process. These new population controls substantially increased the size of the civilian noninstitutional population and the civilian labor force. Data from January 2000 through December 2002 were revised to reflect the higher population estimates from Census 2000 and the higher rates of population growth since the census. At the start of the revision period (January 2000), the new controls raised the civilian noninstitutional population and the civilian labor force by 2.6 and 1.6 million, respectively. By December 2002, the civilian population and labor force were 3.8 and 2.5 million, respectively, higher than originally estimated. In addition to these revisions, the U.S. Census Bureau introduced another large upward adjustment to the population controls as part of its annual update of population estimates for The entire amount of this adjustment was added to the labor force data in January 2003 resulting in increases of 941,000 to the civilian noninstitutional population and 614,000 to the civilian labor force. The unemployment rate and other ratios were not substantially affected by either of these population control adjustments. b) The modification of the questions on race and Hispanic origin to comply with new standards for maintaining, collecting, and presenting Federal data on race and ethnicity for Federal statistical agencies. In accordance with the new standards, the following changes were made to the CPS questions: 1) Individuals were now asked whether they are of Hispanic ethnicity before being asked about their race. Prior to 2003, individuals were asked their ethnic origin after they were asked about their race. 2) Individuals were now asked directly if they are Spanish, Hispanic, or Latino. Previously, individuals were identified as Hispanic based on their, or their ancestors', country of origin. 3) With respect to race, the response category of Asian and Pacific Islanders was split into two categories: a) Asian and b) Native Hawaiian or Other Pacific Islanders. 4) Individuals were allowed to choose more than one race category. Prior to 2003, individuals who considered themselves to belong to more than one race were required to select a single primary race. 5) The questions were reworded to indicate that individuals could select more than one race category and to convey more clearly that individuals should report their own perception of what their race is. These changes had no impact on the overall civilian noninstitutional population and civilian labor force but did reduce the population and labor force levels of whites, blacks or African Americans, and Asians beginning in January For whites and blacks, the differences resulted from the exclusion of individuals who reported more than one race from those groups. For Asians, the difference resulted from the same restriction as well as the split of the old Asian and Pacific Islander category into two separate categories. Analysis of data from a special CPS supplement conducted in May 2002 indicated that these changes reduced the population and labor force levels for whites by about 950,000 and 730,000, respectively, and for blacks and African Americans by about 320,000 and 240,000, respectively, while having little or no impact on their unemployment rates. For Asians, the changes had the effect of reducing the their population by about 1.1 million and their labor force by about 720,000, but did not have a statistically significant effect on their unemployment rate. The changes did not affect the size of the Hispanic or Latino population and had no significant impact on the size of their labor force, but did cause an increase of about half a percentage point in their unemployment rate.

201 c) Improvements were introduced to both the second - stage and composite weighting procedures. These changes adapted the weighting procedures to the new race/ethnic classification system and enhanced the stability over time of national and State/substate labor force estimates for demographic groups. More detailed information on these changes and an. indication of their effect on national labor force estimates appear in "Revisions to the Current Population Survey Effective in January 2003" in the February 2003 issue of this publication available on the Internet at Beginning in January, the population control; used in the survey were updated to reflect revised estimate s of net international migration for 2000 through The updated controls resulted in a decrease of 560,000 in the estimated size of the civilian noninstitutional population 16 years of age and over for December The civilian labor force and employment levels decreased by 437,000 and 409,000, respectively. The Hispanic or Latino popula tion and labor force estimates declined by 583,000 and 446,000, respectively and Hispanic or Latino employment was lowered by 421,000. The updated controls had little or no effect on overall and subgroup unemployment rates and measures of labor market participation. More detailed information on the effect of the updated controls on national labor force estimates appears in "Adjustments to Household Survey Population Estimates in January ' in the February issue of this publication available on the Internet at Beginning in January 2005, the population controls used in the survey were adjusted to reflect revised estimates of net international migration and updated vital statistic:; information. The updated controls resulted in a decrease of 8,000 in the estimated size of the civilian noninstitutiona 1 population 16 years of age and over for December Th civilian labor force and employment levels decreased by 49,000 and 45,000, respectively. The updated controls hat no effect on overall and subgroup unemployment rates ano. measures of labor market participation such the labor force: participation rate and the employment-population ratio. More detailed information on the effect of the updated controls on national labor estimates appears in "Adjustments to Household Survey Population Estimates in January 2005" in the February 2005 issue of this publication available on the internet at Changes in the occupational and industrial classification systems Beginning in the comparability ot occupational employment data was affected as a result of changes in the occupational classification system for the 1970 census that were introduced into the CPS. Comparability was further affected in December 1971, when a question relating to major activity or duties was added to the monthly CPS questionnaire in order to more precisely determine the occupational classification of individuals. As a result of these changes, meaningful comparisons of occupational employment levels could not be made between and prior years nor between those 2 years. Unemployment rates were not significantly affected. For a further explanation of the changes in the occupational classification system, see"revisions in Occupational Classifications for 1971" and "Revisions in the Current Population Survey" in the February 1971 and February 1972 issues, respectively, of this publication. Beginning in January 1983, the occupational and industrial classification systems used in the 1980 census were introduced into the CPS. The 1980 census occupational classification system evolved from the Standard Occupational Classification (SOC) system and was so radically different in concepts and nomenclature from the 1970 system that comparisons of historical data are not possible without major adjustments. For example, the 1980 major group "sales occupations" is substantially larger than the 1970 category "sales workers." Major additions include "cashiers" from "clerical workers" and some self-employed proprietors in retail trade establishments from "managers and administrators, except farm." The industrial classification system used in the 1980 census was based on the 1972 Standard Industrial Classification (SIC) system, as modified in The adoption of the new system had much less of an adverse effect on historical comparability than did the new occupational system. The most notable changes from the 1970 system were the transfer of farm equipment stores from "retail" to "wholesale" trade and of postal service from "public administration" to "transportation," and some interchange between "professional and related services" and "public administration." Additional information on the 1980 census occupational and industrial classification systems appears in "Revisions in the Current Population Survey Beginning in January 1983" in the February 1983 issue of this publication. Beginning in January 1992, the occupational and industrial classification systems used in the 1990 census were introduced into the CPS. (These systems were based largely on the 1980 Standard Occupational Classification (SOC) and 1987 Standard Industrial Classification (SIC) systems, respectively.) There were a few breaks in comparability between the 1980 and 1990 census-based systems, particularly within the "technical, sales, and administrative support" categories. The most notable changes in industry classification were the shift of several industries from "business services" to "professional services" and the splitting of some industries into smaller, more detailed categories. A number of industry titles were changed as well, with no change in content. Beginning in January 2003, the 2002 Census Bureau occupational and industrial classification systems were introduced into the CPS. These systems were derived from the 2000 Standard Occupational Classification (SOC) and the 2002 North American Industry Classification System (NAICS). The composition of detailed occupational and industrial classifications in the new classification systems

202 was substantially changed from the previous systems in use as was the structure for aggregating them into broad groups. Consequently, the use of the new classification systems created breaks in existing data series at all levels of aggregation. Additional information on the 2002 Census Bureau occupational and industrial classification systems appears in "Revisions to the Current Population Survey Effective in January 2003" in the February 2003 issue of this publication available on the Internet at Sampling Since the inception of the survey, there have been various changes in the design of the CPS sample. The sample traditionally is redesigned and a new sample selected after each decennial census. Also, the number of sample areas and the number of sample persons are changed occasionally. Most of these changes are made to improve the efficiency of the sample design, increase the reliability of the sample estimates, or control cost. Changes in this regard since 1960 are as follows: When Alaska and Hawaii received statehood in 1959 and 1960, respectively, three sample areas were added to the existing sample to account for the population of these States. In January 1978, a supplemental sample of 9,000 housing units, selected in 24 States and the District of Columbia, was designed to provide more reliable annual average estimates for States. In October 1978, a coverage improvement sample of approximately 450 sample household units representing 237,000 occupied mobile homes and 600,000 new construction housing units was added. In January 1980, another supplemental sample of 9,000 households selected in 32 States and the District of Columbia was added. A sample reduction of about 6,000 units was implemented in May In January 1982, the sample was expanded by 100 households to provide additional coverage in counties added to the Standard Metropolitan Statistical Areas (SMSAs), which were redefined in In January 1985, a new State-based CPS sample was selected based on 1980 census information. A sample reduction of about 4,000 households was implemented in April 1988; the households were reinstated during the 8-month period, April-November A redesigned CPS sample based on the 1990 decennial census was selected for use during the 1990s. Households from this new sample were phased into the CPS between April 1994 and July The July 1995 sample was the first monthly sample based entirely on the 1990 census. For further information on the 1990 sample redesign, see "Redesign of the Sample for the Current Population Survey" in the May 1994 issue of this publication. The original 1990 census-based sample design included about 66,000 housing units per month located in 792 selected geographic areas called primary sampling units (PSUs). The sample initially was selected to meet specific reliability criteria for the Nation, for each of the 50 States and the District of Columbia, and for the substate areas of New York City and the Los Angeles-Long Beach metropolitan area. In 1996, the original sample design reliability criteria were modified to reduce costs. In July 2001, the CPS sample was expanded to support the State Children's Health Insurance Program. For further information on the sample expansion, see "Expansion of the Current Population Survey Sample Effective July 2001" in the August 2001 issue of this publication. The current criteria, given below, are based on the coefficient of variation (CV) of the unemployment level, where the CV is defined as the standard error of the estimate divided by the estimate, expressed as a percentage. These CV controls assume a 6-percent unemployment rate to establish a consistent specification of sampling error. The current sample design, introduced in July 2001, includes about 72,000 "assigned" housing units from 754 sample areas. Sufficient sample is allocated to maintain, at most, a 1.9-percent CV on national monthly estimates of unemployment level, assuming a 6-percent unemployment rate. This translates into a change of 0.2 percentage point in the unemployment rate being significant at a 90-percent confidence level. For each of the 50 States and for the District of Columbia, the design maintains a CV of at most 8 percent on the annual average estimate of unemployment level, assuming a 6-percent unemployment rate. About 60,000 housing units are required in order to meet the national and State reliability criteria. Due to the national reliability criterion, estimates for several large States are substantially more reliable than the State design criterion requires. Annual average unemployment estimates for California, Florida, New York, and Texas, for example, carry a CV of less than 4 percent. In support of the State Children's Health Insurance Program, about 12,000 additional housing units are allocated to the District of Columbia and 31 States. (These are generally the States with the smallest samples after the 60,000 housing units are allocated to satisfy the national and State reliability criteria.) In the first stage of sampling, the 754 sample areas are chosen. In the second stage, ultimate sampling unit clusters composed of about four housing units each are selected. Each month, about 72,000 housing units are assigned for data collection, of which about 60,000 are occupied and thus eligible for interview. The remainder are units found to be destroyed, vacant, converted to nonresidential use, containing persons whose usual place of residence is elsewhere, or ineligible for other reasons. Of the 60,000 housing units, about 7.5 percent are not interviewed in a given month due to temporary absence (vacation, etc.), other failures to make contact after repeated attempts, inability of persons contacted to respond, unavailability for other reasons, and refusals to cooperate (about half of the noninterviews). Information is obtained each month for about 112,000 persons 16 years of age or older. Selection of sample areas. The entire area of the United States, consisting of 3,141 counties and independent cities, is divided into 2,007 sample units (PSUs). In most States, a

203 PSU consists of a county or a number of contiguous counties. In New England and Hawaii, minor civil divisions are used instead of counties. Metropolitan areas within a State are used as a basis for forming PSUs. Outside of metropolitan areas, counties normally are combined except when the geographic area of an individual county is too large. Combining counties to form PSUs provides greater heterogeneity; a typical PSU includes urban and rural residents of both high and low economic levels and encompasses, to the extent feasible, diverse occupations and industries. Another important consideration is that the PSU be sufficiently compact so that, with a small sample spread throughout, it can be efficiently canvassed without undue travel cost. The 2,007 PSUs are grouped into strata within each State:;. Then, one PSU is selected from each stratum with the probability of selection proportional to the population of the PSU. Nationally, there are a total of 428 PSUs in strata by themselves. These strata are self-representing and are generally the most populous PSUs in each State. The 326 remaining strata are formed by combining PSUs that are similar in such characteristics as unemployment, proportion of housing units with three or more persons, number of persons employed in various industries, and average monthly wages for various industries. The single PSU randomly selected from each of these strata is nonself-representing be - cause it represents not only itself but the entire stratum. The probability of selecting a particular PSU in a nonself-representing stratum is proportional to its 1990 population. For example, within a stratum, the chance that a PSU with a population of 50,000 would be selected for the sample is twice that for a PSU having a population of 25,000. Selection of sample households. Because the sample design is State based, the sampling ratio differs by State and depends on State population size as well as both national and State reli - ability requirements. The State sampling ratios range roughl y from 1 in every 100 households to 1 in every 3,000 households. The sampling ratio occasionally is modified slightly to hold the size of the sample relatively constant given the overall growth of the population. The sampling ratio used within a sample PSU depends on the probability of selection of the PSU and the sampling ratio for the State. In a sample PSU with a probability of selection of 1 in 10 and a State sampling ratio of 3,000, a within-psu sampling ratio of 1 in 300 achieves the desired ratio of 1 in 3,000 for the stratum. The 1990 within-psu sample design was developed using block-level data from the 1990 census. (The 1990 census was the first decennial census that produced data at the block level for the entire country.) Normally, census blocks are bounded by streets and other prominent physical features such as rivers or railroad tracks. County, minor civil division, and census place limits also serve as block boundaries. In cities, blocks can be bounded by four streets and be quite small in land area. In rural areas, blocks can be several square miles in size. For the purpose of sample selection, census blocks were Digitized for FRASER grouped into three strata: Unit, group quarters, and area. (Occasionally, units within a block were split between the unit and group-quarters strata.) The unit stratum contained regular housing units with addresses that were easy to locate (for example, most single-family homes, townhouses, condominiums, apartment units, and mobile homes). The groupquarters stratum contained housing units in which residents shared common facilities or received formal or authorized care or custody. Unit and group-quarters blocks exist primarily in urban areas. The area stratum contains blocks with addresses that are more difficult to locate. Area blocks exist primarily in rural areas. To reduce the variability of the survey estimates and to ensure that the within-psu sample would reflect the demographic and socioeconomic characteristics of the PSU, blocks within the unit, group-quarters, and area strata were sorted using geographic and block-level data from the census. Examples of the census variables used for sorting include proportion of minority renter-occupied housing units, proportion of housing units with female householders, and proportion of owner-occupied housing units. The specific sorting variables used differed by type of PSU (urban or rural) and stratum. Within each block, housing units were sorted geographically and grouped into clusters of approximately four units. A systematic sample of these clusters was then selected independently from each stratum using the appropriate within- PSU sampling ratio. The geographic clustering of the sample units reduces field representative travel costs. Prior to interviewing, special listing procedures are used to locate the particular sample addresses in the group-quarters and area blocks. Units in the three strata described above all existed at the time of the 1990 decennial census. Through a series of additional procedures, a sample of building permits is included in the CPS to represent housing units built after the decennial census. Adding these newly built units keeps the sample up-to-date and representative of the population. It also helps to keep the sample size stable: Over the life of the sample, the addition of newly built housing units compensates for the loss of "old" units that may be abandoned, demolished, or converted to nonresidential use. Rotation of sample. Part of the sample is changed each month. Each monthly sample is divided into eight representative subsamples or rotation groups. A given rotation group is interviewed for a total of 8 months, divided into two equal periods. It is in the sample for 4 consecutive months, leaves the sample during the following 8 months, and then returns for another 4 consecutive months. In each monthly sample, one of the eight rotation groups is in the first month of enumeration, another rotation group is in the second month, and so on. Under this system, 75 percent of the sample is common from month to month, and 50 percent is common from year to year for the same month. This procedure provides a substantial amount of month-to-month and year-to-year overlap in the sample, thus providing better estimates of change and reducing discontinuities in the data series without burdening any specific group of households with an unduly long period of inquiry.

