U.S. Department of Labor Bureau of Labor Statistics October Third quarter 2000 averages for household survey data

Transcription

1 U.S. Department of Labor Bureau of Labor Statistics October In this issue: Third quarter averages for household survey data

2 U.S. DEPARTMENT OF LABOR Alexis M. Herman, Secretary BUREAU Ol" LABOR STATISTICS Katharine G. Abraham, 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 Bureau of the Census (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 $40 domestic and $50 foreign. Single copy $16 domestic and $20 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) Internet: National establishment data: Telephone: (202) CESI b 1 s.gov Internet: State and area establishment data: Telephone: (202) Internet: Region, State, and area labor force data: Telephone: (202) Lauslnfo@bls.gov Internet: Periodicals postage paid at Washington, DC, and at additional mailing addresses. Information in this publication will be made available r> 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. October Vol. 47 No. 10 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 Lmployee absences Quarterly averages: Seasonally adjusted data, persons of Hispanic origin, Vietnamera veterans and nonveterans, and weekly earnings data Establishment data National annual averages: Industry divisions (preliminary) Industry detail Women employees National data revised to reflect new benchmarks and new seasonal adjustment factors State and area annual averages Area definitions Region, State, and area labor force data Annual averages Jan. Jan. Jan. Jan. Jan. Jan. Jan., Apr.,, Oct. Jan. March, June March, June June May May May Cover Design: Keith Tapscott

3 Employment^EarnhiDS Editor John F. Stinson Jr. Design and Layout Phyllis L. Lott Irma Mayfield Contents Page List of statistical tables ii Contents to the explanatory notes and estimates of error v Employment and unemployment developments, September 1 Summary tables and charts 3 Explanatory notes and estimates of error 160 Index to statistical tables 204 Statistical tables Source Historical Seasonally adjusted Not seasonally adjusted Household data 18 Establishment data: Employment: National State Area Hours and earnings: National State and area Local area labor force data: Region State Area Household data: Quarterly averages

4 Monthly Household Data Historical Page Al. Employment status of the civilian noninstitutional population 16 years and over, 1966 to date 5 A2. Employment status of the civilian noninstitutional population 16 years and over by sex, 1988 to date 6 Seasonally Adjusted Data Employment Status A3. Employment status of the civilian noninstitutional population by sex and age 7 A4. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic origin 8 A5. Employment status of the civilian noninstitutional population 25 years and over by educational attainment 10 A6. and unemployed full and parttime workers by sex and age 11 Characteristics of the A7. persons by marital status, occupation, class of worker, and parttime status 12 A8. persons by age and sex 13 Characteristics of the A9. persons by age and sex 14 A10. s by age and sex 15 Al 1. s by occupation, industry, and selected demographic characteristics 16 A12. persons by reason for unemployment 17 A13. persons by duration of unemployment 17 Not Seasonally Adjusted Data Employment Status A14. Employment status of the civilian noninstitutional population by age, sex, and race 18 A15. Employment status of the civilian noninstitutional population by race, sex, and age 21 A16. Employment status of the civilian noninstitutional population 16 to 24 years of age by school enrollment, educational attainment, sex, race, and Hispanic origin 22 A17. Employment status of the civilian noninstitutional population 25 years and over by educational attainment, sex, race, and Hispanic origin 24 A18. and unemployed full and parttime workers by age, sex, and race 25 Characteristics of the A19. persons by occupation, sex, and age 26 A20. persons by occupation, race, and sex 27 A21. persons by industry and occupation 28 A22. persons in agriculture and nonagricultural industries by age, sex, and class of worker 29 A23. Persons at work in agriculture and nonagricultural industries by hours of work 30 A24. Persons at work 1 to 34 hours in all and nonagricultural industries by reason for working less than 35 hours and usual full or parttime status 30 A25. Persons at work in nonagricultural industries by class of worker and usual full or parttime status 31 A26. Persons at work in nonagricultural industries by age, sex, race, marital status, and usual full or parttime status.. 32 A27. Persons at work in nonfarm occupations by sex and usual full or parttime status 33 Characteristics of the A28. persons by marital status, race, age, and sex 34 A29. persons by occupation and sex 35 A30. persons by industry and sex 36 A31. persons by reason for unemployment, sex, age, and race 37 A32. persons by reason for unemployment, sex, age, and duration of unemployment 38 A33. total and fulltime workers by duration of unemployment 38 A34. persons by age, sex, race, marital status, and duration of unemployment 39 A35. persons by occupation, industry, and duration of unemployment 40 Persons Not in the Labor Force A36. Persons not in the labor force by desire and availability for work, age, and sex 40 Multiple Jobholders A37. Multiple jobholders by selected demographic and economic characteristics 41 Vietnamera Veterans and Nonveterans A38. Employment status of male Vietnamera veterans and nonveterans by age 42

5 Monthly Establishment Data Page Historical Bl. Employees on nonfarm payrolls by major industry, 1948 to date 44 B2. Average hours and earnings of production or nonsupervisory workers on private nonfarm payrolls by major industry, 1964 to date 45 Seasonally Adjusted Data Employment National States B3. Employees on nonfarm payrolls by major industry and selected component groups 48 B4. Women employees on nonfarm payrolls by major industry and manufacturing group 50 B5. Production or nonsupervisory workers on private nonfarm payrolls by major industry and manufacturing group 51 B6. Diffusion indexes of employment change 52 B7. Employees on nonfarm payrolls by State and major industry 53 Hours and Earnings National B8. Average weekly hours of production or nonsupervisory workers on private nonfarm payrolls by major industry and manufacturing group 61 B9. Indexes of aggregate weekly hours of production or nonsupervisory workers on private nonfarm payrolls by major industry and manufacturing group 62 B10. Hours of wage and salary workers on nonfarm payrolls by major industry 63 Bl 1. Average hourly and weekly earnings of production or nonsupervisory workers on private nonfarm payrolls by major industry 64 Not Seasonally Adjusted Data Employment National B12. Employees on nonfarm payrolls by detailed industry 65 Bl3. Women employees on nonfarm payrolls by major industry and manufacturing group 77 States and Areas B14. Employees on nonfarm payrolls in States and selected areas by major industry 78 Hours and Earnings National Bl5. Average hours and earnings of production or nonsupervisory workers on private nonfarm payrolls by detailed industry 96 Bl5a. Average hourly earnings in aircraft (SIC 3721) and guided missiles and space vehicles (SIC 3761) manufacturing 116 B16. Average hourly earnings, excluding overtime, of production workers on manufacturing payrolls 117 Bl7. Average hourly and weekly earnings of production or nonsupervisory workers on private nonfarm payrolls by major industry, in current and constant (1982) dollars 118 States and Areas Bl8. Average hours and earnings of production workers on manufacturing payrolls in States and selected areas 119 Monthly Regional, State, and Area Labor Force Data Seasonally Adjusted Data Cl. Labor force status by census region and division 123 C2. Labor force status by State 125 Not Seasonally Adjusted Data C3. Labor force status by State and metropolitan area 130 iii

6 Quarterly Household Data Page Seasonally Adjusted Data Employment Status Dl. Employment status of the civilian noninstitutional population by sex and age 136 D2. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic origin 137 D3. Employment status of the civilian noninstitutional population 25 years and over by educational attainment 139 D4. and unemployed full and parttime workers by sex and age 140 Characteristics of the D5. persons by marital status, occupation, class of worker, and parttime status 141 D6. persons by age and sex 142 Characteristics of the D7. persons by age and sex 143 D8. s by age and sex 144 D9. s by occupation, industry, and selected demographic characteristics 145 D10. persons by reason for unemployment 146 Dl 1. persons by duration of unemployment 146 Not Seasonally Adjusted Data Employment Status Dl2. Employment status of the civilian noninstitutional population by sex, age, race, and Hispanic origin 147 Dl3. Employment status of the Mexican, Puerto Rican, and Cubanorigin population by sex and age 148 Characteristics of the Dl4. white, black, and Hispanicorigin workers by sex, occupation, class of worker, and full or parttime status 149 Dl5. Mexican, Puerto Rican, and Cubanorigin workers by sex, occupation, class of worker, and full or parttime status 150 D16. persons by age, sex, race, and Hispanic origin 151 Characteristics of the D17. s by age, sex, race, and Hispanic origin 152 Dl8. persons by reason for unemployment, race, and Hispanic origin 153 Dl9. persons by duration of unemployment, race, and Hispanic origin 154 Weekly Earnings Data D20. Median weekly earnings of fulltime wage and salary workers by selected characteristics 155 D21. Median weekly earnings of parttime wage and salary workers by selected characteristics 156 D22. Median weekly earnings of fulltime wage and salary workers by occupation and sex 157 Vietnamera Veterans and Nonveterans Data D23. Employment status of male Vietnamera veterans and nonveterans by age 158 D24. Employment status of male Vietnamera veterans and nonveterans by age, race, and Hispanic origin 159 IV

7 Explanatory Notes and Estimates of Error Page Page Introduction 160 Relationship between the household and establishment series 160 Comparability of household data with other series 161 Comparability of payroll employment data with other series 161 Household data 162 Collection and coverage 162 Concepts and definitions 162 Historical comparability 164 Changes in concepts and methods 164 Noncomparability of labor force levels 166 Changes in the occupational and industrial classification systems 168 Sampling 168 Selection of sample areas 169 Selection of sample households 169 Rotation of sample 170 CPS sample, 1947 to present 170 Estimating methods 170 Noninterview adjustment 171 Ratio estimates 171 First stage 171 Second stage 171 Composite estimation procedure 172 Rounding of estimates 172 Reliability of the estimates 172 Nonsampling error 172 Sampling error (Revised effective Oct. ) 173 Tables 1B through 1H 173 Establishment data 180 Data collection 180 Concepts 180 Estimating methods 183 Benchmarks 183 Monthly estimation 183 Stratification 183 Link relative technique 183 Bias adjustment 183 Establishment data Continued Summary of methods table 184 Measures of error table 185 The sample 186 Design 186 Coverage 187 Reliability 187 Benchmark revision as a measure of survey error 187 Estimated standard errors for employment, hours, and earnings 187 Standard errors for differences between industries and times 187 Revisions between preliminary and final data 188 CES sample redesign 188 Original sample design limitations 188 The new CES sample design 188 Frame and sample selection 188 Sample enrollment activities 194 Estimation 194 Benchmarking 195 Business birth and death estimation 195 Difference between the birth/death model and bias adjustment 196 Variance estimation for CES redesign estimates 196 Appropriate uses of sampling variances in CES 196 Sampling errors for wholesale trade 196 Statistics for States and areas 197 Region, State, and area labor force data 199 FederalState cooperative program 199 Estimating methods 199 Estimates for States 199 Current monthly estimates 199 Benchmark correction procedures 199 Estimates for substate areas 200 Preliminary estimate: Employment 200 Unemployment 200 SubState adjustment for additivity 200 Benchmark correction 200 Seasonal adjustment 201 Note on Temporary Census Workers The hiring of temporary workers for Census affects current levels of Federal Government employment and higher aggregates that include the Federal Government. Estimates of these workers are 32,000, 72,000, 189,000, 262,000, 618,000, 480,000, 199,000, 33,000, and 6,000 in January, February, March, April, May, June,,, and September, respectively. Preliminary employment estimates ("B" tables) that include these workers may be subject to larger than normal revisions. For additional information, see "Counting the counters: effects of Census on employment" in the February issue of the Monthly Labor Review.

8 Employment and Unemployment Developments, September Total nonfarm employment rose by 252,000 in September, and the unemployment rate declined to percent. After adjusting for the net return of striking workers (75,000) and a further decline in the number of temporary census jobs (27,000), nonfarm employment was up by 204,000. Job gains were very strong in the services industry, but the overall employment change was tempered by widespread job losses in manufacturing. Unemployment Both the number of unemployed persons, million, and the unemployment rate, percent, declined in September. Over the past year, the rate has ranged from percent to percent. Over the month, the unemployment rates decreased for adult women ( percent) and blacks (7.0 percent). Rates for the other major worker groups adult men ( percent), teenagers (1 percent), whites ( percent), and Hispanics ( percent) showed little or no change. (See tables A3 and A4.) Total employment and the labor force Total employment was little changed at 13 million, seasonally adjusted, in September. The employmentpopulation ratio the proportion of the population age 16 and older with jobs was 6 percent, unchanged from. The civilian labor force, million, and the labor force participation rate, 66.9 percent, were both essentially unchanged in September. (See table A3.) The number of persons employed part time for economic reasons (those who would have preferred fulltime work) was million in September. The number of these involuntary parttime workers has ranged from to million since. (See table A7.) About 7.5 million persons (not seasonally adjusted) held more than one job in September. These multiple jobholders represented percent of total employment, compared with 5.7 percent a year earlier. (See table A37.) Persons not in the labor force About 1.2 million persons (not seasonally adjusted) were marginally attached to the labor force in September, about the same number as a year earlier. These people wanted and were available to work and had looked for a job sometime in the prior 12 months. They were not counted as unemployed, however, because they had not actively searched for work in the 4 weeks preceding the survey. The number of discouraged workers was 250,000 in September. Discouraged workers, a subset of the marginally attached, were not currently looking for work specifically because they believed no jobs were available for them. (See table A36.) Industry payroll employment Total nonfarm payroll employment rose by 252,000 to 13 million in September. Contributing to this increase was the net return of 75,000 striking workers to their jobs. At the same time, the number also reflects the conclusion of 27,000 temporary census jobs. After adjusting for both effects, payroll employment increased by 204,000 in September. (The strike adjustment primarily reflects the return of 87,000 communications workers who were off company payrolls in, which was partly offset by new strikes involving 12,000 workers.) So far this year, employment has increased by an average of 192,000 per month compared to 229,000 per month for all of. (See table B3.) Employment in the services industry rose by 200,000 in September, seasonally adjusted. Monthtomonth growth in services employment has varied widely this year, although the average monthly change (119,000) is close to the monthly average for all of. Employment in help supply services increased by 69,000 in September, after showing little net growth in the prior 3 months. Over the month, job gains continued in health services and in engineering and management services. In September, as in, there were large employment increases in job training services (within social services) and civic and social organizations (within membership organizations) after seasonal adjustment; these increases resulted from lighterthannormal seasonal layoffs that followed weak summer hiring. Construction employment rose by 30,000 in September, seasonally adjusted, following 3 months of very small gains. Seasonal declines in construction usually begin in September. This year those seasonal layoffs were smaller than normal, perhaps reflecting the relatively light hiring over the summer. Thus far this year, construction employment has increased by 17,000 per month on average, compared with 25,000 per month for all of. Employment in transportation and public utilities rose by 105,000 in September, largely reflecting the return of 87,000 telephone communications workers from a strike that kept them off payrolls during the reference period. Apart from the strike effect, employment in the communications industry increased by 7,000, and the transportation industry continued to grow. Finance, insurance, and real estate employment rose by 16,000 in September, following a similar gain in. In the first 7 months of the year, however, the industry had averaged monthly job losses of 4,000. In September, security brokerages added 6,000 jobs, continuing a strong growth trend. Employment also increased in mortgage brokerages and in real estate. Employment in manufacturing fell by 66,000 in Septem 1

9 ber, following an even larger decline of 117,000 in, as revised. Part of September's decline resulted from 10,000 workers being off payrolls due to strikes in transportation equipment and food and kindred products during the survey reference period. September's losses were widespread, with employment down in both durable and nondurable goods manufacturing. Employment fell in industrial machinery and equipment (9,000), apparel (9,000), rubber and miscellaneous plastics (8,000), and fabricated metal products (6,000). The only manufacturing industry to show consistent growth this year has been electronic components, which added 4,000 jobs in September and has added 46,000 jobs since April. Retail trade employment was essentially unchanged in September, as gains in most component industries were offset by losses in eating and drinking places and in building materials stores. The number of jobs in eating and drinking establishments declined for the second consecutive month, following strong gains in June and. Wholesale trade showed little change in September. Federal Government employment fell in September, as 27,000 temporary Census workers completed their assignments. As of September, only about 6,000 temporary census workers remained on the Federal Government payroll, down from a peak of 618,000 in May. Weekly hours The average workweek for production or nonsupervisory workers on private nonfarm payrolls was up by 0 hour in September to 3 hours, seasonally adjusted. The manufacturing workweek edged down by 0 hour to 41.2 hours, following a drop of 0.4 hour in. In September, manufacturing overtime declined by 0 hour for the second consecutive month to hours. (See table B8.) The index of aggregate weekly hours of production or nonsupervisory workers on private nonfarm payrolls increased by 0.3 percent to (1982=100), seasonally adjusted. The manufacturing index fell by 0.7 percent to 10. (See table B9.) Hourly and weekly earnings Average hourly earnings of production or nonsupervisory workers on private nonfarm payrolls increased by 3 cents in September to $13, seasonally adjusted. Over the month, average weekly earnings increased by 0.5 percent to $ Over the year, average hourly earnings rose by percent and average weekly earnings grew by percent. Twelvemonth growth rates in hourly earnings have been in the range of to percent since February. (See table Bl 1.) Expansion of the Current Population Survey (Household Survey) Sample The Census Bureau is expanding the monthly sample for the Current Population Survey (CPS) in response to a legislative mandate under the State Children's Health Insurance Program (SCHIP). This expansion, which will occur in 31 States and the District of Columbia, will increase the total number of households eligible for the monthly survey from about 50,000 to about 60,000. The additional households are being introduced into the survey over a 3month period beginning with September. The SCHIP legislation requires that the Census Bureau improve State estimates of the number of children who live in lowincome families and lack health insurance. The expansion of the monthly CPS sample is one part of the Census Bureau's plan for improving the SCHIP estimates. Other parts of the plan include an increase in the number of households that will be asked the questions from the annual March supplement to the CPS, the source of information on income and access to health insurance. The Bureau of Labor Statistics (BLS) does not plan to use the expanded sample for the official national labor force estimates until at least 2001, after the data collected from the new households have been evaluated. BLS will review estimates for November through April 2001 produced from the expanded sample. If persistent differences are observed between the estimates derived from the current and expanded samples during this period of review, the use of the expanded sample in the official estimates may be further delayed. The announcement of the final decision on whether the expanded sample will be used in the official data for 2001 (scheduled for release in ) will be made in early June. Scheduled Release Dates Employment and unemployment data are scheduled for initial release on the following dates: Reference month Release date Reference month Release date October November 3 January February 2 November December 8 February March 9 December January 5 March April 6

10 Summary table A. Major labor force status categories, seasonally adjusted (Numbers in thousands) Category Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Labor force status Civilian noninstitutional population Percent of DODulation Percent of population... Not in labor force 208, , , ,825 68, , , , ,757 68, , , , ,736 68, , , , ,688 68, , , , ,689 67, , , , ,804 67, , , , ,708 68, , , , ,524 67,986 s 209, , , ,774 68, , , , ,583 68, , , , ,650 69, , , , ,829 69, , , , ,477 69,522 All workers Men 20 years and over Women 20 years and over Both sexes 16 to 19 years White Black Hispanic origin NOTE: Beginning in January, data reflect revised population controls used in the household survey. Summary table B. Employment, hours, and earnings of production or nonsupervisory workers on nonfarm payrolls, seasonally adjusted (Numbers in thousands) Industry Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P P Employment Total Total private Goodsproducing industries Mining Construction Manufacturing Serviceproducing industries Transportation and public utilities... Wholesale trade Retail trade Finance, insurance, and real estate Services Government 129, ,042 25, ,439 18, ,805 6,866 6,962 22,844 7,589 39,321 20, , ,275 25, ,470 18, ,040 6,875 6,973 22,863 7,599 39,482 20, , ,517 25, ,516 18, ,261 22,893 7,604 39,606 20, , ,730 25, ,552 18, ,477 6,911 7,002 22,936 7,613 39,707 20, , ,036 25, ,652 18, ,710 6,925 7,005 22,973 7,612 39,844 20, , ,088 25, ,618 18, ,858 6,937 7,011 22,978 7,624 39,914 20, , ,462 25, ,726 18, ,271 6,953 7,033 23,027 7,621 40,090 20, , ,752 25, ,694 18, ,694 6,970 7,055 23,197 7,610 40,195 20, , ,578 25, ,666 18, ,906 6,962 7,048 23,064 7,600 40,220 21, , ,845 25, ,668 18, ,947 6,985 7,049 23,122 7,588 40,401 20, , ,001 25, ,670 18, ,851 7,010 7,050 23,196 7,586 40,403 20, , ,018 25, ,675 18, ,873 6,941 7,062 23,188 7,606 40,578 20, , ,306 25, ,705 18, ,162 7,046 7,065 23,189 7,622 40,778 20,462 Overthemonth change Total Total private Goodsproducing industries Mining Construction Manufacturing Serviceproducing industries Transportation and public utilities... Wholesale trade Retail trade Finance, insurance, and real estate Services Government Hours of work 1 Total private Manufacturing Overtime Indexes of aggregate weekly hours (1982=100) 1 Total private Manufacturing Earnings 1 Average hourly earnings, total private: Current dollars Constant (1982) dollars 2 Average weekly earnings, total private $ $ $ $ $ $ $ $ $ $ $ $ $13 N.A Data relate to private production or nonsupervisory workers. 2 The Consumer Price Index for Urban Wage Earners and Clerical Workers (CPIW) is used to deflate this series. The data in this series have been revised from January through due to corrections in the CPIW. N.A. = not available. p = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all seasonally adjusted data from January 1996 forward are subject to revision.

11 Chart 1. Nonfarm payroll employment, seasonally adjusted, 1996 Thousands 132,500 Thousands 132, , , ,500 ~ 127, , , , , , , , ,500 Chart 2., seasonally adjusted, 1996 Percent 6.0 Percent NOTE: Beginning in 1997, data incorporate revisions in the population controls. Beginning in 1998, data incorporate new composite estimation procedures and updated population controls. Beginning in and, data incorporate revisions in the population controls. These changes affect comparability with data for prior periods.

12 HOUSEHOLD DATA HISTORICAL A1. Employment status of the civilian noninstitutional population 16 years and over, 1966 to date (Numbers in thousands) Year and month Civilian noninstitutional population Number Percent of population Number Percent of population Agriculture Nonagricultural industries Number Percent of labor force Not in labor force Annual averages , , , ,335 75,770 77,347 78,737 80, ,895 74,372 75,920 77, ,979 3,844 3,817 3,606 68,915 70,527 72,103 74,296 2,875 2,975 2,817 2,832 52,288 52,527 53,291 53, , , , , , , , , , ,863 82,771 84,382 87,034 89,429 91,949 93,775 96,158 99, , , ,678 79,367 82,153 85,064 86,794 85,846 88,752 92,017 96,048 98, ,463 3,394 3,484 3,470 3,515 3,408 3,331 3,283 3,387 3,347 75,215 75,972 78,669 81,594 83,279 82,438 85,421 88,734 92,661 95,477 4,093 5,016 4,882 4,365 5,156 7,929 7,406 6,991 6,202 6, ,315 55,834 57,091 57,667 58,171 59,377 59,991 60,025 59,659 59, , , , , , , , , , , , , , , , , , , , , , ,397 99, , , , , , , , ,364 3,368 3,401 3,383 3,321 3,179 3,163 3,208 3,169 3,199 95,938 97,030 96,125 97, , , , , , ,142 7,637 8,273 10,678 10,717 8,539 8,312 8,237 7,425 6,701 6, ,806 61,460 62,067 62,665 62,839 62,744 62,752 62,888 62,944 62, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,223 3,269 3,247 3,115 3,409 3,440 3,443 3,399 3,378 3, , , , , , , , , , ,207 7,047 8,628 9,613 8,940 7,996 7,404 7,236 6,739 6,210 5, ,324 64,578 64,700 65,638 65,758 66,280 66,647 66,837 67,547 68,385 Monthly data, seasonally adjusted 2 : September. October November.. December.. 208, , , , , , , , , , , , ,179 3,238 3,310 3, , , , ,141 5,825 5,757 5,736 5,688 68,790 68,786 68,832 68,724 : January 3... February... March April May June September. 208, , , , , , , , , , , , , , , , , , , , , , , , , , , ,371 3,408 3,359 3,355 3,298 3,321 3,299 3,344 3, , , , , , , , , ,821 5,689 5,804 5,708 5,524 5,774 5,583 5,650 5,829 5,477 67,872 67,742 68,187 67,986 68,882 68,781 69,329 69,193 69,522 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, data are not strictly comparable with data for and earlier years because of revisions in the population controls used in the household survey. For additional information, see "Revisions in the Current Population Survey Effective January " in the February issue of this publication.

13 HOUSEHOLD DATA HISTORICAL A2. Employment status of the civilian noninstitutional population 16 years and over by sex, 1988 to date (Numbers in thousands) Sex, year, and month Civilian noninstitutional population Number Percent of population Number Percent of population Agriculture Annual averages Nonagricultural industries Number Percent of labor force Not in labor force MEN 87,857 88,762 66,927 67, ,273 64, ,493 2,513 60,780 61,802 3,655 3,525 20,930 20, ,377 91,278 92,270 93,332 94,355 95,178 96,206 97,715 98, ,011 69,168 69,964 70,404 70,817 71,360 72,087 73,261 73, ,104 64,223 64,440 65,349 66,450 67,377 68,207 69,685 70,693 71, ,546 2,589 2,575 2,478 2,554 2,559 2,573 2,552 2,553 2,432 62,559 61,634 61,866 62,871 63,896 64,818 65,634 67,133 68,140 69,014 3,906 4,946 5,523 5,055 4,367 3,983 3,880 3,577 3,266 3, ,367 22,110 22,306 22,927 23,538 23,818 24,119 24, ,210 Monthly data, seasonally adjusted 2 : September October... November December 99, , , ,264 74,643 74,680 74,728 74, ,630 71,623 71,732 71, ,361 2,389 2,501 2,440 69,269 69,234 69,231 69,487 3,013 3,057 2,996 3,003 25,333 25,408 25,451 25,334 : January 3.. February.. March April May June September 100, , , , , , , , ,963 75,304 75,594 75,198 75,189 74,883 75,120 74,917 75,412 75, ,358 72,473 72,313 72,307 71,948 72,217 72,063 72,407 72, ,495 2,494 2,409 2,384 2,381 2,429 2,465 2,465 2,548 69,862 69,979 69,904 69,923 69,568 69,789 69,598 69,942 69,805 2,946 3,121 2,885 2,882 2,934 2,903 2,854 3,005 2,881 24, , ,683 25,534 25,828 25,435 25,730 Annual averages WOMEN 96,756 97,630 54,742 56, ,696 53, ,020 52,341 3, ,787 99, , , , , , , , , ,141 58,795 60,239 60,944 61,857 63,036 63,714 64, ,689 53,496 54,052 54,910 56,610 57,523 58,501 59,873 60,771 62, ,011 52,815 53,380 54,273 55,755 56,642 57,630 59,026 59,945 61, ,683 4,090 3,885 3,629 3,421 3,356 3,162 2, ,957 42,468 42,394 42,711 42,221 42,462 42,528 42,382 42, Monthly data, seasonally adjuste<j2 : September October... November December 108, , ,569 64, ,106 65, ,020 62,317 62,366 62, ,202 61,468 61, ,812 2,700 2,740 2,685 43,457 43,378 43, : January3.. February... March April May June September 108, , , , , , , ,198 65,606 65,572 65,668 66,041 65,606 65,642 65,482 65,330 65, ,863 62,889 62,846 63,399 62,767 62,962 62,686 62,505 62, ,988 61,975 61,896 62,428 61,849 62,070 61,852 61,627 62,016 2,743 2,683 2,823 2,642 2,839 2,680 2, ,597 42, , ,199 43, ,793 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, data are not strictly comparable with data for and earlier years because of revisions in the population controls used in the household survey. For additional information, see "Revisions in the Current Population Survey Effective January " in the February issue of this publication.

14 HOUSEHOLD DATA SEASONALLY ADJUSTED A3. Employment status of the civilian noninstitutional population by sex and age, seasonally adjusted (Numbers in thousands) Employment status, sex, and age Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June TOTAL Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio Not in labor force Persons who currently want a job Men, 16 years and over Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio Agriculture Nonagricultural industries Not in labor force 208, , , ,825 68,790 4,352 99,976 74, , ,361 69,269 3,013 25, , , , ,757 68,786 4, ,088 74, , ,389 69,234 3,057 25, , , , ,736 68,832 4, ,179 74, , ,501 69,231 2,996 25, , , , ,688 68,724 4, ,264 74, , ,440 69,487 3,003 25, , , , ,689 67,872 4, ,266 75, , ,495 69,862 2,946 24, , , , ,804 67,742 4, ,330 75, , ,494 69,979 3,121 24, , , , ,708 68,187 4, ,405 75, , ,409 69,904 2,885 25, , , , ,524 67,986 4, ,487 75, , ,384 69,923 2,882 25, , , , ,774 68,882 4, ,566 74, , ,381 69,568 2,934 25, , , , ,583 68,781 4, ,654 75, , ,429 69,789 2,903 25, , , , ,650 69,329 4, ,745 74, , ,465 69,598 2,854 25, , , , ,829 69,193 4, ,847 75, , ,465 69,942 3,005 25, , , , ,477 69,522 4, ,963 75, , ,548 69,805 2,881 25,730 Men, 20 years and over Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio Agriculture Nonagricultural industries Not in labor force 91,793 70, , ,189 65,754 2,385 21,465 91,896 70, , ,206 65,692 2,441 21,557 91,986 70, , ,262 65,775 2,351 21,598 92,052 70, , ,227 65,970 2,332 21,523 92,057 70, , ,303 66,282 2,332 21,139 92,092 71, , ,309 66,382 2,429 20,972 92,145 70, , ,232 66,249 2,342 21,323 92,303 70, , ,213 66,269 2,280 21,542 92,408 70, , ,217 66,013 2,373 21,805 92,546 70, , ,269 66,161 2,284 21,832 92,642 70, , ,296 66,144 2,263 21,940 92,754 71, , ,288 66,469 2,309 21,688 92,863 71, , ,350 66,349 2,303 21,861 Women, 16 years and over Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio Agriculture Nonagricultural industries Not in labor force Women, 20 years and over Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio Agriculture Nonagricultural industries Not in labor force 108,289 64, , ,202 2,812 43, ,385 60, , ,852 2,230 39, ,395 65, , ,468 2,700 43, ,458 60, , ,000 2,155 39, ,487 65, , ,557 2,740 43, ,573 61, , ,070 2,214 39, ,569 65, , ,654 2,685 43, ,666 61, , ,167 2,196 39, ,516 65, , ,988 2,743 42, ,579 61, , ,454 2,297 39, ,577 65, , ,975 2,683 43, ,666 61, , ,526 2,178 39, ,649 65, , ,896 2,823 42, ,713 61, , ,528 2,249 39, ,729 66, , ,428 2,642 42, ,809 61, , ,858 2,163 38, ,805 65, , ,849 2,839 43, ,929 61, , ,383 2,367 39, ,889 65, , ,070 2,680 43, ,007 61, , ,444 2,318 39, ,983 65, , ,852 2,796 43, ,111 61, , ,430 2,286 39, ,088 65, , ,627 2,824 43, ,209 61, , ,125 2,311 39, ,198 65, , ,016 2,597 43, ,321 61, , ,524 2,118 39,935 Both sexes, 16 to 19 years Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio Agriculture Nonagricultural industries Not in labor force 16,086 8, , ,865 1, ,799 16,129 8, , ,010 1, ,726 16,107 8, , ,943 1, ,713 16,114 8, , ,004 1, ,689 16,147 8, , ,114 1, ,730 16,149 8, , ,046 1, ,679 16,196 8, , ,024 1, ,822 16,104 8, , ,224 1, ,555 16,034 8, , ,020 1, ,762 15,991 8, , , ,539 15,974 8, , ,876 1, ,786 15,972 8, , ,974 1, ,557 15,977 8, , ,948 1, ,726 1 The population figures are not adjusted for seasonal variation. NOTE: Detail for the seasonally adjusted data shown in tables A3 through A13 will not necessarily add to totals because of the independent seasonal adjustment of the various series. Beginning in January, data reflect revised population controls used in the household survey.

15 HOUSEHOLD DATA SEASONALLY ADJUSTED A4. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic origin, seasonally adjusted (Numbers in thousands) Employment status, race, sex, age, and Hispanic origin Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Sept WHITE Civilian noninstitutional population 1.. Percent of population Employmentpopulation ratio Men, 20 years and over 173, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,085 Percent of population Employmentpopulation ratio 59, , ,739 59, , ,734 59, , ,694 59, , ,668 60, , ,693 60, , ,756 60, , ,742 60, , ,662 59, , ,698 60, , ,666 59, , ,647 60, , ,657 60, , ,732 Women, 20 years and over Percent of population Employmentpopulation ratio 49, , , , ,530 49, , ,541 50, , ,525 50, , ,547 50, , , , ,628 50, , ,576 50, , ,670 50, , ,630 50, , ,656 50, , ,673 50, , ,546 Both sexes, 16 to 19 years Percent of population Employmentpopulation ratio Women 7, , , , , , , , , , , , , , , , , , , , , , , , , , BLACK Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio... 24,946 16, , , ,985 16, , , ,019 16, , , ,051 16, , , ,047 16, , , ,076 16, , , ,105 16, , , ,135 16, , , ,161 16, , , , , , ,221 16, , , , , , ,299 16, , , Men, 20 years and over Percent of population Employmentpopulation ratio... 7, , , , , , , , , , , , , , , , , , , , , , , , , , Women, 20 years and over Percent of population Employmentpopulation ratio... 8, , , , , , , , , , , , , , , , , , , , , , , , , See footnotes at end of table.

16 HOUSEHOLD DATA SEASONALLY ADJUSTED A4. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic origin, seasonally adjusted Continued (Numbers in thousands) Employment status, race, sex, age, and Hispanic origin Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June BLACKContinued Both sexes, 16 to 19 years Percent of population Employmentpopulation ratio... Men Women HISPANIC ORIGIN Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio... 21,820 14, , ,881 14, , ,947 14, , ,008 14, , ,047 15, , ,108 15, , ,166 15, , ,231 15, , ,292 15, , ,355 15, , ,422 15, , ,488 15, , ,555 15, , The population figures are not adjusted for seasonal variation. NOTE: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey.