204 Period Number of sample Households eligible areas Interviewed Not interviewed Households visited but not eligible Aug to , ,000 3,000-3, to Apr , ,000 3,000-3,500 May 1956 to ,500 1,500 6, to ,500 1,500 6,000 Mar to ,500 1,500 6, to July ,000 2,000 8,500 Auq to July ,000 2,000 8,000 Aug to ,000 2,000 8, to ,500 2,500 10, to Apr ,200 2,800 12,000 May 1981 to ,800 2,500 11, to Mar ,000 2,500 11,000 Apr to Mar ,200 2,600 11,500 Apr to Oct ,400 2,600 11,800 Nov to Aug ,500 3,500 10,000 Sept to ,900 3,400 9, to June ,250 3,750 10,000 July 2001 to present ,500 4,500 12,000 1 Beginning in May 1956, these areas were chosen to provide coverage in each State and the District of Columbia. 2 Three sample areas were added in 1960 to represent Alaska and Hawaii after statehood. 3 The sample was increased incrementally during the 8-month period, April- November CPS sample, 1947 to present. Table 1-A provides a description of some aspects of the CPS sample designs in use since A more detailed account of the history of the CPS sample design appears in chapter 2 of "The Current Population Survey: Design and Methodology," Technical Paper 63RV, (Washington, U.S. Census Bureau and Bureau of Labor Statistics, March 2002), available on the Internet at A description of the 1990 census-based sample design appears in "Redesign of the Sample for the Current Population Survey," in the May 1994 issue of this publication and in chapter 3 of Technical Paper 63RV referenced above. A description of the sample expansion in support of the State Children's Health Insurance Program appears in "Expansion of the Current Population Survey Sample Effective My 2001", in the August 2001 issue of this publication and in Appendix J, "Changes to the Current Population Survey Sample in July 2001," of Technical Paper 63RV referenced above. ESTIMATING METHODS Under the estimating methods used in the CPS, all of the results for a given month become available simultaneously and are based on returns from the entire panel of respondents. The estimation procedure involves weighting the data from each sample person by the inverse of the probability of the person being in the sample. This gives a rough measure of the number of actual persons that the sample person represents. Since 1985, most sample persons within the same State have had the same probability of selection. Some selection probabilities may differ within a State due to the sample design or for operational reasons. Field subsampling, for example, which is carried out when areas selected for the sample are found to contain many more households than expected, may cause probabilities of selection to differ for some sample 4 Includes 2,000 additional assigned housing units from Georgia and Virginia that were gradually phased in during the 10-month period, October August Includes 12,000 assigned housing units in support of the State Children's Health Insurance Program. areas within a State. Through a series of estimation steps (outlined below), the selection probabilities are adjusted for noninterviews and survey undercover age; data from previous months are incorporated into the estimates through the composite estimation procedure. 1. Noninterview adjustment. The weights for all interviewed households are adjusted to account for occupied sample households for which no information was obtained because of absence, impassable roads, refusals, or unavailability of the respondents for other reasons. This noninterview adjustment is made separately for clusters of similar sample areas that are usually, but not necessarily, contained within a State. Similarity of sample areas is based on Metropolitan Statistical Area (MSA) status and size. Within each cluster, there is a further breakdown by residence. Each MSA cluster is split by "central city" and "balance of the MSA." Each non-msa cluster is split by "urban" and "rural" residence categories. The proportion of sample households not interviewed varies from 7 to 8 percent, depending on weather, vacation, etc. 2. Ratio estimates. The distribution of the population selected for the sample may differ somewhat, by chance, from that of the population as a whole in such characteristics as age, race, sex, and State of residence. Because these characteristics are closely correlated with labor force participation and other principal measurements made from the sample, the survey estimates can be substantially improved when weighted appropriately by the known distribution of these population characteristics. This is accomplished through two stages of ratio adjustment, as follows: a. First-stage ratio estimation. The purpose of the firststage ratio adjustment is to reduce the contribution to variance that results from selecting a sample of PSUs rather than drawing sample households from every PSU in the Nation.

205 This adjustment is made to the CPS weights in two race cells: Black and nonblack; it is applied only to PSUs that are not self-representing and for those States that have a substantial number of black households. The procedure corrects for differences that existed in each State cell at the time of the 1990 census between 1) the race distribution of the population in sample PSUs and 2) the race distribution of all PSUs. (Both 1 and 2 exclude self-representing PSUs.) b. Second-stage ratio estimation. This procedure substantially reduces the variability of estimates and corrects, to some extent, for CPS undercoverage. A national-coverage step and a State-coverage step make preliminary corrections for undercoverage. The CPS sample weights are then adjusted to ensure that sample-based estimates ot population match independent population controls. Three sets of controls are used in different steps of the procedure: 1) State step: Civilian noninstitutional population controls for 6 age-sex cells in the Los Angeles-Long Beach metropolitan area, the balance of California, New York City, the balance of New York State, each of the other 48 States, and the District of Columbia. 2) Ethnicity step: National civilian noninstitutional population controls for 26 Hispanic and 26 non-hispanic age-sex cells. 3) Race step: National civilian noninstitutional population controls for 34 white, 26 black, and 26 Asianplus-residual-race age-sex cells. The independent population controls are prepared by projecting forward the resident population as enumerated on April 1, The projections are derived by updating demographic census data with information from a variety of other data sources that account for births, deaths, and net migration. Estimated numbers of resident Armed Forces personnel and institutionalized persons reduce the resident population to the civilian noninstitutional population. Prior to January 2003, the projections were based on earlier censuses. See "Revisions to the Current Population Survey Effective in January 2003," in the February 2003 issue of this publication for a detailed discussion of changes to the second-stage weighting and composite estimating procedures that were introduced in January Composite estimation procedure. The last step in the preparation of most CPS estimates makes use of a composite estimation procedure. The composite estimate consists of a weighted average of two factors: The two-stage ratio estimate based on the entire sample from the current month and the composite estimate for the previous month, plus an estimate of the month-to-month change based on the six rotation groups common to both months. In addition, a bias adjustment term is added to the weighted average to account for relative oias associatea with month-in-sample estimates. This month-in-sample bias is exhibited by unemployment estimates for persons in their first and fifth months in the CPS being generally higher than estimates obtained for the other months. The composite estimate results in a reduction in the sampling error beyond that which is achieved after the two stages of ratio adjustment. For some items, the reduction is substantial. The resultant gains in reliability are greatest in estimates of month-to-month change, although gains usually are also obtained for estimates of level in a given month, change from year to year, and change over other intervals of time. Rounding of estimates The sums of individual items may not always equal the totals shown in the same tables because of independent rounding of totals and components to the nearest thousand. Similarly, sums of percent distributions may not always equal 100 percent because of rounding. Differences, however, are insignificant. Reliability of the estimates An estimate based on a sample survey has two types of error sampling error and nonsampling error. The estimated standard errors provided in this publication are approximations of the true sampling errors. They incorporate the effect of some nonsampling errors in response and enumeration, but do not account for any systematic biases in the data. Nonsampling error. The full extent of nonsampling error is unknown, but special studies have been conducted to quantify some sources of nonsampling error in the CPS. The effect of nonsampling error is small on estimates of relative change, such as month-to-month change; estimates of monthly levels tend to be affected to a greater degree. Nonsampling errors in surveys can be attributed to many sources, for example, the inability to obtain information about all persons in the sample; differences in the interpretation of questions; inability or unwillingness of respondents to provide correct information; inability of respondents to recall information; errors made in collecting and processing the data; errors made in estimating values for missing data; and failure to represent all sample households and all persons within sample households (undercoverage). Nonsampling errors occurring in the interview phase of the survey are studied by means of a reinterview program. This program is used to estimate various sources of error, as well as to evaluate and control the work of the interviewers. A random sample of each interviewer's work is inspected through reinterview at regular intervals. The results indicate, among other things, that the data published from the CPS are subject to moderate systematic biases. A description of the CPS reinterview program may be found in Appendix G, "Reinterview: Design and Methodology," of "The Current Population Survey: Design and Methodology," Technical Paper 63RV (Washington, U.S. Census Bureau and Bureau of Labor Statistics, March 2002), available on the Internet at The effects of some components of nonsampling error in

206 the CPS data can be examined as a result of the rotation plan used for the sample, because the level of the estimates varies by rotation group. A description appears in Barbara A. Bailar, "The Effects of Rotation Group Bias on Estimates from Panel Surveys," Journal of the American Statistical Association, March 1975, pp Undercoverage in the CPS results from missed housing units and missed persons within sample households. The CPS covers about 92 percent of the decennial census population (adjusted for census undercount). It is known that the CPS undercoverage varies with age, sex, race, and Hispanic origin. Generally, undercoverage is larger for men than for women and is larger for blacks, Hispanics, and other races than for whites. Ratio adjustment to independent age-sexrace-origin population controls, as described previously, partially corrects for the biases due to survey undercoverage. However, biases exist in the estimates to the extent that missed persons in missed households or missed persons in interviewed households have characteristics different from those of interviewed persons in the same age-sex-race-origin group. Additional information on nonsampling error in the CPS appears in Camilla Brooks and Barbara Bailar, "An Error Profile: Employment as Measured by the Current Population Survey," Statistical Policy Working Paper 3 (Washington, U.S. Department of Commerce, Office of Federal Statistical Policy and Standards, September 1978); Marvin Thompson and Gary Shapiro, "The Current Population Survey: An Overview," Annals of Economic and Social Measurement, Vol. 2, April 1973; and "The Current Population Survey: Design and Methodology," Technical Paper 63RV referenced above. The last document includes a comprehensive discussion of various sources of errors and describes attempts to measure them in the CPS. Sampling error. When a sample, rather than the entire population, is surveyed, estimates differ from the true population values that they represent. This difference, or sampling error, occurs by chance, and its variability is measured by the standard error of the estimate. Sample estimates from a given survey design are unbiased when an average of the estimates from all possible samples would yield, hypothetically, the true population value. In this case, the sample estimate and its standard error can be used to construct approximate confidence intervals, or ranges of values that include the true population value with known probabilities. If the process of selecting a sample from the population were repeated many times, an estimate made from each sample, and a suitable estimate of its standard error calculated for each sample, then: 1. Approximately 68 percent of the intervals from one standard error below the estimate to one standard error above the estimate would include the true population value. 2. Approximately 90 percent of the intervals from standard errors below the estimate to standard errors above the estimate would include the true population value. 3. Approximately 95 percent of the intervals from 1.96 standard errors below the estimate to 1.96 standard errors above the estimate would include the true population value. Digitized for FRASER These confidence interval statements are approximately true for the CPS. Although the estimating methods used in the CPS do not produce unbiased estimates, biases for most estimates are believed to be small. Methods for estimating standard errors reflect not only sampling errors but also some kinds of nonsampling error. Although both the estimates and the estimated standard errors depart from the theoretical ideal, the departures are minor and have little impact on the confidence interval statements. When clarity is needed, an estimated confidence interval is specified to be "approximate," as is the estimated standard error used in the computation. Tables 1-B through 1-D are provided so that approximate standard errors of estimates can be easily obtained. Tables 1-B and 1-C give approximate standard errors for estimated monthly levels and rates for selected employment status characteristics; the tables also provide approximate standard Table 1-B. Approximate standard errors for major employment status categories (In thousands) Characteristic Total Monthly level Consecutive month-tomonth change Total, 16 years and over: Civilian labor force Employed Unemployed Men, 20 years and over: Civilian labor force Employed Unemployed Women, 20 years and over: Civilian labor force Employed Unemployed Both sexes, 16 to 19 years: Civilian labor force Employed Unemployed Black or African American Total, 16 years and over: Civilian labor force Employed Unemployed Men, 20 years and over: Civilian labor force Employed Unemployed Women, 20 years and over: Civilian labor force Employed Unemployed Both sexes, 16 to 19 years: Civilian labor force Employed Unemployed Asian Total, 16 years and over: Civilian labor force Employed Unemployed Hispanic or Latino ethnicity Total, 16 years and over: Civilian labor force Employed Unemployed 66 73

207 (In percent) Characteristic Total Men Men, 20 years and over... Women Women, 20 years and over Both sexes, 16 to 19 years... White Black or African American Asian Hispanic or Latino ethnicity Married men, spouse present Married women, spouse present Women who maintain families Consecutive Monthly month-torate month change errors for consecutive month-to-month changes in the estimates. It is impractical to show approximate standard errors for all CPS estimates in this publication, so table 1-D provides parameters and factors that allow the user to calculate approximate standard errors for a wide range of estimated levels, rates, and percentages, and also changes over time. The parameters and factors are used in formul.s that are commonly called generalized variance functions, The approximate standard errors provided in this publication are based on the sample design and estimation procedures as of 1996, and reflect the population levels and sample size as of that year. Standard errors for years prior to 1996 may be roughly approximated by applying these adjustments to the standard errors presented here. (More accurate standard error estimates for historical CPS data may be found m previous issues of this publication.) 1. For the years 1967 through 1995, multiply the standard errors by For the years 1956 through 1966, multiply the standard errors by For years prior to 1956, multiply the standard errors by Use of tables l-b and 1-C. These tables provide a quick reference for standard errors of major characteristics. Table l-b gives approximate standard errors for estimates of monthly levels and consecutive month-to-month changes in levels for major employment status categories. Table 1-C gives approximate standard errors for estimates of monthly unemployment rates and consecutive month-to-month changes in unemployment rates for some demographic, occupational, and industrial categories. For characteristics not given in tables l -B and 1-C, refer to table 1-D. Illustration. Suppose that, tor a given month, the number ot women age 20 years and over in the civilian labor force is estimated to be 65.0u For this characteristic, the approximate standard error ot 207,000 is given in table l-b in the row Women. 20 years and over; Civilian labor force." To calculate an approximate 90-percent confidence interval, multiply the standard error of 207,000 by the factor to obtain 341,000. This number is subtracted from and then added to 65,000,000 to obtain an approximate 90-percent confidence interval: 64,659,000 to 65,341,000. Concluding that the true civilian labor force level lies within an interval calculated in this way would be correct for roughly 90 percent of all possible samples that could have been selected for the CPS. Use of table 1-D. This table gives a and h parameters that can be used with formulas to calculate approximate monthly standard errors for a wide range of estimated levels, proportions, and rates. Factors are provided to convert monthly measures into approximate standard errors of estimates for other periods (quarterly and yearly averages) and approximate standard errors for changes over time (consecutive monthly changes, changes in consecutive quarterly and yearly averages, and changes in monthly estimates 1 year apart). The standard errors for estimated changes in level from one month to the next, one year to the next, etc., depend more on the monthly levels for characteristics than on the size of the changes. Likewise, the standard errors for changes in rates (or percentages) depend more on the monthly rates (or percentages) than on the size of the changes. Accordingly, the factors presented in table 1-D are applied to the monthly standard error approximations for levels, percentages, or rates; the magnitudes of the changes do not come into play. Factors are not given for estimated changes between nonconsecutive months (except for changes of monthly estimates 1 year apart); however, the standard errors may be assumed to be higher than the standard errors for consecutive monthly changes. se(x) - Jax' + bx Standard errors of estimated levels using table 1-D. The approximate standard error se(x) of x, an estimated monthly level, can be obtained using the formula below, where a and b are the parameters from table 1 -D associated with a particular characteristic. Illustration. Assume that, in a given a month, there are an estimated 4 million unemployed men. Obtain the appropriate a and b parameters from table 1-D (Total or white; Men; Unemployed). Use the formula for se(x) to compute an approximate standard error on the estimate of x = 4,000,000. a = b = (4,000,000) = V (4,000,000) (4,000,000)«107,000 Procedure for using table 1-D factors for levels. Table 1-D gives factors that can be used to compute approximate standard errors of levels for other periods or for changes over time. For each characteristic, factors/are given for: Consecutive month-to-month changes Changes in monthly estimates 1 year apart Quarterly averages Changes in consecutive quarterly averages Yearly averages Changes in consecutive yearly averages

208 For a given characteristic, the table 1-D factor is used in the following formula, which also uses the a and b parameters from the same line of the table. A three-step procedure for using the formula is given. The/in the formula is frequently called an adjustment factor, because it appears to adjust a monthly standard error se(x). However, the x in the formula is not a monthly level, but an average of several monthly levels (see examples listed under Step 1, below). se(x, /) = / * se(x) = /* ax 2 +bx) where x is an average of monthly levels over a designated period. Step 1. Average monthly levels appropriately in order to obtain x. Levels for 3 months are averaged for quarterly averages, and those for 12 months are averaged for yearly averages. For changes in consecutive averages, average over the 2 months, 2 quarters, or 2 years involved. For changes in monthly estimates 1 year apart, average the 2 months involved. Step 2. Calculate an approximate standard error se(x), treating the average x from step 1 as if it were an estimate of level for a single month. Obtain parameters a and b from table 1-D. (Note that, for some characteristics, an approximate standard error of level could instead be obtained from table 1-B and used in place of se(x) in the formula.) Step 3. Determine the standard error se (x,f) on the average level or on the change in level. Multiply the result from step 2 by the appropriate factor /. The a and b parameters used in step 2 and the factor/used in this step come from the same line in table 1-D. Illustration of a standard error computation for consecutive month change in level. Continuing the previous example, suppose that in the next month the estimated number of unemployed men increases by 150,000, from 4,000,000 to 4,150,000. Step 1. The average of the two monthly levels is x = 4,075,000. Step 2. Apply the a and b parameters from table 1-D (Total or white; Men; Unemployed) to the average x, treating it like an estimate for a single month. a = b = For an approximate 90-percent confidence interval, compute * 120,000 «197,000. Subtract the number from and add the number to 150,000 to obtain an interval of -47,000 to 347,000. This is an approximate 90-percent confidence interval for the true change, and since this interval includes zero, one cannot assert at this level of confidence that any real change has occurred in the unemployment level. The result also can be expressed by saying that the apparent change of 150,000 is not significant at a 90- percent confidence level. Illustration of a standard error computation for quarterly average level. Suppose that an approximate standard error is desired for a quarterly average of the black or African American employment level. Suppose that the estimated employment levels for the 3 months making up the quarter are 14,900,000, 15,000,000, and 15,100,000. Step 1. The average of the three monthly levels is x = 15,000,000. Step 2. Apply the a and b parameters from table 1 -D (Black; Total; Civilian labor force, employed, and not in labor force) to the average x, treating it like an estimate for a single month. a = b = se(15, ) = (15,000,000) (15,000,000) «133,000 Step 3. Obtain/=.87 from the same row of table 1 -D in the column "Quarterly averages," and multiply the factor by the result from step 2. ^(15,000,000) =-.87 * 133, ,000 Illustration of a standard error computation for change in quarterly level Continuing the example, suppose that, in the next quarter, the estimated average employment level for blacks is 15,400,000, based on monthly levels of 15,300,000, 15,400,000, and 15,500,000. This is an estimated increase of 400,000 over the previous quarter. Step 1. The average of the two quarterly levels is, x = 15,200,000. Step 2. Apply the a and b parameters from table 1-D (Black; Total; Civilian labor force, employed, and not in labor force) to the average x, treating it like an estimate for a single month. a = b = (15,200,000) = (15,200,000) (15,200,000) «132,000 56(4,075,000) = V (4,075,000) (4,075,000)» 108,000 Step 3. Obtain /= 1.11 from the same row of table 1-D in the column "Consecutive month-to-month change," and multiply the factor by the result from step 2. ^(150,000) = f*se(4,075,000) = 1.11*108,000 «120,000 Step 3. Obtain /=.82 from the same row of table 1-D in the column "Change in consecutive quarterly averages," and multiply the factor by the result from step 2. 5^(400,000) =.82 * se(15,200,000) =.82 * 132,000 «108,000

209 pute 1.96 * 108,000 «212,000. Subtract the number from and add the number to 400,000 to obtain an interval of 188,000 to 612,000. The interval excludes zero. Another way of stating this is to observe that the estimated change of 400,000 clearly exceeds 1.96 standard errors, or 212,000. One can conclude from these data that the change in quarterly averages is significant at a 95-percent confidence level. 1-ZX As shown in the standard error se(p,y) of a p depends, in part, upon the base or denominator. Generally are not published unless the than 75,000 persons, the quarterly than 60,000 persons, or the yearly 35,000 persons. The b table 1-D from eter from table 1-D Note that se(p,y) is in se(p,y) = y and the numerator of p are :hin the table, use the b paran i- ^-p(l00-p) For pute 1.96 * 1.0 Subtract this from : to ((32)(100-32) «1.0 percent 6,200,000 For a given y = 6,200,000 women 20 to 24 years ofag to be employed, Of this total, 2,000,000, or p = 32 are classified as part-time workers. Obtain the b = from Part-time workers) that is Apply the forse (p>y)-j- comand round the result to 2 percent, add this to the estimate of p = 32 of 30 percent to 34; 1-D factors fort ages. Table 1-D factors can be used to < standard errors on rates and percentages for other periods or for changes over time. As for levels, there are three ; in the procedure for using the ] se(p, y,f) = f* se(p, y) = f*j-p(100-p) > p and y are averages of monthly estimates over a designated period. Note that se (p, y,f) is in percent. Step 1. Appropriately J or percentages to obtain /?, and monthly levels to obtain y. Rates for 3 ] for quarterly averages, and those for 12 i for yearly averages. For changes in average over the 2 months, 2 quarters, or 2 years involved. For changes in monthly estimates 1 year apart, Step 2. Calculate an approximate standard error se (p, y), treating the averages p and y from step 1 as if they from the table 1-D row that describes the numerator of the rate or percentage. (Note that, for some characteristics, an approximate standard error could instead be obtained from table 1-C and used in place of se (p, y) in the formula.) Step 3. Determine the standard error se (/?, y,f) on the average level or on the change in level. Multiply the result from step 2 by the appropriate factor/. The b parameter used in step 2 and the factor/used in this step come from the same line in table 1-D. Continuing the previous j that, in the next month, 6,300,000 women 20 to 24 years of age are reported employed, and that 2,150,000, or 34 percent, are part-time workers. Step 1. The is 2 percent = 34 percent - 32 The average of the two monthly perand 34 percent is needed (p = 33 centages of 32 percent), as is the of the two bases of 6,200,000 and 6,300,000 (y = 6,250,000). Step 2. Apply the b = (Employment; Part-time workers) to the treating the averages like estimates for a from table 1-D P and y, ((33)(100-33) «1.0 percent 6,250,000 Step 3. Obtain/=l.24 from the: ;row of table 1-D in the column "Consecutive month-to-month tiply the factor by the result from step 2. se (2 percent) = 1.24 * 1.0 = 1.24 percent For an approximate 95-percent confidence interval, compute 1.96 * 1.24 percent, and round the result to 2.4 percent. Subtract this from and add this to the 2-percent estimate of change to obtain an interval of -0.4 percent to 4.4 percent. Because this interval includes zero, it can be concluded at a 95-percent confidence level that the change is not significant.

210 Parameters Factors Characteristic a b Consecutive month-tomonth change Year-to-year change of monthly estimates Quarterly averages Change in consecutive quarterly averages Yearly averages Change in consecutive yearly averages Total or white Total: Civilian labor force and employed Unemployed Not in labor force Men: Civilian labor force, employed, and not in labor force Unemployed Women: Civilian labor force, employed, and not in labor force Unemployed Both sexes, 16 to 19 years: Civilian labor force, employed, and not in labor force Unemployed Black or African American Total: Civilian labor force, employed, and not in labor force Unemployed Men: Civilian labor force, employed, and not in labor force Unemployed Women: Civilian labor force, employed, and not in labor force Unemployed Both sexes, 16 to 19 years: Civilian labor force, employed, and not in labor force Unemployed Asian Total: Civilian labor force, employed, and not in labor force Unemployed Men: Civilian labor force, employed, and not in labor force Unemployed Women: Civilian labor force, employed, and not in labor force Unemployed , Both sexes, 16 to 19 years: Civilian labor force, employed, and not in labor force Unemployed Hispanic or Latino ethnicity Total: Civilian labor force, employed, and not in labor force Unemployed Men: Civilian labor force, employed, and not in labor force Unemployed

211 Parameters Factors Characteristic Consecutive Year-to-year Change in Change in mon :h-to- change Quarterly consecutive Yearly consecutive 3 U mc: nth of monthly averages quarterly averages yearly change estimates averages averages Hispanic or Latino ethnicity Continued Women: Civilian labor force, employed, and not in labor force , Unemployed Both sexes, 16 to 19 years: Civilian labor force, employed, and not in labor force , Unemployed Employment Educational attainment , Marital status, men , Marital status, women Women who maintain families Nonagricultural industries: Total Wage and salary workers , Self-employed workers , Unpaid family workers , Full-time workers ,11! Part-time workers , Multiple jobholders At work Total and nonagricultural industries: Total : to 4 or 5 to 14 hours to 29 hours to 34 or 35 to 39 hours to 34 or 40 hours to 48 or 49 to 59 hours , 41+, or 60+ hours Part time for economic reasons Part time for noneconomic reasons , Unemployment Educational attainment , Marital status, men Marital status, women Women who maintain families Industries and occupations Full-time workers Part-time workers , Less than 5 weeks , to 14 weeks to 26 weeks , or 27+ weeks , All reasons for unemployment, except temporary layoff On temporary layoff Not in the labor force Total Persons who currently want a job and discouraged workers