17 HOUSEHOLD DATA SEASONALLY ADJUSTED A5. Employment status of the civilian noninstitutional population 25 years and over by educational attainment, seasonally adjusted (Numbers in thousands) Educational attainment Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Sept Less than a high school diploma Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 28,583 12, , ,246 12, , ,228 12, , ,144 11, , ,995 11, , ,376 11, , ,523 11, , ,069 11, , ,096 11, , ,227 12, , ,888 12, , ,306 12, , ,346 12, , High school graduates, no college 2 Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 57,518 37, , ,309 57,275 37, , ,206 57,789 37, , ,226 57,590 37, , ,291 57,768 37, , ,311 57,471 37, , ,309 58,033 37, , ,270 58,015 37, , ,265 57,746 37, , ,329 57,581 36, , ,251 57,144 37, , ,236 56,882 36, , ,350 57,244 36, , ,219 Less than a bachelor's degree 3 Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 42,955 32, , ,787 32, , ,070 32, , ,069 32, , ,689 32, , ,486 32, , ,225 32, , ,896 32, , ,153 33, , ,250 33, , ,724 32, , ,616 33, , ,191 32, , College graduates Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 45,081 35, , ,986 35, , ,365 35, , ,821 35, , ,058 36, , ,247 36, , ,838 36, , ,864 36, , ,029 36, , ,092 35, , ,549 35, , ,718 35, , ,863 36, , The population figures are not adjusted for seasonal variation. 2 Includes high school diploma or equivalent. 3 Includes the categories, some college, no degree; and associate degree. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 10

18 HOUSEHOLD DATA SEASONALLY ADJUSTED A6. and unemployed full and parttime workers by sex and age, seasonally adjusted (Numbers in thousands) Full and parttime status, sex, and age Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June EMPLOYED Fulltime 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 110,413 63,985 62,621 46,452 45,497 2, ,877 64,005 62,607 46,847 45,822 2, ,227 64,259 62,825 46,968 45,907 2, ,562 64,358 62,914 47,161 46,094 2, ,089 64,727 63,407 47,152 46,189 2, ,129 64,883 63,468 47,195 46,187 2, ,248 64,933 63,501 47,253 46,357 2, ,054 65,097 63,620 47,841 46,787 2, ,271 64,772 63,238 47,442 46,387 2, ,326 65,009 63,427 47,424 46,331 2, ,051 65,038 63,548 47,115 46,089 2, ,154 65,346 63,815 46,888 45,900 2, ,509 65,006 63,560 47,576 46,435 2,515 Parttime 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 23,205 7,613 5,302 15,666 13,169 4,734 23,081 7,610 5,255 15,483 12,996 4,830 22,946 7,485 5,213 15,450 12,964 4,769 22,975 7,581 5,295 15,377 12,932 4,748 23,224 7,552 5,197 15,641 13,075 4,951 23,210 7,557 5,193 15,627 13,157 4,860 23,105 7,489 5,101 15,619 13,107 4,898 22,697 7,180 4,877 15,509 12,954 4,865 22,508 7,184 4,963 15,350 12,884 4,661 22,808 7,241 5,030 15,531 12,983 4,795 22,517 7,045 4,901 15,533 13,029 4,587 22,696 7,071 4,997 15,607 13,013 4,686 22,619 7,364 5,104 15,355 12,857 4,658 UNEMPLOYED Looking for fulltime work 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 4,568 2,533 2,172 2,068 1, ,614 2,588 2,224 2,068 1, ,536 2,526 2,151 2,068 1, ,540 2,493 2,109 2,065 1, ,554 2,389 2,125 2,093 1, ,595 2,512 2,234 1,978 1, , ,106 2,076 1, ,427 2,393 2,039 2,082 1, ,592 2,478 2,176 2,140 1, ,420 2,477 2,090 1,997 1, ,362 2,370 2,038 1,959 1, ,631 2,497 2,093 2,155 1, ,386 2,443 2,090 1,969 1, Looking for parttime work 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 1, , , , , , , , , , , , , UNEMPLOYMENT RATES 1 Fulltime 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 Parttime 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 These rates reflect a refined definition of the full and parttime labor force and differ from the rates published elsewhere in this publication prior to NOTE: Beginning in January, data reflect revised population controls used in the household survey. 11

19 HOUSEHOLD DATA SEASONALLY ADJUSTED A7. persons by marital status, occupation, class of worker, and parttime status, seasonally adjusted (In thousands) Category Oct. Nov. Dec, Jan. Feb. Mar. Apr. May June MARITAL STATUS Total Married men, spouse present Married women, spouse present Women who maintain families 133,650 43,367 33,275 8, ,940 43,206 33,521 8, ,098 43,273 33,635 8, ,420 43,283 33,762 8, ,221 43,951 34,166 8, ,362 43,535 33,882 8, ,159 43,297 33,780 8, ,706 43,272 33,877 8, ,715 43,216 33,786 8, ,179 43,357 33,824 8, ,749 43,284 33,618 8, ,912 43,372 33,413 8, ,161 43,324 33,402 8,548 OCCUPATION Managerial and professional specialty Technical, sales, and administrative support Service occupations Precision production, craft, and repair Operators, fabricators, and laborers Farming, forestry, and fishing 40,784 38,634 17,876 14,659 18,227 3,365 40,718 39,023 17,694 14,836 18,340 3,365 40,363 39,283 17,633 14,903 18,476 3,407 40,800 39,311 17,706 14,940 18,299 3,367 40,924 39,614 18,155 14,610 18,385 3,574 40,806 39,703 18,344 14,681 18,279 3,630 40,595 39,510 18,711 14,520 18,334 3,562 40,665 39,680 18,885 14,501 18,453 3,477 40,858 39,537 18,181 14,867 18,020 3,410 41,148 39,270 18,090 14,888 18,430 3,368 40,784 39,239 17,877 15,236 18,296 3,309 40,937 39,026 17,675 15,263 18,592 3,400 40,963 38,966 18,128 15,156 18,501 3,395 CLASS OF WORKER Agriculture: Wage and salary workers Selfemployed workers Unpaid family workers Nonagricultural industries: Wage and salary workers Private industries Private households Other industries Government Selfemployed workers Unpaid family workers 1,930 1, , ,503 1, ,468 19,080 8, ,936 1, , , ,898 18,817 8, ,049 1, , , ,119 18,902 8, ,018 1, , , ,519 18,959 8, ,024 1, , , ,858 19,013 8, ,025 1, , ,772 1, ,756 19,394 8, ,043 1, , , ,573 19,598 8, ,054 1, , ,343 1, ,324 19,280 8, ,006 1, , , ,738 19,169 8, ,059 1, , , ,268 18,777 8, ,079 1, , , ,377 18,497 8, ,056 1, , , ,561 18,496 8, ,010 1, , , ,201 18,979 8, PERSONS AT WORK PART TIME 1 All industries: Part time for economic reasons Slack work or business conditions Could only find parttime work Part time for noneconomic reasons 3,283 1,922 1,073 18,801 3,179 1, ,799 3,274 1,930 1,032 18,651 3,320 1,951 1,025 18,618 3,219 1,893 1,012 18,889 3,139 1,807 1,023 19,031 3,124 1, ,770 3,124 1,844 1,016 18,474 3,248 1, ,409 3,117 1,811 1,022 18,308 3,071 1, ,558 3,164 1, ,709 3,189 2, ,456 Nonagricultural industries: Part time for economic reasons Slack work or business conditions Could only find parttime work Part time for noneconomic reasons 3,112 1,806 1,063 18,273 2,983 1, ,249 3,105 1,815 1,013 18,083 3,157 1,843 1,018 18,061 3,066 1, ,347 2,985 1,705 1,005 18,406 3,003 1, ,184 3,021 1, ,943 3,096 1, ,853 2,967 1, ,743 2,940 1, ,041 3,038 1, ,190 3,021 1, ,879 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: Beginning in January, data reflect revised population controls used in the household survey. 12

20 HOUSEHOLD DATA SEASONALLY ADJUSTED A8. persons by age and sex, seasonally adjusted (In thousands) Age and sex Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Total, 16 years and over , , , , , , , , , , , , , to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 20,106 7,077 2,765 4,309 13, ,539 96,200 17,377 20,226 7,242 2,834 4,411 12, ,666 96,436 17,255 20,188 7,223 2,797 4,421 12, ,897 96,635 17,252 20,334 7,265 2,803 4,461 13, ,075 96,729 17,406 20,621 7,356 2,855 4,492 13, ,641 97,199 17,447 20,473 7,273 2,794 4,452 13, ,810 97,246 17,603 20,478 7,257 2,832 4,432 13, ,737 97,120 17,604 20,743 7,467 2,817 4,632 13, ,009 97,349 17,620 20,211 7,237 2,732 4,539 12, ,585 96,841 17,617 20,683 7,471 2,914 4,561 13, ,453 96,790 17,683 20,292 7,087 2,615 4,454 13, ,478 96,768 17,735 20,538 7,206 2,737 4,472 13, ,440 96,566 17,888 20,762 7,195 2,785 4,413 13, ,413 96,657 17,823 Men, 16 years and over 71,630 71,623 71,732 71,927 72,358 72,473 72,313 72,307 71,948 72,217 72,063 72,407 72, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 10,540 3,687 1,421 2,247 6,853 61,083 51,431 9,649 10,521 3,725 1,462 2,267 6,796 61,073 51,523 9,542 10,508 3,695 1,439 2,234 6,813 61,202 51,673 9,574 10,570 3,730 1,445 2,278 6,840 61,349 51,732 9,649 10,727 3,773 1,471 2,301 6,954 61,585 51,944 9,658 10,745 3,782 1,494 2,267 6,963 61,702 51,928 9,784 10,858 3,833 1,510 2,334 7,025 61,482 51,800 9,723 10,858 3,825 1,436 2,385 7,033 61,426 51,796 9,630 10,556 3,718 1,404 2,349 6,838 61,430 51,664 9,691 10,748 3,787 1,486 2,306 6,962 61,456 51,781 9,679 10,556 3,623 1,313 2,296 6,933 61,530 51,803 9,739 10,683 3,650 1,389 2,256 7,032 61,771 51,851 9,952 10,737 3,654 1,394 2,256 7,084 61,618 51,823 9,801 Women, 16 years and over 62,020 62,317 62,366 62,493 62,863 62,889 62,846 63,399 62,767 62,962 62,686 62,505 62, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 9,566 3,390 1,344 2,062 6,176 52,456 44,769 7,728 9,705 3,517 1,372 2,144 6,188 52,593 44,913 7,713 9,680 3,528 1,358 2,187 6,152 52,695 44,962 7,678 9,764 3,535 1,358 2,183 6,229 52,726 44,997 7,757 9,894 3,584 1,385 2,190 6,310 53,056 45,254 7,788 9,728 3,491 1,300 2,185 6,237 53,108 45,319 7,818 9,620 3,424 1,322 2,098 6,196 53,255 45,321 7,882 9,885 3,642 1,381 2,247 6,243 53,583 45,553 7,990 9,655 3,519 1,328 2,190 6,136 53,155 45,177 7,926 9,934 3,684 1,428 2,254 6,250 52,997 45,009 8,004 9,736 3,464 1,302 2,158 6,271 52,947 44,965 7,996 9,855 3,556 1,348 2,216 6,299 52,669 44,715 7,936 10,024 3,541 1,391 2,157 6,483 52,795 44,834 8,023 NOTE: Beginning in January, data reflect revised population controls used in the household survey. 13

21 HOUSEHOLD DATA SEASONALLY ADJUSTED A9. persons by age and sex, seasonally adjusted (In thousands) Age and sex Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Total, 16 years and over... 5,825 5,757 5,736 5,688 5,689 5,804 5,708 5,524 5, ,650 5,829 5, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 2,226 1, ,016 3,618 3, ,247 1, ,086 3,510 3, ,249 1, ,078 3,488 3, ,209 1, ,049 3,479 2, ,119 1, ,059 3,578 3, ,267 1, ,071 3,520 2, ,199 1, ,082 3,531 3, ,115 1, ,033 3,411 2, ,198 1, ,164 3,556 3, , ,067 3,515 3, ,066 1, ,581 3, ,128 1, ,700 3, ,977 1, ,518 3, Men, 16 years and over 3,013 3,057 2,996 3,003 2,946 3,121 2,885 2,882 2,934 2,903 2,854 3,005 2, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 1, ,859 1, , ,842 1, , ,789 1, , ,757 1, , ,800 1, , ,861 1, , ,781 1, , ,735 1, , ,744 1, , ,772 1, , ,747 1, , ,802 1, , ,778 1, Women, 16 years and over 2,812 2,700 2,740 2,685 2,743 2,683 2,823 2,642 2,839 2,680 2,796 2,824 2, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 1, ,759 1, , ,668 1, , ,699 1, ,722 1, ,778 1, , ,659 1, , ,751 1, ,676 1, , ,811 1, ,742 1, ,834 1, ,899 1, ,740 1, NOTE: Beginning in January, data reflect revised population controls used in the household survey. 14

22 HOUSEHOLD DATA SEASONALLY ADJUSTED A10. s by age and sex, seasonally adjusted (Percent) Age and sex Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Total, 16 years and over to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over Men, 16 years and over 16 to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over Women, 16 years and over 16 to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over NOTE: Beginning in January, data reflect revised population controls used in the household survey. 15

23 HOUSEHOLD DATA SEASONALLY ADJUSTED A11. s by occupation, industry, and selected demographic characteristics, seasonally adjusted (Percent) Category Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June CHARACTERISTIC Total Men, 20 years and over Women, 20 years and over Both sexes, 16 to 19 years White Black and other Black Hispanic origin Married men, spouse present Married women, spouse present Women who maintain families OCCUPATION 1 Managerial and professional specialty Technical, sales, and administrative support Precision production, craft, and repair Operators, fabricators, and laborers Farming, forestry, and fishing INDUSTRY Nonagricultural private wage and salary workers Goodsproducing industries Mining Construction Manufacturing Durable goods Nondurable goods Serviceproducing industries Transportation and public utilities Wholesale and retail trade Finance, insurance, and real estate Services Government workers Agricultural wage and salary workers Seasonally adjusted data for service occupations are not available because the seasonal component, which is small relative to the trendcycle and irregular components, cannot be separated with sufficient precision. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 16

24 HOUSEHOLD DATA SEASONALLY ADJUSTED A12. persons by reason for unemployment, seasonally adjusted (Numbers in thousands) Reason Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June NUMBER OF UNEMPLOYED Job losers and persons who completed temporary jobs... On temporary layoff Not on temporary layoff Job leavers Reentrants New entrants 2, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , PERCENT DISTRIBUTION Job losers and persons who completed temporary jobs... On temdorarv lavoff 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, data reflect revised population controls used in the household survey. A13. persons by duration of unemployment, seasonally adjusted (Numbers in thousands) Duration Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June NUMBER OF UNEMPLOYED Less than 5 weeks 5 to 14 weeks 15 weeks and over 15 to 26 weeks 27 weeks and over 2,582 1,805 1, ,545 1,811 1, ,601 1,760 1, ,620 1,694 1, ,447 1,754 1, ,603 1,864 1, ,824 1,719 1, ,455 1,868 1, ,531 1,953 1, ,595 1,759 1, ,470 1,812 1, ,594 1,846 1, ,487 1,717 1, Average (mean) duration, in weeks Median duration, in weeks PERCENT DISTRIBUTION Total unemployed Less than 5 weeks 5 to 14 weeks 15 weeks and over 15 to 26 weeks 27 weeks and over NOTE: Beginning in January, data reflect revised population controls used in the household survey. 17

25 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A14. Employment status of the civilian noninstitutional population by age, sex, and race (Numbers in thousands) September Age, sex, and race Civilian noninstitutional population Total Percent of population Total Percent of population Agriculture Nonagricultural industries Number Percent of labor force Not in labor force TOTAL 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 to 69 years 70 to 74 years 75 years and over. 210,161 15,977 7,928 8,049 18, ,046 37,289 17,884 19,405 44,662 21,991 22,671 37,095 19,904 17,190 23,804 13,260 10,544 32,794 9,258 8,523 15, ,357 7,852 3,156 4,696 14,305 99,810 31,346 15,005 16,341 37,853 18,537 19,316 30,611 16,792 13,819 14,097 9,117 4,980 4,293 2,318 1, ,033 6,840 2,726 4,114 13,390 96,897 30,237 14,434 15,803 36,802 18,022 18,780 29,858 16,336 13,522 13,766 8,911 4,855 4,139 2,226 1, , , ,591 2, ,047 94,800 29,627 14,150 15,478 35,971 17,587 18,384 29,201 15,966 13,235 13,292 8,703 4,589 3,794 2,063 1, ,324 1, , , ,804 8,125 4, ,235 19,236 5,943 2,879 3,065 6,809 3,454 3, ,112 3,372 9,707 4,142 5,564 28,501 6,941 7,349 14,211 Men 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 ,963 8,100 4,055 4,044 9,226 58,317 18, ,525 22,001 10,831 11,170 18,106 9,758 8,348 11,344 6,361 4,983 13,976 4, ,907 74,983 4,029 1,606 2,424 7,499 53,315 16,901 7,939 8,962 20,317 10,076 10,241 16,097 8,800 7,296 7,658 4,956 2,702 2, ,317 3,494 1,369 2,125 7,008 51,938 16,381 7,681 8,699 19,838 9,845 9,993 15,719 8,580 7,139 7,506 4,856 2,650 2,372 1, ,644 3,295 1,282 2,013 6, ,465 8, ,507 9, ,297 6,935 7,155 4, , , , ,071 2,450 1, , , ,052 3,686 1,405 2,281 11,494 2,952 3,096 5,445 Women 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 109,198 7,877 3,873 4, ,079 9,199 9,880 22,661 11,160 11,501 18,989 10,147 8,842 12,461 6,899 5,562 18,818 4,964 4,748 9,105 65,374 3,823 1,551 2, ,445 7,066 7,379 17,536 8, ,515 7,992 6,522 6,439 4,161 2, ,716 3,346 1,357 1, , ,965 8,177 8,787 14,139 7,756 6,383 6,260 4,055 2,206 1, , ,708 6,684 7, ,080 8,681 13,970 7,670 6,300 6,137 4,016 2,120 1, , , , ,322 1,733 2,507 14,233 4,634 2, ,125 2,700 2,426 4,474 2,155 2,319 6,021 2,737 3,284 17,007 3,989 4,253 8,766 See footnotes at end of table. 18

26 A14. Employment status of the civilian noninstitutional population by age, sex, and race Continued (Numbers in thousands) September Civi ian labor force HOUSEHOLD DATA NOT SEASONALLY ADJUSTED Age, sex, and race Civilian noninstitutional population Total Percent of population Total Percent of population Agriculture Nonagricultural industries Number Percent of labor force Not in labor force WHITE 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 174,745 12,699 6,298 6,401 14,812 97,819 29,852 14, ,979 18,678 31,311 16,640 14,671 20,428 11,372 9, ,957 7,529 13, ,780 82,699 25,221 12, ,240 16, ,186 11,963 12,284 7,911 4,372 3,819 2,026 1, ,888 2,386 3,502 11,180 80,584 24,467 11,608 12,859 30,564 14,876 15, ,993 7,739 4,254 3,689 1,949 1, , , ,057 5,648 2, ,868 78, ,564 29,765 14,459 15,306 24,960 13,491 11,470 11,554 7,547 4,007 3, , , ,508 6,045 3,586 2,459 3, ,630 2, ,739 2,588 5, ,708 8,145 3,461 4,684 25,167 5,931 6,461 12,775 Men 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 84,811 6,491 3,243 3,249 7,468 48,572 14,819 7,032 7,787 18,288 8,964 9,324 15,466 8,252 7,214 9,861 5,524 4,337 12,419 3, ,683 3,456 1,384 2,071 6,282 44,956 13,924 6,523 7,401 17,107 8,428 8,679 13,924 7,530 6,395 6,754 4,358 2,396 2,236 1, ,703 3,043 1,202 1,842 5,947 43,966 13,565 6,334 7,232 16,762 8,257 8,505 13,639 7,366 6,273 6,609 4,265 2,344 2,137 1, , , ,242 2,853 1,120 1,734 5,697 42,511 13,138 6,126 7,012 16,162 7,933 8,228 13,211 7,112 6,100 6, ,181 1,889 1, , ,128 3,036 1,858 1,177 1,185 3, , , ,107 1,167 1,941 10,183 2,525 2,764 4,894 Women 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 89,934 6,208 3,055 3,152 7,344 49,247 15,033 7,150 7,883 18, ,353 15,845 8,388 7,457 10,567 5,848 4,719 16,567 4,238 4, ,554 3,198 1,328 1,871 5,498 37,743 11,297 5,483 5,815 14, ,411 12, ,568 5,530 3,554 1,976 1, ,630 2,844 1,185 1,660 5,233 36,618 10, ,628 13,802 6,620 7,182 11,914 6,466 5,449 5,384 3,474 1, ,815 2,795 1,155 1,639 5,171 36,112 10,760 5,208 5,552 13,603 6,525 7,078 11,749 6,379 5,370 5,262 3,436 1,826 1, , , ,380 3,009 1,728 1,281 1,847 11, ,667 2,068 4,147 2,204 1,943 3,621 1,732 1,889 5,037 2,294 2,743 14,984 3,405 3,697 7,881 See footnotes at end of table. 19

27 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A14. Employment status of the civilian noninstitutional population by age, sex, and race Continued (Numbers in thousands) September Age, sex, and race Civilian noninstitutional population Total Percent of population Total Percent of population Agriculture Nonagricultural industries Number Percent of labor force Not in labor force BLACK 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 25, ,220 2,710 14,967 5,138 2,518 2,619 5,677 2,854 2,823 4,152 2, , , ,102 4,288 2,081 2,207 4,629 2,370 2,259 3,185 1,875 1, ,597 11,438 4, ,057 4,392 2,246 2,146 3,044 1, , , ,342 3,975 1,940 2,035 4,368 2,233 2,135 2, ,241 1, , , , , , Men 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 , , ,185 2, , , , , , ,047 2, ,062 1, , ,361 1, ,083 1, ,274 1, ,063 1, , (M Women 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 141 1, ,466 8,199 2,840 1,406 1,434 3,076 1,553 1,523 2,283 1, , , , ,422 2, ,435 1,237 1,198 1, , , ,165 1,143 1, , ,068 2,136 1,053 1,083 2, , , , , Data not shown where base is less than 75,000. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 20

28 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A15. Employment status of the civilian noninstitutional population by race, sex, and age (Numbers in thousands) Employment status and race Total Men, 20 years and over Women, 20 years and over Both sexes, 16 to 19 years TOTAL Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 208, , ,555 3, ,214 5,661 69, , , ,033 3, ,523 5,324 69,804 91,793 70, ,078 2,296 65,782 2,208 21,508 92,863 70, ,823 2,474 66,349 2,130 21, ,385 61, , ,920 2,299 39, ,321 61, , ,583 2,182 39,769 16,086 7, , ,512 1, ,208 15,977 7, , ,591 1, ,125 White Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 173, , ,241 3, ,084 4,002 57, , , ,334 3, ,057 3,903 57,508 77,586 59, ,236 2,160 56,076 1,571 17,779 78,320 60, ,660 2,272 56,388 1,567 18,092 83,102 49, , ,343 1, ,726 50, , ,020 1,570 33,371 12,743 6, , , ,053 12,699 6, , , ,045 Black Civilian noninstitutional population Percent of population Agriculture Nonagricuitural industries Not in labor force 24,946 16, , ,004 1, ,452 25,299 16, , ,077 1, ,874 9,965 7, , , ,749 10,148 7, , , ,863 12, , , ,135 12,689 8, , , ,450 2, ,567 2, ,561 NOTE: Beginning in January, data reflect revised population controls used in the household survey. 21

29 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A16. Employment status of the civilian noninstitutional population 16 to 24 years of age by school enrollment, educational attainment, sex, race, and Hispanic origin (Numbers in thousands) September Enrollment status, educational attainment, race, and Hispanic origin Civilian noninstitutional population Total Percent of population Total Full time Part time Total Looking for fulltime work Looking for parttime work Percent of labor force TOTAL ENROLLED Total. 16 to 24 years 16 to 19 years 20 to 24 years ,950 8,755 5,026 3, , , ,085 3,914 2, High school College Fulltime students Parttime students 8, ,959 1,586 3,346 5,409 4,079 1, , , , ,724 3, Men, 16 to 24 years 16 to 19 years 20 to 24 years , ,224 2, ,855 2, ,856 1, High school College Fulltime students Parttime students 4,658 4, ,787 2,437 1, , ,422 1,434 1, Women, 16 to 24 years 16 to 19 years 20 to 24 years , ,535 1, , ,229 2,011 1, High school College Fulltime students Parttime students 58 5, ,559 2,972 2, ,789 2, , , White Total, 16 to 24 years 16 to 19 years 20 to 24 years 14,303 9,667 4,636 7,402 4,308 3, ,857 3,879 2,978 1, ,152 5,209 3, , Men Women 7, , , ,464 2, High school College Fulltime students Parttime students 6, , ,518 3,417 1, ,283 3,219 1, , ,392 2,816 2, Black Total. 16 to 24 years 16 to 19 years 20 to 24 years Men Women 1, High school College Fulltime students Parttime students 1,433 1,285 1, Hispanic origin Total. 16 to 24 years 16 to 19 years 20 to 24 years 75 1, Men Women High school College Fulltime students Parttime students 1, See footnotes at end of table. 22

30 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A16. Employment status of the civilian noninstitutionai population 16 to 24 years of age by school enrollment, educational attainment, sex, race, and Hispanic origin Continued (Numbers in thousands) September Enrollment status, educational attainment, race, and Hispanic origin Civilian noninstitutionai population Total Percent of population Total Full time Part time Total Looking for fulltime work Looking for parttime work Percent of labor force TOTAL NOT ENROLLED Total, 16 to 24 years 16 to 19 years 20 to 24 years 16,357 3,767 12,590 13,402 2,826 10, ,217 2,379 9,838 10,405 1,742 8,663 1, ,175 1, , Less than a high school diploma High school graduates, no college Less than a bachelor's degree College graduates 3,888 7,224 3,490 1,755 2,684 6,031 3,069 1, ,247 5, ,551 1,758 4,645 2,521 1, Men, 16 to 24 years 16 to 19 years 20 to 24 years 8,290 1,931 6,359 7,304 1,538 5, ,646 1,295 5,351 5,964 1,011 4, Less than a high school diploma High school graduates, no college Less than a bachelor's degree College graduates 2,093 3,817 1, ,698 3,386 1, ,447 3,090 1, ,224 2,771 1, Women, 16 to 24 years 16 to 19 years 20 to 24 years 8,067 1,836 6, ,288 4, ,571 1,084 4,487 4, ,710 1, Less than a high school diploma High school graduates, no college Less than a bachelor's degree College graduates 1,795 3,407 1,779 1, ,645 1, ,415 1, ,874 1, White Total, 16 to 24 years 16 to 19 years 20 to 24 years 13,208 3,032 10, ,346 8, ,211 2,009 8,202 8,712 1,491 7,221 1, Men Women 6,783 6,424 6,121 4, ,650 4,561 5,095 3, Less than a high school diploma High school graduates, no college Less than a bachelor's degree College graduates 3,152 5,702 2,854 1,500 2,226 4,865 2,542 1, ,907 4,514 2,445 1,345 1,506 3,797 2,123 1, Black Total, 16 to 24 years 16 to 19 years 20 to 24 years 2, ,849 1, , , ,224 1, , Men Women 1,170 1, Less than a high school diploma High school graduates, no college Less than a bachelor's degree College graduates 600 1, Hispanic origin Total, 16 to 24 years 16 to 19 years 20 to 24 years 3, ,290 2, , , ,724 1, , Men Women 1,640 1,441 1, , , Less than a high school diploma High school graduates, no college Less than a bachelor's degree College graduates 1,430 1, 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. Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 23

31 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A17. Employment status of the civilian noninstitutional population 25 years and over by educational attainment, sex, race, and Hispanic origin (Numbers in thousands) Educational attainment Total Men Women White Black Hispanic origin TOTAL Civilian noninstitutional population... Percent of population Employmentpopulation ratio 174, , , , , , , ,397 82,842 62, ,715 83,637 63, , ,639 91,294 54, , ,777 92,007 54, , , ,231 98, , , ,234 98, , ,537 19,832 13, , ,127 13, , ,785 11, , ,299 12, , Less than a high school diploma Civilian noninstitutional population... Percent of population Employmentpopulation ratio 28,583 12, , , , , , ,655 7, , ,903 4, , ,691 4, , ,000 9, , ,701 10, , ,219 1, , ,315 1, ,317 4, , ,552 4, , High school graduates, no college Civilian noninstitutional population., Percent of population Employmentpopulation ratio... 57,518 37, , ,264 57,244 36, , ,178 26,024 19, , ,954 19, , ,494 17, , ,289 17, ,508 30, , ,146 30, , ,112 5, , ,011 4, , ,530 3, , ,658 3, , Less than a bachelor's degree 1 Civilian noninstitutional population. Percent of population Employmentpopulation ratio... 42,955 31, , ,191 32, , ,806 16, , ,353 16, , ,149 15, , , , ,056 26, , , , ,280 4, ,418 4, ,032 2, , ,979 2, , Some college, no degree Civilian noninstitutional population. Percent of population Employmentpopulation ratio... 29, , ,328 21, , , , , , ,559 10, , ,974 10, , ,685 17, , , , , , ,872 3, , ,109 1, , ,102 1, , Associate degree Civilian noninstitutional population. Percent of population Employmentpopulation ratio... 13,330 10, , ,863 10, , ,740 4, , ,999 5, , , ,864 5, , ,372 8, , ,777 9, , ,427 1, , ,546 1, , College graduates Civilian noninstitutional population. Percent of population Employmentpopulation ratio... 45,081 35, , ,863 36, , ,331 19, , ,675 19, , ,750 16, , ,189 16, , , , ,260 30, , ,221 2, , ,382 2, , ,908 1, , ,110 1, , Includes the categories, some college, no degree; and associate degree. NOTE: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 24

32 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A18. and unemployed full and parttime workers by age, sex, and race (In thousands) September 1 Fulltime workers Parttime workers Age, sex, and race 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 fulltime work Looking for parttime work TOTAL Total, 16 years and over 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 112,567 2, , ,278 10, ,234 86,812 13, ,204 1, ,738 99,259 8,951 90,308 78,586 11,722 8, , ,831 5,656 1,175 3, , ,095 2, ,466 4,551 2,462 2,089 17,915 3,346 14,569 10,086 4,484 1, , ,219 1, ,542 4,212 2,369 1,843 15,330 2,930 12,400 8,458 3,941 1, , , , ,930 2, , 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 65,057 1,307 63,750 5,656 58,095 50,085 8,009 59,336 1,126 58,210 5,096 53,114 46,041 7,073 4, , ,426 2, , , ,555 1, ,260 2,187 5,073 1,352 3,721 1,852 1, ,204 2,015 4,189 1,158 3,031 1,394 1, , , ,469 1, 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 47, ,528 4,388 42,139 36,727 5,413 41, ,049 3,855 37,194 32,545 4,649 3, , ,405 2, , , ,540 1, ,207 2,364 12,842 1,994 10,848 8,233 2,615 1, ,339 2,197 11,141 1,773 9,369 7,064 2, , , ,461 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 55,504 1,178 54,326 4,794 49,532 42,479 7,053 50,666 1,017 49,648 4,335 45,314 39,085 6,229 3, , ,875 2, , , ,343 1, ,199 1,865 4,334 1,153 3,181 1,488 1, ,336 1,729 3, ,616 1,128 1, , , , 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 38, ,492 3,579 33,913 29,334 4,579 33, ,117 3,145 29,972 26,037 3,935 3, , ,745 2, , , ,196 1, ,329 2,035 11,294 1,654 9,640 7,283 2, ,781 1,900 9,881 1,456 8,425 6,338 2, , , , Black 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 6, , ,749 5, , , ,222 4, 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, , ,049 5, , , ,211 4, , , , persons are classified as full or parttime workers based on their usual weekly hours at all jobs regardless of the number of hours they are 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: Beginning in January, data reflect revised population controls used in the household survey. 25

33 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A19. persons by occupation, sex, and age (In thousands) Total Men Women Occupation 16 years and over 16 years and over 20 years and over 16 years and over 20 years and over Total 133, ,033 71,603 72,317 68,078 68,823 61,952 62,716 58,753 59,370 Managerial and professional specialty Executive, administrative, and managerial Officials and administrators, public administration Other executive, administrative, and managerial Managementrelated occupations Professional specialty Engineers Mathematical and computer scientists Natural scientists Health diagnosing occupations Health assessment and treating occupations Teachers, college and university Teachers, except college and university Lawyers and judges Other professional specialty occupations 40,892 19, ,105 4,851 21,269 1,966 1, ,089 3, , ,364 41,106 19, ,963 4,927 21,514 2,041 2, ,011 3, , ,326 20,649 11, ,575 2,112 9,629 1,762 1, , ,464 20,451 10, ,187 2,122 9,777 1,849 1, , ,417 20,497 10, ,514 2,111 9,539 1,762 1, , ,404 20,323 10, ,151 2,107 9,702 1,839 1, , ,384 20,243 8, ,530 2,739 11, , , ,900 20,655 8, ,776 2,805 11, , , ,909 20,080 8, ,479 2,720 11, , , ,852 20,486 8, ,722 2,802 11, , , ,857 Technical, sales, and administrative support Technicians and related support Health technologists and technicians Engineering and science technicians Technicians, except health, engineering, and science Sales occupations Supervisors and proprietors Sales representatives, finance and business services Sales representatives, commodities, except retail Sales workers, retail and personal services Salesrelated occupations Administrative support, including clerical Supervisors Computer equipment operators Secretaries, stenographers, and typists Financial records processing Mail and message distributing Other administrative support, including clerical 38,519 4,439 1,706 1,205 1,529 15,918 4,884 2,744 1,632 6, , ,340 2, ,769 38,810 4,313 1,668 1,270 1,375 16,100 4,920 2,908 1,610 6, , ,189 2, ,966 13,908 2, ,953 2,795 1,558 1,197 2, , ,649 14,101 2, ,196 2,979 1,599 1,143 2, , ,571 12,957 2, ,284 2,761 1,526 1,191 1, , ,464 13,261 2, ,579 2,933 1,569 1,134 1, , ,396 24,611 2,337 1, ,965 2,090 1, , , ,269 1, ,119 24,708 2,180 1, ,904 1,941 1, , , ,132 2, ,395 22,950 2,288 1, ,943 2,048 1, , , ,184 1, ,667 22,992 2,134 1, ,877 1,906 1, , , ,075 2, ,850 Service occupations Private household Protective service Service, except private household and protective Foodservice Health service Cleaning and building service Personal service 17, ,439 14,502 6,029 2,462 3,066 2,945 18, ,369 14,942 6,403 2,451 3,088 3,000 7, ,987 5,048 2, , , ,937 5,090 2, , , ,937 4,192 1, , , ,904 4,161 1, , , ,454 3,461 2,169 1,444 2,379 10, ,852 3,772 2,193 1,522 2,365 9, ,442 2,763 2,097 1,374 2,208 9, ,779 3,005 2,105 1,443 2,227 Precision production, craft, and repair Mechanics and repairers Construction trades Other precision production, craft, and repair 14,531 4,728 5,918 3,885 15,005 4,843 6,368 3,794 13,283 4,514 5,795 2,974 13,714 4,608 6,213 2,893 12,967 4,424 5,614 2,928 13,391 4,525 6,026 2,840 1, , , , Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Motor vehicle operators Other transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Construction laborers Other handlers, equipment cleaners, helpers, and laborers 18,202 7,360 5,617 4,288 1,328 5, ,303 18,482 7,262 5,767 4,321 1,446 5,453 1,073 4,380 13,789 4,539 5,060 3,815 1,245 4, ,294 14,063 4,417 5,232 3,866 1,367 4,413 1,046 3,367 12,812 4,392 4,968 3,748 1,220 3, ,622 13,042 4,286 5,096 3,756 1,341 3, ,706 4,414 2, , ,009 4,419 2, , ,012 4,208 2, ,199 2, Farming, forestry, and fishing Farm operators and managers Other farming, forestry, and fishing occupations 3,594 1,072 2,522 3,612 1,243 2,369 2, ,100 2, ,982 2, ,881 2, , NOTE: Beginning in January, data reflect revised population controls used in the household survey. 26

34 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A20. persons by occupation, race, and sex (Percent distribution) Occupation and race Total Men Women TOTAL Total, 16 years and over (thousands) Percent 133, , , , , , Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Farming, forestry, and fishing White Total, 16 years and over (thousands) Percent 112, , , , , , Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Farming, forestry, and fishing Black Total, 16 years and over (thousands) Percent 15, , , , , , Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Farming, forestry, and fishing NOTE: Beginning in January, data reflect revised population controls used in the household survey. 27

35 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A21. persons by industry and occupation (In thousands) September Industry Total employed Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales Administrative support, including clerical Service occupations Other service 1 Private household Precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving Handlers, equipment cleaners, helpers, and laborers Farming, forestry, and fishing Agriculture Mining Construction Manufacturing Durable goods Nondurable goods Transportation and public utilities Wholesale and retail trade Wholesale trade Retail trade Finance, insurance, and real estate Services Private households Other service industries Professional services Public administration 3, ,728 19,450 11,870 7,581 10,019 27,842 5,597 22,245 8,525 49, ,762 32,714 5, ,312 2,993 1,848 1,144 1,449 2, ,895 2,516 7, ,268 4,372 1, ,802 1, , ,582 14,202 1, ,565 2,565 2, ,269 9,183 2,269 1, , , ,531 2, ,493 2,629 7, ,407 5,395 1, , , , ,139 5,322 1, ,780 3,671 2,554 1,117 1,365 1, , ,145 2, ,851 3,432 2, ,502 1, , , , , Includes protective service, not shown separately. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 28

36 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A22. persons in agriculture and nonagricultural industries by age, sex, and class of worker (In thousands) September Agriculture Nonagricultural industries Age and sex Wage and salary workers Selfemployed workers Unpaid family workers Total Total Wage and salary workers Private industries Private household workers Other private industries Government Selfemployed workers Unpaid family workers Total, 16 years and over to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 34 years 35 to 44 years 45 to 54 years 55 to 64 years 65 years and over 2, , ,545 6,521 2,587 3,934 12,773 28,181 33,369 26,681 11,837 3, ,718 6,253 2,507 3,745 11,690 24,454 28,127 21,091 9,451 2, ,934 6,184 2,459 3,724 11,613 24,318 27,936 20,937 9,339 2,608 18, ,082 3,728 5,242 5,591 2, , ,440 2,574 2,495 1, Men, 16 years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 34 years 35 to 44 years 45 to 54 years 55 to 64 years 65 years and over 1, ,243 3,241 1,265 1,976 6,548 15,130 17,630 13,716 6,250 1,729 56,055 3,129 1,239 1,889 6,137 13,581 15,421 11,152 5,176 1, ,996 3,124 1,235 1,889 6,130 13,562 15,409 11,146 5,173 1,453 8, ,550 2,209 2,564 1, , ,578 1, Women, 16 years and over 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 to 34 years 35 to 44 years 45 to 54 years 55 to 64 years 65 years and over ,303 3,281 1,322 1,958 6,225 13,051 15,739 12,965 5,587 1,454 47,663 3,124 1,268 1,856 5,554 10,873 12,706 9,939 4,275 1, ,938 3,060 1,225 1,835 5,483 10,756 12,527 9,792 4,166 1,155 10, ,178 3,033 3,026 1, , NOTE: Beginning in January, data reflect revised population controls used in the household survey. 29

37 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A23. Persons at work in agriculture and nonagricuitural industries by hours of work September Hours of work Thousands of persons Percent distribution All industries Agriculture Nonagricuitural industries All industries Agriculture Nonagricuitural industries Total, 16 years and over 130,474 3, , to 34 hours 1 to 4 hours 5 to 14 hours 15 to 29 hours 30 to 34 hours 28,392 1,064 4,808 14,305 8, ,487 1,004 4,595 13,927 7, hours and over 35 to 39 hours 40 hours 41 hours and over 41 to 48 hours 49 to 59 hours 60 hours and over 102,081 8,572 51,394 42,116 15,045 15,637 11,434 2, , ,609 8,424 50,520 40,665 14,777 15,225 10, Average hours, total at work Average hours, persons who usually work full time NOTE: Beginning in January, data reflect revised population controls used in the household survey. A24. Persons at work 1 to 34 hours in all and nonagricuitural industries by reason for working less than 35 hours and usual full or parttime status (Numbers in thousands) September Reason for working less than 35 hours Total All industries Usually work full time Usually work part time Total Nonagricuitural industries Usually work full time Usually work part time Total, 16 years and over 28,392 8,003 20,390 27,487 7,775 19,712 Economic reasons Slack work or business conditions Could only find parttime work Seasonal work Job started or ended during week 2,854 1, ,215 1, , ,724 1, , , Noneconomic reasons Childcare problems Other family or personal obligations Health or medical limitations In school or training Retired or Social Security limit on earnings Vacation or personal day Holiday, legal or religious Weatherrelated curtailment All other reasons 25, , ,541 1,991 3, ,819 6, , ,632 18, , ,437 1,991 4,187 24, , ,354 1,857 2, ,638 6, , ,561 18, , ,249 1,857 4,077 Average hours: Economic reasons Other reasons NOTE: Beginning in January, data reflect revised population controls used in the household survey. 30

38 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A25. Persons at work in nonagricultural industries by class of worker and usual full or parttime status (Numbers in thousands) September 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 127,096 27,487 2,724 6,616 18,147 99, Wage and salary workers 118,664 24,930 2,404 6,158 16,368 93, Mining Construction 7,822 1, , Manufacturing Durable goods Nondurable goods 18,562 11,336 7,227 1, ,687 10,346 6, Transportation and public utilities... Wholesale and retail trade Finance, insurance, and real estate 9,178 25,565 7,558 1,281 7,854 1, , , ,897 17,710 6, Service industries Private households All other industries Public administration 43, ,125 5,646 10, , , , , , , ,712 4, Selfemployed workers Unpaid family workers 8, , , , Data not shown where base is less than 75,000. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 31

39 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A26. Persons at work in nonagricultural industries by age, sex, race, marital status, and usual full or parttime status (Numbers in thousands) September Worked 1 to 34 hours Average hours Age, sex, race, 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 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 127,096 6,425 2,535 3, ,671 12, ,954 91,687 16,267 27,487 4,498 2,324 2,174 22,990 3,886 19,104 14,251 4,853 2, , ,030 1, , , ,725 4, ,147 4,014 2,255 1,760 14,133 2,784 11,349 7,786 3,563 99,609 1, ,716 97,681 8,831 88,850 77,436 11, Men, 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 67,698 3,218 1,244 1,974 64,480 6,583 57,897 49,067 8,830 10,088 2,120 1, ,968 1,630 6,338 4,271 2,067 1, , , , ,749 2, ,597 1,877 1, ,720 1,074 2,646 1,239 1,407 57,609 1, ,512 4,953 51,558 44,796 6, Women, 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 59,398 3,207 1,291 1,916 56,191 6,134 50,057 42,620 7,437 17,399 2,378 1,191 1,186 15,022 2,256 12,765 9,980 2,786 1, , , , , ,976 2, ,551 2,138 1, ,413 1,711 8,702 6,547 2,156 41, ,169 3,878 37,292 32,641 4, Race White, 16 years and over Men Women 106,373 57,580 48,793 23,472 8,545 14,927 2,095 1,011 1,084 5,508 2,717 2,791 15,869 4,817 11,052 82,900 49,035 33, Black, 16 years and over Men Women 14,538 6,797 7,742 2,848 1,021 1, , ,691 5,775 5, Marital status Men, 16 years and over: Married, spouse present Widowed, divorced, or separated Single (never married) 40,913 8,045 18,740 4,184 1,087 4, , , ,392 36,729 6,958 13, Women, 16 years and over: Married, spouse present Widowed, divorced, or separated Single (never married) 31,494 12,057 15,848 9,112 2,723 5, , ,752 1,568 4,231 22,381 9,334 10, NOTE: Beginning in January, data reflect revised population controls used in the household survey. 32

40 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A27. Persons at work in nonfarm occupations by sex and usual full or parttime status (Numbers in thousands) September 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 1 126,998 27,458 2,709 6,590 18,159 99, Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers 39,799 18,968 20,832 37,425 4,147 15,509 17,769 17, ,268 14,413 14,533 17,882 7,046 5,552 5,284 6,190 2,290 3,900 9, ,209 4,692 6, ,752 1,732 3, , , , , ,910 1,202 2,708 7, ,171 3,353 4, , , ,609 16,678 16,931 27,702 3,324 11,300 13,078 10, ,888 8,661 12,801 14,588 6,140 4,645 3, Men, 16 years and over 1 67,458 9,989 1,287 3,161 5,541 57, Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers 19,964 10,414 9,550 13,725 2,063 7,965 3,697 6, ,860 4,936 13,289 13,646 4,308 5,045 4,294 2, ,137 2, , , ,644 1,489 2, , , , , , , ,952 9,539 8,413 11,460 1,824 6,611 3,024 4, ,584 3,292 11,800 11,359 3,900 4,326 3, ( 2 ) ( 2 ) Women, 16 years and over 1 59,540 17,468 1,421 3,429 12,618 42, Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers 19,835 8,554 11,281 23,700 2,084 7,544 14,073 10, ,477 1,244 4,235 2, ,178 1,415 2,763 7, ,854 4,019 4, , , , , , ,090 5, ,244 2,903 3, , ,657 7,139 8,518 16,243 1,500 4,689 10,054 5, ,369 1,001 3,229 2, Excludes farming, forestry, and fishing occupations. Data not shown where base is less than 75,000. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 33

41 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A28. persons by marital status, race, age, and sex Men Women Marital status, race, and age Thousands of persons Unemployment rates Thousands of persons Unemployment rates Total, 16 years and over Married, spouse present Widowed, divorced, or separated Single (never married) 2, ,552 2, , , ,442 2, , White, 16 years and over Married, spouse present Widowed, divorced, or separated Single (never married) 2, ,072 1, , , , Black, 16 years and over Married, spouse present Widowed, divorced, or separated Single (never married) Total, 25 years and over Married, spouse present Widowed, divorced, or separated Single (never married) 1, , , , White, 25 years and over Married, spouse present Widowed, divorced, or separated Single (never married) 1, , , , Black, 25 years and over Married, spouse present Widowed, divorced, or separated Single (never married) NOTE: Beginning in January, data reflect revised population controls used in the household survey. 34

42 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A29. persons by occupation and sex Thousands of persons s Occupation Total Total Men Women Total, 16 years and over 1 5,661 5,324 Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical 1, , Service occupations Private household Protective service Service, except private household and protective 1, , ( 2 ) ( 2 ) Precision production, craft, and repair Mechanics and repairers, Construction trades Other precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Construction laborers Other handlers, equipment cleaners, helpers, and laborers 1, , ( 2 ) ) 7.9 Farming, forestry, and fishing No previous work experience, 16 to 19 years 20 to 24 years 25 years and over Includes a small number of persons whose last job was in the Armed Forces. 2 Data not shown where base is less than 75,000. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 35

43 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A30. persons by industry and sex Thousands of persons s Industry Total Total Men Women Total, 16 years and over 5,661 5,324 Nonagricultural private wage and salary workers 4,504 4,209 Mining Construction Manufacturing Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Fabricated metal products Machinery and computing equipment Electrical machinery, equipment, and supplies Transportation equipment Automobiles Other transportation equipment Professional and photographic equipment Other durable goods industries Nondurable goods Food and kindred products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Rubber and miscellaneous plastics products Other nondurable goods industries Transportation and public utilities Transportation Communications and other public utilities Wholesale and retail trade Wholesale trade Retail trade Finance, insurance, and real estate Service industries Professional services Other service industries , , , , , , Agricultural wage and salary workers Government, selfemployed, and unpaid family workers No previous work experience NOTE: Beginning in January, data reflect revised population controls used in the household survey. 36

44 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A31. persons by reason for unemployment, sex, age, and race (Numbers In thousands) Reason Total, 16 years and over Men, 20 years and over Women, 20 years and over Both sexes, 16 to 19 years White Black NUMBER OF UNEMPLOYED Total unemployed Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Permanent job losers Persons who completed temporary jobs Job leavers Reentrants New entrants 5,661 2, ,678 1, , ,324 2, ,662 1, , ,208 1, ,130 1, , , , , ,002 1, , , ,903 1, , , , , PERCENT DISTRIBUTION 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, data reflect revised population controls used in the household survey. 37

45 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A32. persons by reason for unemployment, sex, age, and duration of unemployment (Percent distribution) September Total unemployed Duration of unemployment Reason, sex, and age Thousands of persons Percent Less than 5 weeks 5 to 14 weeks Total 15 weeks and over 15 to 26 weeks 27 weeks and over Total, 16 years and over Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Permanent job losers Persons who completed temporary jobs Job leavers Reentrants New entrants 5,324 2, ,662 1, , Men, 20 years and over Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Permanent job losers Persons who completed temporary jobs Job leavers Reentrants New entrants 2,130 1, Women, 20 years and over Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Permanent job losers Persons who completed temporary jobs Job leavers Reentrants New entrants 2, Both sexes, 16 to 19 years Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Permanent job losers Persons who completed temporary jobs Job leavers Reentrants New entrants 1, () () () ) ) 7.5 ) Data not shown where base is less than 75,000. NOTE: Beginning in January, data reflect revised population controls used in the household survey. A33. total and fulltime workers by duration of unemployment Total Fulltime workers Duration of unemployment Thousands of persons Percent distribution Thousands of persons Percent distribution Total 16 years and over Less than 5 weeks 5 to 14 weeks 5 to 10 weeks 11 to 14 weeks 15 weeks and over. 15 to 26 weeks 27 weeks and over 27 to 51 weeks 52 weeks and over 5,661 2,627 1,664 1, , ,324 2,547 1,583 1, , ,335 1,847 1, , ,152 1,807 1, , Average (mean) duration in weeks Median duration in weeks NOTE: Beginning in January, data reflect revised population controls used in the household survey. 38

46 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A34. persons by age, sex, race, marital status, and duration of unemployment September Sex, age, race, and marital status Total Less than 5 weeks Thousands of persons 5 to 14 weeks Total 15 weeks and over 15 to 26 weeks 27 weeks and over Average (mean) duration Weeks Median duration TOTAL Total, 16 years and over 16 to 19 years 20 to 24 years 25 to 34 years 35 to 44 years 45 to 54 years 55 to 64 years 65 years and over 5,324 1, ,109 1, , , , Men, 16 years and over 16 to 19 years 20 to 24 years 25 to 34 years 35 to 44 years 45 to 54 years 55 to 64 years 65 years and over 2, , Women, 16 years and over 16 to 19 years 20 to 24 years 25 to 34 years 35 to 44 years 45 to 54 years 55 to 64 years 65 years and over 2, , Race White, 16 years and over Men Women 3,903 1,980 1,924 1,957 1, , Black, 16 years and over Men Women 1, Marital status Men, 16 years and over: Married, spouse present Widowed, divorced, or separated... Single (never married) , Women, 16 years and over: Married, spouse present Widowed, divorced, or separated... Single (never married) , Data not shown where base is less than 75,000. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 39

47 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A35. persons by occupation, industry, and duration of unemployment September Thousands of persons Weeks Occupation and industry Total Less than 5 weeks 5 to 14 weeks Total 15 weeks and over 15 to 26 weeks 27 weeks and over Average (mean) duration Median duration OCCUPATION Managerial and professional specialty Technical, sales, and administrative support Service occupations Precision production, craft, and repair Operators, fabricators, and laborers Farming, forestry, and fishing 810 1, , INDUSTRY 1 Agriculture Construction Manufacturing Durable goods Nondurable goods Transportation and public utilities Wholesale and retail trade Finance, insurance, and real estate Services Public administration , , No previous work experience Includes wage and salary workers only. NOTE: Beginning in January, data reflect revised population controls used in the household survey. A36. Persons not in the labor force by desire and availability for work, age, and sex (In thousands) Total Age Sex Category 16 to 24 years 25 to 54 years 55 years and over Men Women Total not in the labor force Do not want a job now 1 Want a job 1 Did not search for work in previous year Searched for work in previous year* Not available to work now Available to work now Reason not currently looking: Discouragement over job prospects 3 Reasons other than discouragement Family responsibilities In school or training Ill health or disability Other 4 69,048 64,853 4,196 2,486 1, , ,804 65,619 4,184 2,548 1, , ,351 10,846 1, ,360 10,896 1, ,768 16,926 1,842 1, ,236 17,282 1,954 1, ,929 37, ,208 37, ,582 23,785 1,797 1, ,980 24,116 1,863 1, ,466 41,068 2,398 1, ,824 41,503 2,321 1, 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 childcare and transportation problems, as well as a small number for which reason for nonparticipation was not ascertained. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 40

48 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A37. Multiple jobholders by selected demographic and economic characteristics (Numbers in thousands) Both sexes Men Women Characteristic Number Rate 1 Number Rate 1 Number Rate 1 AGE Total, 16 years and over 2 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 to 64 years 65 years and over 7, , ,559 5, , , ,449 5, , , ,458 3, , , ,475 2, , , ,101 2, , , ,973 2, RACE AND HISPANIC ORIGIN White Black Hispanic origin 6, , , , , , MARITAL STATUS Married, spouse present Widowed, divorced, or separated Single (never married) 4,238 1,365 1,981 4,146 1,328 1, , , , ,013 1, , FULL OR PARTTIME STATUS Primary job full time, secondary job part time... Primary and secondary jobs both part time Primary and secondary jobs both full time Hours vary on primary or secondary job 4,171 1, ,420 4,072 1, ,447 2, , ,742 1, ,734 1, Multiple jobholders as a percent of all employed persons in specified 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: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 41

49 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED A38. Employment status of male Vietnamera veterans and nonveterans by age (Numbers in thousands) Civilian noninstitutional population Veteran status and age Total Number Percent of labor force VIETNAMERA VETERANS Total, 40 years and over 40 to 54 years 40 to 44 years 45 to 49 years 50 to 54 years 55 years and over 7,749 5, ,798 3,122 2,359 7,697 4, ,462 3,185 2,798 6,321 4, ,577 2,727 1,619 6,163 4, ,274 2,741 1,945 6,150 4, ,525 2,659 1,589 6,001 4, ,224 2,671 1, NONVETERANS Total, 40 to 54 years 40 to 44 years 45 to 49 years 50 to 54 years 21,529 9,478 7,429 4,623 22,543 9,700 7,934 4,909 19,414 8,763 6,697 3,954 20,463 8,924 7,200 4,339 18,980 8,568 6,549 3,863 19,989 8,697 7,039 4, NOTE: Male Vietnamera veterans are men who served in the Armed Forces between 5, 1964 and May 7, Nonveterans are men who have never served in the Armed Forces. Beginning in January, data reflect revised population controls used in the household survey. 42

50 Need information from the Bureau of Labor Statistics You can get it now on the WEB. Here are the Bureau's addresses. / \ Bureau of Labor Statistics Division of Information Services BLS Regional Offices Employment and Unemployment: Employment, hours, and earnings by industry National State and area National labor force statistics Region, State, and metropolitan area labor force data Longitudinal research Covered employment and wages Occupational employment statistics Mass layoff statistics Prices and Living Conditions: Consumer price indexes Producer price indexes Consumer Expenditure Survey Compensation and Working Conditions: National Compensation Survey Collective bargaining Employment cost trends Employee Benefits Survey Occupational Compensation Survey Safety and health Productivity: Quarterly labor productivity Industry productivity Multifactor productivity Employment Projections International data: Foreign labor statistics U.S. import and export price indexes

51 ESTABLISHMENT DATA HISTORICAL EMPLOYMENT B1. Employees on nonfarm payrolls by major industry, 1948 to date (In thousands) Year and month Total Total private Goodsproducing Total Mining Construction Manufacturing Serviceproducing Total Transportation and public utilities Wholesale trade Retail trade Finance, insurance, and real estate Services Government Federal State Local Annual averages , , : September.. October November... December... : January February March April May June P September? 44,866 43,754 45,197 47,819 48,793 50,202 48,990 50,641 52,369 52,855 51,322 53,270 54,189 53,999 55,549 56,653 58,283 60,763 63,901 65,803 67,897 70,384 70,880 71,211 73,675 76,790 78,265 76,945 79,382 82,471 86,697 89,823 90,406 91,152 89,544 90,152 94,408 97,387 99, , , , , , , , , , , , , , , , , , , , , , , , , , ,768 39,216 37,897 39,170 41,430 42,185 43,556 42,238 43,727 45,091 45,239 43,483 45,186 45,836 45,404 46,660 47,429 48,686 50,689 53,116 54,413 56,058 58,189 58,325 58,331 60,341 63,058 64,095 62,259 64,511 67,344 71,026 73,876 74,166 75,121 73,707 74,282 78,384 80,992 82,651 84,948 87,823 90,105 91,098 89,847 89,956 91,872 95,036 97, , , , ,616 18,774 17,565 18,506 19,959 20,198 21,074 19,751 20,513 21,104 20,967 19,513 20,411 20,434 19,857 20,451 20,640 21,005 21,926 23,158 23,308 23,737 24,361 23,578 22,935 23,668 24,893 24,794 22,600 23,352 24,346 25,585 26,461 25,658 25,497 23,812 23,330 24,718 24,842 24,533 24,674 25,125 25,254 24,905 23,745 23,231 23,352 23,908 24,265 24,493 24,962 25,414 25, ,027 1,139 1, ,198 2,194 2,364 2,637 2,668 2,659 2,646 2,839 3,039 2,962 2,817 3,004 2,926 2,859 2,948 3,010 3,097 3,232 3,317 3,248 3,350 3,575 3,588 3,704 3,889 4,097 4,020 3,525 3,576 3,851 4,229 4,463 4,346 4,188 3,904 3,946 4,380 4,668 4,810 4,958 5,098 5,171 5,120 4,650 4,492 4,668 4,986 5,160 5,418 5,691 6,020 6,404 15,582 14,441 15,241 16,393 16,632 17,549 16,314 16,882 17,243 17,176 15,945 16,675 16,796 16,326 16,853 16,995 17,274 18,062 19,214 19,447 19,781 20,167 19,367 18,623 19,151 20,154 20,077 18,323 18,997 19,682 20,505 21,040 20,285 20,170 18,780 18,432 19,372 19,248 18,947 18,999 19,314 19,391 19,076 18,406 18,104 18,075 18,321 18,524 18,495 18,675 18,805 18,543 26,092 26,189 26,691 27,860 28,595 29,128 29,239 30,128 31,264 31,889 31,811 32,857 33,755 34,142 35,098 36,013 37,278 38,839 40,743 42,495 44,158 46,023 47,302 48,276 50,007 51,897 53,471 54,345 56,030 58,125 61,113 63,363 64,748 65,655 65,732 66,821 69,690 72,544 74,811 77,284 80,084 82,630 84,497 84,504 85,370 87,361 90,256 92,925 95,115 97, , ,304 4,189 4,001 4,034 4,226 4,248 4,290 4,084 4,141 4,244 4,241 3,976 4,011 4,004 3,903 3,906 3,903 3,951 4,036 4,158 4,268 4,318 4,442 4,515 4,476 4,541 4,656 4,725 4,542 4,582 4,713 4,923 5,136 5,146 5,165 5,081 4,952 5,156 5,233 5,247 5,362 5,512 5,614 5,777 5,755 5,718 5,811 5,984 6,132 6,253 6,408 6,611 6,826 2,612 2,610 2,643 2,735 2,821 2,862 2,875 2,934 3,027 3,037 2,989 3,092 3,153 3,142 3,207 3,258 3,347 3,477 3,608 3, , ,014 4,127 4,291 4,447 4,430 4,562 4,723 4,985 5,221 5,292 5,375 5,295 5,283 5,568 5,727 5,761 5,848 6,030 6,187 6,173 6,081 5,997 5,981 6,162 6,378 6,482 6,648 6,800 6,924 6,659 6,654 6,743 7,007 7,184 7,385 7,360 7,601 7,831 7,848 7,761 8,035 8,238 8,195 8,359 8,520 8,812 9,239 9,637 9,906 10,308 10,785 11,034 11,338 11,822 12,315 12,539 12,630 13,193 13,792 14,556 14,972 15,018 15,171 15,158 15,587 16,512 17,315 17,880 18,422 19,023 19,475 19,601 19,284 19,356 19,773 20,507 21,187 21,597 21,966 22,295 22,788 1,800 1,828 1,888 1,956 2,035 2,111 2,200 2,298 2,389 2,438 2,481 2,549 2,628 2,688 2,754 2,830 2,911 2,977 3,058 3,185 3,337 3,512 3,645 3,772 3,908 4,046 4,148 4,165 4,271 4,467 4,724 4,975 5,160 5,298 5,340 5,466 5,684 5,948 6,273 6,533 6,630 6,668 6,709 6,646 6,602 6,757 6,806 6,911 7,109 7,389 7,569 5,181 5,239 5,356 5,547 5,699 5,835 5,969 6, ,708 6,765 7,087 7,378 7,619 7,982 8,277 8, ,276 12,857 13,441 13, ,302 16,252 17,112 17,890 18, , ,927 22,957 24, ,907 27,934 28,336 29,052 30,197 31,579 33,117 34,454 36,040 37,533 39,027 1,863 1, ,302 2,420 2,305 2,188 2,187 2,209 2, ,233 2,270 2,279 2, ,719 2, ,731 2,696 2,684 2,663 2,724 2,748 2,733 2,727 2,753 2,773 2,866 2,772 2,739 2, ,899 2,943 2, ,085 2,966 2,969 2,915 2,870 2,822 2,757 2,699 2,686 2,669 d) (1) (D 0) (1) 0) (D 168 1,250 1,328 1,415 1,484 1, , ,856 1,996 2,141 2,302 2,442 2,533 2,664 2,747 2,859 2,923 3,039 3,179 3,273 3,377 3,474 3,541 3,610 3,640 3,640 3,662 3,734 3, ,967 4,076 4,182 4, ,408 4,488 4,576 4,635 4,606 4,582 4,612 4,695 Monthly data, seasonally adjusted 109, , , , , , , , , , , , ,306 25,460 25,483 25,527 25,561 25,677 25,624 25,738 25,725 25,684 25,700 25,756 25,643 25, ,439 6,470 6,516 6,552 6,652 6,618 6,726 6,694 6,666 6,670 6,675 6,705 18,494 18,484 18,484 18,479 18,495 18,473 18,476 18,492 18,479 18,493 18,548 18,431 18, , , , , , , , , , , , , ,162 6,866 6,875 6,898 6,911 6,925 6,937 6,953 6,970 6,962 6,985 7,010 6,941 7,046 6,962 6,973 7,002 7,005 7,011 7,033 7,055 7,048 7,049 7,050 7,062 7,065 22,844 22,863 22,893 22,936 22,973 22,978 23,027 23,197 23,064 23,122 23,196 23,188 23,189 7,589 7,599 7,604 7,613 7,612 7,624 7,621 7,610 7,600 7,588 7,586 7,606 7,622 39,321 39,482 39,606 39,707 39,844 39,914 40,090 40,195 40,220 40,401 40,403 40,578 40,778 2,655 2,647 2,646 2,646 2,663 2,700 2,816 2,885 3,238 3,092 2,819 2,657 2,624 4,714 4,722 4, ,725 4,728 4,733 4,744 4,737 4,716 4,744 4,763 4,767 (1) (1) (1) (1) (1) (1) (1) 3,558 3,819 4,071 4,232 4,366 4,547 4,708 4,881 5,121 5,392 5,700 6, , , ,146 8,407 8,758 8,865 9,023 9,446 9, , ,434 9,482 9,687 9, ,339 10,609 10,914 11,081 11,267 11,438 11,682 11, ,525 12, ,879 12,902 12,935 12,963 12,966 12,998 13,038 13, Not available. 2 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: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all unadjusted data (beginning April ) and all seasonally adjusted data (beginning January 1996) are subject to revision. 44

52 ESTABLISHMENT DATA HISTORICAL HOURS AND EARNINGS B2. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry, 1964 to date Year and month Total private 1 Weekly hours Hourly earnings Weekly earnings Mining Weekly hours Hourly earnings Weekly earnings Construction Weekly hours Hourly earnings Weekly earnings Annual averages : September. October November.. December.. : January February... March April May June P SeptemberP $ $ $ $ $ Monthly data, not seasonally adjusted $ $ $ $ $ $ $ See footnotes at end of table. 45

53 ESTABLISHMENT DATA HISTORICAL HOURS AND EARNINGS B2. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry, 1964 to date Continued Year and month Manufacturing Weekly hours Hourly earnings Hourly earnings, excluding overtime Weekly earnings Transportation and public utilities Weekly hours Hourly earnings Weekly earnings Wholesale trade Weekly hours Hourly earnings Weekly earnings Annual averages : September. October November.. December.. : January February... March April May June P SeptemberP $ $ $ $ $ $ Monthly data, not seasonally adjusted $ $ $ $ $ $ $ $ See footnotes at end of table. 46

54 ESTABLISHMENT DATA HISTORICAL HOURS AND EARNINGS B2. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry, 1964 to date Continued Year and month Weekly hours Retail trade Hourly earnings Weekly earnings Weekly hours Finance, insurance, and real estate Hourly earnings Weekly earnings Weekly hours Services Hourly earnings Weekly earnings Annual averages $ $ $ $ $ $ Monthly data, not seasonally adjusted : September. October November.. December.. : January February... March April May June P SeptemberP $ $ $ $ $ $ Data relate to production workers in mining and manufacturing; construction workers in construction; and nonsupervisory workers in transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. p = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all unadjusted data from April forward are subject to revision. 47

55 ESTABLISHMENT DATA EMPLOYMENT SEASONALLY ADJUSTED B3. Employees on nonfarm payrolls by major industry and selected component groups, seasonally adjusted (In thousands) Industry Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P P Total 129, , , , , , , , , , , , ,768 Total private 109, , , , , , , , , , , , ,306 Goodsproducing 25,460 25,483 25,527 25,561 25,677 25,624 25,738 25,725 25,684 25,700 25,756 25,643 25,606 Mining Metal mining Coal mining Oil and gas extraction Nonmetallic minerals, except fuels Construction General building contractors Heavy construction, except building.. Special trade contractors 6,439 1, ,115 6,470 1, ,134 6,516 1, ,170 6,552 1, ,196 6,652 1, ,262 6,618 1, ,242 6,726 1, ,313 6,694 1, ,298 6,666 1, ,281 6,668 1, ,293 6,670 1, ,291 6,675 1, ,288 6,705 1, ,315 Manufacturing 18,494 18,484 18,484 18,479 18,495 18,473 18,476 18,492 18,479 18,493 18,548 18,431 18,365 Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Fabricated metal products Industrial machinery and equipment Computer and office equipment... Electronic and other electrical equipment Electronic components and accessories Transportation equipment Motor vehicles and equipment Aircraft and parts Instruments and related products... Miscellaneous manufacturing 11, ,518 2, , ,880 1, , ,519 2, , ,873 1, , ,520 2, , ,870 1, , ,521 2, , ,867 1, , ,523 2, , ,871 1, , ,525 2, , ,855 1, , ,528 2, , ,865 1, , ,534 2, , ,859 1, , ,535 2, , ,863 1, , ,540 2, , ,864 1, , ,539 2, , ,863 1, , ,538 2, , , , ,532 2, , , Nondurable goods Food and kindred products Tobacco products Textile mill products Apparel and other textile products... Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and misc. plastics products. Leather and leather products 7,404 1, ,551 1, , ,401 1, ,551 1, , ,399 1, ,549 1, , ,392 1, ,548 1, , ,396 1, ,549 1, , ,385 1, ,550 1, , ,382 1, ,551 1, , ,388 1, ,554 1, , ,373 1, ,552 1, , ,373 1, ,558 1, , ,387 1, ,561 1, , ,345 1, ,560 1, , ,320 1, ,560 1, Serviceproducing 103, , , , , , , , , , , , ,162 Transportation and public utilities... Transportation Railroad transportation Local and interurban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services Communications and public utilities., Communications Electric, gas, and sanitary services 6,866 4, , , ,430 1, ,875 4, , , ,434 1, ,898 4, , , ,445 1, ,911 4, , , ,452 1, ,925 4, , , ,455 1, ,937 4, , , ,458 1, ,953 4, , , ,461 1, ,970 4, , , ,461 1, ,962 4, , , ,461 1, ,985 4, , , ,475 1, ,010 4, , , ,474 1, ,941 4, , , ,393 1, ,046 4, , , ,488 1, Wholesale trade Durable goods Nondurable goods 6,962 4,143 2,819 6,973 4,155 2,818 6,989 4,165 2,824 7,002 4,173 2,829 7,005 4,174 2,831 7,011 4,177 2,834 7,033 4,185 2,848 7,055 4,201 2,854 7,048 4,199 2,849 7,049 4,195 2,854 7,050 4,205 2,845 7,062 4,201 2,861 7,065 4,196 2,869 See footnotes at end of table. 48

56 B3. Employees on nonfarm payrolls by major industry and selected component groups, seasonally adjusted Continued (In thousands) ESTABLISHMENT DATA EMPLOYMENT SEASONALLY ADJUSTED Industry Oct. Nov. Dec Jan. Feb. Mar. Apr. May June P P Retail trade Building materials and garden supplies General merchandise stores Department stores Food stores Automotive dealers and service stations New and used car dealers Apparel and accessory stores Furniture and home furnishings stores Eating and drinking places Miscellaneous retail establishments 22, ,757 2,414 3,495 2,372 1,087 1,183 1,092 7,956 2,995 22,863 1,004 2,752 2,408 3, ,089 1,186 1,093 7,950 3,005 22,893 1,008 2,752 2,406 3,498 2,380 1,092 1,190 1,091 7,966 3,008 22,936 1,012 2,766 2,416 3,501 2,386 1,094 1,182 1,098 7,986 3,005 22,973 1,016 2,765 2,419 3,501 2,399 1,097 1,176 1,099 7,998 3,019 22,978 1,020 2,762 2,417 3,503 2,394 1,100 1,184 1,102 7,992 3,021 23,027 1,034 2,756 2,409 3,502 2,407 1,105 1,188 1,111 8,000 3,029 23,197 1,032 2,791 2,443 3,522 2,410 1,106 1,195 1,113 8,097 3,037 23,064 1,025 2,744 2,388 3,516 2,408 1,107 1,195 1,113 8,028 3,035 23,122 1,018 2,741 2,386 3,515 2,412 1,110 1,197 1,118 8,071 3,050 23,196 1,018 2,727 2,373 3,519 2,411 1,111 1,206 1,119 8,132 3,064 23,188 1,020 2,738 2,390 3,522 2,417 1,114 1,203 1,121 8,098 3,069 23,189 1,015 2,750 2,399 3,525 2,420 1,118 1,205 1,120 8,077 3,077 Finance, insurance, and real estate... Finance Depository institutions Commercial banks Savings institutions Nondepository institutions Mortgage bankers and brokers Security and commodity brokers Holding and other investment offices Insurance Insurance carriers Insurance agents, brokers, and service Real estate 7,589 3,702 2,063 1, ,376 1, ,511 7,599 3,704 2,063 1, ,378 1, ,517 7,604 3,707 2,061 1, ,375 1, ,522 7,613 3,710 2,059 1, ,378 1, ,525 7,612 3,709 2,058 1, ,372 1, ,531 7,624 3,717 2,057 1, ,373 1, ,534 7,621 3,713 2,054 1, ,373 1, ,535 7,610 3,709 2,052 1, ,365 1, ,536 7,600 3,703 2,044 1, ,361 1, ,536 7,588 3,705 2,042 1, ,359 1, ,524 7,586 3,708 2,036 1, ,354 1, ,524 7,606 3,716 2,037 1, ,357 1, ,533 7,622 3,727 2,036 1, ,355 1, ,540 Services 1 Agricultrual services Hotels and other lodging places Personal services Business services Services to buildings Personnel supply services Help supply services Computer and data processing services Auto repair, services, and parking Miscellaneous repair services Motion pictures Amusement and recreation services... Health services Offices and clinics of medical doctors Nursing and personal care facilities... Hospitals Home health care services Legal services Educational services Social services Child day care services Residential care Museums and botanical and zoological gardens Membership organizations Engineering and management services Engineering and architectural services Management and public relations 39, ,863 1,243 9, ,678 3,298 1,866 1, ,672 10,015 1,888 1,785 3, ,000 2,294 2, ,430 3, ,044 39, ,863 1,247 9, ,712 3,327 1,874 1, ,691 10,027 1,893 1,785 3, ,003 2,299 2, ,431 3, ,054 39, ,868 1,252 9, ,734 3,343 1,880 1, ,701 10,041 1,898 1,785 3, ,005 2,305 2, ,434 3, ,058 39, ,868 1,257 9, ,748 3,358 1,888 1, ,703 10,053 1,903 1,787 3, ,007 2,309 2, ,438 3, ,068 39, ,866 1,263 9, ,753 3,361 1,896 1, ,721 10,066 1,910 1,788 4, ,008 2,308 2, ,439 3, ,074 39, ,868 1,265 9,615 1,000 3,773 3,382 1,906 1, ,723 10,078 1,914 1,790 4, ,007 2,309 2, ,439 3, ,077 40, ,885 1,265 9,681 1,004 3,817 3,418 1,915 1, ,729 10,091 1,920 1,791 4, ,007 2,329 2, ,440 3, ,085 40, ,902 1,272 9,735 1,001 3,885 3,485 1,927 1, ,752 10,093 1,925 1,789 3, ,004 2,329 2, ,439 3, ,088 40, ,904 1,262 9, ,855 3,440 1,929 1, ,755 10,104 1,928 1,788 4, ,006 2,356 2, ,438 3, ,096 40, ,922 1,271 9, ,873 3,444 1,933 1, ,789 10,116 1,928 1,786 4, ,009 2,374 2, ,441 3,415 1,005 1,110 40, ,925 1,273 9,768 1,002 3,851 3,433 1,950 1, ,795 10,143 1,930 1,787 4, ,012 2,374 2, ,429 3,411 1,007 1,107 40, ,923 1,285 9, ,873 3,444 1,954 1, ,808 10,157 1,933 1,792 4, ,014 2,389 2, ,433 3,435 1,010 1,116 40, ,927 1,284 9, ,907 3,513 1,958 1, ,793 10,183 1,945 1,793 4, ,013 2,388 2, ,450 3,454 1,013 1,121 Government Federal Federal, except Postal Service State Education Other State government Local Education Other local government 20,223 2,655 1,785 4,714 1,978 2,736 12,854 7,299 5,555 20,248 2,647 1,779 4,722 1,979 2,743 12,879 7,308 5,571 20,271 2,646 1,780 4,723 1,980 2,743 12,902 7,323 5,579 20,308 2,646 1,780 4,727 1,983 2,744 12,935 7,343 5,592 20,351 2,663 1,797 4,725 1,981 2,744 12,963 7,356 5,607 20,394 2,700 1,835 4,728 1,981 2,747 12,966 7,355 5, s547 2,816 1,951 4,733 1,982 2,751 12,998 7,373 5,625 20,667 2,885 2,022 4,744 1,990 2,754 13,038 7,408 5,630 21,012 3,238 2,374 4,737 1,983 2,754 13,037 7,395 5,642 20,802 3,092 2,230 4,716 1,967 2,749 12,994 7,361 5,633 20,606 2,819 1,954 4,744 1,994 2,750 13,043 7,394 5,649 20,498 2,657 1,790 4,763 2,000 2,763 13,078 7,400 5,678 20,462 2,624 1,761 4,767 1,997 2,770 13,071 7,390 5,681 1 Includes other industries, not shown separately. P = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all seasonally adjusted data from January 1996 forward are subject to revision. 49

57 ESTABLISHMENT DATA WOMEN EMPLOYEES SEASONALLY ADJUSTED B4. Women employees on nonfarm payrolls by major industry and manufacturing group, seasonally adjusted (In thousands) Industry Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June Total 62,395 62,487 62,591 62,713 62,822 62,936 63,078 63,137 63,315 63,616 63,737 63,772 63,738 Total private 51,066 51,127 51,209 51,318 51,396 51,493 51,604 51,644 51,740 51,967 51,919 52,053 52,179 Goodsproducing 6,684 6,667 6,666 6,661 6,659 6,673 6,678 6,682 6,670 6,685 6,685 6,681 6,713 Mining Construction Manufacturing 5,892 5,873 5,871 5,863 5,860 5,868 5,872 5,871 5,859 5,871 5,866 5,858 5,891 Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Fabricated metal products Industrial machinery and equipment Electronic and other electrical equipment Transportation equipment Instruments and related products Miscellaneous manufacturing 2, d) 173 2, ) 173 2, (1) 174 2, (D 174 2, ) 174 2, (1) 175 2, ) 175 2, (D 173 2, (1) 172 2, ) 173 2, (D 171 2, (1) 170 2, ) 173 Nondurable goods Food and kindred products Tobacco products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and misc. plastics products Leather and leather products Serviceproducing Transportation and public utilities Wholesale trade 2, ,711 2,087 2,142 2, ,820 2,099 2,146 2, ,925 2,108 2,151 2, ,052 2,115 2,157 2, ,163 2,123 2,160 2, ,263 2,131 2,166 2, ,400 2,147 2,168 2, ,455 2,147 2,172 2, ,645 2,151 2,180 2, ,931 2,154 2,189 2, ,052 2,150 2,200 2, ,091 2,157 2,206 2, ,025 2,166 2,203 Retail trade 12,024 12,011 12,003 12,006 12,004 12,016 12,033 12,034 12,045 12,159 12,106 12,135 12,176 Finance, insurance, and real estate 4,738 4,748 4,750 4,754 4,752 4,752 4,756 4,761 4,761 4,759 4,752 4,746 4,748 Services 23,391 23,456 23,531 23,625 23,698 23,755 23,822 23,848 23,933 24,021 24,026 24,128 24,173 Government Federal State Local 11,329 1,128 2,413 7,788 11,360 1,128 2,419 7,813 11,382 1,130 2,426 7,826 11,395 1,128 2,432 7,835 11,426 1,131 2,439 7,856 11,443 1,130 2,440 7,873 11,474 1,141 2,441 7,892 11,493 1,161 2,443 7,889 11,575 1,219 2,447 7,909 11,649 1,257 2,452 7,940 11,818 1,429 2,447 7,942 11,719 1,360 2,443 7,916 11,559 1,227 2,452 7,880 1 This series is not published seasonally adjusted because the seasonal component, which is small relative to the trendcycle and irregular components, cannot be separated with sufficient precision. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all seasonally adjusted data from January 1996 forward are subject to revision. 50

58 ESTABLISHMENT DATA EMPLOYMENT SEASONALLY ADJUSTED B5. Production or nonsupervisory workers 1 on private nonfarm payrolls by major industry and manufacturing group, seasonally adjusted (In thousands) Industry Oct. Nov. Dec Jan. Feb. Mar. Apr. May June P P Total private 89,238 89,491 89,659 89,847 90,185 90,199 90,474 90,799 90,624 90,835 91,024 91,003 91,195 Goodsproducing 18,070 18,101 18,134 18,156 18,318 18,255 18,297 18,272 18,243 18,247 18,302 18,176 18,171 Mining Construction 4,973 4,999 5,034 5,055 5,205 5,158 5,212 5,179 5,158 5,161 5,159 5,149 5,182 Manufacturing 12,700 12,702 12,702 12,701 12,713 12,697 12,683 12,689 12,682 12,683 12,741 12,629 12,592 Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Fabricated metal products Industrial machinery and equipment Electronic and other electrical equipment Transportation equipment Motor vehicles and equipment Instruments and related products Miscellaneous manufacturing 7, ,138 1,341 1,043 1, (2) 274 7, ,140 1,340 1,042 1, (2) 275 7, ,141 1,342 1,041 1, (2) 275 7, ,142 1,343 1,039 1, (2) 276 7, ,144 1,344 1,042 1, (2) 276 7, ,146 1,351 1,043 1, (2) 275 7, ,148 1,341 1,041 1, (2) 274 7, ,152 1,342 1,048 1, (2) 275 7, ,154 1,343 1,047 1, (2) 271 7, ,158 1,349 1,051 1, (2) 270 7, ,165 1,356 1,063 1, (2) 270 7, ,157 1,356 1,064 1, (2) 270 7, ,152 1,348 1,061 1, (2) 268 Nondurable goods Food and kindred products Tobacco products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and misc. plastics products Leather and leather products 5,120 1, ,121 1, ,123 1, ,122 1, ,121 1, ,105 1, ,103 1, ,105 1, ,098 1, ,090 1, ,112 1, ,061 1, ,049 1, Serviceproducing 71,168 71,390 71,525 71,691 71,867 71,944 72,177 72,527 72,381 72,588 72,722 72,827 73,024 Transportation and public utilities 5,687 5,694 5,709 5,721 5,747 5,749 5,783 5,801 5,795 5,808 5,842 5,781 5,865 Wholesale trade 5,558 5,569 5,580 5,593 5,592 5,597 5,612 5,623 5,625 5,622 5,619 5,630 5,629 Retail trade 20,104 20,124 20,140 20,193 20,229 20,229 20,265 20,441 20,309 20,354 20,413 20,397 20,390 Finance, insurance, and real estate 5,553 5,555 5,558 5,560 5,564 5,567 5,562 5,555 5,549 5,545 5,552 5,567 5,585 Services 34,266 34,448 34,538 34,624 34,735 34,802 34,955 35,107 35,103 35,259 35,296 35,452 35,555 1 Data relate to production workers in mining and manufacturing; construction workers in construction; and nonsupervisory workers in transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. 2 This series is not published seasonally adjusted because the seasonal component, which is small relative to the trendcycle and irregular components, cannot be separated with sufficient precision. P = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all seasonally adjusted data from January 1996 forward are subject to revision. 51

59 ESTABLISHMENT DATA DIFFUSION INDEXES SEASONALLY ADJUSTED B6. Diffusion indexes of employment change, seasonally adjusted (Percent) Time span Jan. Feb. Mar. Apr. May June Oct. Nov. Dec. Private nonfarm payrolls, 356 industries 1 Over 1month span: P P Over 3month span: P P Over 6month span: P P Over 12month span: P P Manufacturing payrolls, 139 industries 1 Over 1 month span: P P Over 3month span: P P Over 6month span: P P Over 12month span: P P Based on seasonally adjusted data for 1, 3, and 6month spans and unadjusted data for the 12month span. Data are centered within the span. p = preliminary. NOTE: Figures are the percent of industries with employment increasing plus onehalf of the industries with unchanged employment, where 50 percent indicates an equal balance between industries with increasing and decreasing employment. Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all unadjusted data (beginning April ) and all seasonally adjusted data (beginning January 1996) are subject to revision. 52

60 ESTABLISHMENT DATA STATE EMPLOYMENT SEASONALLY ADJUSTED B7. Employees on nonfarm payrolls by State and major industry, seasonally adjusted (In thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Total 1 Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan 2 Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming 1, ,17 1, ,03 2, , , , ,968 2, ,46 1,32 1, , ,37 3, ,54 2, , , , , , ,46 1, , , , ,16 1, ,41 2, , , , ,14 14,06 2,15 1, ,93 3, , , , ,32 1, , , ,25 4,54 2, ,16 2, , ,47 3, , ,46 1, , , ,68 9, , , , , , , ,149 14,08 2, , ,96 3, ,97 2,98 1, ,33 1,80 1, , ,25 4, ,62 1, , , , , , ,470 1,58 5, , ,68 9,21 1, ,43 2, , , , , , ,16 1, , , , ,98 1, , , , , ,25 4,54 2, , , , , ,51 3, , ,47 1, , , , , , , , , , ,20 1,15 14, , , , , ,98 2, ,47 1, ,81 1, , ,26 4, ,63 1, , , , , , , ,47 1, , , ,69 9,26 1, , , , , ,21 1, , , , ,03 3, , , , , ,82 1, , , , , , , , , , , ,58 1,47 1,586 5, , ,69 9,279 1, , , , , ,22 1,16 14,25 2,18 1, , , ,98 2, , , , , ,42 3,27 4, , , , , , , , ,59 1, ,59 5, , , , , , , , , , ,16 14,270 2, , , , ,00 2,98 1,48 1,34 1, , ,43 3,27 4,55 2, , , , , , , , ,48 1, , , , ,349 1, ,46 2, , , , , , , , ,11 4, ,01 2,99 1, ,34 1, , , ,29 4,57 2,65 1, , , , , , , ,486 1, , , , ,358 1, ,471 2, , , ,25 1, ,38 2,20 1, ,151 4, , , ,49 1, ,83 1, ,44 3,29 4, , ,158 2, , , , , ,59 1,49 1,59 5, , , ,40 1, ,47 2, , , , ,17 14,40 2, , ,16 3, ,01 3,00 1,49 1, , , , ,29 4, , ,15 2, , , ,61 3, ,58 1, ,59 5, , ,72 9, , ,47 2, , , ,268 1, , ,20 1, , , , ,00 1,49 1,35 1, , , , , , ,15 2, , , ,61 3, , ,49 1, , , ,72 9, , ,46 2, , , ,27 1, , ,20 1, , , ,01 3,00 1,49 1,35 1,84 1, ,421 3, , , , , , , , , ,59 1,49 1,599 5, , , , , , , ,82 23 See footnotes at end of table. 53