212 Establishment Data ("B" tables) DATA COLLECTION BLS cooperates with State Workforce Agencies in the Current Employment Statistics (CES), or establishment, survey to collect data each month on employment, hours, and earnings from a sample of nonfarm establishments (including government). The sample includes about 160,000 businesses and government agencies covering approximately 400,000 individual worksites. The sample is drawn from a sampling frame of over 8 million unemployment insurance tax accounts. The active CES sample includes approximately one-third of all nonfarm payroll workers. From these data, a large number of employment, hours, and earnings series in considerable industry and geographic detail are prepared and published each month. Historical statistics are available at the BLS Internet site. Each month, BLS and the State agencies collect data on employment, payrolls, and paid hours from a sample of establishments. BLS has established a comprehensive program of new sample unit solicitation in the three BLS regional office data collection centers (DCCs). The DCCs perform initial enrollment of each firm via telephone, collect the data for several months via computer assisted telephone interviewing (CATI), and, where possible, transfer respondents to a self-reporting mode such as touchtone data entry (TDE), FAX, or Web. In addition, the DCCs conduct an ongoing program of refusal conversion. Very large firms are often enrolled via personal visit and ongoing reporting is established via electronic data interchange (EDI). EDI is the most frequently used collection mode (32 percent of respondents), while CATI and TDE are each used by about one-quarter of the respondents. Under EDI, the firm provides an electronic file to BLS each month in a prescribed file format. This file includes data for all of the firms' worksites. The file is received, processed, and edited by the BLS-operated EDI Center. Under the TDE system, the respondent uses a touchtone telephone to call a toll-free number and activate an interview session. The questionnaire resides on the computer in the form of prerecorded questions that are read to the respondent. The respondent enters numeric responses by pressing the touchtone phone buttons. Each answer is read back for respondent verification. CATI and FAX collection through the regional BLS DCCs combined account for most of the remainder of the reports. For establishments that do not use the above methods, data are collected by the State agency using mail, FAX, transcript, magnetic tape, or computer diskette. About 5,000 firms provide data through the World Wide Web. Chart 1 shows the percentage of the establishments using different data collection methods. CONCEPTS Industrial classification All data on employment, hours, and earnings for the Nation and for States and areas are classified in accordance with the 2002 North American Industry Classification System (NAICS), U.S. Office of Management and Budget. The United States, Canada, and Mexico share this classification system, and thus it allows a direct comparison of economic data between the three countries. Establishments are classified into industries on the basis of their primary activity. Those that use comparable capital equipment, labor, and raw material inputs are classified together. This information is collected on a supplement to the quarterly unemployment insurance tax reports filed by employers. For an establishment engaging in more than one activity, the entire employment of the establishment is included under the industry indicated by the principal activity. Industry employment Employment data refer to persons on establishment payrolls who received pay for any part of the pay period that includes the 12th day of the month. Chart 1. Distribution of CES sample by collection mode TDE J 22% 24%

213 The data exclude proprietors, the self-employed, unpaid volunteer or family workers, farmworkers, and domestic workers. Salaried officers of corporations are included. Government employment covers only civilian employees; military personnel a re excluded. Employees of the Central Intelligence Agency, the Defense Intelligence Agency, the National Geospatial-Intelligence Agency, and the National Security Agency also are excluded. Persons on establishment payrolls who are on paid sick leave (for cases in which pay is received directly from the firm), on paid holiday, or on paid vacation, or who work during a part of the pay period even though they are unemployed or on strike during the rest of the period are counted as employed. Not counted as employed are persons who are on layoff, on leave without pay, or on strike for ti e entire period, or who were hired but have not yet reported during the period. Industry hours and earnings Average hours and earnings data are derived from reports of payrolls and hours for production and related workers in natural resources and mining and manufacturing, construction workers in construction, and nonsupervisory employees in private service-providing industries. Production and related workers. This category include s working supervisors and all nonsupervisory workers (including group leaders and trainees) engaged in fabricating, processing, assembling, inspecting, receiving, storing, handling, packing, warehousing, shipping, trucking, hauling, maintenance, repair, janitorial, guard services, product development, auxiliary production for plant's own use (for example, power plant), recordkeeping, and other services closely associated with the above production operations. Construction workers. This group includes the following employees in the construction division: Working supervisors, qualified craft workers, mechanics, apprentices, helpers, laborers, and so forth, engaged in new work, alterations, demolition, repair, maintenance, and the like, whether working at the site of construction or in shops or yards at jobs (such as precutting and preassembling) ordinarily performed by members of the construction trades. Nonsupervisory employees. These are employees (not above the working-supervisor level) such as office and clerical workers, repairers, salespersons, operators, drivers, physicians, lawyers, accountants, nurses, social workers, research aides, teachers, drafters, photographers, beauticians, musicians, restaurant workers, custodial workers, attendants, line installers and repairers, laborers, janitors, guards, and other employees at similar occupational levels whose services are closely associated with those of the employees listed. Payroll This refers to the payroll for full- and part-time production, construction, or nonsupervisory workers who received pay for any part of the pay period that includes the 12th day of the month. The payroll is reported before deductions of any kind, such as those for old-age and unemployment insurance, group insurance, withholding tax, bonds, or union dues; also included is pay for overtime, holidays, and vacation, and for sick leave paid directly by the firm. Bonuses (unless earned and paid regularly each pay period); other pay not earned in the pay period reported (such as retroactive pay); tips; and the value of free rent, fuel, meals, or other payment in kind are excluded. Employee benefits (such as health and other types of insurance, contributions to retirement, and so forth, paid by the employer) also are excluded. Hours. These are the hours paid for during the pay period that includes the 12th of the month for production, construction, or nonsupervisory workers. Included are hours paid for holidays and vacations, and for sick leave when pay is received directly from the firm. Overtime hours. These are hours worked by production or related workers for which overtime premiums were paid because the hours were in excess of the number of hours of either the straight-time workday or the workweek during the pay period that included the 12th of the month. Weekend and holiday hours are included only if overtime premiums were paid. Hours for which only shift differential, hazard, incentive, or other similar types of premiums were paid are excluded. Average weekly hours. The workweek information relates to the average hours for which pay was received and is different from standard or scheduled hours. Such factors as unpaid absenteeism, labor turnover, part-time work, and stoppages cause average weekly hours to be lower than scheduled hours of work for an establishment. Group averages further reflect changes in the workweek of component industries. Indexes of aggregate weekly hours and payrolls. The indexes of aggregate weekly hours are calculated by dividing the current month's aggregate by the average of the 12 monthly figures for For basic industries, the hours aggregates are the product of average weekly hours and production worker or nonsupervisory worker employment. At all higher levels of industry aggregation, hours aggregates are the sum of the component aggregates. The indexes of aggregate weekly payrolls are calculated by dividing the current month's aggregate by the average of the 12 monthly figures for For basic industries, the payroll aggregates are the product of average hourly earnings and aggregate weekly hours. At all higher levels of industry aggregation, payroll aggregates are the sum of the component aggregates.

214 Average overtime hours. Overtime hours represent that portion of average weekly hours that exceeded regular hours and for which overtime premiums were paid. If an employee were to work on a paid holiday at regular rates, receiving as total compensation their holiday pay plus straight-time pay for hours worked that day, no overtime hours would be reported. Because overtime hours are premium hours by definition, weekly hours and overtime hours do not necessarily move in the same direction from month to month. Such factors as work stoppages, absenteeism, and labor turnover may not have the same influence on overtime hours as on average hours. Diverse trends at the industry group level also may be caused by a marked change in hours for a component industry in which little or no overtime was worked in both the previous and current months. Average hourly earnings. Average hourly earnings are on a "gross" basis. They reflect not only changes in basic hourly and incentive wage rates, but also such variable factors as premium pay for overtime and late-shift work and changes in output of workers paid on an incentive plan. They also reflect shifts in the number of employees between relatively high-paid and low-paid work and changes in workers' earnings in individual establishments. Averages for groups and divisions further reflect changes in average hourly earnings for individual industries. Averages of hourly earnings differ from wage rates. Earnings are the actual return to the worker for a stated period; rates are the amount stipulated for a given unit of work or time. The earnings series do not measure the level of total labor costs on the part of the employer because the following are excluded: Benefits, irregular bonuses, retroactive items, payroll taxes paid by employers, and earnings for those employees not covered under production worker, construction worker, or nonsupervisory employee definitions. Average hourly earnings, excluding overtime. Average hourly earnings, excluding overtime-premium pay, are computed by dividing the total production worker payroll for the industry group by the sum of total production worker hours and one-half of total overtime hours. No adjustments are made for other premium payment provisions, such as holiday pay, late-shift premiums, and overtime rates other than time and one-half. Average weekly earnings. These estimates are derived by multiplying average weekly hours estimates by average hourly earnings estimates. Therefore, weekly earnings are affected not only by changes in average hourly earnings but also by changes in the length of the workweek. Monthly variations in such factors as the proportion of part-time workers, stoppages for varying reasons, labor turnover during the survey period, and absenteeism for which employees are not paid may cause the average workweek to fluctuate. Long-term trends of average weekly earnings can be affected by structural changes in the makeup of the workforce. For example, persistent long-term increases in the proportion of part-time workers in retail trade and many of the services industries have reduced average workweeks in these industries and have affected the average weekly earnings series. Real earnings. These earnings are in constant dollars and are calculated from the earnings averages for the current month using a deflator derived from the Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI- W). The reference year for these series is Indexes of diffusion of employment change. These indexes measure the dispersion of change in employment among industries over the specified timespan. The overall indexes are calculated from 278 seasonally adjusted employment series (4-digit NAICS industries) covering all nonfarm payroll employment in the private sector. The manufacturing diffusion indexes are based on 84 4-digit NAICS industries. To derive the indexes, each component industry is assigned a value of 0, 50, or 100 percent, depending on whether its employment showed a decrease, no change, or an increase, respectively, over the timespan. The average value (mean) is then calculated, and this percent is the diffusion index number. The reference point for diffusion analysis is 50 percent, the value indicating that the same number of component industries had increased as had decreased. Index numbers above 50 show that more industries had increasing employment and values below 50 indicate that more had decreasing employment. The margin between the percent that increased and the percent that decreased is equal to the difference between the index and its complement that is, 100 minus the index. For example, an index of 65 percent means that 30 percent more industries had increasing employment than had decreasing employment (65-( ) = 30). However, for dispersion analysis, the distance of the index number from the 50-percent reference point is the most significant observation. Although diffusion indexes commonly are interpreted as showing the percent of components that increased over the timespan, the index reflects half of the unchanged components as well. (This is the effect of assigning a value of 50 percent to the unchanged components when computing the index.) ESTIMATING METHODS The Current Employment Statistics (CES) or establishment survey estimates of employment are generated through an annual benchmark and monthly sample link procedure. Annual universe counts or benchmark levels are generated primarily from administrative records on employees covered by unemployment insurance (UI) tax laws. These annual benchmarks, established for March of each year, are projected

215 forward for each subsequent month based on the trend of the sample employment, using an estimation procedure called the link relative. Benchmarks and sample link relatives are computed for each basic estimating cell and summed to create aggregate-level employment estimates. Benchmarks For the establishment survey, annual benchmarks are constructed in order to realign the sample-based employment totals for March of each year with the Ul-based populatio n counts for March. These population counts are much less timely than sample-based estimates and are used to provide an annual point-in-time census for employment. For nationa l series, only the March sample-based estimates are replaced with XJI counts. For State and metropolitan area series, all available months oflji data are used to replace sample-based estimates. State and area series are based on smaller samples and are therefore more vulnerable to both sampling and nonsampling errors man national estimates. Population counts are derived from the administrative file of employees covered by UI. All employers covered by UI laws are required to report employment and wage infbrmatic m to the appropriate State workforce agency four times a yea r. Approximately 97 percent ol private employment within the scope of the establishment survey is covered by UI. A benchmark for the remaining 3 percent is constructed from alternate sources, primarily records from the Railroad Retirement Board and County Business Patterns, The foil benchmark developed tor March replaces the March samplebased estimate for each basic cell. The monthly sample-based estimates for the year preceding and the year following the benchmark also are than subject to revision. Monthly estimates tor the year preceding the March benchmark are readjusted using a wedge-back" procedure. The difference between the final benchmark level and the previously published March sample estimate is calculated and spread back across the previous 11 months. The wedge is linear; eleven-tweltths of the March difference is adde d to the February estimate, ten-twelfths to the January estimate, and so on, back to the previous April estimate, which receives one-twelfth of the March difference. This assumes that the total estimation error since the last benchmark accumulated at a steady rate throughout the current benchmark year. Estimates for the 7 months following the March benchmark also are recalculated each year. These post-benchmark estimates reflect the application of sample-based monthly changes to new benchmark levels for March and the recomputation of net birth/death model factors for each month. Following the revision of basic employment estimates, all other derivative series (such as the number of production workers and average hourly earnings) also are recalculated. New seasonal adjustment factors are calculated and all data series for the previous 5 years are re-seasonally adjusted before full publication of all revised data in February of each year. Changing data ratios for educational services and religious organizations. Due to definitional exclusions in the collection of data for educational services, NAICS 611, and a small sample in religious organizations, NAICS 8131, certain ratios for these series are recalculated with each benchmark to allow for the creation of aggregate totals. Production worker and women worker ratios, average hourly earnings, and average weekly hours are calculated based on the weighted average of the previous year's professional and technical services, education and health services, leisure and hospitality, and other services supersectors annual averages. The March values were set based on the 2003 annual averages. The educational services series uses the nonsupervisory worker ratio, average hourly earnings, and average weekly hours calculated from the weighted average. The religious organizations series uses the production worker and women worker ratios, average hourly earnings, and average weekly hours calculated from the weighted average. In both cases, the ratios, average hourly earnings, and average weekly hours are held constant through the next benchmark. Monthly estimation CES uses a matched sample concept and weighted link relative estimator to produce employment, hours, and earnings estimates. These methods are described in table 2- A. A matched sample is defined to be all sample members that have reported data for the reference month and the previous month. Excluded from the matched sample is any sample unit that reports that it is out ofbusiness. This aspect of the estimation methodology is more fully described in the section on estimation ofbusiness births and deaths below. Stratification. The sample is stratified into 688 estimation cells for purposes of computing national employment, hours, and earnings estimates. Cells are defined primarily by detailed industry. In the construction supersector, geographic stratification also is used. The estimation cells can be defined at the 3-, 4-, 5-, and 6-digit NAICS levels. In addition to the estimation cells mentioned above, there are 40 independently estimated cells which do not aggregate to the summary cell levels. Weighted link-relative technique. The estimator for the all-employee series uses the sample trend in the cell to move the previous level to the current-month estimated level. A model-based component is applied to account for the net employment resulting from business births and deaths not captured by the sample. The basic formula for estimating all employees is: AE C =. Y( w i xae J P X( w + (net birth / death estimate), / x^/j