61 ESTABLISHMENT DATA STATE EMPLOYMENT SEASONALLY ADJUSTED B7. Employees on nonfarm payrolls by State and major industry, seasonally adjusted Continued (In thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May P Construction Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii 3 Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan 2 Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota 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

62 ESTABLISHMENT DATA STATE EMPLOYMENT SEASONALLY ADJUSTED B7. Employees on nonfarm payrolls by State and major industry, seasonally adjusted Continued (In thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Manufacturing Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan 2 Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota 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 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

63 ESTABLISHMENT DATA STATE EMPLOYMENT SEASONALLY ADJUSTED B7. Employees on nonfarm payrolls by State and major industry, seasonally adjusted Continued (In thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. I May June P Transportation and public utilities Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan 2 Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota 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 (4) (4) (4) (4) (4) (4) (4) (4) (4) T (4) (4) 27 A (4) (4)

64 ESTABLISHMENT DATA STATE EMPLOYMENT SEASONALLY ADJUSTED B7. Employees on nonfarm payrolls by State and major industry, seasonally adjusted Continued (In thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Trade Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan 2 Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota 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 , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,751 1, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,77 1, , , , , , ,

65 ESTABLISHMENT DATA STATE EMPLOYMENT SEASONALLY ADJUSTED B7. Employees on nonfarm payrolls by State and major industry, seasonally adjusted Continued (In thousands) State Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan 2 Minnesota Mississippi Missouri... Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon.. Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin.. Wyoming Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Finance, insurance, and real estate See footnotes at end of table. 58

66 ESTABLISHMENT DATA STATE EMPLOYMENT SEASONALLY ADJUSTED B7. Employees on nonfarm payrolls by State and major industry, seasonally adjusted Continued (In thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Services Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan 2 Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming , , , , , , , , , , , , , , , , , , , ,94 1,00 9 1, , , , , ,587 1, , ,17 1, , ,95 1, , , , , , ,60 1, , ,17 1, , , ,01 9 1, , , , ' 4, ,62 1, , , , , ,97 1,01 9 1, , , , , , , , , , , , ,02 9 1, , , , , ,65 1, , ,18 1, , , , , , , , , ,66 1, , ,18 1, , , ,02 9 1, , , , , ,678 1, , , , , , , , , , , , , , , ,186 1, , , ,02 9 1, , , , , , , , , , , ,02 1,03 9 1, , , , , ,71 1, , , , , ,027 1, , , , , , , , , , , , ,04 1, , , , See footnotes at end of table. 59

67 ESTABLISHMENT DATA STATE EMPLOYMENT SEASONALLY ADJUSTED B7. Employees on nonfarm payrolls by State and major industry, seasonally adjusted Continued (In thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Government Alabama Alaska Arizona Arkansas California , , , , , , , , , , , , ,31 Colorado Connecticut Delaware District of Columbia Florida , Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan 2 Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota , , , , , , , , , , , , , Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah , , , , , , , , , , , , Vermont Virginia Washington West Virginia Wisconsin Wyoming Includes mining, not shown separately. 2 Nonfarm payroll employment levels for Michigan are understated and will be corrected with the release of final estimates for on Oct. 20. The error occurred in the latest benchmark revision and affects 1998 forward. The upward adjustment to the March benchmark reference month is expected to be in the range of 35,000 to 45,000. Seasonal adjustment factors will be recalculated based on the revised data and applied to employment levels from 1995 forward. 3 Mining is combined with construction. 4 This series is not published seasonally adjusted because the seasonal component, which is small relative to the trendcycle and irregular components, cannot be separated with sufficient precision. P = preliminary. NOTE: All data have been adjusted to March benchmarks (with the exception of data for New Jersey) and incorporate updated seasonal adjustment factors. 60

68 B8. Average weekly hours of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry and manufacturing group, seasonally adjusted ESTABLISHMENT DATA HOURS SEASONALLY ADJUSTED Industry Oct. Nov. Dec Jan. Feb. Mar. Apr. May June P P Total private Goodsproducing Mining Construction Manufacturing Overtime hours Durable goods Overtime hours Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Blast furnaces and basic steel products Fabricated metal products Industrial machinery and equipment Electronic and other electrical equipment Transportation equipment Motor vehicles and equipment Instruments and related products Miscellaneous manfacturing Nondurable goods Overtime hours Food and kindred products Tobacco products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and misc. plastics products Leather and leather products (2) (2) (2) (2) (2) (2) (2) (2) (2) (2) (2) (2) (2) Serviceproducing Transportation and public utilities Wholesale trade Retail trade Finance, insurance, and real estate Services Data relate to production workers in mining and manufacturing; construction workers in construction; and nonsupervisory workers in transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. 2 This series is not published seasonally adjusted because the seasonal components, which are small relative to the trendcycle and irregular components, cannot be separated with sufficient precision. p = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all seasonally adjusted data from January 1996 forward are subject to revision. 61

69 ESTABLISHMENT DATA HOURS SEASONALLY ADJUSTED B9. Indexes of aggregate weekly hours of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry and manufacturing group, seasonally adjusted (1982=100) Industry Oct. Nov. Dec Jan. Feb. Mar. Apr. May June P P Total private Goodsproducing Mining Construction Manufacturing Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Blast furnaces and basic steel products Fabricated metal products Industrial machinery and equipment Electronic and other electrical equipment Transportation equipment Motor vehicles and equipment Instruments and related products Miscellaneous manf acturing Nondurable goods Food and kindred products Tobacco products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and misc. plastics products Leather and leather products Serviceproducing Transportation and public utilities Wholesale trade Retail trade Finance, insurance, and real estate Services Data relate to production workers in mining and manufacturing; construction workers in construction; and nonsupervisory workers in transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. P = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all seasonally adjusted data from January 1996 forward are subject to revision. 62

70 ESTABLISHMENT DATA ALLEMPLOYEE HOURS SEASONALLY ADJUSTED B10. Hours of wage and salary workers on nonfarm payrolls by major industry, seasonally adjusted Millions of hours (annual rate) 1 Percent change Industry r / * to * to r To * Total 242, , , Private sector 201, , ,581.3 Mining Construction Manufacturing Durable goods Nondurable goods Transportation and public utilities.. Wholesale trade Retail trade Finance, insurance, and real estate Services 1,270 13,631 40,213 24,496 15,717 14,162 14,114 34,738 14,307 69,280 1,248 13,606 39,699 24,102 15,597 13,874 14,065 34,726 14,327 69,576 1,246 13,423 39,459 23,936 15,523 14,179 14,144 34,728 14,457 69, Government 41,239 38,473 38, Total hours paid for 1 week in the month, seasonally adjusted, multiplied by 52. p = preliminary. r = revised. NOTE: Data refer to hours of all employees production workers, nonsupervisory workers, and salaried workers and are based largely on establishment data. See BLS Handbook of Methods, BLS Bulletin 2490, chapter 10, "Productivity Measures: Business Sector and Major Subsectors". SOURCE: Office of Productivity and Technology ( ). Historical data for this series also are available on the Internet at the following address: ftp://ftp.bls.qov/pub/special.requests/opt/tableb10.txt 63

71 ESTABLISHMENT DATA EARNINGS SEASONALLY ADJUSTED B11. Average hourly and weekly earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry, seasonally adjusted Industry Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June? P Average hourly earnings Total private (in current dollars) Goodsproducing Mining Construction Manufacturing Excluding overtime 2 Serviceproducing Transportation and public utilities Wholesale trade Retail trade Finance, insurance, and real estate Services $ $ $ $ $ $ $ $ $ $ $ $ $ Total private (in constant (1982) dollars) 3 Goodsproducing Serviceproducing (4) (4) (4) Average weekly earnings Total private (in current dollars) Goodsproducing Mining Construction Manufacturing Serviceproducing Transportation and public utilities Wholesale trade Retail trade Finance, insurance, and real estate Services Total private (in constant (1982) dollars) 3 Goodsproducing Serviceproducing (4) (4) (4) 1 Data relate to production workers in mining and manufacturing; construction workers in construction; and nonsupervisory workers in transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. 2 Derived by assuming that overtime hours are paid at the rate of time and onehalf. 3 The Consumer Price Index for Urban Wage Earners and Clerical Workers (CPIW) is used to deflate these series. The data in these series have been revised from January through due to corrections in the CPIW. 4 Not available. p = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all seasonally adjusted data from January 1996 forward are subject to revision. 64

72 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry (In thousands) Industry 1987 SIC Code All employees P P Production workers 1 P P Total 128, , , , ,086 Total private 109, , , , ,823 90,001 89,739 91,926 91,951 91,696 Mining Metal mining Iron ores Copper ores Coal mining Bituminous coal and lignite mining Oil and gas extraction Crude petroleum and natural gas Oil and gas field services Nonmetallic minerals, except fuels Crushed and broken stone Sand and gravel Chemical and fertilizer minerals Construction 6,764 6,704 7,036 7,050 6,976 5,281 5,228 5,497 5,513 5,444 General building contractors Residential building construction Operative builders Nonresidential building construction , , , , ,54 1, , , , Heavy construction, except building Highway and street construction Heavy construction, except highway Special trade contractors Plumbing, heating, and air conditioning Painting and paper hanging Electrical work Masonry, stonework, and plastering Carpentry and floor work Roofing, siding, and sheet metal work , , , , ,47 3, , , , Manufacturing 18,591 18,571 18,500 18,517 18,443 12,769 12,775 12,661 12,690 12,662 Durable goods 11,110 11,103 11,112 11,100 11,060 7,587 7,592 7,566 7,564 7,557 Lumber and wood products Logging Sawmills and planing mills Sawmills and planing mills, general Hardwood dimension and flooring mills... Miilwork, plywood, and structural members Miilwork Wood kitchen cabinets Hardwood veneer and plywood Softwood veneer and plywood Wood containers Wood buildings and mobile homes Mobile homes Miscellaneous wood products U Furniture and fixtures Household furniture Wood household furniture Upholstered household furniture Metal household furniture Mattresses and bedsprings See footnotes at end of table. 65

73 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Code All employees P P Production workers 1 P P Durable goods Continued Furniture and fixtures Continued Office furniture Public building and related furniture Partitions and fixtures Miscellaneous furniture and fixtures Stone, clay, and glass products Flat glass Glass and glassware, pressed or blown Glass containers Pressed and blown glass, nee Products of purchased glass Cement, hydraulic Structural clay products Pottery and related products Concrete, gypsum, and plaster products Concrete block and brick Concrete products, nee Readymixed concrete Misc. nonmetallic mineral products Abrasive products Asbestos products Mineral wool Primary metal industries Blast furnaces and basic steel products Blast furnaces and steel mills Steel pipe and tubes Iron and steel foundries Gray and ductile iron foundries Malleable iron foundries Steel foundries, nee Primary nonferrous metals Primary aluminum Nonferrous rolling and drawing Copper rolling and drawing Aluminum sheet, plate, and foil Nonferrous wire drawing and insulating Nonferrous foundries (castings) Aluminum foundries Fabricated metal products 34 Metal cans and shipping containers 341 Metal cans 3411 Cutlery, handtools, and hardware 342 Hand and edge tools, and blades and handsaws ,5 Hardware, nee 3429 Plumbing and heating, except electric 343 Plumbing fixture fittings and trim 3432 Heating equipment, except electric 3433 Fabricated structural metal products 344 Fabricated structural metal 3441 Metal doors, sash, and trim 3442 Fabricated plate work (boiler shops) 3443 Sheet metal work 3444 Architectural metal work 3446 Screw machine products, bolts, etc 345 Screw machine products 3451 Bolts, nuts, rivets, and washers 3452 Metal forgings and stampings 346 Iron and steel forgings 3462 Automotive stampings 3465 Metal stampings, nee , , , , ,53 1, , , , ,15 See footnotes at end of table. 66

74 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Code All employees P P Production workers 1 P P Durable goods Continued Fabricated metal products Continued Metal services, nee Plating and polishing Metal coating and allied services Ordnance and accessories, nee Ammunition, except for small arms, nee Miscellaneous fabricated metal products Valves and pipe fittings, nee Misc. fabricated wire products Industrial machinery and equipment Engines and turbines.; Turbines and turbine generator sets Internal combustion engines, nee Farm and garden machinery Farm machinery and equipment Construction and related machinery Construction machinery Mining machinery Oil and gas field machinery Conveyors and conveying equipment Industrial trucks and tractors Metalworking machinery Machine tools, metal cutting types Machine tools, metal forming types Special dies, tools, jigs, and fixtures Machine tool accessories Power driven handtools Special industry machinery Textile machinery Printing trades machinery Food products machinery General industrial machinery Pumps and pumping equipment Ball and roller bearings Air and gas compressors Blowers and fans Speed changers, drives, and gears Power transmission equipment, nee Computer and office equipment Electronic computers Computer terminals, calculators, and office machines, nee Refrigeration and service machinery Refrigeration and heating equipment Misc. industrial and commercial machinery Carburetors, pistons, rings, valves Scales, balances, and industrial machinery, nee ,8, ,9 2, , , , , , , , , ,34 Electronic and other electrical equipment Electric distribution equipment Transformers, except electronic Switchgear and switchboard apparatus Electrical industrial apparatus Motors and generators Relays and industrial controls Household appliances Household refrigerators and freezers Household laundry equipment Electric housewares and fans , , , , ,71 1, , , , ,06 See footnotes at end of table. 67

75 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Code All employees P P Production workers 1 P P Durable goods Continued Electronic and other electrical equipment Continued Electric lighting and wiring equipment 364 Electric lamps 3641 Currentcarrying wiring devices 3643 Noncurrentcarrying wiring devices 3644 Residential lighting fixtures 3645 Household audio and video equipment 365 Household audio and video equipment 3651 Communications equipment 366 Telephone and telegraph apparatus 3661 Electronic components and accessories 367 Electron tubes 3671 Semiconductors and related devices 3674 Electronic components, nee 3679 Misc. electrical equipment and supplies 369 Storage batteries 3691 Engine electrical equipment Transportation equipment Motor vehicles and equipment Motor vehicles and car bodies Truck and bus bodies Motor vehicle parts and accessories Truck trailers Aircraft and parts Aircraft Aircraft engines and engine parts Aircraft parts and equipment, nee Ship and boat building and repairing Ship building and repairing Boat building and repairing Railroad equipment Guided missiles, space vehicles, and parts Guided missiles and space vehicles Miscellaneous transportation equipment Travel trailers and campers , , , , , , , , , , , , ,20 75 Instruments and related products Search and navigation equipment Measuring and controlling devices Environmental controls Process control instruments Instruments to measure electricity Medical instruments and supplies Surgical and medical instruments Surgical appliances and supplies Ophthalmic goods Photographic equipment and supplies Watches, clocks, watchcases, and parts Miscellaneous manufacturing industries Jewelry, silverware, and plated ware Jewelry, precious metal Musical instruments Toys and sporting goods Dolls, games, toys, and children's vehicles Sporting and athletic goods, nee Pens, pencils, office, and art supplies Costume jewelry and notions Costume jewelry Miscellaneous manufactures Signs and advertising specialties , See footnotes at end of table. 68

76 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Code All employees P P Production workers' P P Nondurable goods Food and kindred products Meat products Meat packing plants Sausages and other prepared meats Poultry slaughtering and processing Dairy products Cheese, natural and processed Fluid milk Preserved fruits and vegetables Canned specialties Canned fruits and vegetables Frozen fruits and vegetables Grain mill products Flour and other grain mill products Prepared feeds, nee Bakery products Bread, cake, and related products Cookies, crackers, and frozen bakery products, except bread Sugar and confectionery products Raw cane sugar Cane sugar refining Beet sugar Candy and other confectionery products Fats and oils Beverages Malt beverages Bottled and canned soft drinks Misc. food and kindred products , ,481 1, ,468 1, ,388 1, ,417 1, ,383 1, ,182 1, ,183 1, ,095 1, ,126 1, ,105 1,29 Tobacco products Cigarettes Textile mill products Broadwoven fabric mills, cotton Broadwoven fabric mills, synthetics Broadwoven fabric mills, wool Narrow fabric mills Knitting mills Women's hosiery, except socks Hosiery, nee Knit outerwear mills Knit underwear mills Weft knit fabric mills Textile finishing, except wool Finishing plants, cotton Finishing plants, synthetics Carpets and rugs Yarn and thread mills Yarn spinning mills Throwing and winding mills Miscellaneous textile goods Apparel and other textile products Men's and boys' suits and coats Men's and boys' furnishings Men's and boys' shirts Men's and boys' trousers and slacks Men's and boys' work clothing Women's and misses' outerwear Women's and misses' blouses and shirts Women's, juniors', and misses' dresses Women's and misses' suits and coats Women's and misses' outerwear, nee See footnotes at end of table. 69

77 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC L>UUc All employees P P Production workers 1 P P Nondurable goods Continued Apparel and other textile products Continued Women's and children's undergarments Women's and children's underwear Brassieres, girdles, and allied garments Girls' and children's outerwear Girls' and children's dresses and blouses Misc. apparel and accessories Misc. fabricated textile products Curtains and draperies House furnishings, nee Automotive and apparel trimmings Paper and allied products Paper mills Paperboard mills Paperboard containers and boxes Corrugated and solid fiber boxes Sanitary food containers Folding paperboard boxes Misc. converted paper products Paper, coated and laminated, nee Bags: plastics, laminated, and coated Envelopes Printing and publishing Newspapers Periodicals Books Book publishing Book printing Miscellaneous publishing Commercial printing Commercial printing, lithographic Commercial printing, nee Manifold business forms Blankbooks and bookbinding Printing trade services , , , , , Chemicals and allied products Industrial inorganic chemicals Industrial inorganic chemicals, nee Plastics materials and synthetics Plastics materials and resins Organic fibers, noncellulosic Drugs Pharmaceutical preparations Soap, cleaners, and toilet goods Soap and other detergents Polishing, sanitation, and finishing preparations Toilet preparations Paints and allied products Industrial organic chemicals Cyclic crudes and intermediates Industrial organic chemicals, nee Agricultural chemicals Miscellaneous chemical products , , , , , , Petroleum and coal products Petroleum refining Asphalt paving and roofing materials Rubber and misc. plastics products Tires and inner tubes :.. Rubber and plastics footwear Hose, belting, gaskets, and packing Rubber and plastics hose and belting Fabricated rubber products, nee Miscellaneous plastics products, nee , , , , See footnotes at end of table. 70

78 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Code All employees P P Production workers 1 P P Nondurable goods Continued Leather and leather products Leather tanning and finishing Footwear, except rubber Men's footwear, except athletic Women's footwear, except athletic Luggage Handbags and personal leather goods Transportation and public utilities Transportation Railroad transportation Class I railroads plus Amtrak ,831 4, ,908 4, ,992 4, ,924 4, ,088 4, , , , , ,901 Local and interurban passenger transit Local and suburban transportation Taxicabs Intercity and rural bus transportation School buses Trucking and warehousing Trucking and courier services, except air.. Public warehousing and storage , , ,84 1, ,86 1, ,87 1, , , , , , , , , ,47 16 Water transportation Water transportation of freight, nee Water transportation services Transportation by air Air transportation, scheduled Air transportation, scheduled Airports, flying fields, and services , , ,23 1, ,28 1, ,28 1, ,286.2 Pipelines, except natural gas Transportation services Passenger transportation arrangement Travel agencies Freight transportation arrangement Communications and public utilities 2,433 2,430 2,486 2,403 2,487 Communications Telephone communications Telephone communications, except radio Radio and television broadcasting Radio broadcasting stations Television broadcasting stations Cable and other pay television services ,56 1, ,56 1, ,62 1, ,54 1, ,63 1, , , , Electric, gas, and sanitary services Electric services Gas production and distribution Combination utility services Sanitary services Wholesale trade 6,973 6,967 7,089 7,089 7,070 5,583 5,566 5,661 5,662 5,636 Durable goods Motor vehicles, parts, and supplies Automobiles and other motor vehicles Motor vehicle supplies and new parts Furniture and home furnishings Furniture Home furnishings , , , , ,193 3, , , , See footnotes at end of table. 71

79 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Pnrtp vuuc All employees P P Production workers 1 P P Wholesale trade Continued Durable goods Continued Lumber and other construction materials Lumber, plywood, and millwork Construction materials, nee Professional and commercial equipment Office equipment Computers, peripherals and software Medical and hospital equipment Metals and minerals, except petroleum Electrical goods Electrical apparatus and equipment Electrical appliances, television and radio sets Electronic parts and equipment Hardware, plumbing, and heating equipment... Hardware Plumbing and hydronic heating supplies Machinery, equipment, and supplies Construction and mining machinery Farm and garden machinery Industrial machinery and equipment Industrial supplies Misc. wholesale trade durable goods Scrap and waste materials Nondurable goods Paper and paper products Stationery and office supplies Drugs, proprietaries, and sundries Apparel, piece goods, and notions Groceries and related products Groceries, general line Meats and meat products Fresh fruits and vegetables Farmproduct raw materials Chemicals and allied products Petroleum and petroleum products Petroleum bulk stations and terminals Petroleum products, nee Beer, wine, and distilled beverages Beer and ale Wine and distilled beverages Misc. wholesale trade nondurable goods Farm supplies , , , , ,877 2, , , , Retail trade 22,993 22,893 23,324 23,347 23,234 20,258 20,144 20,542 20,550 20,429 Building materials and garden supplies Lumber and other building materials Paint, glass, and wallpaper stores Hardware stores Retail nurseries and garden stores , , , , General merchandise stores Department stores Variety stores Miscellaneous general merchandise stores ,71 2, ,71 2, , , , , , , , , ,54 2, ,49 2, , , Food stores Grocery stores Meat and fish markets Dairy products stores Retail bakeries ,51 3, ,48 3, ,54 3, , , ,51 3, , ,146 2, , , ,19 2, Automotive dealers and service stations New and used car dealers ,39 1, ,38 1, ,439 1, ,44 1, , , , , , ,04 94 See footnotes at end of table. 72

80 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Code All employees P P Production workers 1 P P Retail trade Continued Automotive dealers and service stations Continued Auto and home supply stores Gasoline service stations Automotive dealers, nee Apparel and accessory stores Men's and boys' clothing stores Women's clothing stores Family clothing stores Shoe stores , , , , , , Furniture and home furnishings stores Furniture and home furnishings stores Furniture stores Household appliance stores Radio, television, and computer stores Radio, television, and electronic stores Record and prerecorded tape stores , , , , , Eating and drinking places 58 8, ,088 8,30 8,29 8, , , , ,47 Miscellaneous retail establishments Drug stores and proprietary stores Liquor stores Used merchandise stores Miscellaneous shopping goods stores Sporting goods and bicycle shops Bookstores Stationery stores Jewelry stores Gift, novelty, and souvenir shops Sewing, needlework, and piece goods Nonstore retailers Catalog and mailorder houses Merchandising machine operators Fuel dealers Retail stores, nee Florists, tobacco stores, and newsstands Optical goods stores Miscellaneous retail stores, nee ,3, , , , , , , , , , , , , , Finance, insurance, and real estate 3 7,668 7,590 7,688 7,685 7,623 5,631 5,548 5,649 5,643 5,579 Finance 3,722 3,692 3,736 3,735 3,717 Depository institutions Commercial banks State commercial banks National and commercial banks, nee Savings institutions Federal savings institutions Savings institutions, except federal Credit unions , ,07 1, , , ,05 1, , , ,030 1, , , , , ,48 1, , , Nondepository institutions Personal credit institutions Business credit institutions Mortgage bankers and brokers Security and commodity brokers Security brokers and dealers Commodity contracts brokers, dealers, and exhanges Security and commodity services , Holding and other investment offices Holding offices See footnotes at end of table. 73

81 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Code All employees P P Production workers 1 P P Finance, insurance, and real estate Continued Insurance 63,64 2,383 2,372 2,367 2,365 2,352 Insurance carriers Life insurance Medical service and health insurance Hospital and medical service plans Fire, marine, and casualty insurance Title insurance , , , , ,58 1, , , , Insurance agents, brokers, and service Real estate Real estate operators and lessors Real estate agents and managers Subdividers and developers , , , , ,554 Services 39,490 39,421 40,832 40,892 40,844 34,428 34,351 35,684 35,729 35,640 Agricultural services Veterinary services Landscape and horticultural services Hotels and other lodging places Hotels and motels ,00 1, ,91 1,85 2,08 1, ,07 1, ,98 1,68 1, , ,747 Personal services Laundry, cleaning, and garment services Photographic studios, portrait Beauty shops Funeral service and crematories Miscellaneous personal services , , , , , Business services Advertising Advertising agencies Credit reporting and collection Mailing, reproduction, and stenographic services Photocopying and duplicating services Services to buildings Disinfecting and pest control services Building maintenance services, nee Miscellaneous equipment rental and leasing Medical equipment rental Heavy construction equipment rental Equipment rental and leasing, nee Personnel supply services Employment agencies Help supply services Computer and data processing services Computer programming services Prepackaged software Computer integrated systems design Data processing and preparation Information retrieval services Computer maintenance and repair Miscellaneous business services Detective and armored car services Security systems services Photofinishing laboratories , , , ,34 1, , , , , ,35 1, , , , , ,45 1, , , , , , , , ,96 1,00 4, ,57 1,95 8, , , , , , , , , ,32 1, , , , , , Auto repair, services, and parking Automotive rentals, without drivers Passenger car rental Automobile parking Automotive repair shops Automotive and tire repair shops General automotive repair shops , , , , , , See footnotes at end of table. 74

82 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC uuuc All employees P P Prodijction wor ^ers 1 P P Services Continued Auto repair, services, and parking Continued Automotive services, except repair Carwashes Miscellaneous repair services Electrical repair shops Motion pictures Motion picture production and services Motion picture theaters Video tape rental Amusement and recreation services Bowling centers Misc. amusement and recreation services Physical fitness facilities Membership sports and recreation clubs Health services Offices and clinics of medical doctors Offices and clinics of dentists Offices and clinics of other health practitioners Offices and clinics of chiropractors and optometrists Nursing and personal care facilities Skilled nursing care facilities Intermediate care facilities Nursing and personal care, nee Hospitals General medical and surgical hospitals Psychiatric hospitals Specialty hospitals, excluding psychiatric Medical and dental laboratories Home health care services Legal services Educational services Elementary and secondary schools Colleges and universities Vocational schools Social services Individual and family services Job training and related services Child day care services Residential care Social services, nee Museums and botanical and zoological gardens Membership organizations Business associations Professional organizations Labor organizations Civic and social associations Engineering and management services Engineering and architectural services Engineering services Architectural services Surveying services Accounting, auditing, and bookkeeping , , , , , , ,99 3, ,00 1, , , , , , , , ,787? 1, ,98 3, , , , , , , , , ,79 1, , , , , , , , ,44 1, , , , , , , , , , , , , ,449 1, , ,94 1,79 4, , ,33 2, , ,43 1, ,71 6 1, ,87 1, , , , , , , ,858 1, , , , , , , , , , , , , ,87 6 1, ,01 1, , , , , See footnotes at end of table. 75

83 ESTABLISHMENT DATA EMPLOYMENT NOT SEASONALLY ADJUSTED B12. Employees on nonfarm payrolls by detailed industry Continued (In thousands) Industry 1987 SIC Code All employees P P Production workers 1 P P Services Continued Engineering and management services Continued Research and testing services Commercial physical research Commercial nonphysical research Noncommercial research organizations Management and public relations Management services Management consulting services Public relations services , , , , , Services, nee Government 19,006 20,025 19,517 19,299 20,263 Federal Government 4 2,657 2,647 2,837 2,659 2,614 Executive, by agency 4 Department of Defense Postal Service 5 Other executive agencies Legislative Judicial 2, , , , , , Federal Government, except Postal Service 1,79 1,78 1, ,80 1,759.2 Federal Government, by industry: Manufacturing activities Ship building and repairing Transportation and public utilities, except Postal Service Services Hospitals State government Construction Transportation and public utilities Services Hospitals Education Social services Services, except hospitals, education, and social services General administration, including executive, legislative, and judicial functions State government, except education , , , ,90 2, , , , ,89 2,74 4, , , , , , , , , , ,741 1, ,779.5 Local government Transportation and public utilities Services Hospitals Education Social services Services, except hospitals, education, and social services General administration, including executive, legislative, and judicial functions Local government, except education , , , ,06 5, , , , ,87 5,54 12, , , , ,96 12, , , , ,908 7,241 5, Data relate to production workers in mining and manufacturing; construction workers in construction; and nonsupervisory workers in transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. 2 Data relate to linehaul railroads with operating revenues of $25 million or more in 1993 and to Amtrak. 3 Excludes nonoffice commissioned real estate sales agents. 4 Prepared by the Office of Personnel Management. Data relate to civilian employment only and exclude the Central Intelligence Agency and the National Security Agency. 5 Includes rural mail carriers. " Data not available. P = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all unadjusted data from April forward are subject to revision. 76

84 ESTABLISHMENT DATA WOMEN EMPLOYEES NOT SEASONALLY ADJUSTED B13. Women employees on nonfarm payrolls by major industry and manufacturing group (In thousands) Industry June May June Total 62,557 61,574 64,057 64,121 62,845 Total private 51,240 51,194 51,939 52,376 52,259 Goodsproducing 6,720 6,686 6,672 6,730 6,707 Mining Construction Manufacturing 5,917 5,874 5,854 5,893 5,864 Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Fabricated metal products Industrial machinery and equipment Electronic and other electrical equipment Transportation equipment Instruments and related products Miscellaneous manfacturing 2, , , , , Nondurable goods Food and kindred products Tobacco products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and misc. plastics products Leather and leather products 2, , , , , Serviceproducing 55,837 54,888 57,385 57,391 56,138 Transportation and public utilities 2,089 2,059 2,154 2,162 2,138 Wholesale trade 2,138 2,148 2,195 2,216 2,206 Retail trade 12,105 12,063 12,076 12,228 12,204 Finance, insurance, and real estate 4,764 4,782 4,746 4,782 4,790 Services 23,424 23,456 24,096 24,258 24,214 Government Federal State Local 11,317 1,135 2,327 7,855 10,380 1,130 2,279 6,971 12,118 1,431 2,478 8,209 11,745 1,372 2,360 8,013 10,586 1,234 2,310 7,042 NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all unadjusted data from April forward are subject to revision. 77

85 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry (In thousands) Total Mining Construction State and area P P P Alabama Birmingham Huntsville Mobile Montgomery Tuscaloosa 1, , , (J) Alaska Anchorage Arizona PhoenixMesa Tucson 2,13 1, , , ,23 1, Arkansas FayettevilleSpringdaleRogers Fort Smith Little RockNorth Little Rock Pine Bluff 1, , , (M California Bakersfield Fresno Los AngelesLong Beach Modesto Oakland Orange County RiversideSan Bernardino Sacramento Salinas San Diego San Francisco San Jose Santa BarbaraSanta MariaLompoc Santa Rosa StocktonLodi VallejoFairfieldNapa Ventura 13, , , , , , , , , ,17 1, , , ,029 1, ,17 1, ( 2 ) ( 2 ) ( 2 ) Colorado BoulderLongmont Colorado Springs Denver 2, , , , , ,18 1 (\) (\) Connecticut Bridgeport Danbury Hartford New HavenMeriden New LondonNorwich StamfordNorwalk Waterbury Delaware Dover WilmingtonNewark 1, , , ( 2 ) (M (M ( 2 ).9.2 ( 2 ) (]) ( 2 ).9.2 ( 2 ) ( 2 ) District of Columbia Washington PMSA 61 2, , , Florida Daytona Beach Fort Lauderdale Fort MyersCape Coral Gainesville Jacksonville LakelandWinter Haven MelbourneTitusvillePalm Bay Miami Orlando Pensacola SarasotaBradenton Tallahassee TampaSt. PetersburgClearwater... West Palm BeachBoca Raton 6, , , , , , , , ( 2 ).2 ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ).2 ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ).2 ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) See footnotes at end of table. 78

86 B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED State and area ManufacturingI P Transportation and public utilities P Wholesale and retail trade P Alabama Birmingham, Huntsville Mobile Montgomery Tuscaloosa in Alaska Anchorage Arizona PhoenixMesa Tucson Arkansas FayettevilleSpringdale Rogers Fort Smith Little RockNorth Little Rock Pine Bluff California Bakersfield Fresno Los AngelesLong Beach Modesto Oakland Orange County RiversideSan Bernardino Sacramento Salinas San Diego San Francisco San Jose Santa BarbaraSanta MariaLompoc Santa Rosa StocktonLodi VallejoFairfieldNapa Ventura 1, , , , , Colorado BoulderLongmont Colorado Springs Denver Connecticut Bridgeport Danbury Hartford New HavenMeriden New LondonNorwich StamfordNorwalk Waterbury Delaware Dover WilmingtonNewark District of Columbia Washington PMSA Florida Daytona Beach Fort Lauderdale Fort MyersCape Coral Gainesville Jacksonville LakelandWinter Haven MelbourneTitusvillePalm Bay Miami Orlando Pensacola SarasotaBradenton Tallahassee TampaSt. PetersburgClearwater... West Palm BeachBoca Raton , , , See footnotes at end of table. 79

87 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area Finance, insurance, and real estate P , , , , Services , , , , P , , ,10 2, , Government , P , Alabama Birmingham Huntsville Mobile Montgomery Tuscaloosa Alaska Anchorage Arizona PhoenixMesa Tucson Arkansas FayettevilleSpringdaleRogers Fort Smith Little RockNorth Little Rock Pine Bluff California Bakersfield Fresno Los AngelesLong Beach Modesto Oakland Orange County RiversideSan Bernardino Sacramento Salinas San Diego San Francisco San Jose Santa BarbaraSanta MariaLompoc Santa Rosa StocktonLodi VallejoFairfieldNapa Ventura Colorado BoulderLongmont Colorado Springs Denver Connecticut Bridgeport Danbury Hartford New HavenMeriden New LondonNorwich StamfordNorwalk Waterbury Delaware Dover WilmingtonNewark District of Columbia Washington PMSA Florida Daytona Beach Fort Lauderdale Fort MyersCape Coral Gainesville Jacksonville LakelandWinter Haven MelbourneTitusvillePalm Bay Miami Orlando Pensacola SarasotaBradenton Tallahassee TampaSt. PetersburgClearwater... West Palm BeachBoca Raton See footnotes at end of table. 80

88 B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED Total Mining Construction State and area P P P Georgia Albany Athens Atlanta aaiken Columbus Macon Savannah Hawaii Honolulu Idaho Boise City 3, , , , , , < 2 ) ( 2 ) (M 7.8 ( 2 ) Illinois BloomingtonNormal ChampaignUrbana Chicago DavenportMolineRock Island.. Decatur Kankakee PeoriaPekin Rockford Springfield Indiana Bloomington ElkhartGoshen EvansvilleHenderson Fort Wayne Gary Indianapolis Kokomo Lafayette Muncie South Bend Terre Haute 5, , , , , , , , , (M <;> ( 1 > 7.0 (]) 1 ( 1 ) 1 ) 1 ) 1 ) 2 ) (]) 1.0 (M.8 ( 2 ) 10.9 (M ( 2 ) Iowa Cedar Rapids Des Moines Dubuque Iowa City Sioux City WaterlooCedar Falls Kansas Lawrence Topeka Wichita 1, , , , , , ) 1 ) 1 ) 1 ) 1 ) 1 ) 1 ) ) 1 0) Kentucky Lexington Louisville Owensboro 1, , , Louisiana Alexandria Baton Rouge Houma Lafayette Lake Charles Monroe New Orleans ShreveportBossier City 1, , , Maine LewistonAuburn Portland ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ) See footnotes at end of table. 81

89 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area Manufacturing P Transportation and public utilities P Wholesale and retail trade , , , P 1, , Georgia Albany Athens Atlanta aaiken Columbus Macon Savannah Hawaii Honolulu Idaho Boise City Illinois BloomingtonNormal ChampaignUrbana Chicago DavenportMolineRock island Decatur Kankakee PeoriaPekin Rockford Springfield Indiana Bloomington ElkhartGoshen EvansvilleHenderson Fort Wayne Gary Indianapolis Kokomo Lafayette Muncie South Bend Terre Haute Iowa Cedar Rapids Des Moines Dubuque Iowa City Sioux City WaterlooCedar Falls Kansas Lawrence Topeka Wichita Kentucky Lexington Louisville Owensboro Louisiana Alexandria Baton Rouge Houma Lafayette Lake Charles Monroe New Orleans ShreveportBossier City Maine LewistonAuburn Portland See footnotes at end of table. 82

90 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area Finance, insurance, and real estate P , , , Services 1, , , P 1, Ml , , Government P Georgia Albany Athens Atlanta aaiken Columbus Macon Savannah Hawaii Honolulu Idaho Boise City Illinois BloomingtonNormal ChampaignUrbana Chicago DavenportMolineRock Island Decatur Kankakee PeoriaPekin Rockford Springfield Indiana Bloomington ElkhartGoshen EvansvilleHenderson Fort Wayne Gary Indianapolis Kokomo Lafayette Muncie South Bend Terre Haute Iowa Cedar Rapids DesMoines Dubuque Iowa City Sioux City WaterlooCedar Falls Kansas Lawrence Topeka Wichita Kentucky Lexington Louisville Owensboro Louisiana Alexandria Baton Rouge Houma Lafayette Lake Charles Monroe New Orleans ShreveportBossier City Maine LewistonAubum Portland See footnotes at end of table. 83

91 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) Total Mining Construction State and area P P P Maryland Baltimore PMSA Baltimore City Suburban MarylandD.C Massachusetts BarnstableYarmouth Boston Brockton FitchburgLeominster Lawrence Lowell New Bedford Pittsfield Springfield Worcester 2, , , , , , ,29 7 2, , , , , ( 2 ) ( 2 ) ( 2 ) O ( 2 ) ( 2 ) ( 2 ) ( 2 ) ( 2 ).2 (M (M.6 ( 2 ) ( 2 ) ( 2 ) ( 2 ) S Michigan 3 Ann Arbor Benton Harbor Detroit Flint Grand RapidsMuskegonHolland Jackson KalamazooBattle Creek LansingEast Lansing SaginawBay CityMidland Minnesota DuluthSuperior MinneapolisSt. Paul Rochester St. Cloud 4, , , , , , , , , , , , <;> 1.0 <;> < 1 ) (M 7.0 ( 2 ) (M 7.7 ( 2 ) ( 2 ) Mississippi Jackson 1, , , ( 2 ) 6.2 ( 2 ) 6.3 ( 2 ) Missouri Kansas City St. Louis Springfield Montana 2, , , , , , (M Lincoln Omaha Nevada Las Vegas Reno , , (M (M New Hampshire Manchester Nashua PortsmouthRochester New Jersey AtlanticCape May BergenPassaic Camden Jersey City MiddlesexSomersetHunterdon.. MonmouthOcean Newark Trenton VinelandMillvilleBridgeton 3, , , <;> < > <;> (M (]) (M New Mexico Albuquerque Las Cruces Santa Fe (J) 1 1 (\) See footnotes at end of table. 84