216 Table 2-A. Summary of methods for computing industry statistics on employment, hours, and earnings estimates Employment, hours,and earnings Basic estimating cell (industry, 6-digit published level) Aggregate industry level (supersector and, where stratified, industry) Annual average data All employees All-employee estimate for previous month multiplied by weighted ratio of all employees in current month to all employees in previous month, for sample establishments that reported for both months plus net birth/death model estimate. Sum of all-employee estimates for component cells. Sum of monthly estimates divided by 12. Production or nonsupervisory workers, women employees All-employee estimate for current month multiplied by (1) weighted ratio of production or nonsupervisory workers to all employees in sample establishments for current month, (2) weighted ratio of women employees to all employees. Sum of production or nonsupervisory worker estimates, or estimates of women employees, for component cells. Sum of monthly estimates divided by 12. Average weekly hours Production or nonsupervisory worker hours divided by number of production or nonsupervisory workers. Average, weighted by production or nonsupervisory worker employment, of the average weekly hours for component cells. Annual total of aggregate hours (production or nonsupervisory worker employment multiplied by average weekly hours) divided by annual sum of production worker employment. Average weekly overtime hours Production worker overtime hours divided by number of production workers. Average, weighted by production worker employment, of the average weekly overtime hours for component cells. Annual total of aggregate overtime hours (production worker employment multiplied by average weekly overtime hours) divided by annual sum of production worker employment. Average hourly earnings Total production or nonsupervisory worker payroll divided by total production or nonsupervisory worker hours. Average, weighted by aggregate hours, of the average hourly earnings for component cells. Annual total of aggregate payrolls (production or nonsupervisory worker employment multiplied by weekly hours and hourly earnings) divided by annual aggregate hours. Average weekly earnings Product of average weekly hours and average hourly earnings. Product of average weekly hours and average hourly earnings. Product of average weekly hours annual average and average hourly earnings annual average. where: i w i = matched sample unit; = weight associated with the CES report; ae c i = current-month reported all employees; ae pj = previous-month reported all employees; Mc = current-month estimated all employees; and AE = p previous-month estimated all employees. Weighted link and taper technique. The estimator used for all non-all-employee data types accounts for the overthe-month change in the sampled units, but also includes a tapering feature used to keep the estimates close to the overall sample average over time. The taper is considered to be a level correction. This estimator uses matched sample data; it tapers the estimate toward the sample average for the previous month of the current matched sample before applying the current month's change; and it promotes continuity by heavily favoring the estimate for the previous month when applying the numerical factors. Current-month estimate of production or nonsupervisory workers (PW) is defined as: (f \ \ {PW) PW = x PWRATIO^ + Z. PWcv where: W PWRATIO n = or x PWRATIO + Z x p w oj I-1X w j x P w *J I I Z w i xae cj ~ Z xae *cj W) for all i e I and j^j Z W,. X ae Ptl J - Z x «< (,7 ) x p w P,i r Z x P w IJ

217 Current-month estimate of women workers (WW) is identical to that described for production workers, with the appropriate substitution of women worker values for the production worker values in the previous formulas. Current-month estimate of average weekly hours (AWE) is defined as: A WH C = axa WH p+ /? x Z W J - Ya W J X P W \ PW +y wh*. Lu J pj ]Tw (.xw/z c, - Y, w J xwh l. T, w ' x p w cj H 1l w J x P w,*(wh) c,j 1 PW +Z w/ C j T w ' xw^j\-\jl w j xwh lj T w i x P w PJ r 1l V j w j x p w Z (WH) PW n fiwh) J j J) for all ie I andj^j Current-month estimate of average hourly earnings (AHE) is defined as: AHEc -ax AHE p + fix I ^. x w ^, -\Y w j xwh *pj J J WH '(PR) (( / Iw,xpr, - Y w J x P f i *(PR) T w i xwh cj H T w j xwh 2 c,j WH c-t wh l '(PR) J + j Hp<j H w x w i h pj\- H w J xwh PJ R) + Z p r pj J WH,. WH n for all i g / and 7 e J

218 i I = a matched CES report; = the set of all matched CES reports; AWH : = current-month estimated average weekly hours; j = a matched CES report where the current month is atypical; = previous-month estimated average weekly hours; MA P W c,i P W p,i PWcJ PWpJ *{WH) PW c,j pw pw c, PW. p,l w hi wh p,i wh cj wh* P j p,j wh* {PR Kj = wh HPR) PJ WH = the set of all matched CES reports where the current month is atypical (NOTE: J is a subset of I); = weight associated with the CES report; = current-month reported production workers; = previous-month reported production workers; = current-month reported production workers, atypical record; = previous-month reported production workers, atypical record; = current-month reported production workers, atypical weekly hours (WH) record; previous-month reported production workers, atypical weekly hours (WH) record; current-month estimated production workers; previous-month estimated production workers; current-month reported weekly hours; previous-month reported weekly hours; current-month reported weekly hours, atypical record; previous-month reported weekly hours, atypical record; current-month reported weekly hours, atypical payroll (PR) record; previous-month reported weekly hours, atypical payroll (PR) record; current-month estimated weekly hours; P r a P r p,i pr*cj pr%j AHE CJ AHE fj = current-month reported weekly payroll; = previous-month reported weekly payroll; = current-month reported weekly payroll, atypical record; = previous-month reported weekly payroll, atypical record; = current-month estimated average hourly earnings; and = previous-month estimated average hourly earnings. Current-month estimate of overtime hours (OT) is identical to that described for weekly hours, with the appropriate substitution of overtime hours values for the weekly hours values in the previous formula. Business birth and death estimation. In a dynamic economy, firms are continually opening and closing. These two occurrences offset each other to some extent. That is, firms that are born replace firms that die. CES uses this fact to account for a large proportion of the employment associated with business births. This is accomplished by excluding such business death units from the matched sample definition. Effectively, business deaths are not included in the sample-based link portion of the estimate, and the implicit imputation of their previous month's employment is assumed to offset a portion of the employment associated with births. There is an operational advantage associated with this approach as well. Most firms will not report that they have gone out of business; rather, they simply cease reporting and are excluded from the link, as are all other nonrespondents. As a result, extensive follow-up with monthly nonrespondents to determine whether a company is out of business or simply did not respond is not required. Employment associated with business births will not exactly equal that associated with business deaths. The amount by which it differs varies by month and by industry. As a result, the residual component of the birth/ death offset must be accounted for by using a model-based approach.

219 With any model-based approach, it is desirable to have 5 or more years of history to use in developing the models Due to the absence of reliable counts of monthly business births and deaths, development of an appropriate birth/death residual series assumed the following form: Birth-death residual = Population - Sample-based estimate + Error During the net birth/death modeling process, simulated monthly probability estimates over a 5-year period arc created and compared with population employment levels. Moving from a simulated benchmark, the differences between the series across time represent a cumulative birth ^ death component. Those residuals are converted to month - to-month differences and used as input series to the modeling process. Models are fit using X-12 ARIMA (Auto-Regressive Integrated Moving Average). Outliers, level shifts, and temporary ramps are automatically identified. Seven models are tested, and the model exhibiting the lowest average forecast error is selected for each series. Table 2-B shows the net birth/death model figures for the postbenchmark period of April to October by supersector. Residential and nonresidential specialty trade contractors estimates. Residential and nonresidential specialty trade contractors estimates are produced as sub-breakouts ii specialty trade contractors (NAICS 238) under the standard NAICS coding structure. Benchmarks for these series are developed from the QCEW data and independent estimates for these series are made on a monthly basis and raked to the estimates produced under the standard structure to ensure that the sum of the residential specialty trade contractors and nonresidential specialty trade contractors series is consistent with the published total for specialty trade contractors at the 3-digit NAICS level. The raking adjustment follows the following methodology: Estimates are derived independently for the residential and nonresidential groups at the 4-digit NAICS level for each region. The regional estimates are rounded and summed to the 4-digit NAICS level for both the residential and nonresidential groups. Within each 4-digit NAICS series, ratios of residential-to-total employment and nonresidential-to-total employment are calculated. At the 4-digit NAICS level, the sum of the residential/ nonresidential series is subtracted from the official industryregion cell structure total to determine the amount that must be raked. The total amount that must be raked then is multiplied by the ratios to determine what percentage of the raked amount should be applied to the residential group and what percentage should be applied to the nonresidential group. Once the residential and nonresidential groups receive their proportional amount of raked employment, the two groups are aggregated again to the 4-digit NAICS level. At this point, they are equal to the 4-digit NAICS total derived from the official industry-region cell structure. This raking process also forces additivity at the 3-digit NAICS level. No estimates of hours and earnings are made for the residential and nonresidential series. THE SAMPLE Design The CES sample is a stratified, simple random sample of worksites, clustered by UI account number. The UI account number is a major identifier on the BLS longitudinal database of employer records, which serves as both the sampling frame and the benchmark source for the CES employment estimates. The sample strata, or subpopulations, are defined by State, industry, and employment size, yielding a Statebased design. The sampling rates for each stratum are determined through a method known as optimum allocation, Table 2-B. Net birth/death estimates for private nonfarm Industries,, post-benchmark (In thousands) Year and month Natural resources and mining Construction Manufacturing Trade, transportation, and utilities Financial activities Information Professional and business services Education and health services Leisure and hospitality Other services Total monthly amount contributed : April May June July August September October November December Cumulative Total

220 which distributes a fixed number of sample units across a set of strata to minimize the overall variance, or sampling error, on the primary estimate of interest. The total nonfarm employment level is the primary estimate of interest, and the CES sample design gives top priority to measuring it as precisely as possible, or, in other words, minimizing the statistical error around the statewide total nonfarm employment estimates. Frame and sample selection. The longitudinal data base (LDB) is the universe from which BLS draws the CES sample. The LDB contains data on the approximately 8 million U.S. business establishments covered by UI, representing nearly all elements of the U.S. economy. The Quarterly Census of Employment and Wages (QCEW), or ES-202, program collects these data from employers, on a quarterly basis, in cooperation with State workforce agencies. The LDB contains employment and wage information from employers, as well as name, address, and location information. It also contains identification information such as unemployment insurance (UI) account number and reporting unit or worksite number. The LDB contains records of all employers covered under the unemployment insurance tax system. The system covers 97 percent of all employers in the 50 States, the District of Columbia, Puerto Rico, and the Virgin Islands. There are a few sections of the economy that are not covered, including the self-employed, unpaid family workers, railroads, religious organizations, small agricultural employers, and elected officials. Data for employers generally are reported at the worksite level. Employers who have multiple establishments within a State usually report data for each individual establishment. The LDB tracks establishments over time and links them from quarter to quarter. Permanent random numbers (PRNs) have been assigned to all UI accounts on the sampling frame. As new units appear on the frame, random numbers are assigned to those units as well. As records are linked across time, the PRN is carried forward in the linkage. The CES sample is stratified by State, industry, and size. Stratification groups population members together for the purpose of sample allocation and selection. The strata, or groups, are composed of homogeneous units. With 13 industries and 8 size classes, there are 104 total allocation cells per State. The sampling rate for each stratum is determined through a method known as optimum allocation. Optimum allocation minimizes variance at a fixed cost or minimizes cost for a fixed variance. Under the CES probability design, a fixed number of sample units for each State is distributed across the allocation strata in such a way as to minimize the overall variance, or sampling error, of the total State employment level. The number of sample units in the CES probability sample was fixed according to available program resources. The optimum allocation formula places more sample in cells for which data cost less to collect, cells that have more units, and cells that have a larger variance. During the first quarter of each year, a new sample is drawn from the LDB. Annual sample selection helps keep the CES survey current with respect to employment from business births and business deaths. In addition, the updated universe files provide the most recent information on industry, size, and metropolitan area designation. After all out-of-scope records are removed, the sampling frame is sorted into allocation cells. Within each allocation cell, units are sorted by metropolitan statistical area (MSA) and by the size of the MSA, defined as the number of UI accounts in that MSA. As the sampling rate is uniform across the entire allocation cell, implicit stratification by MSA ensures that a proportional number of units are sampled from each MSA. Some MSAs may have too few UI accounts in the allocation cell; these MSAs are collapsed and treated as a single MSA. Within each selection cell, the units are sorted by PRN, and units are selected according to the specified sample selection rate. The number of units selected randomly from each selection cell is equal to the product of the sample selection rate and the number of eligible units in the cell, plus any carryover from the prior selection cell. The result is rounded to the nearest whole number. Carryover is defined as the amount that is rounded up or down to the nearest whole number. As a result of the cost and workload associated with enrolling new sample units, all units remain in the sample for a minimum of 2 years. To insure that all units meet this minimum requirement, BLS has established a "swapping in" procedure. The procedure allows units to be swapped into the sample that were newly selected during the previous sample year and not reselected as part of the current probability sample. The procedure removes a unit within the same selection cell and places the newly selected unit from the previous year back into the sample. Selection weights. Once the sample is drawn, sample selection weights are calculated based on the number of UI accounts actually selected within each allocation cell. The sample selection weight is approximately equal to the inverse of the probability of selection, or the inverse of the sampling rate. It is computed as: Sample selection weight = N h / where: N h = the number of noncertainty UI accounts within the allocation cell that are eligible for sample selection; and n h = the number of noncertainty UI accounts selected within the allocation cell Sample Rotation. Sample rotation eases the burden on respondents who have been participating in the survey for an extended time period. A 25-percent rotation is utilized in

221 Table 2-C. Employment benchmarks and approximate coverage of BLS employment and payrolls sample, March Sample coverage Industry Employment benchmarks (thousands) Unemployment insurance counts (UI) 1 Number of establishments 1 Number (thousands) 2 Employees Percent of employment benchmarks Total , , ,061 42, Natural resources and mining , Construction 6,551 12,411 14, Manufacturing 14, ,579 4, Trade, transportation, and utilities... 25,130 25, ,235 6, Information 3,126 3,103 14, Financial activities 7,966 7,875 56,155 1, Professional and business services. 15,995 19,981 40,871 3, Education and health services 16,988 16,059 36,795 5, Leisure and hospitality 12,077 14,902 37,988 2, Other services 5,404 6,680 11, Government. 21, ,995 37,477 15, Counts reflect active sample reports. Because not all establishments report pciyroll and hours information, hours and earnings estimates are based on a smaller sample than are the employment estimates. 2 Average employment of reported values for. 3 The Surface Transportation Board provides a complete count of employment for Class I railroads plus Amtrak. A small sample is used to estimate hours and earnings data. selection cells with weights greater than Units that rotate out of the sample will not be reselected as part of the sample for 3 years. In an effort to keep units from movii g back into the sample after a single year, a "swap out" procedure has been established. The "swap out" procedure removes units from the current sample that had been rotated out of the sample within the last 3 years and replaces them with other units within the selection cell eligible for sample selection. As a result of sample rotation, approximately 68 percent of the Current Employment Statistics sample for the private industries overlaps from one year to the next. Frame maintenance and sample updates. Due to the dynamic economy, there is a constant cycle ofbusiness births and deaths. A semiannual update is performed during the third quarter of each year. This update selects units from the population of births and other units not previously eligible for selection, and includes them as part of the sample. Updated location, contact, and administrative information is provided for all establishments that were selected in the annual sample selection. Subsampling. The primary enrollment of new establishments takes place in BLS regional office data collection centers (DCCs). After the sample has been sent to the DCCs, interviewers enroll the selected establishments. While the UI account is the sample unit, interviewers attempt to collect the data for all individual establishments withir a UI account. For multiple-worksite UI accounts, it is sometimes necessary to subsample employers. This occurs when: - the company cannot report for all worksites from a central location; - the company cannot provide an aggregate report for the entire UI account; - there are too many individual worksites to make it practical to contact each of them. With subsampling of a smaller number of worksites, both interviewer workload and respondent burden are reduced without significantly reducing the accuracy of the estimates, but this technique will result in a small increase in variance. In the event that a UI account is subsampled, weight adjustments are made to reflect each of the worksites' probability of selection. Coverage Table 2-C shows the latest benchmark employment levels and the approximate proportion of total universe employment coverage at the total nonfarm and major industry supersector levels. The coverage for individual industries within the supersectors may vary from the proportions shown. Reliability The establishment survey, like other sample surveys, is subject to two types of error, sampling and nonsampling error. The magnitude of sampling error, or variance, is directly related to the size of the sample and the percentage of universe coverage achieved by the sample. The establishment survey sample covers over one-third of total universe employment; this yields a very small variance for the total nonfarm estimates. Measurements of error associated with sample estimates are provided in tables 2-D through 2-F.

222 Table 2-D. Errors of preliminary employment estimates Industry Rootmeansquare error of monthly level 1 Mean percent revision Actual Absolute Total 53, Total private 43, Government 28, Federal 14, Federal, except U.S. Postal Service 12, U.S. Postal Service 6, State government 12, State government education... 12, State government, excluding education 5, Local government 21, Local government education... 22, Local government, excluding education 8, The root-mean-square error is the square root of the mean squared error. The mean squared error is the square of the difference between the final and preliminary estimates averaged across a series of monthly observations. NOTE: Errors are based on differences from January 2000 through October. Benchmark revision as a measure of survey error. The sum of sampling and nonsampling error can be considered total survey error. Unlike most sample surveys which publish sampling error as their only measure of error, the CES can derive an annual approximation of total error, on a lagged basis, because of the availability of the independently derived universe data. While the benchmark error is used as a measure of total error for the CES survey estimate, it actually represents the difference between two independent estimates derived from separate survey processes (specifically, the CES sample process and the UI administrative process) and thus reflects the errors present in each program. Historically, the benchmark revision has been very small for total nonfarm employment. Over the past decade, percentage benchmark error has averaged 0.2 percent, with an absolute range from less than 0.05 percent to 0.5 percent. Revisions between preliminary and final data. First preliminary estimates of employment, hours, and earnings, based on less than the total sample, are published immediately following the reference month. Final revised sample-based estimates are published 2 months later when nearly all the reports in the sample have been received. Table 2-D presents the root-mean-square error, the mean percent, and the mean absolute percent revision that may be expected between the preliminary and final employment estimates. Revisions of preliminary hours and earnings estimates are normally not greater than 0.1 hour for weekly hours and 1 cent for hourly earnings, at the total private nonfarm level, and may be slightly larger for the more detailed industry groupings. Variance estimation. The estimation of sample variance for the CES survey is accomplished through use of the method of balanced half samples (BHS). This replication technique uses half samples of the original sample and calculates estimates using those subsamples. The sample variance is calculated by measuring the variability of the subsample estimates. The weighted link estimator is used to calculate both estimates and variances. The sample units in each cell where a cell is based on State, industry, and size classification are divided into two random groups. The basic BHS method is applied to both groups. The subdivision of the cells is done systematically, in the same order as the initial sample selection. Weights for units in the half sample are multiplied by a factor of 1 + y where weights for units not in the half sample are multiplied by a factor of 1 - y. Estimates from these subgroups are calculated using the estimation formula described previously. The formula used to calculate CES variances is as follows: where: /V / /V /\ \ \2 k i A+.. e\ = z Oa-6 y 2 k a-l 0 + a =*(Y a \x;, ). is the half-sample estimator; r =v 2 ; k = number of half-samples; and Q = original full-sample estimates. Appropriate uses of sampling variances. Variance statistics are useful for comparison purposes, but they do have some limitations. Variances reflect the error component of the estimates that is due to surveying only a subset of the population, rather than conducting a complete count of the entire population. However, they do not reflect nonsampling error, such as response errors, and bias due to nonresponse. The overall performance of the CES employment estimates is best measured in terms of the benchmark revisions. The variances of the over-the-month change estimates are very useful in determining when changes are significant at some level of confidence. Variance statistics for first-closing estimates are provided in Table 2-F. In addition, variances for second- and third-closing estimates are available upon request. Sampling errors. The sampling errors shown for total nonfarm and for total private industries have been calculated for estimates that follow the benchmark employment revision by a period of 16 to 20 months. The errors are presented as median values of the observed error estimates. These estimates have been estimated using the method of balanced half samples with the probability sample data and sample weights assigned at the time of sample selection.

223 Illustration of the use of table 2-E. Table 2-E provides a reference for relative standard errors of three major series developed from the CES estimates of the number of all employees (AE), of average weekly hours (AWH), and of average hourly earnings (AHE) within the same industry. The standard errors of differences between estimates in two non-overlapping industries are calculated as: S difference = ^js 2 X + s^ since the two estimates are independent. The errors are presented as relative standard errors (standard error divided by the estimate and expressed as a percent). Multiplying the relative standard error by its estimated value gives the estimate of the standard error. Suppose that the level of all employees for financial activities in a given month is estimated at 7,819,000. The approximate relative standard error of this estimate (0 4 percent) is provided in table 2-E. A 90-percent confidence interval would then be the interval: 7,819,000 +/- (1.645*.004*7,819,000) - 7 :,819,000 +/-51,449 = 7,767,551 to 7,870,449 Illustration of the use of table 2-F. Table 2-F provides a reference for the standard errors of 1-, 3-, and 12-monih changes in AE, AWH, and AHE. The errors are presented as standard errors of the changes. Suppose that the over-the-month change in AHE from January to February in coal mining is $0.11. The standar d error for a 1 -month change for coal mining from the table is $0.22. The interval estimate of the over-the-month change in AHE that will include the true over-the-month. change with 90-percent confidence is calculated as: $0.11 +/-(1.645 * $0.22) = $0.11+/- $0.36 = -$0.25 to $0.47 The true value of the over-the-month change is in the interval -$0.25 to $0.47. Because this interval includes $0.00 (no change), the change of $0.11 shown is not significant at the 90-percent confidence level. Alternatively, the estimated change of $0.11 does not exceed $0.36 (1.645 * $0.22); therefore, one could conclude from these data that the change is not significant at the 90-percent confidence level. STATISTICS FOR STATES, AREAS, AND DIVISIONS (Tables B-7, B-14, B-15, B-19, and B-20) As explained earlier, State agencies in cooperation with BLS collect and prepare State, area, and division employment, hours, and earnings data. These statistics are based on the same establishment reports used by BLS. However, BLS uses the full CES sample to produce monthly national employment estimates, while each State agency uses its portion of the sample to independently develop a State employment estimate. The CES area statistics relate to metropolitan areas and divisions. Definitions for all areas are published each year in the issue of Employment and Earnings that contains State and area annual averages (usually the May issue). Changes in definitions are noted as they occur. Estimates for States and areas are produced using two methods. The majority of State and area estimates are produced using direct sample-based estimation. However, published area and industry combinations (domains) that do not have a large enough sample to support estimation using only sample responses are estimated by using a small-domain model. Small-domain model The small-domain model consists of a weighted sum of three different relative over-the-month change estimates, L x, L 2 > and L 3. These three relative over-the-month change estimates are then weighted based on the variance of each of the three estimates. The larger the variance of each L k estimate relative to the other L^ variances, the smaller the weight. The resulting estimate of current-month employment Y iat is defined as: where: hat = (^iat,l^iat,l + W iat,2^iat,2 + ^iat,3^iat,3 )?ia,t-\ Y iat = current-month t employment estimate for domain ia defined by the intersection of industry i and area a; L iat l = current-month relative over-the-month change estimate based on available sample responses for domain ia; W iat X = current-month weight assigned to L iat j based on the variances of L iat^, L iat l, and L iat^ (The weights W iat 2 and W i(lt 3 are defined similarly.); L iat 2 = current-month relative over-the-month change estimate based on time series forecasts using historical universe employment counts for domain ia. (These historical universe employment counts are available from January 1990 to 12 months prior to the current month t.); L iat^3 = current-month relative over-the-month change estimate based on a synthetic estimate of the relative change that uses all sample responses in the State that includes area a, for industry i; and ia,t \ = previous-month employment estimate for domain ia from the small-domain model.

224 It is possible that for a given industry i and area a, one or even two of the inputs L iat k to the model are assigned weights of 0. The reasons for assigning a weight of 0 to a model input are due to concerns regarding the stability of the inputs. For example, if L iat \ or L iat 3 has five or fewer responses, then it is assigned a weight of 0. If L iat 2 exhibits an unstable variance or has an extremely poor model fit, then it may also be assigned a weight of 0. In these cases, the small-domain model estimate may be based on only one or two of the three described inputs. Sampling errors are not applicable to the estimates made using the small-domain models. The measure available to judge the reliability of these modeled estimates is their performance over past time periods compared with the universe values for those time periods. These measures are useful; however, it is not certain that the past performance of the modeled estimates accurately reflects their current performance. It should also be noted that extremely small estimates of 2,000 employees or less are potentially subject to large percentage revisions that are caused by occurrences such as the relocation of one or two businesses or a change in the activities of one or two businesses. These are noneconomic classification changes that relate to the activity or location of businesses and will be present for sample-based estimates as well as the model-based estimates. Error measures for State and area estimates are available on the BLS Web site at 790stderr.htm. Caution in aggregating State data. The national estimation procedures used by BLS are designed to produce accurate national data by detailed industry; correspondingly, the State estimation procedures are designed to produce accurate data for each individual State. State estimates are not forced to sum to national totals nor vice versa. Because each State series is subject to larger sampling and nonsampling errors than the national series, summing them cumulates individual State level errors and can cause distortion at an aggregate level. This has been a particular problem at turning points in the U.S. economy, when the majority of the individual State errors tend to be in the same direction. Due to these statistical limitations, the Bureau does not compile or publish a "sum-of-states" employment series. Additionally, BLS cautions users that such a series is subject to a relatively large and volatile error structure, particularly at turning points.

225 Table 2-E. Relative standard errors for first-closing estimates of employment, hours, and earnings in selected industries 1 (Percent) Relative standard error Industry All employees Average weekly hours Average hourly earnings Total nonfarm Total private Goods-producing. Natural resources and mining... Logging Mining Oil and gas extraction Mining, except oil and gas... Coal mining Support activities lor mining. Construction Construction of buildings Residential building Nonresidential building Heavy and civil engineering construction Specialty trade contractors Residential specialty trade contractors Nonresidential specialty trade contractors. Manufacturing. Durable goods Wood products Nonmetallic mineral products Primary metals Fabricated metal products Machinery Computer and electronic products Computer and peripheral equipment Communications equipment Semiconductors and electronic components. Electronic instruments Electrical equipment and appliances Transportation equipment Motor vehicles and parts Furniture and related products Miscellaneous manufacturing Nondurable goods Food manufacturing Beverages and tobacco products Textile mills Textile product mills Apparel. Leather and allied products Paper and paper products Printing and related support activities. Petroleum and coal products Chemicals Plastics and rubber products Service-providing Private service-providing. Trade, transportation, and utilities Wholesale trade Durable goods Nondurable goods Electronic markets and agents and brokers 0.1 ( 2 ) ( 2 ) ( 3 ) ( 3 ) ( 3 ) ( 3 ) ( 2 ) ( 2 )

226 Table 2-E. Relative standard errors for first-closing estimates of employment, hours, and earnings in selected industries 1 Continued (Percent) Industry Retail trade Motor vehicle and parts dealers Automobile dealers Furniture and home furnishings stores Electronics and appliance stores Building material and garden supply stores Food and beverage stores Health and personal care stores Gasoline stations Clothing and clothing accessories stores Sporting goods, hobby, book, and music stores. General merchandise stores Department stores Miscellaneous store retailers Nonstore retailers Transportation and warehousing Air transportation Rail transportation Water transportation Truck transportation Transit and ground passenger transportation. Pipeline transportation Scenic and sightseeing transportation Support activities for transportation Couriers and messengers Warehousing and storage Utilities. Information Publishing industries, except Internet Motion picture and sound recording industries. Broadcasting, except Internet Internet publishing and broadcasting Telecommunications ISPs, search portals, and data processing Other information services Financial activities Finance and insurance Monetary authorities - central bank Credit intermediation and related activities Depository credit intermediation Commercial banking Securities, commodity contracts, investments. Insurance carriers and related activities Funds, trusts, and other financial vehicles... Real estate and rental and leasing Real estate Rental and leasing services Lessors of nonfinancial intangible assets Professional and business services Professional and technical services Legal services Accounting and bookkeeping services Architectural and engineering services Computer systems design and related services. Management and technical consulting services. Management of companies and enterprises Relative standard error iployees Average weekly hours Average hourly ( 3 ) ( 3 )

227 Table 2-E. Relative standard errors for first-closing estimates of employment, hours, and earnings in selected industries 1 Continued (Percent) Industry Relative standard error All employees Average weekly hours Average hourly earnings Administrative and waste services Administrative and support services Employment services Temporary help services Business support services Services to buildings and dwellings Waste management and remediation services Education and health services Educational services Health care and social assistance Health care Ambulatory health care services Offices of physicians Outpatient care centers Home health care services Hospitals Nursing and residential care facilities Nursing care facilities Social assistance Child day care services Leisure and hospitality Arts, entertainment, and recreation Performing arts and spectator sports Museums, historical sites, zoos, and parks Amusements, gambling, and recreation Accommodations and food services Accommodations Food services and drinking places Other services Repair and maintenance Personal and laundry services Membership associations and organizations Estimates of variance are not available for government sectc s due to lack of historical probability-based estimates. 2 Hours and earnings estimates are not published, 3 Estimates are not available as a result of confidentiality standards.