92 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area Manufacturing P Transportation and public utilities P Wholesale and retail trade , , P , Maryland Baltimore PMSA Baltimore City Suburban MarylandD.C Massachusetts BarnstableYarmouth Boston Brockton FitchburgLeominster Lawrence Lowell New Bedford Pittsfield Springfield Worcester Michigan 3 Ann Arbor Benton Harbor Detroit Flint Grand RapidsMuskegonHolland Jackson KalamazooBattle Creek LansingEast Lansing SaginawBay CityMidland Minnesota DuluthSuperior MinneapolisSt. Paul Rochester St. Cloud Mississippi Jackson Missouri Kansas City St. Louis Springfield Montana Nebraska Lincoln Omaha Nevada Las Vegas Reno New Hampshire Manchester Nashua PortsmouthRochester New Jersey AtlanticCape May BergenPassaic Camden Jersey City MiddlesexSomersetHunterdon... MonmouthOcean Newark Trenton VinelandMillvilleBridgeton New Mexico Albuquerque Las Cruces Santa Fe See footnotes at end of table. 85

93 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area Finance, insurance, and real estate P , , , Services , , , P , , , Government ? Maryland Baltimore PMSA Baltimore City Suburban MarylandD.C Massachusetts BarnstableYarmouth Boston Brockton FitchburgLeominster Lawrence Lowell New Bedford Pittsfield Springfield Worcester Michigan 3 Ann Arbor Benton Harbor Detroit Flint Grand RapidsMuskegonHolland Jackson KalamazooBattle Creek LansingEast Lansing SaginawBay CityMidland Minnesota DuluthSuperior MinneapolisSt. Paul Rochester St. Cloud Mississippi Jackson Missouri Kansas City St. Louis Springfield Montana Nebraska Lincoln Omaha Nevada Las Vegas Reno New Hampshire Manchester Nashua PortsmouthRochester New Jersey AtlanticCape May BergenPassaic Camden Jersey City MiddlesexSomersetHunterdon.. MonmouthOcean Newark Trenton VinelandMillvilleBridgeton New Mexico Albuquerque Las Cruces Santa Fe See footnotes at end of table. 86

94 B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED Total Mining Construction State and area P P P New York AlbanySchenectadyTroy Binghamton BuffaloNiagara Falls Dutchess County Elmira Glens Falls NassauSuffolk New York PMSA New York City Newburgh Rochester Rockland County Syracuse UticaRome Westchester County North Carolina Asheville CharlotteGastoniaRock Hill GreensboroWinston3alemHigh Point RaleighDurhamChapel Hill North Dakota Bismarck FargoMoorhead Grand Forks 8, ,187 4,16 3, , , ,21 4,25 3, , , ,207 4, , , (]) 1 (M.3.4 (]) 1 1 (]) 1.7 (M.3.4 (]) 1 1 (M (]) (\) Ohio Akron CantonMassillon Cincinnati ClevelandLorainElyria Columbus DaytonSpringfield HamiltonMiddletown Lima Mansfield SteubenvilleWeirton Toledo YoungstownWarren 5, , , , , , <;> < > (]) Oklahoma Enid Lawton Oklahoma City Tulsa 1, , , Oregon EugeneSpringfield MedfordAshland PortlandVancouver Salem 1, , , Pennsylvania AllentownBethlehemEaston Altoona Erie HarrisburgLebanonCarlisle Johnstown Lancaster Philadelphia PMSA Philadelphia City Pittsburgh Reading ScrantonWilkesBarreHazleton Sharon State College Williamsport York 5, , , , , , , , , (M.4.5 (M <;> See footnotes at end of table. 87

95 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area , Manufacturing , P , Transportation and public utilities P Wholesale and retail trade 1, , , , , , P 1, , , New York AlbanySchenectadyTroy Binghamton BuffaloNiagara Falls Dutchess County Elmira Glens Falls NassauSuffolk New York PMSA New York City Newburgh Rochester Rockland County Syracuse UticaRome Westchester County North Carolina Asheville ChariotteGastoniaRock Hill GreensboroWinstonSalemHigh Point RaleighDurhamChapel Hill North Dakota Bismarck FargoMoorhead Grand Forks Ohio Akron CantonMassillon Cincinnati ClevelandLorainElyria Columbus DaytonSpringfield HamiltonMiddletown Lima Mansfield SteubenvilleWeirton Toledo YoungstownWarren Oklahoma Enid Lawton Oklahoma City Tulsa Oregon EugeneSpringfield MedfordAshland PortlandVancouver Salem Pennsylvania AllentownBethlehemEaston Altoona Erie HarrisburgLebanonCarlisle Johnstown Lancaster Philadelphia PMSA Philadelphia City Pittsburgh Reading ScrantonWilkesBarreHazleton Sharon State College Williamsport York See footnotes at end of table. 88

96 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area Finance, insurance, i and real estate P , , , , , Services 3, ,63 1, , , , Auqust P 3, ,63 1, , , , , Government 1, P 1, New York AlbanySchenectadyTroy Binghamton BuffaloNiagara Falls Dutchess County Elmira Glens Falls NassauSuffolk New York PMSA New York City Newburgh Rochester Rockland County Syracuse UticaRome Westchester County North Carolina Asheville CharlotteGastoniaRock Hill GreensboroWinstonSalemHigh Point RaleighDurhamChapel Hill North Dakota Bismarck FargoMoorhead Grand Forks Ohio Akron CantonMassillon Cincinnati ClevelandLorainElyria Columbus DaytonSpringfield HamiltonMiddletown Lima Mansfield SteubenvilleWeirton Toledo YoungstownWarren Oklahoma Enid Lawton Oklahoma City Tulsa Oregon EugeneSpringfield MedfordAshland PortlandVancouver Salem Pennsylvania AllentownBethlehemEaston Altoona Erie HarrisburgLebanonCariisle Johnstown Lancaster Philadelphia PMSA Philadelphia City Pittsburgh Reading ScrantonWilkesBarreHazleton Sharon State College Williamsport York See footnotes at end of table. 89

97 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) Total Mining Construction State and area P P P Rhode Island ProvidenceFall RiverWarwick South Carolina CharlestonNorth Charleston Columbia GreenvilleSpartanburgAnderson 1, , , South Dakota Rapid City Sioux Falls Tennessee Chattanooga Johnson CityKingsportBristol Knoxville Memphis Nashville 2, , , C) Texas Abilene Amarillo AustinSan Marcos BeaumontPort Arthur Brazoria BrownsvilleHarlingenSan Benito BryanCollege Station Corpus Christi Dallas El Paso Ft. WorthArlington GalvestonTexas City Houston KilleenTemple Laredo LongviewMarshall Lubbock McAllenEdinburgMission OdessaMidland San Angelo San Antonio ShermanDenison Texarkana Tyler Victoria Waco Wichita Falls 9, , , , , , , , , M ) ) Utah ProvoOrem Salt Lake CityOgden 1, , , ) Vermont BarreMontpelier Burlington < 1 > Virginia Bristol Charlottesville Danville Lynchburg NorfolkVirginia BeachNewport News.. Northern Virginia RichmondPetersburg Roanoke 3, , , , , , <;> (]) Washington SeattleBellevueEverett Spokane Tacoma 2, , , , , , ) See footnotes at end of table. 90

98 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area , Manufacturing , P , Transportation and public utilities P Wholesale and retail trade , , P , Rhode Island ProvidenceFall RiverWarwick South Carolina CharlestonNorth Charleston Columbia GreenvilleSpartanburgAnderson South Dakota Rapid City Sioux Falls Tennessee Chattanooga Johnson CityKingsportBristol Knoxville Memphis Nashville Texas Abilene Amarillo AustinSan Marcos BeaumontPort Arthur Brazoria BrownsvilleHarlingenSan Benito BryanCollege Station Corpus Christi Dallas El Paso Ft. WorthArlington GalvestonTexas City Houston KilleenTemple Laredo LongviewMarshall Lubbock McAllenEdinburgMission OdessaMidland San Angelo San Antonio ShermanDenison Texarkana Tyler Victoria Waco Wichita Falls Utah ProvoOrem Salt Lake CityOgden Vermont BarreMontpelier Burlington Virginia Bristol Charlottesville Danville Lynchburg NorfolkVirginia BeachNewport News Northern Virginia RichmondPetersburg Roanoke Washington SeattleBellevueEverett Spokane Tacoma See footnotes at end of table. 91

99 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area Finance, insurance, and real estate P , , Services , , P , , , Government , P Rhode Island ProvidenceFall RiverWarwick South Carolina CharlestonNorth Charleston Columbia GreenvilleSpartanburg Anderson South Dakota Rapid City Sioux Falls Tennessee Chattanooga Johnson CityKingsportBristol Knoxville Memphis Nashville Texas Abilene Amarillo AustinSan Marcos BeaumontPort Arthur Brazoria BrownsvilleHarlingenSan Benito BryanCollege Station Corpus Christi Dallas El Paso Ft. WorthArlington GalvestonTexas City Houston KilleenTemple Laredo LongviewMarshall Lubbock McAllenEdinburgMission OdessaMidland San Angelo San Antonio ShermanDenison Texarkana Tyler Victoria Waco Wichita Falls Utah ProvoOrem Salt Lake CityOgden Vermont BarreMontpelier Burlington Virginia Bristol Charlottesville Danville Lynchburg NorfolkVirginia BeachNewport News Northern Virginia RichmondPetersburg Roanoke Washington SeattleBellevueEverett Spokane Tacoma See footnotes at end of table. 92

100 B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED Total Mining Construction State and area P P P West Virginia Charleston HuntingtonAshland ParkersburgMarietta Wheeling Wisconsin AppletonOshkoshNeenah Eau Claire Green Bay JanesvilleBeloit Kenosha LaCrosse Madison MilwaukeeWaukesha Racine Sheboygan Wausau Wyoming Casper 2, , , ) 1 ) 1 ) 1 ) ;> M1 ) 16 (J) 16.2 []) 1 ) 1 ) 1 ) 1 ) ]) 1 ) 1 ) Puerto Rico Caguas Mayaguez Ponce San JuanBayamon , ) 1 ) Virgin Islands 41.0 ( 2 ) ( 2 ) ( 2 ) ( 2 ) See footnotes at end of table. 93

101 ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) State and area Manufacturing P Transportation and public utilities P Wholesale and retail trade P West Virginia Charleston HuntingtonAshland ParkersburgMarietta Wheeling Wisconsin AppletonOshkoshNeenah Eau Claire Green Bay JanesvilleBeloit Kenosha LaCrosse Madison MilwaukeeWaukesha Racine Sheboygan Wausau Wyoming Casper Puerto Rico Caguas Mayaguez Ponce San JuanBayamon Virgin Islands ( 2 ) ( 2 ) ( 2 ) ( 2 ) 8.4 ( 2 ) ( 2 ) See footnotes at end of table. 94

102 B14. Employees on nonfarm payrolls in States and selected areas by major industry Continued (In thousands) ESTABLISHMENT DATA STATE AND AREA EMPLOYMENT NOT SEASONALLY ADJUSTED State and area Finance, insurance, and real estate P Services P Government P West Virginia Charleston HuntingtonAshland ParkersburgMarietta Wheeling Wisconsin AppletonOshkoshNeenah Eau Claire Green Bay JanesvilleBeloit Kenosha LaCrosse Madison MilwaukeeWaukesha Racine Sheboygan Wausau Wyoming Casper Puerto Rico Caguas Mayaguez Ponce San JuanBayamon Virgin Islands Combined with construction. 2 Not available. 3 Nonfarm payroll employment levels for Michigan are understated and will be corrected with the release of final estimates for on Oct. 20. The error occurred in the latest benchmark revision and affects 1998 forward. The upward adjustment to the March benchmark reference month is expected to be in the range of 35,000 to 45,000. P = preliminary. NOTE: Area definitions are published annually in the May issue of this publication. All State and area data (with the exception of data for New Jersey) have been adjusted to March benchmarks. 95

103 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Total private Goodsproducing Mining Metal mining Iron ores Copper ores Coal mining Bituminous coal and lignite mining Oil and gas extraction Crude petroleum and natural gas Oil and gas field services Nonmetallic minerals, except fuels Crushed and broken stone Construction General building contractors Residential building construction Operative builders Nonresidential building construction Heavy construction, except building Highway and street construction Heavy construction, except highway Special trade contractors Plumbing, heating, and air conditioning Painting and paper hanging Electrical work Masonry, stonework, and plastering Carpentry and floor work Roofing, siding, and sheet metal work Manufacturing Durable goods Lumber and wood products Logging Sawmills and planing mills Sawmills and planing mills, general Hardwood dimension and flooring mills... Millwork, plywood, and structural members Millwork Wood kitchen cabinets Hardwood veneer and plywood Softwood veneer and plywood Wood containers Wood buildings and mobile homes Mobile homes Miscellaneous wood products Furniture and fixtures Household furniture Wood household furniture Upholstered household furniture Metal household furniture Mattresses and bedsprings Office furniture Public building and related furniture Partitions and fixtures Miscellaneous furniture and fixtures See footnotes at end of table. 96

104 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Total private $10 $18 $18 $17 $18 $462 $ $ $475 $ Goodsproducing Mining Metal mining Iron ores Copper ores Coal mining Bituminous coal and lignite mining Oil and gas extraction Crude petroleum and natural gas Oil and gas field services , Nonmetallic minerals, except fuels Crushed and broken stone Construction General building contractors Residential building construction Operative builders Nonresidential building construction Heavy construction, except building Highway and street construction Heavy construction, except highway Special trade contractors Plumbing, heating, and air conditioning Painting and paper hanging Electrical work Masonry, stonework, and plastering Carpentry and floor work Roofing, siding, and sheet metal work Manufacturing Durable goods Lumber and wood products Logging Sawmills and planing mills Sawmills and planing mills, general Hardwood dimension and flooring mills... Millwork, plywood, and structural members Millwork Wood kitchen cabinets Hardwood veneer and plywood Softwood veneer and plywood Wood containers Wood buildings and mobile homes Mobile homes Miscellaneous wood products Furniture and fixtures Household furniture Wood household furniture Upholstered household furniture Metal household furniture Mattresses and bedsprings Office furniture Public building and related furniture Partitions and fixtures Miscellaneous furniture and fixtures See footnotes at end of table. 97

105 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Durable goods Continued Stone, clay, and glass products Flat glass Glass and glassware, pressed or blown Glass containers Pressed and blown glass, nee Products of purchased glass Cement, hydraulic Structural clay products Pottery and related products Concrete, gypsum, and plaster products Concrete block and brick Concrete products, nee Readymixed concrete Misc. nonmetallic mineral products Abrasive products Asbestos products Primary metal industries Blast furnaces and basic steel products Blast furnaces and steel mills Steel pipe and tubes Iron and steel foundries Gray and ductile iron foundries Malleable iron foundries Steel foundries, nee Primary nonferrous metals Primary aluminum Nonferrous rolling and drawing Copper rolling and drawing Aluminum sheet, plate, and foil Nonferrous wire drawing and insulating Nonferrous foundries (castings) Aluminum foundries Fabricated metal products Metal cans and shipping containers Metal cans Cutlery, handtools, and hardware Hand and edge tools, and blades and handsaws Hardware, nee Plumbing and heating, except electric Plumbing fixture fittings and trim Heating equipment, except electric Fabricated structural metal products Fabricated structural metal Metal doors, sash, and trim Fabricated plate work (boiler shops) Sheet metal work Architectural metal work Screw machine products, bolts, etc Screw machine products Bolts, nuts, rivets, and washers Metal forgings and stampings Iron and steel forgings Automotive stampings Metal stampings, nee Metal services, nee Plating and polishing Metal coating and allied services Ordnance and accessories, nee Ammunition, except for small arms, nee Misc. fabricated metal products Valves and pipe fittings, nee Misc. fabricated wire products , See footnotes at end of table. 98

106 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Durable goods Continued Stone, clay, and glass products Flat glass Glass and glassware, pressed or blown Glass containers Pressed and blown glass, nee Products of purchased glass Cement, hydraulic Structural clay products Pottery and related products Concrete, gypsum, and plaster products Concrete block and brick Concrete products, nee Readymixed concrete Misc. nonmetallic mineral products Abrasive products Asbestos products $ $ $ $ $14 $ $ $ $ $ Primary metal industries Blast furnaces and basic steel products Blast furnaces and steel mills Steel pipe and tubes Iron and steel foundries, Gray and ductile iron foundries Malleable iron foundries Steel foundries, nee Primary nonferrous metals Primary aluminum Nonferrous rolling and drawing Copper rolling and drawing Aluminum sheet, plate, and foil Nonferrous wire drawing and insulating Nonferrous foundries (castings) Aluminum foundries Fabricated metal products Metal cans and shipping containers Metal cans Cutlery, handtools, and hardware Hand and edge tools, and blades and handsaws Hardware, nee Plumbing and heating, except electric Plumbing fixture fittings and trim Heating equipment, except electric Fabricated structural metal products Fabricated structural metal Metal doors, sash, and trim Fabricated plate work (boiler shops) Sheet metal work Architectural metal work Screw machine products, bolts, etc Screw machine products Bolts, nuts, rivets, and washers Metal forgings and stampings Iron and steel forgings Automotive stampings Metal stampings, nee Metal services, nee Plating and polishing Metal coating and allied services Ordnance and accessories, nee Ammunition, except for small arms, nee Misc. fabricated metal products Valves and pipe fittings, nee Misc. fabricated wire products , See footnotes at end of table. 99

107 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED EM5. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Durable goods Continued Industrial machinery and equipment Engines and turbines Turbines and turbine generator sets Internal combustion engines, nee Farm and garden machinery Farm machinery and equipment Construction and related machinery Construction machinery Mining machinery Oil and gas field machinery Conveyors and conveying equipment Industrial trucks and tractors Metalworking machinery Machine tools, metal cutting types Machine tools, metal forming types Special dies, tools, jigs, and fixtures Machine tool accessories Power driven handtools Special industry machinery Textile machinery Printing trades machinery Food products machinery General industrial machinery Pumps and pumping equipment Ball and roller bearings Air and gas compressors Blowers and fans Speed changers, drives, and gears Power transmission equipment, nee Computer and office equipment Electronic computers Computer terminals, calculators, and office machines, nee Refrigeration and service machinery Refrigeration and heating equipment Misc. industrial and commercial machinery Carburetors, pistons, rings, valves Scales, balances, and industrial machinery, nee ,8, , Electronic and other electricai equipment.. Electric distribution equipment Transformers, except electronic Switchgear and switchboard apparatus. Electrical industrial apparatus Motors and generators Relays and industrial controls Household appliances Household refrigerators and freezers... Household laundry equipment Electric housewares and fans Electric lighting and wiring equipment Electric lamps Currentcarrying wiring devices Noncurrentcarrying wiring devices Residential lighting fixtures Household audio and video equipment... Household audio and video equipment. Communications equipment Telephone and telegraph apparatus Electronic components and accessories. Electron tubes Semiconductors and related devices Electronic components, nee Misc. electrical equipment and supplies.. Storage batteries Engine electrical equipment See footnotes at end of table. 100

108 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Durable goods Continued Industrial machinery and equipment Engines and turbines Turbines and turbine generator sets Internal combustion engines, nee Farm and garden machinery Farm machinery and equipment Construction and related machinery Construction machinery Mining machinery Oil and gas field machinery Conveyors and conveying equipment Industrial trucks and tractors Metalworking machinery Machine tools, metal cutting types Machine tools, metal forming types Special dies, tools, jigs, and fixtures Machine tool accessories Power driven handtools Special industry machinery Textile machinery Printing trades machinery Food products machinery General industrial machinery Pumps and pumping equipment Ball and roller bearings Air and gas compressors Blowers and fans Speed changers, drives, and gears Power transmission equipment, nee Computer and office equipment Electronic computers Computer terminals, calculators, and office machines, nee Refrigeration and service machinery Refrigeration and heating equipment Misc. industrial and commercial machinery Carburetors, pistons, rings, valves Scales, balances, and industrial machinery, nee ,8, ,9 $ $ $ $ $15.74 $ $ $ $ $665 Electronic and other electrical equipment Electric distribution equipment Transformers, except electronic Switchgear and switchboard apparatus Electrical industrial apparatus Motors and generators Relays and industrial controls Household appliances Household refrigerators and freezers Household laundry equipment Electric housewares and fans Electric lighting and wiring equipment Electric lamps Currentcarrying wiring devices Noncurrentcarrying wiring devices Residential lighting fixtures Household audio and video equipment Household audio and video equipment Communications equipment Telephone and telegraph apparatus Electronic components and accessories Electron tubes Semiconductors and related devices Electronic components, nee Misc. electrical equipment and supplies Storage batteries Engine electrical equipment See footnotes at end of table. 101

109 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC POHP uuuc Average weekly hours P P Average overtime hours P P Durable goods Continued Transportation equipment Motor vehicles and equipment Motor vehicles and car bodies Truck and bus bodies Motor vehicle parts and accessories Truck trailers Aircraft and parts Aircraft Aircraft engines and engine parts Aircraft parts and equipment, nee Ship and boat building and repairing Ship building and repairing Boat building and repairing Railroad equipment Guided missiles, space vehicles, and parts. Guided missiles and space vehicles Misc. transportation equipment Travel trailers and campers Instruments and related products Search and navigation equipment Measuring and controlling devices Environmental controls Process control instruments Instruments to measure electricity Medical instruments and supplies Surgical and medical instrument Surgical appliances and supplies Ophthalmic goods Photographic equipment and supplies Watches, clocks, watchcases, and parts Miscellaneous manufacturing industries Jewelry, silverware, and plated ware Jewelry, precious metal Musical instruments Toys and sporting goods Dolls, games, toys, and children's vehicles Sporting and athletic goods, nee Pens, pencils, office, and art supplies Costume jewelry and notions Costume jewelry Miscellaneous manufactures Signs and advertising specialties , Nondurable goods Food and kindred products Meat products Meat packing plants Sausages and other prepared meats Poultry slaughtering and processing Dairy products Cheese, natural and processed Fluid milk Preserved fruits and vegetables Canned specialties Canned fruits and vegetables Frozen fruits and vegetables Grain mill products Flour and other grain mill products Prepared feeds, nee See footnotes at end of table. 102

110 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Durable goods Continued Transportation equipment Motor vehicles and equipment Motor vehicles and car bodies Truck and bus bodies Motor vehicle parts and accessories Truck trailers Aircraft and parts Aircraft Aircraft engines and engine parts Aircraft parts and equipment, nee Ship and boat building and repairing Ship building and repairing Boat building and repairing Railroad equipment Guided missiles, space vehicles, and parts. Guided missiles and space vehicles Misc. transportation equipment Travel trailers and campers $ (2) (2) $ (2) (2) $ (2) (2) $ (2) (2) $ $ , $ , $ , $ , $ Instruments and related products Search and navigation equipment Measuring and controlling devices Environmental controls Process control instruments Instruments to measure electricity Medical instruments and supplies Surgical and medical instrument Surgical appliances and supplies Ophthalmic goods Photographic equipment and supplies Watches, clocks, watchcases, and parts Miscellaneous manufacturing industries Jewelry, silverware, and plated ware Jewelry, precious metal Musical instruments Toys and sporting goods Dolls, games, toys, and children's vehicles Sporting and athletic goods, nee Pens, pencils, office, and art supplies Costume jewelry and notions Costume jewelry Miscellaneous manufactures Signs and advertising specialties , Nondurable goods Food and kindred products Meat products Meat packing plants Sausages and other prepared meats Poultry slaughtering and processing Dairy products Cheese, natural and processed Fluid milk Preserved fruits and vegetables Canned specialties Canned fruits and vegetables Frozen fruits and vegetables Grain mill products Flour and other grain mill products Prepared feeds, nee , See footnotes at end of table. 103

111 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Nondurable goods Continued Food and kindred products Continued Bakery products Bread, cake, and related products Cookies, crackers, and frozen bakery products, except bread Sugar and confectionery products Raw cane sugar Cane sugar refining Beet sugar Candy and other confectionery products Fats and oils Beverages Malt beverages Bottled and canned soft drinks Misc. food and kindred products , Tobacco products Cigarettes Textile mill products Broadwoven fabric mills, cotton Broadwoven fabric mills, synthetics Broadwoven fabric mills, wool Narrow fabric mills Knitting mills Women's hosiery, except socks Hosiery, nee Knit outerwear mills Knit underwear mills Weft knit fabric mills Textile finishing, except woo! Finishing plants, cotton Finishing plants, synthetics Carpets and rugs Yarn and thread mills Yarn spinning mills Throwing and winding mills Miscellaneous textile goods Apparel and other textile products Men's and boys' suits and coats Men's and boys' furnishings Men's and boys' shirts Men's and boys' trousers and slacks Men's and boys' work clothing Women's and misses' outerwear Women's and misses' blouses and shirts Women's, juniors', and misses' dresses Women's and misses' suits and coats Women's and misses' outerwear, nee Women's and children's undergarments Women's and children's underwear Brassieres, girdles, and allied garments Girls' and children's outerwear Girls' and children's dresses and blouses Misc. apparel and accessories Misc. fabricated textile products Curtains and draperies House furnishings, nee Automotive and apparel trimmings Paper and allied products Paper mills Paperboard mills See footnotes at end of table. 104

112 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Nondurable goods Continued Food and kindred products Continued Bakery products Bread, cake, and related products Cookies, crackers, and frozen bakery products, except bread Sugar and confectionery products Raw cane sugar Cane sugar refining Beet sugar Candy and other confectionery products Fats and oils Beverages Malt beverages Bottled and canned soft drinks Misc. food and kindred products , $ $ $ $ $ , , $ , , $ , , $ , , Tobacco products Cigarettes $ , i , , $793 Textile mill products Broadwoven fabric mills, cotton Broadwoven fabric mills, synthetics Broadwoven fabric mills, wool Narrow fabric mills Knitting mills Women's hosiery, except socks Hosiery, nee Knit outerwear mills Knit underwear mills Weft knit fabric mills Textile finishing, except wool Finishing plants, cotton Finishing plants, synthetics Carpets and rugs Yarn and thread mills Yarn spinning mills Throwing and winding mills Miscellaneous textile goods Apparel and other textile products Men's and boys' suits and coats Men's and boys' furnishings Men's and boys' shirts Men's and boys' trousers and slacks Men's and boys' work clothing Women's and misses' outerwear Women's and misses' blouses and shirts Women's, juniors', and misses' dresses Women's and misses' suits and coats Women's and misses' outerwear, nee Women's and children's undergarments Women's and children's underwear Brassieres, girdles, and allied garments Girls' and children's outerwear Girls' and children's dresses and blouses Misc. apparel and accessories Misc. fabricated textile products Curtains and draperies House furnishings, nee Automotive and apparel trimmings Paper and allied products Paper mills Paperboard mills See footnotes at end of table. 105

113 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Nondurable goods Continued Paper and allied products Continued Paperboard containers and boxes Corrugated and solid fiber boxes Sanitary food containers Folding paperboard boxes Misc. converted paper products Paper, coated and laminated, nee Bags: plastics, laminated, and coated Envelopes Printing and publishing Newspapers Periodicals Books Book publishing Book printing Miscellaneous publishing Commercial printing Commercial printing, lithographic Commercial printing, nee Manifold business forms Blankbooks and bookbinding Printing trade services Chemicals and allied products Industrial inorganic chemicals Industrial inorganic chemicals, nee Plastics materials and synthetics Plastics materials and resins Organic fibers, noncellulosic Drugs Pharmaceutical preparations Soap, cleaners, and toilet goods Soap and other detergents Polishing, sanitation, and finishing preparations Toilet preparations Paints and allied products Industrial organic chemicals Cyclic crudes and intermediates Industrial organic chemicals, nee Agricultural chemicals Miscellaneous chemical products , Petroleum and coal products Petroleum refining Asphalt paving and roofing materials Rubber and misc. plastics products Tires and inner tubes Rubber and plastics footwear Hose, belting, gaskets, and packing Rubber and plastics hose and belting Fabricated rubber products, nee Miscellaneous plastics products, nee Leather and leather products Leather tanning and finishing Footwear, except rubber Men's footwear, except athletic Women's footwear, except athletic Luggage Handbags and personal leather goods Serviceproducing Transportation and public utilities See footnotes at end of table. 106

114 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Nondurable goods Continued Paper and allied products Continued Paperboard containers and boxes Corrugated and solid fiber boxes Sanitary food containers Folding paperboard boxes Misc. converted paper products Paper, coated and laminated, nee Bags: plastics, laminated, and coated Envelopes $ $ $ $ $ $ $ $ Printing and publishing Newspapers Periodicals Books Book publishing Book printing Miscellaneous publishing Commercial printing Commercial printing, lithographic Commercial printing, nee Manifold business forms Blankbooks and bookbinding Printing trade services $ $555 Chemicals and allied products Industrial inorganic chemicals Industrial inorganic chemicals, nee Plastics materials and synthetics Plastics materials and resins Organic fibers, noncellulosic Drugs Pharmaceutical preparations Soap, cleaners, and toilet goods Soap and other detergents Polishing, sanitation, and finishing preparations Toilet preparations Paints and allied products Industrial organic chemicals Cyclic crudes and intermediates Industrial organic chemicals, nee Agricultural chemicals Miscellaneous chemical products , Petroleum and coal products Petroleum refining Asphalt paving and roofing materials , , , Rubber and misc. plastics products Tires and inner tubes Rubber and plastics footwear Hose, belting, gaskets, and packing Rubber and plastics hose and belting Fabricated rubber products, nee Miscellaneous plastics products, nee Leather and leather products Leather tanning and finishing Footwear, except rubber Men's footwear, except athletic Women's footwear, except athletic Luggage Handbags and personal leather goods Serviceproducing Transportation and public utilities See footnotes at end of table. 107

115 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Transportation and public utilities Continued Railroad transportation: Class I railroads plus Amtrak Local and interurban passenger transit Local and suburban transportation Intercity and rural bus transportation Trucking and warehousing Trucking and courier services, except air. Public warehousing and storage Water transportation: Water transportation services Pipelines, except natural gas Transportation services Passenger transportation arrangement... Travel agencies Freight transportation arrangement Communications Telephone communications Telephone communications, except radio. Radio and television broadcasting Cable and other pay television services Electric, gas, and sanitary services Electric services Gas production and distribution Combination utility services Sanitary services Wholesale trade Durable goods Motor vehicles, parts, and supplies Furniture and home furnishings Lumber and other construction materials Professional and commercial equipment Medical and hospital equipment Metals and minerals, except petroleum Electrical goods Hardware, plumbing, and heating equipment. Machinery, equipment, and supplies Misc. wholesale trade durable goods Nondurable goods Paper and paper products Drugs, proprietaries, and sundries Apparel, piece goods, and notions Groceries and related products Farmproduct raw materials Chemicals and allied products Petroleum and petroleum products Beer, wine, and distilled beverages Misc. wholesale trade nondurable goods Retail trade Building materials and garden supplies. Lumber and other building materials... Paint, glass, and wallpaper stores Hardware stores Retail nurseries and garden stores See footnotes at end of table. 108

116 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Transportation and public utilities Continued Railroad transportation: Class I railroads plus Amtrak $17.54 $17.49 $182 $18.08 $796 $ $ $ Local and interurban passenger transit Local and suburban transportation Intercity and rural bus transportation Trucking and warehousing Trucking and courier services, except air Public warehousing and storage Water transportation: Water transportation services Pipelines, except natural gas Transportation services Passenger transportation arrangement Travel agencies Freight transportation arrangement Communications Telephone communications Telephone communications, except radio Radio and television broadcasting Cable and other pay television services Electric, gas, and sanitary services Electric services Gas production and distribution Combination utility services Sanitary services , , , , Wholesale trade $ $ Durable goods Motor vehicles, parts, and supplies Furniture and home furnishings Lumber and other construction materials Professional and commercial equipment Medical and hospital equipment Metals and minerals, except petroleum Electrical goods Hardware, plumbing, and heating equipment... Machinery, equipment, and supplies Misc. wholesale trade durable goods Nondurable goods Paper and paper products Drugs, proprietaries, and sundries Apparel, piece goods, and notions Groceries and related products Farmproduct raw materials Chemicals and allied products Petroleum and petroleum products Beer, wine, and distilled beverages Misc. wholesale trade nondurable goods Retail trade Building materials and garden supplies Lumber and other building materials Paint, glass, and wallpaper stores Hardware stores Retail nurseries and garden stores See footnotes at end of table. 109

117 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Retail trade Continued General merchandise stores Department stores Variety stores Misc. general merchandise stores Food stores Grocery stores. Retail bakeries Automotive dealers and service stations New and used car dealers Auto and home supply stores Gasoline service stations Automotive dealers, nee Apparel and accessory stores Men's and boys' clothing stores Women's clothing stores Family clothing stores Shoe stores Furniture and home furnishings stores Furniture and home furnishings stores... Household appliance stores Radio, television, and computer stores... Radio, television, and electronic stores. Record and prerecorded tape stores Eating and drinking places Miscellaneous retail establishments Drug stores and proprietary stores Used merchandise stores Miscellaneous shopping goods stores. Nonstore retailers Fuel dealers Retail stores, nee Optical goods stores Miscellaneous retail stores, nee Finance, insurance, and real estate Depository institutions Commercial banks State commercial banks National and commercial banks, nee. Credit unions , Nondepository institutions... Personal credit institutions Security and commodity brokers: Security and commodity services Insurance carriers Life insurance Medical service and health insurance Hospital and medical service plans.. Fire, marine, and casualty insurance Services Agricultural services See footnotes at end of table. 110

118 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Retail trade Continued General merchandise stores Department stores Variety stores Misc. general merchandise stores $ $ $ $ $ $ $ $ Food stores Grocery stores Retail bakeries Automotive dealers and service stations. New and used car dealers Auto and home supply stores Gasoline service stations Automotive dealers, nee Apparel and accessory stores Men's and boys' clothing stores Women's clothing stores Family clothing stores Shoe stores Furniture and home furnishings stores... Furniture and home furnishings stores.. Household appliance stores Radio, television, and computer stores. Radio, television, and electronic stores Record and prerecorded tape stores Eating and drinking places Miscellaneous retail establishments Drug stores and proprietary stores Used merchandise stores Miscellaneous shopping goods stores... Nonstore retailers Fuel dealers Retail stores, nee Optical goods stores Miscellaneous retail stores, nee Finance, insurance, and real estate $ $547 Depository institutions Commercial banks State commercial banks National and commercial banks, nee... Credit unions , Nondepository institutions Personal credit institutions Security and commodity brokers: Security and commodity services Insurance carriers Life insurance Medical service and health insurance... Hospital and medical service plans Fire, marine, and casualty insurance Services Agricultural services See footnotes at end of table. 111

119 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Services Continued Agricultural services Continued Veterinary services Landscape and horticultural services Hotels and other lodging places: Hotels and motels Personal services: Laundry, cleaning, and garment services Beauty shops 4 Miscellaneous personal services Business services Advertising Mailing, reproduction, and stenographic services Photocopying and duplicating services Services to buildings Disinfecting and pest control services Building maintenance services, nee Miscellaneous equipment rental and leasing Medical equipment rental Heavy construction equipment rental Equipment rental and leasing, nee Personnel supply services: Help supply services Computer and data processing services Computer programming services Computer integrated systems design Information retrieval services Computer maintenance and repair Miscellaneous business services Detective and armored car services Security systems services Auto repair, services, and parking Automotive rentals, without drivers Passenger car rental Automobile parking Automotive repair shops Automotive and tire repair shops General automotive repair shops Automotive services, except repair Carwashes , Miscellaneous repair services Motion pictures Motion picture production and services Video tape rental Amusement and recreation services Bowling centers Misc. amusement and recreation services Physical fitness facilities Membership sports and recreation clubs Health services Offices and clinics of medical doctors Offices and clinics of dentists Offices and clinics of other health practitioners.. Nursing and personal care facilities Intermediate care facilities Hospitals See footnotes at end of table. 112

120 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Services Continued Agricultural services Continued Veterinary services Landscape and horticultural services $ $ $ $ $ $ $ $ Hotels and other lodging places: Hotels and motels Personal services: Laundry, cleaning, and garment services Beauty shops 4 Miscellaneous personal services Business services Advertising Mailing, reproduction, and stenographic services: Photocopying and duplicating services Services to buildings Disinfecting and pest control services Building maintenance services, nee Miscellaneous equipment rental and leasing Medical equipment rental Heavy construction equipment rental Equipment rental and leasing, nee Personnel supply services: Help supply services Computer and data processing services Computer programming services Computer integrated systems design Information retrieval services Computer maintenance and repair Miscellaneous business services Detective and armored car services Security systems services , , Auto repair, services, and parking Automotive rentals, without drivers Passenger car rental Automobile parking Automotive repair shops Automotive and tire repair shops General automotive repair shops Automotive services, except repair Carwashes , Miscellaneous repair services Motion pictures Motion picture production and services Video tape rental Amusement and recreation services Bowling centers Misc. amusement and recreation services Physical fitness facilities Membership sports and recreation clubs Health services Offices and clinics of medical doctors Offices and clinics of dentists Offices and clinics of other health practitioners... Nursing and personal care facilities Intermediate care facilities Hospitals See footnotes at end of table. 113

121 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average weekly hours P P Average overtime hours P P Services Continued Health services Continued Home health care services Legal services Social services Individual and family services Job training and related services Child day care services Residential care Social services, nee Membership organizations: Professional organizations Engineering and management services... Engineering and architectural services... Engineering services Architectural services Surveying services Accounting, auditing, and bookkeeping.. Research and testing services Commercial physical research Commercial nonphysical research Noncommercial research organizations Management and public relations Management services Management consulting services Public relations services Services, nee See footnotes at end of table. 114

122 ESTABLISHMENT DATA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B15. Average hours and earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by detailed industry Continued Industry 1987 SIC Code Average hourly earnings P P Average weekly earnings P P Services Continued Health services Continued Home health care services 808 $16 $18 $13 $12 $356 $354 $ $365 Legal services Social services Individual and family services Job training and related services Child day care services Residential care Social services, nee Membership organizations: Professional organizations Engineering and management services... Engineering and architectural services... Engineering services Architectural services Surveying services Accounting, auditing, and bookkeeping.. Research and testing services Commercial physical research Commercial nonphysical research Noncommercial research organizations Management and public relations Management services Management consulting services Public relations services Services, nee Data relate to production workers in mining and manufacturing; construction workers in construction; and nonsupervisory workers in transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. 2 See table B15a for average hourly earnings in aircraft (SIC 3721) and guided missiles and space vehicles (SIC 3761) manufacturing. 3 Data relate to linehaul railroads with operating revenues of $25 million or more in 1993 and to Amtrak. 4 Money payments only tips; not included. 5 Excludes nonoffice commissioned real estate sales agents. ~ Data not available. P = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all unadjusted data from April forward are subject to revision. 115

123 A Note on Average Hourly Earnings in Aircraft (SIC 3721) and Guided Missiles and Space Vehicles (SIC 3761) Manufacturing For many years, the Bureau of Labor Statistics average hourly earnings series for production workers in aircraft manufacturing (SIC 3721) and guided missiles and space vehicles manufacturing (SIC 3761) have been used to escalate labor costs in contracts between aerospace companies and their customers. Although the Bureau's series by definition take account of traditional wage rate changes, they do not capture "lumpsum payments to workers in lieu of general wage increases" which were negotiated in aerospace manufacturers' collective bargaining agreements beginning in late Because of special circumstances in the aerospace industry, BLS has calculated average hourly earnings series for SIC 3721 and SIC 3761 which include lumpsum payments. These series, beginning in October 1983, the effective date of the first aerospace bargaining agreement using lumpsum payments, were published in the June 1988 issue of Employment and Earnings. Current and year earlier data are presented in table BlSa along with the average hourly earnings series produced as part of the Current Employment Statistics program. An explanation of the methodology used to derive these series appears in the Explanatory Notes of this publication. B15a. Average hourly earnings in aircraft (SIC 3721) and guided missiles and space vehicles (SIC 3761) manufacturing Aircraft (SIC 3721) Guided missiles and space vehicles (SIC 3761) Series P P Average hourly earnings, excluding lumpsum payments $20 $25 $22 $23 $21 $21.63 $21.51 $21.45 Average hourly earnings, including lumpsum payments preliminary. 116

124 B16. Average hourly earnings, excluding overtime 1, of production workers on manufacturing payrolls ESTABLISHMENT DATA EARNINGS NOT SEASONALLY ADJUSTED Industry P P Manufacturing 10 $13 $14 $12 $12 Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Fabricated metal products Industrial machinery and equipment Electronic and other electrical equipment Transportation equipment Instruments and related products Miscellaneous manufacturing (2) (2) (2) (2) (2) (2) (2) (2) (2) (2) Nondurable goods Food and kindred products Tobacco products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and misc. plastics products Leather and leather products $13 (2) (2) (2) (2) (2) (2) (2) (2) (2) (2) 1 Derived by assuming that overtime hours are paid at the rate of time and onehalf. 2 Not available. P = preliminary. NOTE: Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all unadjusted data from April forward are subject to revision. 117

125 ESTABLISHMENT DATA EARNINGS NOT SEASONALLY ADJUSTED B17. Average hourly and weekly earnings of production or nonsupervisory workers 1 on private nonfarm payrolls by major industry, in current and constant (1982) dollars 2 Average hourly earnings Average weekly earnings Industry P P P P Total private: Current dollars Constant (1982) dollars $ $ $ $ $18 (3) $ $ $ $ $ (3) Mining: Current dollars Constant (1982) dollars $179 (3) $ (3) Construction: Current dollars Constant (1982) dollars $189 (3) $ (3) Manufacturing: Current dollars Constant (1982) dollars $11 (3) $607 (3) Transportation and public utilities: Current dollars Constant (1982) dollars $16.28 (3) $639 (3) Wholesale trade: Current dollars Constant (1982) dollars $15 (3) $ (3) Retail trade: Current dollars Constant (1982) dollars $9.57 (3) $272 (3) Finance, insurance, and real estate: Current dollars Constant (1982) dollars $11 (3) $547 (3) Services: Current dollars Constant (1982) dollars $16 (3) $450 (3) 1 Data relate to production workers in mining and manufacturing; construction workers in construction; and nonsupervisory workers in transportation and public utilities; wholesale and retail trade; finance, insurance, and real estate; and services. 2 Data for all constant (1982) dollar series have been revised from January through due to corrections in the CPIW. 3 Not available. P = preliminary. NOTE: The Consumer Price Index for Urban Wage Earners and Clerical Workers (CPIW) is used to deflate the earnings series. Establishment survey estimates are currently projected from March benchmark levels. When more recent benchmark data are introduced, all unadjusted data from April forward are subject to revision. 118

126 ESTABLISHMENT DATA STATE AND AREA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B18. Average hours and earnings of production workers on manufacturing payrolls in States and selected areas Average weekly hours Average hourly earnings Average weekly earnings State and area P P P Alabama Birmingham Mobile $ $ $ $ $ $ Alaska Arizona Arkansas FayettevilleSpringdaleRogers Fort Smith Little RockNorth Little Rock Pine Bluff California Bakersfield Fresno Los AngelesLong Beach Modesto Oakland Orange County RiversideSan Bernardino Sacramento Salinas San Diego San Francisco San Jose Santa BarbaraSanta MariaLompoc Santa Rosa StocktonLodi VallejoFairfieldNapa Ventura Colorado Denver Connecticut Bridgeport Danbury Hartford New HavenMeriden New LondonNorwich StamfordNorwalk Waterbury Delaware Dover WilmingtonNewark District of Columbia: Washington PMSA Florida Georgia Atlanta Savannah Hawaii Honolulu Idaho Illinois BloomingtonNormal ChampaignUrbana Chicago DavenportMolineRock Island Decatur Kankakee PeoriaPekin Rockford Springfield , See footnotes at end of table. 119

127 ESTABLISHMENT DATA STATE AND AREA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B18. Average hours and earnings of production workers on manufacturing payrolls in States and selected areas Continued Average weekly hours Average hourly earnings Average weekly earnings State and area P P P Indiana Bloomington ElkhartGoshen EvansvilleHenderson Fort Wayne Gary Indianapolis Kokomo Lafayette Muncie South Bend Terre Haute $ $ $ $ , $ , $ , Iowa Cedar Rapids Des Moines Dubuque Sioux City Kansas Topeka Wichita Kentucky Lexington Louisville Louisiana Baton Rouge New Orleans ShreveportBossier City Maine LewistonAubum Portland Maryland Baltimore PMSA Massachusetts Boston Springfield Worcester Michigan Ann Arbor Detroit Flint Grand RapidsMuskegonHolland Jackson KalamazooBattle Creek Lansing East Lansing SaginawBay CityMidland , , , , Hiinnosoui DuluthSuperior MinneapolisSt. Paul St. Cloud Mississippi Jackson Missouri Kansas City St. Louis Springfield Montana Nebraska Lincoln Omaha Nevada Las Vegas See footnotes at end of table. 120

128 ESTABLISHMENT DATA STATE AND AREA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B18. Average hours and earnings of production workers on manufacturing payrolls in States and selected areas Continued State and area Average weekly hours P Average hourly earnings P Average weekly earnings P New Hampshire Manchester Nashua PortsmouthRochester New Jersey New Mexico Albuquerque New York AlbanySchenectadyTroy Binghamton BuffaloNiagara Falls Dutchess County Elmira NassauSuffolk New York PMSA New York City Newburgh Rochester Rockland County Syracuse UticaRome Westchester County North Carolina Asheville CharlotteGastoniaRock Hill GreensboroWinstonSalemHigh Point RaleighDurhamChapel Hill North Dakota FargoMoorhead Ohio Akron CantonMassillon Cincinnati ClevelandLorainElyria Columbus DaytonSpringfield HamiltonMiddletown Lima Mansfield SteubenvilleWeirton Toledo YoungstownWarren Oklahoma Oklahoma City Tulsa Oregon EugeneSpringfield MedfordAshland PortlandVancouver Salem Pennsylvania AllentownBethlemEaston Altoona Erie HarrisburgLebanonCarlisle Johnstown Lancaster Philadelphia PMSA Pittsburgh Reading ScrantonWilkesBarreHazleton Sharon State College Williamsport York See footnotes at end of table $ $ $ $ $ $

129 ESTABLISHMENT DATA STATE AND AREA HOURS AND EARNINGS NOT SEASONALLY ADJUSTED B18. Average hours and earnings of production workers on manufacturing payrolls in States and selected areas Continued Average weekly hours Average hourly earnings Average weekly earnings State and area P P P Rhode Island ProvidenceFall RiverWarwick South Carolina South Dakota Rapid City Sioux Falls Tennessee Chattanooga Johnson CityKingsportBristol Knoxville Memphis Nashville $ $ $ $ $ $ Texas Dallas Ft. WorthArlington Houston San Antonio Utah Salt Lake CityOgden Vermont Burlington Virginia Bristol Charlottesville Danville Lynchburg Northern Virginia RichmondPetersburg Roanoke Washington West Virginia Charleston HuntingtonAshland ParkersburgMarietta Wheeling Wisconsin AppletonOshkoshNeenah Eau Claire Green Bay JanesvilleBeloit Kenosha La Crosse Madison MilwaukeeWaukesha Racine Sheboygan Wausau Wyoming Puerto Rico Virgin Islands Not available. P = preliminary. NOTE: Area definitions are published annually in the May issue of this publication. All State and area data (with the exception of data for New Jersey) have been adjusted to March benchmarks. 122

130 LABOR FORCE DATA REGIONS AND DIVISIONS SEASONALLY ADJUSTED C1. Labor force status by census region and division, seasonally adjusted 1 (Numbers in thousands) Census region and division Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P NORTHEAST 26, , , , ,09 1, ,29 25, ,13 26, ,209 1, , ,25 1,08 26, ,36 1, ,417 25, , ,36 25, ,47 25, , ,45 25,44 1,01 26,42 25, ,367 25, ,39 25, ,01 New England 7,15 6, ,16 6, ,18 6, ,19 6, , , , , ,23 7, , , ,24 7, ,22 7, , , , , , , Middle Atlantic 19,08 18, ,08 18, , , ,12 18, ,13 18, , , ,18 18, ,16 18, , , ,230 18, ,20 18, , , ,17 18, SOUTH 2 48, , , , , ,97 48, ,77 1,97 48, , ,95 49,01 47, ,936 49,14 47,25 1, , , , , ,38 1,92 49,32 47,43 1, , , , , ,38 1,91 49, , , ,37 47,46 1,911.3 South Atlantic 2 25,101 24, ,18 24, , , , , , , , , , , , , ,63 24, , , ,63 24, , , , , East South Central 8,21 7, , , , , , , ,27 7, ,31 7, ,33 7, ,33 7, , , ,33 7, , , , , , ,99 34 West South Central 15, , , , ,211 14, , , , , , , ,35 14, ,36 14, ,367 14, ,38 14, ,33 14, , , , , See footnotes at end of table. 123

131 LABOR FORCE DATA REGIONS AND DIVISIONS SEASONALLY ADJUSTED C1. Labor force status by census region and division, seasonally adjusted 1 Continued (Numbers in thousands) Census region and division Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P MIDWEST 3 33,47 32, ,20 33,54 32, , , , , , ,56 1,15 33, ,671 1,14 33, ,791 1, , ,77 1, , , ,14 33,95 32,81 1, , , , ,95 32, ,17 33,99 32,79 1,200 33,99 32, ,211.6 East North Central 3 23,27 22, , , , , ,40 22, , , , , , , ,49 22, ,55 22, , , , , ,59 22, ,57 22, West North Central 10, , , , , , , , , , ,38 10, , , , , , , , , ,39 10, , , , ,13 28 WEST 31, , , , ,78 1, , , , ,43 29, , , ,06 1,44 31, , , ,641 30,24 1, , ,25 1,43 31,78 30,36 1, , , , ,92 30,42 1, , , ,48 31, ,44 1,50 Mountain 8,87 8, ,89 8, , , , , ,99 8, ,01 8, , , ,03 8, ,04 8, ,04 8, , , ,07 8, , , Pacific 22,36 21, ,13 22,36 21, , ,42 21,31 1, , ,37 1, ,51 21,41 1, ,59 21, ,07 22, , , ,65 21, ,10 22, , , ,77 21,63 1, ,87 21, ,17 22, , ,15 22,877 21, ,160.9 p = preliminary. 1 These estimates are obtained from summing offical State estimates produced and published through the Local Area Unemployment Statistics (LAUS) program. 2 June LAUS estimates for the South region and the South Atlantic division have been corrected as the result of a correction for Florida. 3 LAUS estimates for the Midwest region and East North Central division are subject to revision when Current Employment Statistics data for Michigan are corrected. NOTE: 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. 124

132 STATE LABOR FORCE DATA SEASONALLY ADJUSTED C2. Labor force status by State, seasonally adjusted (Numbers in thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Alabama 2,14 2, ,15 2, , , , , ,18 2, , , , , , , , ,09 9 2, , , , , , Alaska Arizona , , , , ,39 2, , , , ,30 9 2,398 2,30 9 2, , , , ,30 9 2,39 2, , Arkansas 1,22 1, , , , ,18 5 1,24 1,19 5 1,25 1, ,20 5 1, , , , , , , , , , California 16, , , , , ,69 15, , , ,79 15, ,80 16, , , ,94 16, , , , , Colorado 2,26 2, ,27 2, ,281 2, , , , , ,31 2, , , , , , , ,32 2, , ,24 6 Connecticut. 1, , , , ,69 1, , ,697 1, , , , , , , , , ,70 1, ,70 1, , , Delaware District of Columbia Florida , , , , , , , , , , , , , , ,581 7, ,59 7, , , See footnotes at end of table. 125

133 STATE LABOR FORCE DATA SEASONALLY ADJUSTED C2. Labor force status by State, seasonally adjusted Continued (Numbers in thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Georgia 4, ,10 3, , , , , , ,14 4, ,15 4, , , , , Hawaii Idaho Illinois , ,41 6, ,41 6, , , , , , , ,43 6, , , , , , , , Indiana Unemployment ra'.e ,98 9 3, ,098 3, ,10 3, , , , , ,11 3, ,09 2, , Iowa.. 1, , , , ,578 1, , ,54 3 1,58 1, ,58 1, , ,55 3 1,58 1,55 3 1, ,57 1, , ,54 3 1, ,54 3 Kansas. 1, ,39 4 1, ,39 4 1,44 1, ,44 1, , , , , , , , ,45 1, ,45 1, ,45 1,40 49 Kentucky 1,97 1, , , , ,89 8 1, , , , , , , , , ,986 1, , ,98 1, , , , , Louisiana 2, , ,05 1, , , ,056 1,96 9 2, , ,04 1, , ,05 1, , , , ,03 1,94 9 2,031 1, Maine See footnotes at end of table. 126

134 STATE LABOR FORCE DATA SEASONALLY ADJUSTED C2. Labor force status by State, seasonally adjusted Continued (Numbers in thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P Maryland 2, ,66 9 2, , ,79 2, ,80 2, , , , , ,82 2, ,82 2, ,82 2, , , , , , , , Massachusetts 3,28 3, ,28 3, ,29 3, ,29 3, ,29 3, , , ,30 3, ,27 3, ,30 3, , ,20 8 3, , ,29 3, ,28 3, Michigan 2 5,14 4, , , , , , , ,09 4, , , , , , , , , , , , , ,13 4, , , Minnesota 2,70 2, , ,63 7 2, ,64 7 2, , , , , , , , ,75 2, , , , ,68 8 2,75 2, ,76 2, ,77 2, Mississippi 1, , , ,21 6 1,28 1, , , , , ,30 1, ,31 1, ,31 1, , , ,32 1, , , , , , , Missouri. 2, , ,86 2, , , , , , , , , , , , , ,92 2,84 8 2, ,85 7 2, , , , Montana Nebraska Nevada New Hampshire See footnotes at end of table. 127

135 STATE LABOR FORCE DATA SEASONALLY ADJUSTED C2. Labor force status by State, seasonally adjusted Continued (Numbers in thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P New Jersey 4 4, , ,218 4, , , , , , ,22 4, ,23 4, , ,246 4, , , ,22 4, ,22 4, ,24 4, New Mexico New York 8,88 8, , , , , , , ,97 8, , , , ,02 8, , , , , , , , ,57 40 North Carolina 3, , , , , , ,90 3, ,91 3, ,930 3, ,95 3, ,93 3, , , , , , , , , North Dakota ,76 5, , ,80 5, ,82 5, ,85 5, ,869 5, , , ,87 5, ,87 5, , , ,87 5, , , , Oklahoma , ,65 1, ,65 1,60 5 1, , ,60 5 1,65 1, ,65 1, , ,65 1, ,648 1, , , ,65 1, , ,606 5 Oregon 1,75 1, , ,767 1, ,69 9 1, , ,80 1, , , ,73 8 1, ,74 8 1, ,81 1, , , , Pennsylvania.... 5, ,97 5, , ,969 5, ,99 5, , , ,959 5, ,959 5, , ,96 5, ,957 5, ,95 5, Rhode Island South Carolina 1, ,96 1, ,97 1, , , , , , ,98 1, ,98 1, ,98 1, ,00 1, ,00 1, ,007 1, , , See footnotes at end of table. 128

136 STATE LABOR FORCE DATA SEASONALLY ADJUSTED C2. Labor force status by State, seasonally adjusted Continued (Numbers in thousands) State Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June P South Dakota Tennessee 2,82 2, ,82 2, , , ,82 2, , , , , , , , , , , , , , ,84 2, Texas 10, , , ,26 9, , , , ,37 9, , , , , , , , , , , Itah uian 1, , , , ,09 1, ,09 1, , , ,10 1, , ,07 3 1, , , , , , , , , , Vermont Virginia 3,52 3, , , , , , , ,53 9 3,64 3, , , , , , ,55 9 3, , , ,641 3, Washington Civilian <aix»r force 3, , , ,07 2, ,07 2, , ,07 2, ,081 2, , , , , ,08 2, ,10 2, , , ,06 2, West Virginia Wisconsin 2, ,79 8 2,89 2, ,92 2, ,95 2, , , , , ,00 2, , ,91 9 3,01 2, , , , , , , Wyoming UnemDloved Puerto Rico UnemDloved 1,29 1, , , ,29 1, , , , , , , , , , , , , ,34 1, ,30 1, ,31 1, , , P s preliminary. 1 June LAUS estimates for Florida have been corrected. 2 LAUS estimates for Michigan are subject to revision when Current Employment Statistics data for Michigan are corrected. NOTE: Data refer to place of residence. Data for Puerto Rico are derived from a monthly household survey similar to the Current Population Survey. All estimates are provisional and will be revised when new benchmark and population information becomes available. 129

137 STATE AND AREA LABOR FORCE DATA NOT SEASONALLY ADJUSTED C3. Labor force status by State and metropolitan area (Numbers in thousands) State and area P Number P Percent of labor force P Alabama Anniston AuburnOpelika Birmingham Decatur Dothan Florence Gadsden Huntsville Mobile Montgomery Tuscaloosa Alaska Anchorage Arizona Flagstaff PhoenixMesa Tucson Yuma Arkansas FayettevilleSpringdaleRogers Fort Smith Jonesboro Little RockNorth Little Rock Pine Bluff California Bakersfield ChicoParadise Fresno Los AngelesLong Beach Merced Modesto Oakland Orange County Redding RiversideSan Bernardino Sacramento Salinas San Diego San Francisco San Jose San Luis ObispoAtascaderoPaso Robles Santa BarbaraSanta MariaLompoc Santa CruzWatsonville Santa Rosa StocktonLodi VallejoFairfieldNapa Ventura VisaliaTularePorterville Yolo YubaCity Colorado BoulderLongmont Colorado Springs Denver Fort CollinsLoveland Grand Junction Greeley Pueblo Connecticut Bridgeport Danbury Hartford New HavenMeriden New LondonNorwich StamfordNorwalk Waterbury Delaware Dover WilmingtonNewark 2, , , , , , ,22 1,48 7 1, , , , , , , , , , , , , , , , , , , , , , , , ,48 7 1, , , , , , ,41 6 1, , , , ,24 1, , , , , , See footnotes at end of table. 130

138 STATE AND AREA LABOR FORCE DATA NOT SEASONALLY ADJUSTED C3. Labor force status by State and metropolitan area Continued (Numbers in thousands) State and area Civilian laoor force 29 2,66 7, , , , , , , , , , , , , , , , , , , ,64 7, , , , , , , P 28 2,72 7, , , , , , , Number P Percent of labor force P District of Columbia. Washington Florida Daytona Beach Fort Lauderdale Fort MyersCape Coral Fort PiercePort St. Lucie Fort Walton Beach Gainesville Jacksonville LakelandWinter Haven MelboumeTitusvillePalm Bay Miami Naples Ocala Orlando Panama City Pensacola Punta Gorda SarasotaBradenton Tallahassee TampaSt. PetersburgClearwater... West Palm BeachBoca Raton Georgia Albany Athens Atlanta aaiken Columbus Macon Savannah Hawaii Honolulu. Idaho Boise City. Pocatello... Illinois BloomingtonNormal ChampaignUrbana Chicago DavenportMolineRock Island... Decatur Kankakee PeoriaPekin Rockford Springfield Indiana Bloomington ElkhartGoshen EvansvilleHenderson. Fort Wayne Gary Indianapolis Kokomo Lafayette Muncie South Bend Terre Haute Iowa Cedar Rapids Des Moines Dubuque Iowa City Sioux City WaterlooCedar Falls. See footnotes at end of table. 131

139 STATE AND AREA LABOR FORCE DATA NOT SEASONALLY ADJUSTED C3. Labor force status by State and metropolitan area Continued (Numbers in thousands) State and area Civilian lador Torce 1, , , , , , , , , , , , , , , , ,88 1, , , , , , , , , , , , , , , , ,32 8 1, , , , , , , , P 1, , , , , , , , , , , , , , , Number P Percent of labor force P Kansas Lawrence Topeka Wichita Kentucky Lexington Louisville Owensboro Louisiana Alexandria Baton Rouge Houma Lafayette Lake Charles Monroe New Orleans ShreveportBossier City Maine Bangor LewistonAubum Portland Maryland Baltimore Cumberland Hagerstown Massachusetts Bamstable Yarmouth Boston Brockton FitchburgLeominster Lawrence Lowell New Bedford Pittsfield Springfield Worcester Michigan 1 Ann Arbor Benton Harbor Detroit Flint Grand RapidsMuskegonHolland Jackson KalamazooBattle Creek LansingEast Lansing SaginawBay CityMidland Minnesota DuluthSuperior MinneapolisSt.Paul Rochester St. Cloud Mississippi BiloxiGulf portpascagoul a Hattiesburg Jackson Missouri Columbia Joplin Kansas City St. Joseph St. Louis LMA Springfield Montana Billings Great Falls Missoula See footnotes at end of table. 132

140 STATE AND AREA LABOR FORCE DATA NOT SEASONALLY ADJUSTED C3. Labor force status by State and metropolitan area Continued (Numbers in thousands) State and area Civilian laoor rorce , , , ,44 4, , , , , , , , , , , , , , , , , ,43 4, , , , , P , , , ,16 3, , , , Number P Percent of labor force P Nebraska... Lincoln... Omaha... Nevada Las Vegas. Reno New Hampshire Manchester Nashua PortsmouthRochester.. New Jersey AtlanticCape May BergenPassaic Jersey City MiddlesexSomersetHunterdon. MonmouthOcean Newark Trenton VinelandMillvilleBridgeton New Mexico Albuquerque. Las Cruces... Santa Fe New York AlbanySchenectadyTroy... Binghamton BuffaloNiagara Falls Dutchess County Elmira Glens Falls Jamestown NassauSuffolk NewYork New York City Newburgh Rochester Syracuse UticaRome North Carolina Asheville CharlotteGastoniaRock Hill Fayetteville Goldsboro Greensboro WinstonSalem High Point Greenville HickoryMorgantonLenoir Jacksonville RaleighDurhamChapel Hill Rocky Mount Wilmington North Dakota Bismarck FargoMoorhead.. Grand Forks Ohio Akron CantonMassillon Cincinnati ClevelandLorainElyria Columbus DaytonSpringfield HamiltonMiddletown Lima Mansfield SteubenvilleWeirton Toledo YoungstownWarren See footnotes at end of table. 133

141 STATE AND AREA LABOR FORCE DATA NOT SEASONALLY ADJUSTED C3. Labor force status by State and metropolitan area Continued (Numbers in thousands) State and area Oklahoma Enid Lawton Oklahoma City Tulsa Oregon Corvallis EuQeneSpringfield.... MedfordAshland PortlandVancouver Salem Pennsylvania AllentownBethlehemEaston Altoona Erie HarrisburgLebanonCarlisle Johnstown Lancaster Philadelphia Pittsburgh Reading... Scranton WilkesBarre Hazleton Sharon State College.... Williamsport York Rhode Island ProvidenceFall RiverWarwick South Carolina CharlestonNorth Charleston Columbia Florence GreenvilleSpartanburgAnderson Myrtle Beach Sumter South Dakota Rapid City Sioux Falls Tennessee Chattanooga. ClarksvilleHopkinsville Jackson Johnson CityKingsportBristol Knoxville Memphis Nashville Texas Abilene Amarillo AustinSan Marcos... BeaumontPort Arthur Brazoria BrownsvilleHarlingenSan Benito BrvanColleae Station Corpus Christi Dallas El Paso.. Fort WorthArlinaton GalvestonTexas City Houston. KilleenTemple Laredo.. LongviewMarshall Lubbock McAllenEdinburgMission OdessaMidland San Angelo San Antonio ShermanDenison Texarkana 1, , , , ,57 1, , , , , , , , , , , , , , , , , , , , , , , , , , , , P 1, , , , ,57 1, , , , , Number P Percent of labor force P See footnotes at end of table. 134

142 STATE AND AREA LABOR FORCE DATA NOT SEASONALLY ADJUSTED C3. Labor force status by State and metropolitan area Continued (Numbers in thousands) State and area Number Percent of labor force P P P Texas Continued Tyler Victoria Waco Wichita Falls Utah ProvoOrem Salt Lake CityOgden 1, , , , Vermont Burlington Virginia Chariottesville Danville Lynchburg NorfolkVirginia BeachNewport News RichmondPetersburg Roanoke 3, , , , Washington Bellingham Bremerton Olympia RichlandKennewickPasco SeattleBellevueEverett Spokane Tacoma Yakima 3, , , , , , , , West Virginia Charleston HuntingtonAshland ParkersburgMarietta Wheeling Wisconsin AppletonOshkoshNeenah Eau Claire Green Bay JanesvilleBeloit Kenosha LaCrosse Madison MilwaukeeWaukesha Racine Sheboygan Wausau 2, , , , Wyoming Casper Cheyenne Puerto Rico Aguadilla Arecibo Caguas Mayaguez Ponce San JuanBayamon 1, , , , P = preliminary. 1 LAUS estimates for Michigan and its substate areas are subject to revision when Current Employment Statistics data are corrected. NOTE: Data refer to place of residence. Data for Puerto Rico are derived from a monthly household survey similar to the Current Population Survey. All estimates are provisional and will be revised when new benchmark and population information becomes available. 135

143 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D1. Employment status of the civilian noninstitutional population by sex and age, seasonally adjusted (Numbers in thousands) Employment status, sex, and age 1997 IV 1998 IV IV TOTAL Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 2 203, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,652 Men, 16 years and over Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 2 Agriculture Nonagricultural industries Not in labor force 97,839 73, , ,522 67,317 3,475 24,525 98,139 73, , ,481 67,633 3,404 24,621 98,326 73, , ,458 67,855 3,362 24,651 98,595 73, , ,536 68,097 3,169 24,793 98,894 74, , ,620 68,075 3,309 24,891 99,216 74, , ,579 68,546 3,195 24,896 99,280 74, , ,444 68,845 3,106 24,884 99,565 74, , ,446 68,802 3,086 25,231 99,867 74, , ,402 69,099 3,046 25, ,177 74, , ,443 69,317 3,019 25, ,334 75, , ,466 69,915 2,984 24, ,569 75, , ,398 69,760 2,907 25, ,852 75, , ,493 69,782 2,913 25,664 Men, 20 years and over Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 2 Agriculture Nonagricultural industries Not in labor force 89,979 69, , ,343 64,132 2,767 20,738 90,244 69, , ,307 64,311 2,780 20,846 90,456 69, , ,272 64,530 2,677 20,977 90,634 69, , ,353 64,746 2,519 21,016 90,898 69, , ,397 64,720 2,603 21,178 91,171 70, , ,361 65,158 2,494 21,158 91,176 70, , ,258 65,384 2,440 21,094 91,386 70, , ,258 65,301 2,470 21,357 91,682 70, , ,227 65,577 2,440 21,437 91,978 70, , ,232 65,812 2,375 21,559 92,098 70, , ,281 66,304 2,368 21,145 92,419 70, , ,233 66,148 2,312 21,726 92,753 70, , ,311 66,321 2,292 21,830 Women, 16 years and over Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 2 Agriculture Nonagricultural industries Not in labor force 105,528 63, , ,217 3,139 42, ,797 63, , ,455 2,983 42, ,069 63, , ,717 3,051 42, ,310 63, , ,814 2,907 42, ,588 63, , ,982 2,898 42, ,882 64, , ,273 2,918 42, ,596 64, , ,926 2,875 42, ,866 64, , ,092 2,844 43, ,177 64, , ,197 2,822 43, ,484 65, , ,560 2,708 43, ,580 65, , ,953 2,749 42, ,808 65, , ,115 2,720 43, ,090 65, , ,832 2,739 43,684 Women, 20 years and over Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 2 Agriculture Nonagricultural industries Not in labor force 98,000 59, , ,017 2,551 38,610 98,219 59, , ,215 2,439 38,735 98,475 59, , ,285 2,552 38,867 98,662 59, , ,400 2,383 39,134 98,891 59, , ,528 2,373 39,197 99,118 59, , ,829 2,388 39,139 99,755 60, , ,468 2,329 39, ,021 60, , ,664 2,332 39, ,291 60, , ,800 2,287 39, ,566 61, , ,079 2,188 39, ,652 61, , ,503 2,241 39, ,915 61, , ,562 2,283 39, ,214 61, , ,360 2,238 39,829 Both sexes, 16 to 19 years Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 2 Agriculture Nonagricultural industries Not in labor force 15,387 7, , ,385 1, ,478 15,473 7, , ,563 1, ,520 15,464 8, , ,757 1, ,277 15,609 8, , ,766 1, ,423 15,694 8, , ,810 1, ,375 15,809 8, , ,832 1, ,479 15,945 8, , ,919 1, ,582 16,025 8, , ,929 1, ,731 16,071 8, , ,919 1, ,794 16,117 8, , ,986 1, ,710 16,164 8, , ,061 1, ,744 16,043 8, , ,166 1, ,619 15,974 8, , ,933 1, ,690 1 The population figures are not adjusted for seasonal variation. D11 will not necessarily add to totals because of the independent seasonal 2 Employment as a percent of the civilian noninstitutional population. adjustment of the various series. Beginning in January, data reflect revised N O T E: Detail for the seasonally adjusted data shown in tables D1 through population controls used in the household survey. 136

144 D2. Employment status of the civilian noninstitutionai population by race, sex, age, and Hispanic origin, seasonally adjusted (Numbers in thousands) HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES Employment status, race, sex, age, and Hispanic origin 1997 IV 1998 IV IV WHITE Civilian noninstitutionai population 1 Percent of population Employmentpopulation ratio 2 170, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,129 Men, 20 years and over Percent of population Employmentpopulation ratio 2 59, , ,074 59, , ,059 59, , ,974 59, , ,864 59, , ,939 59, , ,888 59, , ,847 59, , ,857 59, ,836 59, , ,699 60, , ,730 60, , ,675 60, , ,679 Women, 20 years and over Percent of population Employmentpopulation ratio 2 48, , ,780 49, , ,678 48, , ,773 48, , ,650 49, , ,659 49, , ,665 49, , ,632 49, , ,698 49, , ,603 49, , , , ,573 50, , ,625 50, , ,625 Both sexes, 16 to 19 years Percent of population Employmentpopulation ratio 2 Men Women 6, , , , , , , , , , , , , , , , , , , , , , , , , , BLACK Civilian noninstitutionai population 1 Percent of population Employmentpopulation ratio 2 24,043 15, , , ,149 15, , , ,227 15, , , ,319 15, , , ,419 15, , , ,529 16, , , ,697 16, , , ,799 16, , , ,906 16, , , ,018 16, , , ,076 16, , , ,162 16, , , ,260 16, , , Men, 20 years and over Percent of population Employmentpopulation ratio 2 7, , , , , , , , , , , , , , , , , , , , , , , , , , Women, 20 years and over Percent of population Employmentpopulation ratio 2 7, , , , , , , , , , , , , , , , , , , , , , , , , , See footnotes at end of table. 137

145 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D2. Employment status of the civilian noninstitutional population by race, sex, age, and Hispanic origin, seasonally adjusted Continued (Numbers in thousands) Employment status, race, sex, age, and Hispanic origin 1997 IV 1998 IV IV BLACKContinued Both sexes, 16 to 19 years Percent of population Employmentpopulation ratio 2 Men Women , , , , HISPANIC ORIGIN Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 2 20,408 13, , , ,574 13, , , ,797 14, , ,975 14, , , ,160 14, , , ,347 14, , , ,355 14, , ,549 14, , ,752 14, , ,945 14, , ,107 15, , ,293 15, , ,488 15, , The population figures are not adjusted for seasonal variation. 2 Employment as a percent of the civilian noninstitutional population. NOTE: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 138

146 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D3. Employment status of the civilian noninstitutional population 25 years and over by educational attainment, seasonally adjusted (Numbers in thousands) Educational attainment 1997 IV 1998 III IV IV Less than a high school diploma Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 29,318 12, , ,372 12, , ,487 12, , ,878 12, , ,174 12, , ,964 12, , ,485 12, , ,268 11, , ,389 12, , ,206 12, , ,631 11, , ,131 11, , ,180 12, , High school graduates, no college 2 Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 57,557 37, , ,577 57,467 37, , ,506 57,636 37, , ,556 57,545 37, , ,455 57,564 37, , ,483 57,351 37, , ,444 57,448 37, , ,320 57,946 37, , ,366 57,292 37, , ,307 57,551 37, , ,241 57,757 37, , ,297 57,781 37, , ,281 57,090 36, , ,269 Less than a bachelor's degree 3 Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 42,266 31, , ,005 42,372 31, , ,186 31, , ,069 31, , ,968 31, , ,819 31, , ,365 32, , ,860 31, , ,231 32, , ,975 32, , ,133 32, , ,100 32, , ,510 33, , College graduates Civilian noninstitutional population 1 Percent of population Employmentpopulation ratio 41,391 33, , ,752 33, , ,099 33, , ,250 34, , ,470 34, , ,471 34, , ,775 35, , ,398 35, , ,070 35, , ,724 35, , ,048 36, , ,995 36, , ,710 35, , The population figures are not adjusted for seasonal variation. 2 Includes high school diploma or equivalent. 3 Includes the categories, some college, no degree; and associate degree. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 139

147 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D4. and unemployed full and parttime workers by sex and age, seasonally adjusted (Numbers in thousands) Full and parttime status, sex, and age 1997 IV 1998 IV IV III EMPLOYED Fulltime 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 106,915 62,478 61,204 44,456 43,543 2, ,711 61,385 44,489 43,583 2, ,548 62,765 61,473 44,732 43,763 2, ,942 63,113 61,767 44,815 43,866 2, ,346 63,233 61,877 45,188 44,125 2, ,981 63,647 62,233 45,326 44,431 2, ,930 63,919 62,537 45,947 45,057 2, ,989 63,732 62,315 46,254 45,286 2, ,090 63,864 62,427 46,302 45,329 2, ,222 64,207 62,782 46,992 45,941 2, ,155 64,848 63,459 47,200 46,244 2, ,550 64,959 63,428 47,569 46,502 2, ,238 65,130 63,641 47,193 46,141 2,456 Parttime 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 22,995 7,366 5,283 15,654 13,288 4,424 23,305 7,432 5,247 15,865 13,490 4,568 23,346 7,541 5,330 15,791 13,286 4,730 23,309 7,515 5,319 15,790 13,275 4,716 23,106 7,468 5,241 15, ,685 23,281 7,493 5,289 15,784 13,194 4,798 23,203 7,370 5,132 15,814 13,217 4,853 23,209 7,515 5,236 15,691 13,200 4,773 23,343 7,618 5,379 15,741 13,228 4,736 23,001 7,559 5,254 15,437 12,964 4,782 23,179 7,533 5,163 15,629 13,113 4,903 22,671 7,202 4,957 15,463 12,941 4,774 22,611 7,160 5,001 15,498 12,966 4,644 UNEMPLOYED Looking for fulltime work 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 5,269 2,915 2,526 2,366 2, ,117 2,892 2,558 2,240 1, ,072 2,722 2,449 2,303 2, ,867 2,683 2,323 2,214 1, ,903 2,765 2,383 2,141 1, ,801 2,643 2,286 2,185 1, ,746 2,520 2,242 2,152 1, ,694 2,558 2,240 2,169 1, ,662 2,571 2,235 2,099 1, ,563 2,536 2,161 2,067 1, ,546 2,409 2,155 2,049 1, ,480 2,449 2,102 2,073 1, ,460 2,436 2,073 2,028 1, Looking for parttime work 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 1, , , , , , , , , , , , , UNEMPLOYMENT RATES 1 Fulltime 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 Parttime 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 These rates reflect a refined definition of the full and parttime labor force and differ from the rates published elsewhere in this publication prior to NOTE: Beginning in January, data reflect revised population controls used in the household survey. 140

148 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D5. persons by marital status, occupation, class of worker, and parttime status, seasonally adjusted (In thousands) Category III 1997 IV 1998 I II III IV I II III IV MARITAL STATUS Total Married men, spouse present Married women, spouse present Women who maintain families 129,927 42,637 32,895 7, ,448 42,838 32,896 7, ,861 42,854 32,816 7, ,256 42,722 32,834 7, ,526 42,930 32,795 7, ,208 43,171 33,037 7, ,077 43,227 33,277 8, ,214 43,162 33,495 8, ,526 43,362 33,389 8, ,153 43,254 33,639 8, ,247 43,594 33,943 8, ,200 43,282 33,829 8, ,941 43,327 33,478 8,516 OCCUPATION Managerial and professional specialty.. Technical, sales, and administrative support Service occupations Precision production, craft, and repair... Operators, fabricators, and laborers Farming, forestry, and fishing 37,674 38,415 17,679 14,184 18,463 3,469 38,017 38,569 17,849 14,184 18,362 3,455 38,328 38,467 17,894 14,347 18,441 3,408 38,650 38,496 17,710 14,625 18,329 3,483 39,089 38,702 17,768 14,279 18,072 3,565 39,676 38,429 17,979 14,407 18,179 3,528 39,849 38,912 18,051 14,639 18,225 3,449 40,588 38,844 17,987 14,378 17,957 3,475 40,802 38,727 17,947 14,471 18,112 3,399 40,627 39,206 17,678 14,893 18,372 3,380 40,775 39,609 18,404 14,604 18,333 3,589 40,890 39,496 18,385 14,752 18,301 3,418 40,895 39,077 17,893 15,218 18,463 3,368 CLASS OF WORKER Agriculture: Wage and salary workers Selfemployed workers Unpaid family workers Nonagricultural industries: Wage and salary workers Private industries Private households Other industries Government Selfemployed workers Unpaid family workers PERSONS AT WORK PART TIME 1 1,860 1, ,490 99, ,378 18,198 8, ,825 1, ,049 99, ,963 18,166 8, ,919 1, , ,311 1,010 99,300 18,243 8, ,932 1, , , ,560 18,304 9, ,091 1, , , ,695 18,333 9, ,042 1, , , ,170 18,651 8, ,922 1, , , ,204 18,797 8, ,928 1, , , ,285 18,852 8, ,926 1, , , ,281 19,075 8, ,001 1, , , ,179 18,893 8, ,031 1, , , ,729 19,335 8, ,040 1, , , ,110 19,075 8, ,048 1, , , ,379 18,658 8, All industries: Part time for economic reasons Slack work or business conditions Could only find parttime work Part time for noneconomic reasons 4,023 2,201 1,499 17,961 3,951 2,248 1,393 18,275 3,877 2,174 1,392 18,483 3,749 2,125 1,293 18,469 3,586 2,094 1,190 18,583 3,424 1,972 1,153 18,679 3,474 2,018 1,145 18,629 3,393 1,978 1,093 18,720 3,293 1,933 1,060 19,005 3,258 1,936 1,017 18,689 3,161 1, ,897 3,163 1,872 1,005 18,397 3,141 1, ,574 Nonagricultural industries: Part time for economic reasons Slack work or business conditions Could only find parttime work Part time for noneconomic reasons 3,849 2,089 1,470 17,403 3,761 2,137 1,360 17,662 3,706 2,060 1,365 17,885 3,602 2,042 1,258 17,888 3,404 1,989 1,158 17,988 3,265 1,882 1,127 18,136 3,316 1,925 1,109 18,053 3,221 1,864 1,069 18,134 3,127 1,823 1,046 18,464 3,082 1, ,131 3,018 1, ,312 3,028 1, ,846 3,000 1, ,037 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: Beginning in January, data reflect revised population controls used in the household survey. 141