228 Table 2-F. Standard errors for change in levels of first-closing estimates of employment, hours, and earnings in selected industries 1 Industry Standard error Standard error Standard error 1 -month change 3-month change 12-month change All Average Average All Average Average Ail Average Average em- weekly hourly em- weekly hourly em- weekly hourly ployees hours earnings ployees hours earnings ployees hours earnings Total nonfarm 62,800 ( 2 ) ( 2 ) 100,900 ( 2 ) ( 2 ) 207,400 ( 2 ) ( 2 ) Total private 55, , , Goods-producing 18, , , Natural resources and mining 3, , , Logging , , Mining 3, , , Oil and gas extraction 1, , , Mining, except oil and gas 1, , , Coal mining , , Support activities for mining 2, , , Construction 14, , , Construction of buildings 5, , , Residential building 4, , , Nonresidential building 4, , , Heavy and civil engineering construction.. 4, , , Specialty trade contractors 12, , , Residential specialty trade contractors.. 8,000 ( 2 ) ( 2 ) 11,900 ( 2 ) ( 2 ) 19,100 ( 2 ) ( 2 ) Nonresidential specialty trade contractors 8,500 ( 2 ) ( 2 ) 13,800 ( 2 ) ( 2 ) 27,500 ( 2 ) ( 2 ) Manufacturing 11, , , Durable goods 8, , , Wood products 2, , , Nonmetallic mineral products 2, , , Primary metals 1, , , Fabricated metal products 3, , , Machinery 2, , , Computer and electronic products 2, , , Computer and peripheral equipment , , Communications equipment , , Semiconductors and electronic components 1, , , Electronic instruments 1, , , Electrical equipment and appliances 1, , , Transportation equipment 5, , , Motor vehicles and parts 4, , , Furniture and related products 2, , , Miscellaneous manufacturing 2, , , Nondurable goods 7, , , Food manufacturing 5, , , Beverages and tobacco products 2, , , Textile mills , , Textile product mills 1, , , Apparel 2, , , Leather and allied products , Paper and paper products 1, , , Printing and related support activities 2, , , Petroleum and coal products , , Chemicals 2, , , Plastics and rubber products 2, , , Service-providing 59,700 ( 2 ) ( 2 ) 98,000 ( 2 ) ( 2 ) 196,700 ( 2 ) ( 2 ) Private service-providing 51, , ,

229 Table 2-F. Standard errors for change in levels of first-closing estimates of employment, hours, and earnings in selected industries 1 Continued Industry Standard error Standard error Standard error 1 -month change 3-month change 12-month change All Average Average All Average Average All Average Average em- weekly hourly em- weekly hourly em- weekly hourly ployees hours earnings ployees hours earnings ployees hours earnings Trade, transportation, and utilities 21, , , Wholesale trade 9, , , Durable goods 5, , , Nondurable goods. 5, , , Electronic markets and agents and brokers 2,900 o.3o : , , Retail trade 18, , , Motor vehicle and parts dealers 3, , , Automobile dealers 2, I , , Furniture and home furnishings stores 2, , , Electronics and appliance stores 3, , , Building material and garden supply stores 4, , , Food and beverage stores 6, , , Health and personal care stores 4, , , Gasoline stations 3, , , Clothing and clothing accessories stores.. 6, , , Sporting goods, hobby, book, and music stores 4, , , General merchandise stores 9, , , Department stores 7, , , Miscellaneous store retailers 3, , , Nonstore retailers 3, , , Transportation and warehousing 10, , , Air transportation 2, , , Rail transportation 1,300 (3) 0 2,100 ( 3 ) ( 3 ) 2,900 ( 3 ) ( 3 ) Water transportation 1, , , Truck transportation 4, , , Transit and ground passenger transportation 3, , , Pipeline transportation , Scenic and sightseeing transportation 1, , , Support activities for transportation 3, , , Couriers and messengers 3, , , Warehousing and storage 3, : , , Utilities 1, , , Information 6, , , Publishing industries, except Internet 2, , , Motion picture and sound recording industries 5, , , Broadcasting, except Internet 1, , , Internet publishing and broadcasting , Telecommunications 3, , , ISPs, search portals, and data processing. 2, , , Other information services , Financial activities 10, , , Finance and insurance 7, , , Monetary authorities - central bank Credit intermediation and related activities 5, , , Depository credit intermediation 2, , , Commercial banking 2, , , Securities, commodity contracts, investments 2, , ,

230 Table 2-F. Standard errors for change in levels of first-closing estimates of employment, hours, and earnings in selected industries 1 Continued Industry Standard error Standard error Standard error 1 -month change 3-month change 12-month change All Average Average All Average Average All Average Average em- weekly hourly em- weekly hourly em- weekly hourly ployees hours earnings ployees hours earnings ployees hours earnings Financial activities Continued Insurance carriers and related activities... 3, , , Funds, trusts, and other financial vehicles , , Real estate and rental and leasing 6, , , Real estate 5, , , ,22 Rental and leasing services 4, , , Lessors of nonfinancial intangible assets , ,46 Professional and business services 26, , , Professional and technical services 11, , , Legal services 2, , , Accounting and bookkeeping services.. 7, , , Architectural and engineering services.. 3, , , Computer systems design and related services 4, , , Management and technical consulting services 3, , , Management of companies and enterprises. 4, , , Administrative and waste services 23, , , Administrative and support services 22, , , Employment services 21, , , Temporary help services 16, , , Business support services 4, , , Services to buildings and dwellings 6, , , Waste management and remediation services 3, , , Education and health services 17, , , Educational services 13, , , Health care and social assistance 11, , , Health care 8, , , Ambulatory health care services 7, , , Offices of physicians 3, , , Outpatient care centers 2, , , Home health care services 3, , , Hospitals 3, , , Nursing and residential care facilities 3, , , Nursing care facilities 2, , , Social assistance 5, , , Child day care services 3, , , Leisure and hospitality 17, , , Arts, entertainment, and recreation 10, , , Performing arts and spectator sports 5, , , Museums, historical sites, zoos, and parks 1, , , Amusements, gambling, and recreation... 8, , , Accommodations and food services 14, , , Accommodations 6, , , Food services and drinking places 13, , , Other services 20, , , Repair and maintenance 3, , , Personal and laundry services 4, , , Membership associations and organizations 19, , , Estimates of variance are not available for government sectors due to lack of historical probability-based estimates. 2 Hours and earnings estimates are not published, 3 Estimates are not available as a result of confidentiality standards.

231 Region, State, Area, and! Division Labor Force Data ("C" tables) FEDERAL-STATE COOPERATIVE PROGRAM Labor force and unemployment estimates for States, labor market areas (LMAs), and other areas covered under Federal assistance programs are developed by State Workforce Agencies under a Federal-State cooperative program. The local unemployment estimates, which derive from standard - ized procedures developed by BLS, are the basis for determining eligibility of an area for benefits under Federal pro - grams such as the Workforce Investment Act. Annual average data for the States and 375 areas shown in table C-3 are published in Employment and Earnings (usually the May issue). For regions, States, selected metropolitan areas, and central cities, annual average data classified by selected demographic, social, and economic characteristics are published in the BLS bulletin, Geographic Profile of Employment and Unemployment. Labor force estimates for counties, cities, and other small areas have been prepared for administration of various Federal economic assistance programs and are available on the Internet at or by subscription by calling ESTIMATING METHODS Monthly labor force, employment, and unemployment estimates are prepared for the 50 States, the District of Columbia, Puerto Rico, and over 7,000 areas, including nearly 2,400 LMAs, all counties, and cities with a population of25,00 ) or more. Regional aggregations are derived by summing the division estimates. The estimation methods are described below for States (and the District of Columbia) and for substate areas. At the sub-lma (county and city) leve, estimates are prepared using disaggregation techniques based on decennial and annual population estimates and current unemployment insurance data. A more detailed description of the estimation procedure is contained in the BLS document, Manual for Developing Local Area Unemployment Statistics. Estimates for States For all States and the District of Columbia, the Los Angeles- Long Beach-Glendale metropolitan division, New York City, and the respective balances of State, models based on a "signal-plus-noise" approach are used to develop employment and unemployment estimates. The model of the signal is a time series model of the true labor force which consists of three components: A variable coefficient regression, a flexible trend, and aflexibleseasonal component. The regression techniques are based on historical and current relationships found within each State's economy as reflected in the different sources of data that are available for each State the Current Population Survey (CPS), the Current Employment Statistics (CES) survey, and the UI system. The noise component of the models explicitly accounts for autocorrelation in the CPS sampling error and changes in the average magnitude of the error. In addition, the models can identify and remove the effects of outliers in the historical CPS series. While all the State models have important components in common, they differ somewhat from one another to better reflect individual State labor force characteristics. Seasonal adjustment occurs within the model structure through the removal of the seasonal component. The models also produce reliability measures on the adjusted and unadjusted series, and on over-the-month change. The Redesign bivariate models incorporate a major change in the approach to benchmarking and the benchmarking process. Rather than continue with an annual average State benchmark applied retrospectively that reintroduces sampling error to the historical monthly estimates, the Redesign approach uses a reliable real-time monthly national benchmark for controlling current State model estimates of employment and unemployment. In this process, benchmarking is part of the monthly State model estimation process. Under real-time benchmarking, a tiered approach to estimation is used. Model-based estimates are developed for the 9 Census divisions that geographically exhaust the Nation using univariate signal-plus-noise models. The division models are similar to the State models, but do not use unemployment insurance claims or nonfarm payroll employment as variables. The division estimates are benchmarked to the national levels of employment and unemployment on a monthly basis. The benchmarked division model estimate is then used as the benchmark for the States within the division. The distribution of the monthly benchmark adjustment to the States is based on each State's monthly model estimate. In this manner, the monthly State employment and unemployment estimates will add to the national levels. Estimates for substate labor market areas As noted, monthly labor force estimates for two large substate areas New York City and the Los Angeles-Long Beach-Glendale, CA metropolitan division and the respective balances of New York and California are developed using bivariate signal-plus-noise models. Signal-plus-noise models also have been developed for six additional substate areas and their State balances. The areas are: the Chicago- Naperville-Joliet, IL metropolitan division; the Cleveland-

232 Elyria-Mentor, OH metropolitan area; the Detroit-Warren- Livonia, MI metropolitan area; the Miami-Miami Beach- Kendall, FL metropolitan division; the New Orleans-Metairie- Kenner, LA metropolitan area; and the Seattle-Bellevue- Everett, WA metropolitan division. As with the Redesign State and division models, these area models are based on the classical decomposition of a time series into trend, seasonal, and irregular components. A component to identify and remove the CPS sampling error also is included. Area models, like the division models, are univariate in design in that only the historical relationship of the inputs is considered UI claims and CES inputs are not used each month in the estimation process. Area and balance of State models are controlled directly to the State totals, which are themselves controlled to the national CPS via the Census division models. Estimates for the nearly 2,400 remaining LMAs are prepared through indirect estimation techniques, described below. The LAUS Handbook method is an effort to estimate unemployment for an area, using available information without the expense of expanding a labor force survey like the CPS. The Handbook presents a series of estimating "building blocks," in which categories of unemployed workers are classified by their previous status. Two broad categories of unemployed persons are: (1) Those who were last employed in industries covered by State UI laws, and (2) those who either entered the labor force for the first time or reentered after a period of separation. Handbook inputs were updated using the Census 2000 results and other improvements to Handbook estimation were implemented with January 2005 estimates. Employment. The total employment estimate is based on data from several sources. The primary source for most metropolitan areas (MAs) is the Federal-State CES survey. The CES is designed to produce estimates of the total number of employees on payrolls in nonfarm industries for the particular area. In small labor market areas and the remainder of the MAs, the establishment employment data come from the Quarterly Census of Employment and Wages (ES-202 Report). These "place-of-work" employment estimates must be adjusted to a place-of-residence basis, as in the CPS. Estimated adjustment factors have been developed using employment relationships which existed at the time of the most recent decennial census. The adjustment approach implemented in January 2005 is more dynamic than the previous one and incorporates commuting to nearby labor market areas. These factors are applied to the place-of-work employment estimates for the current period to obtain adjusted employment estimates, to which are added synthetically developed estimates for employment not represented in the establishment series agricultural workers, nonfarm self-employed and unpaid family workers, and private household workers. Unemployment. The estimate of unemployment is an aggregate of the estimates for each of the two building-block categories. The "covered" category further consists of two unemployed worker groups: (1) Those who are currently receiving UI benefits and (2) those who have exhausted their benefits. Only the number of those currently collecting benefits is obtained directly from an actual count of UI claimants for the reference week. The estimate of persons who have exhausted their benefits is based upon the number actually exhausting benefits in previous periods "survived" using a conditional probability approach based on CPS data. The second category, "new entrants and reentrants into the labor force," cannot be estimated directly from UI statistics, because unemployment for these persons is not immediately preceded by the period of employment required to receive UI benefits. In addition, there is no uniform source of new entrants and reentrants data for States available at the LMA level; the only existing source available is from the CPS at the State level. Separate estimates for new entrants and for reentrants are derived from econometric models based on current and historical State entrants data from the CPS. These model estimates are then allocated to all LMAs based on the age distribution of the population of each LMA. For new entrants, the area's proportion of the year-old population group to the State year-old population total is used, and for reentrants, the Handbook area's proportion of the 20 years and older population to the State total 20 years and older population is used. Substate adjustment for consistency and additivity. Each month, Handbook estimates are prepared for labor market areas that exhaust the entire State area. To obtain a labor force estimate for a given area, a "Handbook share" is computed for that area which is defined as the ratio of that area's Handbook estimates of employment and unemployment to the sum of the Handbook estimates of employment and unemployment for all LMAs in the State. These ratios are then multiplied by the current statewide estimate for employment and unemployment to produce the final adjusted LMA estimates. Estimates for parts of LMAs Current labor force estimates at the sub-lma level are required by several Federal programs. Disaggregation techniques are used to obtain current estimates of employment and unemployment for counties within multicounty LMAs and cities, towns, and townships within counties. Two alternative methods are used to disaggregate the LMA estimates. The population-claims method is the preferred technique. If residence-based UI claims data are available for the subareas within the labor market area, the ratio of claims in the subarea to the total number of claims within the LMA is used to disaggregate the estimate of experienced unemployed to the subarea level. To ensure the quality of the claims data used in this technique, claimant records are processed through a residency assignment system that verifies and/or corrects

233 residence addresses and assigns the associated residency codes. This provides a more accurate count of claims by city. The estimates of unemployed entrants are allocated based on the latest available census distribution of the adult and teenage population groups. Employment is disaggregated using decennial census employment-population ratio s updated by current population estimates. Estimates for all disaggregated counties and New England cities and towns are developed using this method. If the necessary UI claims data are not available, the census-share method is used. This method uses each subarea's decennial census share of total LMA employment and unemployment., respectively, in order to disaggregate employment and unemployment. Very few States will be using this method for data after. Annual activities Once each year, labor force estimates are revised to reflect updated input data and new U.S. Census Bureau population controls. As part of this procedure, all of the State ai d substate models are reviewed, revised as necessary, and then reestimated; this reestimation is called "smoothing." When new population controls are available from the Bureau of the Census, typically in January, CPS estimates for all States, the District of Columbia, New York City; the Chicago-Naperville-Joliet, IL metropolitan division; Cleveland-Elyria-Mentor, OH metropolitan area; Detroit- Warren-Livonia, MI metropolitan area; Los Angeles-Long Beach-Glendale, CA metropolitan division; Miami-Miami Beach-Kendall, FL metropolitan division; New Orleans- Metairie-Kenner, LA metropolitan area; and, the Seattle- Bellevue-Everett, WA metropolitan division are adjusted to these controls. Additionally, the time series regression models for the States and model-based areas are reestimated based on the latest input data. Other substate estimates for previous years are also revised on an annual basis. The updates incorporate any changes in the inputs, such as revisions to establishmentbased employment estimates or claims data and updated historical relationships. The revised estimates are then readjusted to the latest statewide estimates of employment and unemployment.

234 Seasonal Adjustment Over the course of a year, the size of the Nation's labor force, the levels of employment and unemployment, and other measures of labor market activity undergo sharp fluctuations due to such seasonal events as changes in weather, reduced or expanded production, harvests, major holidays, and the opening and closing of schools. Because these seasonal events follow a more or less regular pattern each year, their influence on statistical trends can be eliminated by adjusting the statistics from month to month. These adjustments make it easier to observe the cyclical and other nonseasonal movements in the series. Seasonally adjusted series for selected labor force and establishment-based data are published monthly in Employment and Earnings. Household data Beginning in January 2003, BLS started using the X-12- ARIMA (Auto-Regressive Integrated Moving Average) seasonal adjustment program to seasonally adjust national labor force data from the Current Population Survey (CPS), or household survey. This program replaced the X-11ARIMA program which had been used since January For a detailed description of the X-12-ARIMA program and its features, see D.F. Findley, B.C. Monsell, W.R. Bell, M.C. Otto, andb.c. Chen, "New Capabilities and Methods of the X-12- ARIMA Seasonal Adjustment Program," Journal of Business and Economic Statistics, April 1998, Vol. 16, No. 2, pp See "Revision of Seasonally AdjustedLabor Force Series in 2003," in the February 2003 issue of this publication for a discussion of the introduction of the use of X-12 ARIMA for seasonal adjustment of the labor force data and the effects that it had on the data. Beginning in January, BLS converted to the use of concurrent seasonal adjustment to produce seasonally adjusted labor force estimates from the household survey. Concurrent seasonal adjustment uses all available monthly estimates, including those for the current month, in developing seasonal factors. Previously, seasonal factors for the CPS data had been projected twice a year. As a result of this change in methodology, BLS no longer publishes seasonal factors for the labor force data. For more information on the adoption of concurrent seasonal adjustment for the labor force data, see "Revision of Seasonally Adjusted Labor Force Series in," in the January issue of this publication available on the Internet at cps/cpsrs.pdf. Revisions of historical data, usually for the most recent 5 years, are made only at the beginning of each calendar year. However, as a result of the revisions to the estimates for based on 1980 census population counts, revisions to seasonally adjusted series in early 1982 were carried back to In 1994, data were revised only for that year because of the major survey redesign and the introduction of 1990 census-based population controls, adjusted for the estimated undercount, into the Current Population Survey. In 1996, data also were revised to incorporate these 1990 censusbased population controls and seasonally adjusted series were revised back to Subsequent revisions were carried back only to 1994 through 1998, when the standard 5-year revision period was reinstated. All labor force and unemployment rate statistics, as well as the major employment and unemployment estimates, are computed by aggregating independently adjusted series. For example, for each of the major labor force components employment, and unemployment data for four sex-age groups (men and women under and over 20 years of age) are separately adjusted for seasonal variation and are then added to derive seasonally adjusted total figures. The seasonally adjusted figure for the labor force is a sum of four seasonally adjusted civilian employment components and four seasonally adjusted unemployment components. The total for unemployment is the sum of the four unemployment components, and the unemployment rate is derived by dividing the resulting estimate of total unemployment by the estimate of the labor force. Because of the independent seasonal adjustment of various series, components will not necessarily add to totals. Each January issue (March issue in 1996 and February issue in 2003) of Employment and Earnings contains revised seasonally adjusted data for selected labor force series based on the experience through December and a description of the current seasonal adjustment procedure. National establishment data BLS also uses the X-12-ARIMA seasonal adjustment program to seasonally adjust national establishment-based employment, hours, and earnings series derived from the Current Employment Statistics (CES) program. (Use of X-12 ARIMA to seasonally adjust the CES data began in June 1996, with the release of the March 1995 benchmark revisions.) Individual series are seasonally adjusted using either a multiplicative or an additive model. For employment, seasonal adjustment factors are directly applied to the component levels. Individual 3-digit NAICS levels are seasonally adjusted, and higher-level aggregates are formed by the summation of these components. Seasonally adjusted totals for hours and earnings are obtained by taking weighted averages of the seasonally adjusted data for the component series. Revised seasonally adjusted national establishmentbased series based on the experience through January 2005 and a detailed description of the current seasonal adjustment

235 procedure appear in the February 2005 issue of Employment and Earnings. Concurrent seasonal adjustment Beginning in June 200 $ with the May 2003 first preliminary estimates, BLS began computing seasonal factors concurrently with the monthly estimate production. Previously, the factors were forecasted twice a year. Concurrent seasonal adjustment is expected to provide a more accurate seasonal adjustment, and smaller revisions from the first preliminary estimates to the final benchmarked estimates, than the semiannual updates. As i result of the adoption of concurrent seasonal adjustment, the CES program has discontinued the publication of projected seasonal factors. Additive and multiplicative models. Prior to the March 2002 benchmark release in June 2003, all CES series were adjusted using multiplicative seasonal adjustment models. Althoug i the X-12-ARIMA seasonal adjustment program provides for either an additive or a multiplicative adjustment depending on which model best fits the individual series, the previous CES processing system was unable to utilize additive seasonal adjustments. Anew processing system, introduced simultaneously with the conversion to NAICS in June 2003, is able to utilize both additive and multiplicative adjustments. The article, "BLS National Establishment Estimates Revise! to Incorporate March Benchmarks" published in the February 2005 issue of this publication contains a list of which series are adjusted with additive seasonal adjustment models and which series are adjusted with multiplicative models. The article also lists which series are subject to the calendar-effects modeling described below. Variable survey intervals. Beginning with the release of th e 1995 benchmark, BLS refined the seasonal adjustment procedures to control for survey interval variations, sometimes referred to as the 4- versus 5-week effect. Although the CES survey is referenced to a consistent concept the pay period including the 12th of each month inconsistencies arise because there are sometimes 4 and sometimes 5 weeks between the week including the 12th in a given pair of months. In highly seasonal industries, these variations can be an important determinant of the magnitude of seasonal hires or layoffs that have occurred at the time the survey is taken, thereby complicating seasonal adjustment. Standard seasonal adjustment methodology relies heavily on the experience of the most recent 3 years to determine the expected seasonal change in employment for each month of the current year. Prior to the implementation of the adjustment, the procedure did not distinguish between 4- and 5-week survey intervals and the accuracy of the seasonal expectation depended in large measure on how well the current year's survey interval corresponded with those from the previous 3 years. All else being the same, the greatest potential for distortion occurred when the current month being estimated had a 5-week interval but the 3 years preceding it were all 4-week intervals, or conversely, when the current month had a 4-week interval but the 3 years preceding it were all 5-week intervals. BLS uses REGARIMA (regression with autocorrelated errors) modeling to identify the estimated size and significance of the calendar effect for each published series. REGARIMA combines standard regression analysis, which measures correlation among two or more variables, with ARIMA modeling, which describes and predicts the behavior of data series based on its own past history. For many economic time series, including nonfarm payroll employment, observations are autocorrelated over time. That is, each month's value is significantly dependent on the observations that precede it; these series, thus, usually can be successfully fit using ARIMA models. If autocorrelated time series are modeled through regression analysis alone, the measured relationships among other variables of interest may be distorted due to the influence of the autocorrelation. Thus, the REGARIMA technique is appropriate to measuring relationships among variables of interest in series that exhibit autocorrelation, such as nonfarm payroll employment. In this application, the correlations of interest are those between employment levels in individual calendar months and the lengths of the survey intervals for those months. The REGARIMA models evaluate the variation in employment levels attributable to 11 separate survey interval variables, one specified for each month, except March. March is excluded because there is almost always 4 weeks between the February and March surveys. Models for individual basic series are fitted with the most recent 10 years of data available, the standard time span used for CES seasonal adjustment. The REGARIMA procedure yields regression coefficients for each of the 11 months specified in the model. These coefficients provide estimates of the strength of the relationship between employment levels and the number of weeks between surveys for the 11 modeled months. The X-12-ARIMA software also produces diagnostic statistics that permit the assessment of the statistical significance of the regression coefficients, and all series are reviewed for model adequacy. Because the 11 coefficients derived from the REGARIMA models provide an estimate of the magnitude of variation in employment levels associated with the length of the survey interval, these coefficients are used to adjust the CES data to remove the calendar effect. These "filtered" series then are seasonally adjusted using the standard X-12-ARIMA software previously used. For a few series, REGARIMA models did not fit well; these series are seasonally adjusted with the X-12 software but without the interval-effect adjustment. There are several additional special effects modeled through the REGARIMA process which are described below.

236 Construction series. BLS continues its special treatment in seasonally adjusting the construction industry series, which began with the 1996 benchmark revision. In the application of the interval-effect modeling process to the construction series, there initially was difficulty in accurately identifying and measuring the effect because of the strong influence of variable weather patterns on employment movements in the industry. Further research allowed BLS to incorporate interval-effect modeling for the construction industry by disaggregating the construction series into its finer industry and geographic estimating cells and tightening outlier designation parameters. This process allowed a more precise identification of weather-related outliers that had masked the interval effect and clouded the seasonal adjustment patterns in general. With these outliers removed, interval-effect modeling became feasible. The result is a seasonally adjusted series for construction that is improved because it is controlled for two potential distortions, unusual weather events and the 4- versus 5-week effect. Floating holidays. BLS also makes special adjustments for average weekly hours and average weekly overtime series to account for the presence or absence of religious holidays in the April survey reference period and the occurrence of Labor Day in the September reference period. Local government series. A special adjustment also is made in the local government, excluding education series in November each year to account for variations in employment due to the presence or absence of poll workers. Refinements in hours and earnings seasonal adjustment With the release of the 1997 benchmark, BLS implemented refinements to the seasonal adjustment process for the hours and earnings series to correct for distortions related to the method of accounting for the varying length of payroll periods across months. There is a significant correlation between over-the-month changes in both the average weekly hours and the average hourly earnings series and the number of weekdays in a month, resulting in noneconomic fluctuations in these two series. Both series show more growth in "short" months (20 or 21 weekdays) than in "long" months (22 or 23 weekdays). The effect is stronger for the hours than for the earnings series. The calendar effect is traceable to response and processing errors associated with converting payroll and hours information from sample respondents with semimonthly or monthly pay periods to a weekly equivalent. The response error comes from sample respondents reporting a fixed number of total hours for workers regardless of the length of the reference month, while the CES conversion process assumes that the hours reporting will be variable. Most likely, a constant level of hours is reported when employees are salaried rather than paid by the hour, because employers are less likely to keep actual detailed hours records for such employees. This gap in information causes artificial peaks in the hours series in shorter months that are reversed in longer months. The processing error occurs when respondents with salaried workers report hours correctly (vary them according to the length of the month), which than dictates that different conversion factors be applied to payroll and hours. The CES processing system uses the hours conversion factor for both fields, resulting in peaks in the hourly earnings series in short months and reversals in long months. The series to which the length-of-pay-period adjustment is applied are not subject to the 4- versus 5-week adjustment, because the modeling cannot support the number of variables that would be required in the regression equation to make both adjustments. State establishment data Seasonally adjusted nonfarm payroll employment data by selected industry supersectors for all States and the District of Columbia are presented in table B-7 of this publication. As with the national establishment data, the State establishment data are seasonally adjusted with the X-l 2- ARIMA seasonal adjustment program. Seasonal adjustment factors are applied directly to the employment estimates at the supersector level and then aggregated to the State totals for most States. For a few States that do not have many publishable seasonally adjusted supersectors, however, total nonfarm data are seasonally adjusted directly at the aggregate level. The recomputation of seasonal factors and historical revisions are made coincident with the annual benchmark adjustments. Region and State labor force data Beginning in 1992, BLS introduced publication of seasonally adjusted labor force data for the census regions and divisions, the 50 States, the District of Columbia, and Puerto Rico (tables C-l and C-2). Beginning in 2005, labor force estimates for census regions are derived by summing the component division estimates of employment and unemployment and then calculating the unemployment rate. Since 2005, a unified model-based approach has been used at the census division and State level to simultaneously remove the effects of sampling error and seasonality to provide seasonally adjusted estimates for employment and unemployment levels directly from the model, along with associated error measures. Labor force levels and unemployment rates are calculated from these two estimates. Prior to 2005, a two-step approach was used. In the first step, time-series models estimated and removed the effects of sampling error from the series. In the second step, the error-corrected series were seasonally adjusted using the latest available version of X-l 1, initially X-l 1ARIMA, and later the X-12-ARIMA seasonal adjustment program. Usually, historical data for the most recent 5 years are revised near the beginning of each calendar year, coincident with the release of January estimates.