149 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D6. persons by age and sex, seasonally adjusted (In thousands) Age and sex 1997 IV 1998 IV IV Total, 16 years and over , , , , , , , , , , , , , to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over Men, 16 years and over 16 to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 19,023 6,613 2,630 3,979 12, ,905 94,908 16,016 69,839 9,936 3,364 1,352 1,999 6,572 59,921 50,954 8,961 19,224 6,785 2,697 4,093 12, ,203 94,839 16,373 70,114 9,997 3,496 1,397 2,100 6,501 60,099 51,010 9,113 19,501 7,004 2,789 4,203 12, ,368 94,996 16,391 70,313 10,119 3,511 1,422 2,087 6,608 60,189 51,144 9,054 19,579 7,012 2,749 4,279 12, ,700 95,137 16,514 70,633 10,197 3,534 1,400 2,154 6,662 60,450 51,249 9,171 19,566 7,088 2,766 4,326 12, ,956 95,340 16,640 70,695 10,159 3,578 1,391 2,182 6,581 60,548 51,252 9,299 19,789 7,098 2,748 4,349 12, ,393 95,575 16,840 71,125 10,308 3,606 1,380 2,218 6,703 60,798 51,460 9,364 19,966 7,151 2,782 4,362 12, ,124 96,177 16,959 71,289 10,365 3,647 1,420 2,224 6,718 60,924 51,509 9,426 19,967 7,166 2,785 4,391 12, ,264 96,039 17,170 71,248 10,309 3,689 1,434 2,273 6,619 60,951 51,398 9,517 20,084 7,137 2,795 4,332 12, ,438 96,105 17,354 71,501 10,461 3,696 1,444 2,237 6,764 61,052 51,439 9,614 20,249 7,243 2,811 4,431 13, ,879 96,600 17,304 71,761 10,533 3,717 1,449 2,260 6,816 61,208 51,643 9,588 20,524 7,296 2,827 4,459 13, ,729 97,188 17,551 72,381 10,777 3,796 1,492 2,301 6,981 61,589 51,891 9,722 20,546 7,392 2,821 4,577 13, ,682 96,993 17,640 72,157 10,721 3,777 1,442 2,347 6,944 61,437 51,747 9,667 20,530 7,163 2,712 4,446 13, ,444 96,664 17,815 72,274 10,659 3,642 1,365 2,269 7,017 61,640 51,826 9,830 Women, 16 years and over 60,088 60,334 60,548 60,622 60,831 61,083 61,788 61,966 62,025 62,392 62,866 63,043 62, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 9,086 3,248 1,278 1,981 5,838 50,984 43,953 7,054 9,227 3,289 1,300 1,993 5,938 51,103 43,829 7,259 9,382 3,493 1,367 2,116 5,889 51,178 43,852 7,337 9,382 3,478 1,349 2,124 5,904 51,250 43,889 7,343 9,407 3,510 1,376 2,144 5,897 51,408 44,088 7,340 9,481 3,492 1,368 2,131 5,989 51,595 44,115 7,475 9,601 3,504 1,362 2,138 6,097 52,200 44,668 7,533 9,659 3,477 1,351 2,118 6,182 52,313 44,641 7,653 9,623 3,440 1,351 2,095 6,183 52,386 44,666 7,740 9,716 3,527 1,363 2,171 6,190 52,671 44,957 7,716 9,747 3,500 1,335 2,158 6,248 53,140 45,298 7,830 9,825 3,615 1,379 2,230 6,210 53,245 45,246 7,973 9,872 3,520 1,347 2,177 6,351 52,804 44,838 7,985 NOTE: Beginning in January, data reflect revised population controls used in the household survey. 142

150 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D7. persons by age and sex, seasonally adjusted (In thousands) Age and sex III 1997 IV 1998 II III IV I II III IV Total, 16 years and over... 6,614 6,387 6,412 6,076 6,207 6,114 5,981 5,930 5,868 5,727 5,733 5,627 5, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 2,374 1, ,078 4,260 3, ,332 1, ,163 4,048 3, ,348 1, ,165 4,067 3, ,228 1, ,054 3,842 3, ,348 1, ,118 3,869 3, ,205 1, ,899 3, ,240 1, ,028 3,741 3, ,171 1, ,043 3,754 3, ,175 1, ,034 3,701 3, ,235 1, ,071 3,492 3, ,195 1, ,071 3,543 3, ,120 1, ,088 3,494 3, ,057 1, ,600 3, Men, 16 years and over 3,475 3,404 3,362 3,169 3,309 3,195 3,106 3,086 3,046 3,019 2,984 2,907 2, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 1, ,170 1, , ,107 1, , ,053 1, , ,948 1, , ,000 1, , ,972 1, , ,900 1, , ,887 1, , ,890 1, , ,796 1, , ,814 1, , ,750 1, , ,775 1, Women, 16 years and over 3,139 2,983 3,051 2,907 2,898 2,918 2,875 2,844 2,822 2,708 2,749 2,720 2, to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 1, ,090 1, , ,941 1, , ,014 1, , ,894 1, , ,869 1, ,927 1, , ,841 1, ,867 1, , ,811 1, , ,696 1, , ,729 1, ,743 1, ,824 1, NOTE: Beginning in January, data reflect revised population controls used in the household survey. 143

151 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D8. s by age and sex, seasonally adjusted (Percent) Age and sex 1997 IV 1998 IV IV Total, 16 years and over to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over Men, 16 years and over 16 to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over , Women, 16 years and over 16 to 24 years 16 to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over NOTE: Beginning in January, data reflect revised population controls used in the household survey. 144

152 D9. s by occupation, industry, and selected demographic characteristics, seasonally adjusted (Percent) HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES Category 1997 IV 1998 IV IV CHARACTERISTIC Total Men, 20 years and over Women, 20 years and over Both sexes, 16 to 19 years White Black and other Black Hispanic origin Married men, spouse present Married women, spouse present Women who maintain families OCCUPATION 1 Managerial and professional specialty Technical, sales, and administrative support Precision production, craft, and repair Operators, fabricators, and laborers Farming, forestry, and fishing INDUSTRY Nonagricultural private wage and salary workers Goodsproducing industries Mining Construction Manufacturing, Durable goods Nondurable goods Serviceproducing industries Transportation and public utilities Wholesale and retail trade Finance, insurance, and real estate, Services Government workers Agricultural wage and salary workers, Seasonally adjusted data for service occupations are not available because the seasonal component, which is small relative to the trendcycle and/or irregular components, cannot be separated with sufficient precision. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 145

153 HOUSEHOLD DATA SEASONALLY ADJUSTED QUARTERLY AVERAGES D10. persons by reason for unemployment, seasonally adjusted (Numbers in thousands) Reason 1997 IV 1998 IV IV NUMBER OF UNEMPLOYED Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Job leavers Reentrants New entrants 2, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , PERCENT DISTRIBUTION 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, data reflect revised population controls used in the household survey. D11. persons by duration of unemployment, seasonally adjusted (Numbers in thousands) Duration 1997 IV 1998 IV IV NUMBER OF UNEMPLOYED Less than 5 weeks 5 to 14 weeks 15 weeks and over 15 to 26 weeks 27 weeks and over 2,470 2,098 2, ,077 2,522 1,982 1, ,657 1,936 1, ,598 1,992 1, ,608 1,971 1, ,642 1,912 1, ,501 1,940 1, ,594 1,825 1, ,607 1, ,589 1,755 1, ,624 1,779 1, ,527 1,860 1, ,517 1,792 1, Average (mean) duration, in weeks Median duration, in weeks PERCENT DISTRIBUTION Total unemployed Less than 5 weeks 5 to 14 weeks 15 weeks and over 15 to 26 weeks 27 weeks and over NOTE: Beginning in January, data reflect revised population controls used in the household survey. 146

154 D12. Employment status of the civilian noninstitutional population by sex, age, race, and Hispanic origin (Numbers in thousands) HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES Employment status, sex, and age III Total III White III Black III Hispanic origin III TOTAL Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 208, , ,207 3, ,679 5,935 67, , , ,577 3, ,943 5,718 68, , , ,837 3, ,511 4,226 56, , , ,824 3, ,414 4,105 56,662 24,906 16, , ,017 1, ,334 25,260 16, , ,139 1, ,639 21,752 14, , , ,969 22,488 15, , , ,097 Men, 16 years and over Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 99,867 75, ,251 2,612 69,639 2,923 24, ,852 75, ,008 2,717 70,292 2,796 25,047 84,031 64, ,877 2,450 59,428 2, ,023 84,732 64, ,347 2,528 59,819 2,002 20,382 11,167 7, , , ,444 11,339 7, , , ,498 10,760 8, , , ,139 11,109 8, , , ,147 Men, 20 years and over Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 91,682 70, ,166 2,381 65,786 2,302 21,213 92,753 71, ,976 2,478 66,497 2,163 21,615 77,512 60, ,327 2,227 56,101 1,689 17,495 78,240 60, ,808 2,297 56,510 1,547 17,885 9,946 7, , , ,748 10,128 7, , , ,802 9,564 7, , , ,581 9,902 8, , , ,578 Women, 16 years and over Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 108,177 64, , ,040 3,012 43, ,090 65, , ,652 2,921 43,599 89,249 53, , ,084 2,095 36,194 89,860 53, , ,596 2,103 36,280 13,738 8, , , ,890 13,920 8, , , ,140 10,992 6, , , ,830 11,379 6, , , ,950 Women, 20 years and over Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 100,291 60, , ,372 2,449 39, ,214 61, , ,913 2,394 40,055 83,031 49, , ,928 1,707 33,579 83,653 49, , ,415 1,735 33,682 12,475 8, , , ,170 12,668 8, , , ,450 9,870 5, , , ,191 10,241 5, , , ,301 Both sexes, 16 to 19 years Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 16,071 8, , ,521 1, ,074 15,974 8, , ,533 1, ,977 12,737 7, , , ,143 12,700 7, , , ,096 2,485 1, ,415 2,464 1, ,386 2,318 1, ,197 2,345 1, ,219 NOTE: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 147

155 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D13. Employment status of the Mexican, Puerto Rican, and Cubanorigin population by sex and age (Numbers in thousands) Employment status, sex, and age Total Hispanic origin 1 I I Mexican origin I I Puerto Rican origin I I Cuban origin I I TOTAL Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force , , , ,969 22, ,578 9, , , ,338 14,462 10, , , ,450 2,040 1, , , ,941 1, , , , , Men, v6 years and over Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 10, ,139 11, , ,147 6,928 5, , S292 7,409 6, , , , Men, 20 years and over Civilian noninstitutional population, Percent of population Agriculture Nonagricultural industries Not in labor force 9,564 7, , , , , , , ,578 6,104 5, , , ,544 5, , , Women, 16 years and over Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 10,992 6, , ,379 6, , , ,950 6,649 3, , , ,046 7,053 3, , , ,149 1, , Women, 20 years and over Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 9,870 5, , , ,191 10,241 5, , , ,301 5,853 3, , ,588 6,213 3, , , , Both sexes, 16 to 19 years Civilian noninstitutional population Percent of population Agriculture Nonagricultural industries Not in labor force 2,318 1, ,345 1, ,219 1, , ( 2 ) ( 2 ) 47 1 Includes persons of Central or South American origin and of other Hispanic origin, not shown separately. * Data not shown where base is less than 60,000. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 148

156 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D14. white, black, and Hispanicorigin workers by sex, occupation, class of worker, and full or parttime status (Numbers in thousands) Total White Black Hispanic origin Category III III III SEX Total (all civilian workers) Men Women 134,207 72,251 61, ,577 73,008 62, ,837 61,877 50, ,824 62,347 51,477 15,138 7,075 8,063 15,290 7,193 8,096 13,819 8,151 5,668 14,507 8,539 5,968 OCCUPATION Managerial and professional specialty Executive, administrative, and managerial Professional specialty 40,644 19,623 21,021 40,762 19,658 21,103 35,242 17,295 17,947 35,124 17,319 17,805 3,256 1,456 1,800 3,385 1,496 1,889 1,975 1, ,001 1, Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical 38,825 4,468 16,090 18,267 39,129 4,382 16,290 18,458 32,704 3,738 13,990 14,976 32,949 3,582 14,143 15,224 4, ,356 2,558 4, ,456 2,464 3, ,259 1,796 3, ,353 1,783 Service occupations Private household Protective service Service, except private household and protective 18, ,553 14,777 18, ,462 14,910 13, ,947 11,287 14, ,957 11,504 3, ,643 3, ,659 2, ,265 2, ,410 Precision production, craft, and repair Mechanics and repairers Construction trades Other precision production, craft, and repair 14,488 4,819 5,837 3,832 15,249 4,942 6,440 3,867 12,834 4,210 5,327 3,296 13,441 4,332 5,830 3,279 1, , , , , Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Construction laborers Other handlers, equipment cleaners, helpers, and laborers 18,240 7,327 5,561 5, ,399 18,587 7,255 5,715 5,617 1,122 4,495 14,577 5,728 4,529 4, ,489 14,791 5,672 4,582 4, ,562 2,878 1, ,928 1, ,086 1, , ,270 1, , Farming, forestry, and fishing 3,807 3,755 3,519 3, CLASS OF WORKER Agriculture: Wage and salary workers Selfemployed workers Unpaid family workers Nonagricultural industries: Wage and salary workers Government Private industries Private households Other industries Selfemployed workers Unpaid family workers 2,113 1, ,637 18, , ,933 8, ,251 1, ,090 18, , ,987 8, ,966 1, ,426 14,928 86, ,703 8, ,093 1, ,535 14,743 87, ,145 7, ,531 2,959 11, , ,578 2,773 11, , ,321 1,403 10, , ,010 1,388 11, , FULL OR PARTTIME STATUS Fulltime workers Parttime workers 111,871 22, ,950 21,627 93,478 19,359 94,981 18,843 13,061 2,077 13,397 1,893 11,893 1,926 12,636 1,871 NOTE: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household data. 149

157 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D15. Mexican, Puerto Rican, and Cubanorigin workers by sex, occupation, class of worker, and full or parttime status (In thousands) Category Total Hispanic origin 1 III III Mexican origin III Puerto Rican origin III III Cuban origin III III SEX Total (all civilian workers) Men Women 13,819 8,151 5,668 14,507 8,539 5,968 8,657 5,332 3,325 9,422 5,815 3,606 1, , OCCUPATION Managerial and professional specialty Executive, administrative, and managerial Professional specialty 1,975 1, ,001 1, , Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical 3, ,259 1,796 3, ,353 1,783 1, ,029 1, , Service occupations Private household Protective service Service, except private household and protective 2, ,265 2, ,410 1, ,453 1, , Precision production, craft, and repair Mechanics and repairers Construction trades Other precision production, craft, and repair 1, , , , , Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Construction laborers Other handlers, equipment cleaners, helpers, and laborers 3,086 1, , ,270 1, , , , Farming, forestry, and fishing CLASS OF WORKER Agriculture: Wage and salary workers Selfemployed workers Unpaid family workers Nonagricultural industries: Wage and salary workers Government Private industries Private households Other industries Selfemployed workers Unpaid family workers ,321 1,403 10, , ,010 1,388 11, , , , , , , , , , FULL OR PARTTIME STATUS Fulltime workers Part time workers 11,893 1,926 12,636 1,871 7,447 1,209 8,224 1,198 1, Includes persons of Central or South American origin and of other Hispanic origin, not shown separately. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 150

158 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D16. persons by age, sex, race, and Hispanic origin (In thousands) Total White Black Hispanic origin Age and sex III III III III III Total, 16 years and over , , , ,824 15,138 15,290 13,819 14, to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 7,813 3,195 4,618 13, ,204 95,978 17,226 7,836 3,110 4,727 13, ,150 96,458 17,693 6,764 2,775 3,989 10,962 95,111 79,886 15,224 6,781 2,709 4,072 11,326 95,718 80,181 15, ,660 12,716 11,327 1, ,637 12,862 11,391 1, ,893 11,009 9,925 1, ,030 11,562 10,371 1,190 Men, 16 years and over 72,251 73,008 61,877 62,347 7,075 7,193 8,151 8, to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 4,085 1,680 2,405 6,961 61,205 51,616 9,590 4,032 1,598 2,434 7,197 61,779 51,968 9,811 3,550 1,445 2,105 5,938 52,389 43,810 8,579 3,539 1,408 2,131 6,105 52,703 43,994 8, ,953 5, ,070 5, ,162 6,455 5, ,252 6,763 6, Women, 16 years and over 61,956 62,569 50,960 51,477 8,063 8,096 5,668 5, to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over 3, ,213 6,229 51,999 44,362 7,637 3,804 1,511 2,293 6,393 52,372 44,490.7,882 3,214 1,330 1,884 5,024 42,722 36,077 6,645 3,241 1,301 1,940 5,221 43,015 36,188 6, ,763 6, ,792 6, ,554 4, ,798 4, NOTE: Beginning in January, data reflect revised population controls used in the household survey. 151

159 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D17. s by age, sex, race, and Hispanic origin Age and sex III Total III III White III III Black III Hispanic origin III III Total, 16 years and over to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over Men, 16 years and over to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over Women, 16 years and over to 19 years 16 to 17 years 18 to 19 years 20 to 24 years 25 years and over 25 to 54 years 55 years and over NOTE: Beginning in January, data reflect revised population controls used in the household survey. 152

160 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D18. persons by reason for unemployment, race, and Hispanic origin (Numbers in thousands) Total White Black Hispanic origin Reasons III III III III III III II! NUMBER OF UNEMPLOYED Total unemployed Job losers and persons who completed temporary jobs On temporary layoff Not on temporary layoff Permanent job losers Persons who completed temporary jobs Job leavers Reentrants New entrants 5,935 2, ,773 1, , ,718 2, ,655 1, , ,226 1, , , ,105 1, , , , , PERCENT DISTRIBUTION 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: Detail for the above race and Hispanicorgin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 153

161 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D19. persons by duration of unemployment, race, and Hispanic origin (Numbers in thousands) Total White Black Hispanic origin Duration III III III III III III NUMBER OF UNEMPLOYED Total, 16 years and over Less than 5 weeks 5 to 14 weeks 15 weeks and over 15 to 26 weeks 27 weeks and over 5,935 2,679 1,858 1, ,718 2,598 1,861 1, ,226 2,023 1, ,105 1,982 1, , , Average (mean) duration, in weeks Median duration, in weeks Total unemployed Less than 5 weeks 5 to 14 weeks 15 weeks and over 15 to 26 weeks 27 weeks and over PERCENT DISTRIBUTION NOTE: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 154

162 D20. Median weekly earnings of fulltime wage and salary workers by selected characteristics HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES Characteristic Number of workers (in thousands) III Median weekly earnings III III SEX AND AGE Total, 16 years and over 99, ,462 $546 $575 Men, 16 years and over 16 to 24 years 25 years and over 56,199 7,296 48,903 57,430 7,719 49, Women, 16 years and over 16 to 24 years 25 years and over 42,853 5,433 37,421 44,031 5,872 38, RACE, HISPANIC ORIGIN, AND SEX White Men Women 81,874 47,670 34,204 83,623 48,505 35, Black Men Women 12,496 5,972 6,524 12,776 6,143 6, Hispanic origin Men Women 11,087 6,841 4,246 11,767 7,271 4, NOTE: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 155

163 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D21. Median weekly earnings of parttime wage and salary workers by selected characteristics Characteristic III Number of workers (in thousands) III Median weekly earnings III III SEX AND AGE Total, 16 years and over 19,996 19,103 $171 $174 Men, 16 years and over 16to 24 years 25 years and over 6,135 3,383 2,752 5,721 3,169 2, Women, 16 years and over 16 to 24 years 25 years and over 13,861 4,330 9,531 13,382 4,168 9, RACE, HISPANIC ORIGIN, AND SEX White Men Women 17,316 5,222 12,094 16,578 4,871 11, Black Men Women 1, ,289 1, , Hispanic origin Men Women 1, ,081 1, , NOTE: Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other races" group are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 156

164 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D22. Median weekly earnings of fulltime wage and salary workers by occupation and sex Occupation and sex Number of workers (in thousands) I I Median weekly earnings I I TOTAL Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Mechanics and repairers Construction trades Other precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Farming, forestry, and fishing 30,779 14,792 15,988 27,749 3,634 9,860 14,255 11, ,191 8,624 11,914 4,383 4,043 3,488 15,429 6,771 4,678 3,980 1,879 31,849 15,482 16,367 28,620 3,780 10,237 14,603 11, ,147 8,537 12,336 4,287 4,553 3,495 15,740 6,631 4,724 4,386 1,881 $ $ Men Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Mechanics and repairers Construction trades Other precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Farming, forestry, and fishing 15,635 7,998 7,637 10,664 1,863 5,491 3,310 5, ,804 3,593 10,863 4,182 3,941 2,740 11,996 4,418 4,391 3,186 1,620 16,144 8,319 7,824 11,072 1,941 5,564 3,567 5, ,796 3,427 11,285 4,082 4,461 2,741 12,130 4,205 4,341 3, $ , $ Women Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Mechanics and repairers Construction trades Other precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Farming, forestry, and fishing 15,145 6,794 8,351 17,085 1,771 4,370 10,944 5, ,030 1, ,434 2, , ,543 17,548 1,839 4,673 11,036 5, , ,611 2, $ Data not shown where base is less than 100,000. NOTE: Beginning in January, data reflect revised population controls used in the household survey. 157

165 HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES D23. Employment status of male Vietnamera veterans and nonveterans by age (Numbers in thousands) Civilian noninstitutional population Total Veteran status and age III III III III Number III Percent of labor force III III VIETNAMERA VETERANS Total, 40 years and over 40 to 54 years 40 to 44 years 45 to 49 years 50 to 54 years 55 years and over 7,754 5, ,826 3,123 2,319 7,699 4, ,495 3,143 2,780 6,321 4, ,587 2,731 1,586 6,159 4, ,309 2,725 1,888 6,166 4, ,536 2,669 1,557 5,986 4, ,264 2,643 1, NONVETERANS Total, 40 to 54 years 40 to 44 years 45 to 49 years 50 to 54 years 21,460 9,467 7,407 4,586 22,491 9,689 7,898 4,904 19,387 8,749 6,708 3,929 20,367 8,925 7,159 4,284 18,942 8,539 6,561 3,842 19,916 8,719 6,994 4, NOTE: Male Vietnamera veterans are men who served in the Armed Forces between 5, 1964 and May 7, Nonveterans are men who have never served in the Armed Forces. Beginning in January, data reflect revised population controls used in the household survey. 158

166 D24. Employment status of male Vietnamera veterans and nonveterans by age, race, and Hispanic origin (Numbers in thousands) HOUSEHOLD DATA NOT SEASONALLY ADJUSTED QUARTERLY AVERAGES Veterans Nonveterans Employment status and age White Black Hispanic origin White Black Hispanic origin III Total, 40 to 54 years Civilian noninstitutional population 4,766 4,219 4, ,268 3,744 3, ,106 16,616 16, ,037 17,487 17, ,234 1,786 1, ,307 1,836 1, ,203 1,939 1, ,279 2,026 1, to 44 years Civilian noninstitutional population ,988 7,481 7, ,166 7,622 7, , , , to 49 years Civilian noninstitutional population 1,569 1,388 1, ,233 1,089 1, ,253 5,763 5, ,723 6,177 6, to 54 years Civilian noninstitutional population 2,801 2,483 2, ,814 2,460 2, ,865 3,373 3, ,148 3,688 3, Data not shown where base is less than 60,000. NOTE: Male Vietnamera veterans are men who served in the Armed Forces between 5, 1964 and May 7, Nonveterans are men who have never served in the Armed Forces. Detail for the above race and Hispanicorigin groups will not sum to totals because data for the "other racesgroup are not presented and Hispanics are included in both the white and black population groups. Beginning in January, data reflect revised population controls used in the household survey. 159

167 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 50,000 households (beginning with January 1996 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 from mail questionnaires and telephone interviews by the Bureau of Labor Statistics, in cooperation with State agencies. 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 Nation, States, and metropolitan areas. The employment, hours, and earnings series are based on payroll reports from a sample of about 300,000 establishments employing about 48 million nonfarm wage and salary 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 BETWEEN THE 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), selfemployed persons, and unpaid workers who worked 15 hours or more during the reference week in familyoperated 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. 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 labormanagement 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 private production or nonsupervisory workers paid for by 160

168 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 paid 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 from the establishment survey generally refer to average earnings of production and related workers in mining and manufacturing, construction workers in construction, and nonsupervisory employees in private serviceproducing 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 off, 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 selfemployed 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. 161

169 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 over. 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 50,000 occupied units are eligible for interview. Some 3,200 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 6 and 7 percent. In addition to the 50,000 occupied units, there are about 9,000 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 threefourths of the sample to be common from one month to the next, and onehalf 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. 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, labormanagement 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. 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 some time during the 4week 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 never worked. Each of these five categories of the unemployed can be exp r essed 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.) 162

170 Jobseekers. All unemployed persons who made specific efforts to find a job sometime during the 4week period preceding the survey week are classified as jobseekers. Jobseekers 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 employer directly or to a public or private employment agency, seeking assistance from friends 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 to 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.. The unemployment rate represents the number unemployed as a percent of the labor force. Participation rate. This represents the proportion of the population that is in the labor force. Employmentpopulation ratio. This represents the proportion of the population that is employed. Not in the labor force. Included in this group are all persons in the civilian noninstitutional population who are neither employed nor unemployed. Information is collected on their desire for 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 4week 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 looking 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. The occupational and industrial classification of CPS data is based on the coding systems used in the 1990 census. The classofworker breakdown assigns workers to the following categories: Private and government wage and salary workers, selfemployed 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. Selfemployed persons are those who work for profit or fees in their own business, profession, trade, or farm. Only the unincorporated selfemployed are included in the selfemployed category in the class of worker typology. Selfemployed 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 selfemployed 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 selfemployed 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 fulltime work, and seasonal declines in demand. Those who usually work part time must also indicate that they want and are available for fulltime 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 job where fulltime 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 parttime status. Data on persons "at work" 163

171 exclude persons who were temporarily absent from a job and therefore classified in the zerohoursworked 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 parttime status. In this context, fulltime 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, parttime 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 fulltime labor force includes all employed persons who usually work full time and unemployed persons who are either looking for fulltime work or are on layoff from fulltime jobs. The parttime labor force consists of employed persons who usually work part time and unemployed persons who are seeking or are on layoff from parttime jobs. s for full and parttime workers are calculated using the concepts of the full and parttime labor force. White, black, and other. These are terms used to describe the race of persons. Included in the "other" group are American Indians, Alaskan Natives, and Asians and Pacific Islanders. Because of the relatively small sample size, data for "other" races are not published. In the enumeration process, race is determined by the household respondent. Hispanic origin. This refers to persons who identified themselves in the enumeration process as Mexican, Puerto Rican, Cuban, Central or South American, or of other Hispanic origin or descent. Persons of Hispanic origin may be of any race; thus, they are included in both the white and black population groups. Vietnamera veterans. These are persons who served in the Armed Forces of the United States between 5, 1964, and May 7, Published data are limited to men in the civilian noninstitutional population; that is, veterans in institutions and women are excluded. Nonveterans are persons who never served in the Armed Forces. 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 selfemployed persons regardless of whether or not 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 (CPIU). Single, 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, 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 marriedcouple 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 marriedcouple 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 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. 164

172 In 1953, the current 484 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. Before this system was introduced, households were interviewed for 6 consecutive months and then replaced. The new system provided some yeartoyear 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 greater consistency with the reference period used for other laborrelated 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. The only exception was the small subgroup in school during the reference week but waiting to start new jobs, which was transferred to not in the labor force. In 1967, more substantive changes were made as a result of the recommendations of the President's Committee to Appraise Employment and Unemployment Statistics (the Gordon Committee). The principal improvements were as follows: a) A 4week 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 the concept mainly affected students, who, for example, may begin to look for summer jobs in the spring although they will not be available until June or. Such persons, until 1967, had been classified as unemployed but 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 selfemployment. In 1994, major changes to the Current Population Survey (CPS) were introduced, which included a complete redesign of the questionnaire and the use of computerassisted 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 stateoftheart 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 fulltime work) was tightened by adding two new criteria for persons who usually work part time: They must want and be available for fulltime 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 ex 165

173 pect 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 63 (Washington, U.S. Census Bureau and Bureau of Labor Statistics, March ), 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. Fourfifths 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 blackandother 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 blackandother 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 blackandother 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 "inflationdeflation" approach. This change in the derivation of the estimates had its greatest impact on estimates of 20 to 24yearold men particularly those in the blackandother 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 InflationDeflation Method of Estimation," in the February 1974 issue of this publication. Effective in 1975, as a result of the large inflow of Vietnamese refugees to the United States, the total and blackandother 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 blackandother population by less than 1 percent in any agesex 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, oneeighth 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 firststage 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 and an indication of the differences appear in "Revisions in the Current Population Survey in January 1979" in the February 1979 issue of this publication. Beginning in January 1982, the secondstage ratio adjustment 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 Population Survey Beginning in January 1982" in the Feb 166

174 ruary 1982 issue of this publication. In addition, current population estimates used in the secondstage estimation procedure 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 estimates 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 firststage ratio adjustment method was updated to incorporate data from the 1980 census. The rationale for the change and an indication of its effect on national estimates for labor force characteristics 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 between the old and new procedures in estimates of levels for the various labor force characteristics and virtually no differences in estimates of participation rates. Beginning in January 1985, most of the steps of the CPS estimation procedure the noninterview adjustment, the first and secondstage ratio adjustments, and the composite 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 "Changes in the Estimation Procedure in the Current Population Survey Beginning in January 1985" 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 of persons of Hispanic origin. Major estimates were revised back to January Beginning in January 1986, the population controls used in the secondstage 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 foreignborn 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 Hispanicorigin 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 1989, the secondstage 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 censusbased population controls, adjusted for the estimated undercount, were introduced into the secondstage 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 million, employment by about 880,000, and unemployment by approximately 175,000. The overall unemployment rate rose by about 0 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 secondstage 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 Hispanicorigin 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 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: (229,000), total employed (256,000), and total unemployed (+27,000). s were not significantly affected. 167

175 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 foreignborn legal residents. As a result, the Hispanicorigin 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, 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 nonhispanic 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 " in the February issue of this publication. Beginning in January, the population controls used in the survey were revised to reflect newly updated information on immigration and an upward revision in the number of deaths. As a result, the civilian noninstitutional population 16 years and over was lowered by about 215,000. The labor force and employment levels were decreased by about 125,000 and 120,000, respectively. Overall and subgroup unemployment rates and other percentages of labor market participation were not significantly 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 " in the February issue of this publication. Changes in the occupational and industrial classification systems Beginning in 1971, the comparability of 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. s 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 selfemployed 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 censusbased 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. 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. 168

176 Changes in this regard since 1960 are as foliows: 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 Statebased 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 8month period, AprilNovember 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 The 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 censusbased 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 AngelesLong Beach metropolitan area. In 1996, the original sample design reliability criteria were modified to reduce costs. 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 6percent unemployment rate to establish a consistent specification of sampling error. The current sample design, introduced in January 1996, includes about 59,000 households from 754 sample areas and maintains a percent CV on national monthly estimates of unemployment level. This translates into a change of 0.2 percentage point in the unemployment rate being significant at a 90percent 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 6percent unemployment rate. 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 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 59,000 housing units are assigned for data collection, of which about 50,000 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 50,000 housing units, about 6.5 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 94,000 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 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 selfrepresenting 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 nonselfrepresenting because it represents not only itself but the entire stratum. The probability of selecting a particular PSU in a nonselfrepresenting 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 169

177 and State reliability requirements. The State sampling ratios range roughly 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 withinpsu sample design was developed using blocklevel 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 grouped into three strata: Unit, group quarters, and area. (Occasionally, units within a block were split between the unit and groupquarters strata.) The unit stratum contained regular housing units with addresses that were easy to locate (for example, most singlefamily 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 groupquarters 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 withinpsu sample would reflect the demographic and socioeconomic characteristics of the PSU, blocks within the unit, groupquarters, and area strata were sorted using geographic and blocklevel data from the census. Examples of the census variables used for sorting include proportion of minority renteroccupied housing units, proportion of housing units with female householders, and proportion of owneroccupied 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 groupquarters 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 uptodate 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 monthtomonth and yeartoyear 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. CPS sample, 1947 to present. Table 1A 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 "The Current Population Survey: Design and Methodology," Technical Paper 63, (Washington, U.S. Census Bureau and Bureau of Labor Statistics, March ). available on the Internet at A description of the 1990 censusbased sample design appears in "Redesign of the Sample for the Current Population Survey," in the May 1994 issue of this publication. 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 areas within a State. Through a series of estimation steps (outlined below), the selection probabilities are adjusted for noninterviews and survey undercoverage; data from previous months are incorporated into the estimates through the composite estimation procedure. 170

178 Table 1 A. Characteristics of the CPS sample, 1947 to present Period Number of sample areas Interviewed Households eligible Not interviewed Households visited but not eligible 1947 to Jan Feb to Apr May 1956 to Dec Jan to Feb Mar to Dec Jan to to to Dec Jan to Dec Jan to Apr May 1981 to Dec Jan to Mar Apr to Mar April 1989 to Oct Nov to to Dec Jan to present ,000 21,000 33,500 33,500 33,500 48,000 45,000 45,000 53,500 62,200 57,800 57,000 53,200 57,400 54,500 52,900 46, , ,000 1,500 1,500 1,500 2,000 2,000 2,000 2,500 2,800 2,500 2,500 2,600 2,600 3,500 3,400 3,200 3,0003,500 3,0003,500 6,000 6,000 6,000 8,500 8,000 8,000 10,000 12,000 11,000 11,000 11,500 11,800 10,000 9,700 9,000 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 8month period, April November Includes 2,000 additional assigned housing units from Georgia and Virginia that were gradually phased in during the 10month period, October /. 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 nonmsa cluster is split by "urban" and "rural" residence categories. The proportion of sample households not interviewed varies from 6 to 7 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. Firststage 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. This adjustment is made to the CPS weights in two race cells: Black and nonblack; it is applied only to PSUs that are not selfrepresenting 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 selfrepresenting PSUs.) b. Secondstage ratio estimation. This procedure substantially reduces the variability of estimates and corrects, to some extent, for CPS undercoverage. The CPS sample weights are adjusted to ensure that samplebased estimates of population match independent population controls. Three sets of controls are used: 1)51 State controls of the civilian noninstitutional population 16 years of age and older, 2) National civilian noninstitutional population controls for 14 Hispanic and 5 nonhispanic agesex categories, 3) National civilian noninstitutional population controls for 66 white, 42 black, and 10 "other" agesex categories. 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. Esti 171

179 mates of net census undercount, determined from the Post Enumeration Survey, are added to the population projections. Prior to January 1994, the projections were based on earlier censuses, and there was no correction for census undercount. A summary of the current procedures used to make population projections is given in "Revisions in the Current Population Survey Effective January 1994," appearing in the February 1994 issue of this publication. 3. 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 twostage ratio estimate based on the entire sample from the current month and the composite estimate for the previous month, plus an estimate of the monthtomonth 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 bias associated with monthinsample estimates. This monthinsample 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 monthtomonth 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 alway equal the totals shown in the same tables because 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 monthtomonth 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 and some results may be found in "The Current Population Survey Reinterview Program, January 1961 through December 1966," Technical Paper No. 19 (Washington, U.S. Census Bureau, 1968). The effects of some components of nonsampling error in 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 agesexraceorigin 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 agesexraceorigin 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 63 (Washington, U.S. Census Bureau and Bureau of Labor Statistics, March ), available on the Internet at The last document includes a comprehensive discussion of various sources of errors and describes attempts to measure them in the CPS. 172

180 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 6 standard errors below the estimate to 6 standard errors above the estimate would include the true population value. 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 errors for consecutive monthtomonth changes in the estimates. It is impractical to show approximate standard errors for all CPS estimates in this publication, so table 1D 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 formulas 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 Table 1 B. Approximate standard errors for major employment status categories (In thousands) Characteristic Total Total, 16 years and over:. Men, 20 years and over: Women, 20 years and over: Both sexes, 16 to 19 years: Black Total, 16 years and over:... Men, 20 years and over: Women, 20 years and over: Both sexes, 16 to 19 years: Hispanic origin Total, 16 years and over: Monthly level Consecutive monthtomonth change 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 in 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 1B and 1C. These tables provide a quick reference for standard errors of major characteristics. Table 173

181 Table 1 C. Approximate standard errors for unemployment rates by major characteristics (In percent) Characteristic Total Men Men, 20 years and over Women Women, 20 years and over Both sexes, 16 to 19 years White Black Hispanic origin Married men, spouse present Married women, spouse present Women who maintain families Occupation Managerial and professional specialty Executive, administrative, and managerial Professional specialty Technical, sales, and administrative support Technicians and related support Sales occupations Administrative support, including clerical Service occupations Private household Protective service Service, except private household and protective Precision production, craft, and repair Mechanics and repairers Construction trades Other precision production, craft, and repair Operators, fabricators, and laborers Machine operators, assemblers, and inspectors Transportation and material moving occupations Handlers, equipment cleaners, helpers, and laborers Construction laborers Other handlers, equipment cleaners, helpers, and laborers Farming, forestry, and fishing Industry Nonagricultural private wage and salary workers Goodsproducing industries Mining Construction Manufacturing Durable goods Nondurable goods Serviceproducing industries Transportation, communications, and public utilities Wholesale and retail trade Finance, insurance, and real estate.. Services Government workers Agricultural wage and salary workers Monthly rate Consecutive monthtomonth change B gives approximate standard errors for estimates of monthly levels and consecutive monthtomonth changes in levels for major employment status categories. Table 1C gives approximate standard errors for estimates of monthly unemployment rates and consecutive monthtomonth changes in unemployment rates for some demographic, occupational, and industrial categories. For characteristics not given in tables 1 B and 1 C, refer to table 1 D. Illustration. Suppose that, for a given month, the number of women age 20 years and over in the civilian labor force is estimated to be 60,000,000. For this characteristic, the approximate standard error of 245,000 is given in table 1 B in the row "Women, 20 years and over; Civilian labor force." To calculate an approximate 90percent confidence interval, multiply the standard error of 245,000 by the factor to obtain 403,000. This number is subtracted from and then added to 60,000,000 to obtain an approximate 90percent confidence interval: 59,597,000 to 60,403,000. 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 1D. This table gives a and b 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 1D 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. Standard errors of estimated levels using table 1D. 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 i D associated with a particular characteristic. se (x) = y/ax 2 + bx 174

182 Illustration. Assume that, in a given a month, there are an estimated 3 million unemployed men. Obtain the appropriate a and b parameters from table 1D (Total or white; Men; ). Use the formula for se(x) to compute an approximate standard error on the estimate of x = 3,000,000. a b = ^(3,000,000) = V0.0OOO348(3,OOO,0OO) (3,000,000) «92,000 Procedure for using table 1D factors for levels. Table 1D 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 monthtomonth changes Changes in monthly estimates 1 year apart Quarterly averages Changes in consecutive quarterly averages Yearly averages Changes in consecutive yearly averages For a given characteristic, the table 1D factor is used in the following formula, which also uses the a and b parameters from the same line of the table. A threestep 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, f) = f * se(x) = / * yl(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 1D. (Note that, for some characteristics, an approximate standard error of level could instead be obtained from table 1B 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 1D. 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 3,000,000 to 3,150,000. Step 1. The average of the two monthly levels is x = 3,075,000. Step 2. Apply the a and b parameters from table 1D (Total or white; Men; ) to the average x, treating it like an estimate for a single month. a b ^(3,075,000) = V (3,075,000) (3,075,000) «93,000 Step 3. Obtain/= 1.27 from the same row of table 1D in the column "Consecutive monthtomonth change," and multiply the factor by the result from step 2. se{\ 50,000) = / * ^(3,075,000) = 1.27 * 93, ,000 For an approximate 90percent confidence interval, compute * 118,000 «194,000. Subtract the number from and add the number to 150,000 to obtain an interval of 44,000 to 344,000. This is an approximate 90percent 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 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 1D (Black; Total;, employed, and not in labor force) to the average x, treating it like an estimate for a single month. 175

183 a b ^(15,000,000) > /OOOO154ia5,OOO,OOQ (15,200,000) «122,000 Step 3. Obtain/=.86 from the same row of table 1D in the column "Quarterly averages," and multiply the factor by the result from step 2. ^(15,000,000) =.86*122,000 «105,000 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 1D (Black; Total;, employed, and not in labor force) to the average x, treating it like an estimate for a single month. a b = ^(15,200,000) = V (15,200,000) (15,200,000) «120,000 Step 3. Obtain/=.78 from the same row of table 1D in the column "Change in consecutive quarterly averages," and multiply the factor by the result from step 2. the base y and the numerator of/? are from different categories within the table, use the b parameter from table 1D relevant to the numerator of the rate or percentage. se(p,y)=lp(\00p) Note that se(p,y) is in percent. Illustration. For a given month, suppose y = 6,200,000 women 20 to 24 years of age are estimated to be employed. Of this total, 2,000,000, or p = 32 percent, are classified as parttime workers. Obtain the parameter b = 3006 from the table 1D row (Employment; Parttime workers) that is relevant to the numerator of the percentage. Apply the formula to obtain:, /3005.I 3006 (32)(10032)»1.0 percent se(p,y) = J 200,000 y V6,200,( For an approximate 95percent confidence interval, compute 6 * 1.0 percent, and round the result to 2 percent. Subtract this from and add this to the estimate of p = 32 percent to obtain an interval of 30 percent to 34 percent. Procedure for using table 1D factors for rates and percentages. Table 1D factors can be used to compute approximate standard errors on rates and percentages for other periods or for changes over time. As for levels, there are three steps in the procedure for using the formula. 5^(400,000) =.78 * se{\ 5,200,000) =.78*120,000 «94,000 For an approximate 95percent confidence interval, compute 6 * 94,000 «184,000. Subtract the number from and add the number to 400,000 to obtain an interval of 216,000 to 584,000. The interval excludes zero. Another way of stating this is to observe that the estimated change of 400,000 clearly exceeds 6 standard errors, or 184,000. One can conclude from these data that the change in quarterly averages is significant at a 95percent confidence level. Standard errors of estimated rates and percentages using table I'D. As shown in the formula below, the approximate standard error se(p,y) of an estimated rate or percentage p depends, in part, upon the number of persons y in its base or denominator. Generally, rates and percentages are not published unless the monthly base is greater than 75,000 persons, the quarterly average base is greater than 60,000 persons, or the yearly average base is greater than 35,000 persons. The b parameter is obtained from table 1D. When where p and y are averages of monthly estimates over a designated period. Note that se (p,y,f) is in percent. Step 1. Appropriately average estimates of monthly rates or percentages to obtain /?, and also average estimates of monthly levels to obtain y. Rates 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 (p, y), treating the averages p and y from step 1 as if they were estimates for a single month. Obtain the b parameter from the table 1D 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 1C and used in place of se (/?, y) in the formula.) 176

184 Step 3. Determine the standard error se (p, 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 1D. Illustration of a standard error computation for consecutive month change in percentage. Continuing the previous example, suppose 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 parttime workers. Step 1. The monthtomonth change is 2 percent = 34 percent 32 percent. The average of the two monthly percentages of 32 percent and 34 percent is needed (p = 33 percent), as is the average of the two bases of 6,200,000 and 6,300,000 (y = 6,250,000). Step 2. Apply the b = 3006 parameter from table 1D (Employment; Parttime workers) to the averaged p and y, treating the averages like estimates for a single month (33)(10033)»1.0 percent 6,250,000 Step 3. Obtain/^.65 from the same row of table 1D in the column "Consecutive monthtomonth change," and multiply the factor by the result from step 2. se(2%) =.65 * 1.0 percent =.65 percent For an approximate 95percent confidence interval, compute 6 *.65 percent, and round the result to 1.3 percent. Subtract this from and add this to the 2percent estimate of change to obtain an interval of 0.7 percent to percent. Because this interval excludes zero, it can, be concluded at a 95percent confidence level that the change is significant. 177

185 Table 1 D. Parameters and factors for computation of approximate standard errors for estimates of monthly levels Parameters Factors Characheristic Consecutive monthtomonth change Yeartoyear change of monthly estimates Quarterly averages Change in consecutive quarterly averages Yearly averages Change in consecutive yearly Total or white Total:, employed, and not in labor force Men:, employed, and not in labor force Women:, employed, and not in labor force Both sexes, 16 to 19 years:, employed, and not in labor force Black Total:, employed, and not in labor force Men:, employed, and not in labor force Women:, employed, and not in labor force Both sexes, 16 to 19 years:, employed, and not in labor force Hispanic origin Total:, employed, and not in labor force Men:, employed, and not in labor force Women:, employed, and not in labor force Both sexes, 16 to 19 years:, employed, and not in labor force

186 Table 1 D. Parameters and factors for computation of approximate standard errors for estimates of monthly levels Continued Parameters Factors Characheristic Consecutive monthtomonth change Yeartoyear change of monthly estimates Quarterly averages Change in consecutive quarterly averages Yearly averages Change in consecutive yearly averages Employment Educational attainment Marital status, men Marital status, women Women who maintain families.. Mining and manufacturing Other industries and occupations Agriculture: Total Wage and salary workers Selfemployed workers Unpaid family workers Nonagricultural industries: Total Wage and salary workers Selfemployed workers Unpaid family workers Fulltime workers Parttime workers Multiple jobholders At work Total and nonagricultural industries: Total 1 to 4 and 5 to 14 hours 15 to 29 hours 30 to 34 or 35 to 39 hours 1 to 34 or 40 hours 41 to 48 or 49 to 59 hours 35+, 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 Fulltime workers Parttime workers Less than 5 weeks 5 to 14 weeks 15 to 26 weeks 15+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

187 Establishment Data ("B" tables) DATA COLLECTION BLS cooperates with State Employment Security 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). This sample includes about 300,000 reporting units. 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. Data are collected by touchtone data entry (TDE) from most respondents. Under the TDE system, the respondent uses a touchtone telephone to call a tollfree 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. A majority of sample units use TDE. For establishments that do not use TDE, data are collected mostly by mail, FAX, or Electronic Data Interchange (EDI), through sites established on the World Wide Web, or on magnetic tape or computer diskette. Computerassisted telephone interviewing (CATI) is used for a small number of respondents (5 percent). Chart 1 shows the percentages of the stablishments using different data collection methods. All reports are edited by the State agencies each month to make sure that the data are correctly reported and that they are consistent with the data reported by the establishment in earlier months. The State agencies forward the data to BLS Washington. They also use the data to develop State and area Chart 1: Distribution of CES sample by collection mode Tape/diskette 7% FAX /EDI/WEB 11% estimates of employment, hours, and earnings. At BLS, the data are edited again by computer to detect processing and reporting errors that may have been missed in the initial State editing; the edited data are used to prepare national estimates. It should be noted that, in the case of employment, the sum of the State figures will differ from the official U.S. national totals because of the effects of differing industrial and geographic stratification and differences in the timing of benchmark adjustments. CONCEPTS Industrial classification Establishments reporting on Form BLS 790 are classified into industries on the basis of their principal product or activity, as determined from information on annual sales volume. Since January 1980, this information has been collected on a supplement to the quarterly unemployment insurance tax reports filed by employers. For an establishment making more than one product or engaging in more than one activity, the entire employment of the establishment is included under the industry indicated by the principal product or activity. All data on employment, hours, and earnings for the Nation (beginning with 1990 data) and for States and areas (beginning with January 1990 data) are classified in accordance with the 1987 Standard Industrial Classification Manual (SIC), U.S. Office of Management and Budget. Industry employment Employment data, except those for the Federal Government, refer to persons on establishment payrolls who received pay for any part of the pay period that includes the 12th day of the month. For Federal Government establishments, employment figures represent the number of persons who occupied positions on the last day of the calendar month. Intermittent workers are counted if they performed any service during the month. The data exclude proprietors, the selfemployed, unpaid volunteer or family workers, farmworkers, and domestic workers. Salaried officers of corporations are included. Government employment covers only civilian employees; military personnel are excluded. Employees of the Central 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 the entire period, or who were hired but have not yet reported during the period. 180

188 Indexes of diffusion of employment change. These indexes measure the dispersion among industries of the change in employment over the specified timespan. The overall indexes are calculated from 356 seasonally adjusted employment series (3digit industries) covering all nonfarm payroll employment in the private sector. The manufacturing diffusion indexes are based on 139 3digit 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( 10065) = 30). However, for dispersion analysis, the distance of the index number from the 50percent reference point is the most significant observation. Although diffusion indexes commonly are interpreted as showing the percent of components that increased over the timespan, it should be remembered that 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.) Industry hours and earnings Average hours and earnings data are derived from reports of payrolls and hours for production and related workers in manufacturing and mining, construction workers in construction, and nonsupervisory employees in private serviceproducing industries. Production and related workers. This category includes 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 workingsupervisor 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 parttime 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 oldage 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 straighttime 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, parttime 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. 181

189 Indexes of aggregate weekly hours. The indexes of aggregate weekly hours are prepared 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. 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 his or her holiday pay plus straighttime 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 lateshift work and changes in output of workers paid on an incentive plan. They also reflect shifts in the number of employees between relatively highpaid and lowpaid 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: Irregular bonuses, retroactive items, payments of various welfare benefits, payroll taxes paid by employers, and earnings for those employees not covered under production worker, construction worker, or nonsupervisory employee definitions. Average hourly earnings, including lumpsum wage payments. These series are compiled only for aircraft (SIC 3721) and guided missiles and space vehicles (SIC 3761) manufacturing. The same concepts and estimation methods apply to these series as apply to the average hourly earnings series described above; the one difference between the series is definitional. The payroll data used to calculate these series include lumpsum payments made to production workers in lieu of general wage rate increases; such payments are excluded from the definition of gross payrolls used to calculate the other average hourly earnings series. For each sample establishment in SIC 3721 and SIC 3761 covered by a lumpsum agreement, the reported payroll data are adjusted to include a prorated portion of the lumpsum payment. Such payments generally are made once a year and cover the following 12month period. In order to spread the payment across this period, a prorated portion of the payment is added to the payroll each month. This prorated portion is adjusted by an exit rate to reduce the lumpsum amount to account for persons who received the payment but left before the payment allocation period expired. Average hourly earnings, excluding overtime. Average hourly earnings, excluding overtimepremium pay, are com ; puted by dividing the total production worker payroll for the industry group by the sum of total production worker hours and onehalf of total overtime hours. No adjustments are made for other premium payment provisions, such as holiday pay, lateshift premiums, and overtime rates other than time and onehalf. Railroad hours and earnings. The figures for Class I railroads plus Amtrak (excluding switching and terminal companies) are based on monthly data summarized in the M300 report of the Interstate Commerce Commission, and relate to all employees except executives, officials, and staff assistants (ICC group I) who received pay during the month. Average hourly earnings are computed by dividing total compensation by total hours paid for. Average weekly hours are obtained by dividing the total number of hours paid for, reduced to a weekly basis, by the number of employees. Multiplying average weekly hours by average hourly earnings yields average weekly earnings. 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 parttime 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. Longterm trends of average weekly earnings can be affected by structural changes in the makeup of the workforce. For example, persistent longterm increases in the proportion of parttime 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 Earnings and Clerical Workers (CPIW). The reference year for these series is

190 ESTIMATING METHODS [NOTE: This section and the next apply to all industries except those in the wholesale trade major industry division. (See the section on CES sample redesign for information on wholesale trade.)] 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 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 aggregatelevel employment estimates. Benchmarks For the establishment survey, annual benchmarks are constructed in order to realign the samplebased employment totals for March of each year with the Ulbased population counts for March. These population counts are much less timely than samplebased estimates; however, they provide an annual pointintime census for employment. 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 information to the appropriate State Employment Security Agency four times a year. Approximately 99 percent of private employment within the scope of the establishment survey is covered by UI. A benchmark for the remaining 1 percent is constructed from alternate sources, primarily records from the Interstate Commerce Commission and the Social Security Administration. The full benchmark developed for March replaces the March samplebased estimate for each basic cell. The monthly samplebased estimates for the year preceding and the year following the benchmark are also then subject to revision. Monthly estimates for the year preceding the March benchmark are readjusted using a "wedge back" procedure. The difference between the final benchmark levei and the previously published March sample estimate is calculated and spread back across the previous 11 months. The wedge is linear; eleventwelfths of the March difference is added to the February estimate, tentwelfths to the January estimate, and so on, back to the previous April estimate, which receives onetwelfth 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 11 months following the March benchmark also are recalculated each year. These postbenchmark estimates reflect the application of samplebased monthly changes to new benchmark levels for March, and the recomputation of bias adjustment factors for each month. Bias factors are updated to take into account the most recent experience of the estimates generated by the monthly sample versus the full universe counts derived from the UI. Following the revision of basic employment estimates, all other derivative series (such as 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 reseasonally adjusted before full publication of all revised data in June of each year. Monthly estimation Estimates are derived from a sample of approximately 300,000 business establishments nationwide. A current month's estimate is derived as the product of the previous month's estimate and a sample link relative for the current month. A bias adjustment factor is then applied to this result, primarily to account for new business births during the month. Stratification. The sample is stratified into basic estimating cells for purposes of computing national employment, hours, and earnings estimates. Cells are defined primarily by detailed industry, and secondarily by size, for a majority of cells. In a few industries, mostly within the construction division, geographic stratification also is used. Industry classification is in accordance with the 1987 Standard Industrial Classification Manual (SIC); most estimation cells are defined at the 4digit SIC level. This detailed stratification pattern allows for the production and publication of estimates in considerable industry detail. Subindustry stratification by size is important because major statistics that the survey measures, particularly employment change and average earnings, often vary significantly between establishments of different size. Stratification reduces the variance of the published industrylevel estimates. Link relative technique. A ratio of the previous to the current month's employment is computed from a sample of establishments reporting for both months this ratio is called a "link relative." For each basic cell, a link relative is computed and applied to the previous month's employment estimate to derive the current month's estimate. Thus, a March benchmark is moved forward to the next March benchmark through application of monthly link relatives. Basic cell estimates created through the link relative technique are aggregated to form published industry level estimates for employment, as described in table 2A. Basic estimation and aggregation methods for the hours and earnings data also are shown in table 2A. Bias adjustment. Except for the wholesale trade division, bias adjustment factors are computed at the 3digit SIC level and applied each month at the basic cell level, as part of the standard estimation procedures. The main purpose of bias adjustment is to reduce a primary source of nonsampling er 183

191 Table 2A. Summary of methods for computing industry statistics on employment, hours, and earnings for the nonprobabilitybased and the probabilitybased sample estimates Employment, hours, and earnings Nonprobability sample Basic estimating cell (industry, region, size, or region/size cell) Probability sample Basic estimating cell (industry, 4digit published level) Aggregate industry level (division and, where stratified, industry) Both samples Annual average data All employees Allemployee estimate for previous month multiplied by ratio of all employees in current month to all employees in previous month, for sample establishments that reported for both months. 1 Allemployee estimate for previous month multiplied by weighted ratio of all employees in current month to all employees in previous month, for sample establishments, which reported for both months. 2 Sum of allemployee estimates for component cells. Sum of monthly estimates divided by 12. Production or nonsupervisory workers, women employees Allemployee estimate for current month multiplied by (1) ratio of production or nonsupervisory workers to all employees in sample establishments for current month, (2) estimated ratio of women to all employees. 3 Allemployee estimate for current month multiplied by (1) the ratio of the sum of the weighted production or nonsupervisory workers and the sum of the weighted all employees for the current month and the sum of the weighted production or nonsupervisory workers and the sum of the weighted all employees for the previous month that is applied to the previous month's production or nonsupervisory worker ratio, (2) the ratio of the sum of the weighted women workers and the sum of the weighted all employees for the current month and the sum of the weighted women workers and the sum of the weighted all employees for the previous month that is applied to the previous month's women worker ratio. 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. 3 Production or nonsupervisory worker hours divided by number of production or nonsupervisory workers. 4 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 employment. Average weekly overtime hours Production worker overtime hours divided by number of production workers. 3 Production worker overtime hours divided by number of production workers. 4 Average, weighted by production worker employment, of the average weekly overtime hours for component cells. Annual total of aggregate overtime hours (production or nonsupervisory worker employment multiplied by average weekly overtime hours) divided by annual sum of employment. Average hourly earnings Total production or nonsupervisory Total production or nonsupervisory worker payroll di vided by total production or nonsupervisory worker hours. 3 worker payroll divided vided by total production or nonsupervisory worker hours. 4 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. See footnotes at end of table. 184

192 Table 2A. Summary of methods for computing industry statistics on employment, hours, and earnings for the nonprobabilitybased and the probabilitybased sample estimates Continued Employment, hours, and earnings Nonprobability sample Basic estimating cell (industry, region, size, or region/size cell) Probability sample Basic estimating cell (industry, 4digit published level) Aggregate industry level (division and, where stratified, industry) Both samples Annual average data 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 and average hourly earnings. Product of average weekly hours and average hourly earnings. 1 The estimates are computed by multiplying the above product by bias adjustment factors that compensate for the underrepresentation of newly formed enterprises and other sources of bias in the sample. 2 The estimates are computed by applying a unique monthly birth/ death model component that estimates the residual net birth/death employment not accounted for by the sample. 3 The sample productionworker ratio, womenworker ratio, average weekly hours, average overtime hours, and average hourly earnings are modified by a wedging technique designed to compensate for changes in the sample arising mainly from the voluntary characteristics of the reporting. The wedging procedure accepts the advantage of continuity from the use of the match sample and, at the same ror in the survey the inability to capture, on a timely basis, employment generated by new firm births. There is a lag of several months between an establishment's opening for business and its appearing on the UI universe frame and being available for sampling. Nonsampling methods must be used to capture the portion of employment growth accounted for by new firms; otherwise, substantial underestimation of total employment levels would occur. Formal bias adjustment procedures have been used in the establishment survey since the late 1960s. Prior to the 1983 benchmark, bias adjustments were derived from a simple mean error model, which averaged undercount errors for the previous 3 years to arrive at bias projections for the coming year. The undercount errors were measured as the difference between samplebased estimate results and benchmark levels. This procedure eventually proved inadequate during periods of rapidly changing employment trends, and the bias adjustment methodology was revised. Research done in the early 1980s indicated that bias requirements were strongly correlated with current employment growth or decline. Based on this research, a revised method was developed that uses the sample data on employment growth over the most recent two quarters, and a regressionderived coefficient for the significance of that change, to adjust the mean error model results. This change in methodology provided a more cyclically sensitive bias model. The regressionadjusted mean error model has been used for the production of national estimates since The current model still has limitations on its ability to react tc changing economic conditions or changing error structure relationships between the samplebased estimates and the UI universe counts. A principal limitation is the inability to incorporate UI universe counts as they become available on an ongoing basis, with a 6 to 9month lag from the reference period. For this reason, the current quarterly outputs from the model are subject to intervention analysis and adtime, tapers or wedges the estimate toward the level of the latest sample average. 4 A weighted link relative estimator is used to move average weekly hours, average overtime hours, and average hourly earnings forward from the point at which the probabilitybased sample estimates are introduced. For average weekly hours, this ratio is weighted hours divided by weighted production/nonsupervisory workers. For average hourly earnings, this ratio is weighted payroll divided by weighted hours. This will effectively preserve the true monthtomonth sample movement if the new probability sample has different levels than the current sample. justments can be made to model results prior to the establishment of final bias levels for a quarter. Review for purposes of intervention analysis is done primarily in terms of detection of outlier (abnormally high or low) values, and by comparison of CES sample and bias trends with the most recent quarterly observations of UI universe counts. Although the primary function of bias adjustment is to account for employment resulting from new business formations, it also adjusts for other elements of nonsampling error in the survey, because the primary input to the modeling procedure is total estimation error. Significant among these nonsampling error sources is a business death bias. When a sampled firm closes down, most often it simply does not respond to the survey that month, rather than reporting zero employment. Followup with nonrespondents may reveal an outofbusiness firm, but this information often is received too late to incorporate into monthly estimates, and the firm is simply treated as a nonrespondent for that month. Because the bias adjustments incorporated into the estimates represent a composite of a birth bias, a death bias, and a number of other differences between the samplebased estimates and the population counts, the monthly bias adjustment levels have no specific economic meaning in and of themselves. Table 2B summarizes bias adjustments for the past decade. The table displays the average monthly "bias added" and the average monthly "bias required" with the benchmark revisions for each year. Bias added shows the average amount of bias that was added each month over the course of an interbenchmark period. For example, the bias added for is listed as 150,000; this represents the average of bias adjustments made each month over the period April 1998 through March. Bias required is computed retrospectively, after the March benchmark for a given year is known. Bias required figures are calculated by taking the difference between a March estimate derived purely from the sample 185

193 (that is, a series calculated without bias adjustment) and the March benchmark. Dividing this figure by 12 gives the average monthly bias required figure. The bias required is thus defined as the amount of bias adjustment that would have achieved a zero benchmark error. The difference between the total bias required and the total bias added is then, by definition, approximately the benchmark revision amount, for any given year. Also provided in table 2B are the MarchtoMarch changes. As discussed above, the overtheyear changes indicate correlation with the bias added and bias required figures. THE SAMPLE Design The emphasis in the establishment survey is on producing timely data at minimum cost. Therefore, the primary goal of its design is to sample a large enough segment of the universe to provide reliable estimates that can be published both promptly and regularly. The present sample allows BLS to produce preliminary total nonfarm employment estimates for each months including some limited industry detail, within 3 weeks after the reference period, and data in considerably more detail with an additional 1month lag. The CES survey, which was begun over 50 years ago, predates the introduction of probability sampling methods and has operated as a quota sample since its inception. Quota sampling is different from probability sampling in that it requires a fixed number of units, but they need not have been drawn in a random selection process. The sampling plan used in the establishment survey is a form of sampling with probability proportionate to size, known as "sampling proportionate to average size of establishment." This design results in an optimum allocation of the sample among strata because sampling variance is proportional to the average size of establishments. The universe of establishment employment is highly skewed, with a large percentage of total employment concentrated in relatively few establishments. Because variance on a population total estimate is a function of percentage universe coverage achieved by the sample, it is efficient to sample larger establishments at a higher rate than smaller establishments, assuming the cost per sample unit is fairly constant across size classes. Under the establishment survey design, large establishments fall into certainty strata for sample selection. The size of the sample for the various industries is determined empirically based on experience and cost considerations. For iexaraple,, in a manufacturing industry with a high proportion of total; employment concentrated in a small number of establishments, a larger percent of total employment is included in the sample. Consequently, the sample design for such industries provides for a complete census of the large establishments, with a relatively few chosen from among the smaller establishments. For an industry in which a large proportion of total employment is accounted for by small establishments, the sample design again calls for inclusion of all large establishments but also for a more substantial number of smaller ones. Many industries in the trade and services divisions fall into this category. To keep the sample to a size that can be handled with available resources, these industries are sampled with a smaller proportion of total universe coverage than is the case for most manufacturing industries. Table 2B. March employment benchmarks and bias adjustments for total private industries (In thousands) Year Employment 1 Benchmark Revision 2, March Average monthly bias Added 3 Required 4 Overtheyear employment change , , ,546 88,790 88,347 89,790 92,730 96,175 98, , , , ,531 1, ,443 2,940 3,445 1,983 2,882 2,925 2,662 1 Universe counts for March of each year are used to make annual benchmark adjustments to the employment estimates. About 97 percent of the benchmark employment is from unemployment insurance administrative records, and the remaining 3 percent is from alternate sources. Data represent benchmark levels as originally computed. 2 Difference between the final March samplebased estimate and the benchmark level for total private employment. 3 The average amount of bias adjustment each month over the course of an interbenchmark period, that is, from April of the prior year through March of the given year. 4 The difference between the March benchmark and the March estimate derived solely from the sample without bias adjustment, converted to a monthly amount by dividing by MarchtoMarch changes in the benchmark employment level. NOTE: Data in this table exclude government employment because there is no bias adjustment for this sector. 186

194 Coverage Table 2C shows the latest benchmark employment levels and the approximate proportion of total universe employment coverage at the total nonfarm and major industry division levels. The coverage for individual industries within the divisions may vary from the proportions shown. Reliability The establishment survey, like other sample surveys, is subject to two types of error sampling and nonsampling. 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 more than onethird of total universe employment; this yields a very small variance on the total nonfarm estimates. Measurements of error associated with sample estimates are provided in tables 2D through 2G. 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, for which only Table 2C. Employment benchmarks and approximate coverage of BLS employment and payrolls sample, March Industry Total Mining Construction Manufacturing Transportation and public utilities... Wholesale trade. Retail trade Finance, insurance, and real estate.. Services Government: Federal State Local Benchmarks (thousands) 127, ,918 18,533 6,720 6,846 22,262 7,486 38,323 2,697 4,804 12,997 Number of establishments 2 292,718 2,594 24,697 48, ,453 22,821 54,469 19,901 69, ,594 8,176 20,129 Sample coverage 1 Number (thousands) 41, ,025 7,561 2,009 1,052 4,701 1,835 7,881 Employees 2,697 3,907 8,742 Percent of benchmarks Counts reflect reports used in final estimates. Because not all establishments report payroll and hours information, hours and earnings estimates are based on a smaller sample than employment estimates. 2 In the CES redesign probabilitybased sample for wholesale trade, this figure is a count of the number of Ul accounts sampled. 3 The Interstate Commerce Commission provides a complete count of employment for Class I railroads plus Amtrak. Hours and earnings estimates are derived from a sample. 4 Total Federal employment counts by agency for use in national estimates are provided to BLS by the U.S. Office of Personnel Management. Detailed industry estimates for the Executive Branch, as well as State and area estimates of Federal employment, are based on a sample of reports covering about 60 percent of employment in Federal establishments. sampling error can be estimated, the CES yields 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 universe 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 0.3 percent, with absolute revisions ranging from less than 0.05 percent to 0.7 percent. Table 2D shows the most current benchmark revisions, along with 10year mean revisions and mean absolute revisions for major industries. Mean revisions give an indication of bias in the estimates; unbiased estimates have a mean revision close to zero, as over and underestimations cancel out over time. Mean absolute revisions give an overall indication of the accuracy of the estimates; the larger the value, the further the estimate was from the final benchmark level. Estimated standard errorsfor employment, hours, and earnings. The hours and earnings estimates for the basic estimating cells cannot be compared with universe data sources, and therefore are not subject to benchmark revisions, although the broader groupings may be affected slightly by changes in employment weights. Like the employment estimates, the hours and earnings estimates also are subject to sampling and nonsampling errors. Estimates of the sampling error for employment, hours, and earnings are computed using the method of random groups, and are expressed as relative standard errors (standard error divided by the estimate). Relative standard errors for individual industries having specified numbers of employees are presented in table 2E; those for major industries appear in table 2F. Multiplying the relative standard error by its estimated value gives the estimate of the standard error. The errors presented here are based on averages observed from sample data over the March 1994 through March 1995 period. Standard errors for differences between industries and times. The standard error of a difference is required to test for significant differences between estimates from two different industries. Because the estimates for the two industries are independent, the standard error of a difference is the square root of the sum of the estimated variance of each estimate, S, 2 and S 2 2: S difference = The CES sample overlaps almost entirely from month to month, so monthly estimates are not independent. The covariance between these estimates must be accounted for when testing the significance of the change in estimates over time. 187

195 The standard error of the change can be estimated as follows: S change If Si = S2, then: S change = f + s* 2ps { s 2 Conservative estimates of p after 1 month are 0.8 for employment, 0.6 for average weekly hours, and 0.8 for average hourly earnings. If the bias is small, the standard error can be used to construct an approximate confidence interval, or range of values, that includes the true population value. If the process of selecting a sample from the population were repeated many times, and an estimate and its standard error were calculated for each sample, then approximately 68 percent of the intervalsfrom 1 standard error below the estimate to 1 standard error above the estimatewould include the true population value. 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 samplebased estimates are published 2 months later, when nearly all the reports in the sample have been received. Table 2G presents the rootmeansquare 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 of an 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. CES sample redesign In June 1995, BLS announced plans for a comprehensive sample redesign of its monthly payroll survey. The initial research phase for the CES sample redesign was completed in 1997, and BLS launched a production test of the new sample design at that time. The production test phase concluded in June, when the first estimates from the new design, for the wholesale trade industry, were published with the benchmark revisions. Redesigned samples for the remaining industry divisions will be phased in with subsequent years' benchmark releases, between 2001 and Original sample design limitations. The original CES survey is based on a quota sample, the inception of which, over 50 years ago, predated the introduction of probability sampling as the internationally recognized standard for sample surveys. Quota samples are known to be at risk for potentially significant biases. Introducing a probabilitybased sample for CES ensures a proper representation of the universe of nonfarm business establishments through randomized selection techniques and the regular rotation of sample members. In addition, the CES sample redesign addresses a second critical limitation of the current CES sample, which is lack of timely samplebased representation of employment from new business births. Procedures have been developed for regular sample updates that will ensure better representation of new units in the CES sample. Time series modeling techniques are being used to estimate the residual portion of birth employment not accounted for through the improved sampling techniques. Introduction of a probabilitybased sample for the CES survey allows for the publication of sampling errors and confidence intervals, standard survey accuracy measures not directly applicable to the current nonprobability design. Overall accuracy of the survey employment estimates, however, is still best measured by the magnitude of annual benchmark revisions, as they encompass the total estimation error associated with the CES employment series. The new CES sample design. The new design 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 sates for each stratum are determined through a method known as optimum allocation, 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 new 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. For the CES redesign, the number of sample units drawn was fixed to the approximate size of the original CES sample, which is the sample size supported by current program resources. This sample size makes possible the publication of considerable industry and geographic detail within a State, and provides for highly reliable national CES estimates at the total nonfarm and detailed industry levels. Frame and sample selection. The Longitudinal Data Base (LDB) is the universe from which BLS draws the CES sample. The LDB contains data on approximately 7.5 million U.S. business establishments, representing nearly all nonfarm elements of the U.S. economy. The ES202 program collects these data from employers, on a quarterly basis, in cooperation with State Employment Security Agencies (SESAs). The LDB contains employment and wage information from employers, as well as name, address, and location information. It also contains identification information such as Unemploy 188

196 Table 2D. Current (March ) and historical benchmark revisions (Numbers in thousands) Total Total private Industry March) benchmark revision Level Percent Tenyear average mean percent revision Actual 0 Absolute Goodsproducing Mining Metal mining Coal mining Oil and gas extraction Nonmetallic minerals, except fuels Construction General building contractors ' Heavy construction, except building Special trade contractors Manufacturing Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Blast furnaces and basic steel products Fabricated metal products Industrial machinery and equipment Computer and office equipment Electronic and other electrical equipment Electronic components and accessories Transportation equipment Motor vehicles and equipment Aircraft and parts Instruments and related products Miscellaneous manufacturing Nondurable goods Food and kindred products Tobacco products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and miscellaneous plastics products Leather and leather products Serviceproducing 41.3 Transportation and public utilities Transportation Railroad transportation Local and inter urban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services Communications and public utilities Communications Electric, gas, and sanitary services Wholesale trade Durable goods Nondurable goods See footnotes at end of table. 189

197 Table 2D. Current (March ) and historical benchmark revisions Continued (Numbers in thousands) Industry March benchmark revision Level Percent Tenyear average mean percent revision Actual Absolute Retail trade Building materials and garden supplies General merchandise stores Department stores Food stores Automotive dealers and service stations New and used car dealers Apparel and accessory stores Furniture and home furnishings stores Eating and drinking places Miscellaneous retail establishments Finance, insurance, and real estate Finance Depository institutions Commercial banks Savings institutions Nondepository institutions Mortgage bankers and brokers Security and commodity brokers Holding and other investment offices Insurance Insurance carriers Insurance agents, brokers, and service Real estate Services 2 Agricultural services Hotels and other lodging places Personal services Business services Services to buildings Personnel supply services Help supply services Computer and data processing services Auto repair, services, and parking Miscellaneous repair services Motion pictures Amusement and recreation services Health services Offices and clinics of medical doctors Nursing and personal care facilities Hospitals Home health care services Legal services Educational services Social services Child day care services Residential care Museums and botanical and zoological gardens. Membership organizations Engineering and management services Engineering and architectural services Management and public relations Services, nee Government Federal Federal, except Postal Service State Education Other State government Local Education Other local government O Less than 0.05 percent. 2 Includes other industries, not shown separately. 190 NOTE: Nee is an abbreviation for "not elsewhere classified" and designates broad categories of industries that cannot be more specifically identified.

198 Table 2E. Relative standard errors 1 for estimates of employment, hours, and earnings (In percent) 50, , , ,000 1,000,000 2,000,000 Number of employees Employment Relative standard error Average weekly hours Average hourly earnings Relative errors were estimated using sample data from March 1994March Table 2F. Relative standard errors 1 for estimates of employment, hours, and earnings by industry (In percent) Industry Total private Mining Construction Manufacturing Durable goods Nondurable goods Transportation and public utilities Wholesale trade Retail trade Finance, insurance, and real estate Services Employment Relative standard error Average weekly hours Average hourly earnings Relative errors were estimated using sample data from March 1994March ment Insurance (UI) Account Number, Reporting Unit Number, and LDB Number. The LDB consists of all employers covered under the Unemployment Insurance Tax System. That 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 selfemployed, small family businesses, railroads, charitable 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..7.4 The probability 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 11 industries and 8 size classes, there are 88 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 is fixed to the approximate size of the existing nonprobability CES survey. The optimum allocation formula will place more sample in cells for which data cost less to collect, cells that have more units, and cells that have a larger variance. When compared with the quota sample, there are fewer units selected in manufacturing and more units selected in services. 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 outofscope records are removed, the sampling frame is sorted into allocation cells. Within each allocation cell, units are sorted by MSA and by the size of the MSA, which is 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 art 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. 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 n h = the number of noncertanity UI accounts selected within the allocation cell 191

199 Table 2G. Errors of preliminary employment estimates Industry Rootmeansquare error of monthly level 1 Actual Mean percent revision Absolute Total Total private 47,200 40,800 Goodsproducing 12,800 Mining Metal mining Coal mining Oil and gas extraction Nonmetallic minerals, except fuels 1, , Construction General building contractors Heavy construction, except building Special trade contractors \ Manufacturing Durable goods Lumber and wood products Furniture and fixtures Stone, clay, and glass products Primary metal industries Blast furnaces and basic steel products Fabricated metal products Industrial machinery and equipment Computer and office equipment Electronic and other electrical equipment Electronic components and accessories Transportation equipment Motor vehicles and equipment Aircraft and parts Instruments and related products Miscellaneous manufacturing 7,500 3,900 2,900 5,000 9,600 6,600 1,500 1,100 1,200 1,600 1,200 2,100 2,900 2,100 2,300 1,600 4,700 3,900 1,600 1, Nondurable goods Food and kindred products Tobacco products Textile mill products Apparel and other textile products Paper and allied products Printing and publishing Chemicals and allied products Petroleum and coal products Rubber and miscellaneous plastics products Leather and leather products 4,800 2, ,200 2,600 1,100 1,700 1, , Serviceproducing 43,700 Transportation and public utilities Transportation Railroad transportation Local and interurban passenger transit Trucking and warehousing Water transportation Transportation by air Pipelines, except natural gas Transportation services Communications and public utilities Communications Electric, gas, and sanitary services 9,300 8,900 1,800 3,500 5,600 1,400 6, ,100 4,100 3,600 1, Wholesale trade Durable goods Nondurable goods 7,500 4,400 4,700 See footnotes at end of table. 192

200 Table 2G. Errors of preliminary employment estimates Continued Industry Rootmeansquare error of monthly level 1 Actual Mean percent revision Absolute Retail trade Building materials and garden supplies... General merchandise stores Department stores Food stores Automotive dealers and service stations.. New and used car dealers Apparel and accessory stores Furniture and home furnishings stores Eating and drinking places Miscellaneous retail establishments Finance, insurance, and real estate Finance Depository institutions Commercial banks Savings institutions Nondepository institutions Mortgage bankers and brokers Security and commodity brokers Holding and other investment offices Insurance Insurance carriers Insurance agents, brokers, and service. Real estate Services 2 Agricultural services Hotels and other lodging places Personal services Business services Services to buildings Personnel supply services Help supply services Computer and data processing services Auto repair, services, and parking Miscellaneous repair services Motion pictures Amusement and recreation services Health services Offices and clinics of medical doctors Nursing and personal care facilities Hospitals Home health care services Legal services Educational services Social services Child day care services Residential care Museums and botanical and zoological gardens. Membership organizations Engineering and management services Engineering and architectural services Management and public relations Services, nee Government Federal Federal, except Postal Service. State Education Other State government Local Education Other local government 25,200 2,900 17,500 17,200 6,400 3,000 1,100 6,400 2,400 8,800 8,000 5,700 3,900 3,100 2, ,600 1,200 1,000 1,700 2,500 2,100 1,300 2,600 28,700 3,000 5,600 4,900 12,700 2,400 11,100 10,900 2,800 1,900 1,100 6,800 9,200 5,500 2,500 1,600 3,500 2,000 1,300 12,100 9,200 4,000 1, ,400 5,200 2,000 3, ,000 8,700 7,700 10,200 8,600 4,900 12,600 11,700 7, , The rootmeansquare 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. 2 Includes other industries, not shown separately. NOTE: Nee is an abbreviation for "not elsewhere classified" and designates broad categories of industries that cannot be more specifically identified. Errors are based on differences from January 1995 through December. 193

201 To further reduce enrollment workload caused by the annual update of the sample, BLS has established a "swapping" procedure in which sample members selected in the previous year are used in lieu of new sample members. As a result of the swap procedure, the amount of sample overlap from year to year is increased. A sample is selected from the firstquarter frame using the random sampling procedures. If a new sample member is selected during random sampling, a check is made for a previously selected unit that was not selected in the new sample. The previously selected unit must be within the same State, industry, and size class and must have the same PRN date as the originally selected unit. Newly selected units are replaced until all suitable replacements are exhausted. The units are generally available for swapping due to changes in the MSA, SIC, and size of units. As a result of the swap procedure, approximately 90 percent of the Current Employment Statistics Sample Redesign (CESR) sample overlaps from one year to the next. Before the swap procedure was implemented, approximately 35,000 new UI accounts were selected each year during the annual update. With the swap procedure, this number is reduced by as much as 40 percent, or 15,000 units. Due to the dynamic economy, there is a constant cycle of business 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. Sample enrollment activities. The primary enrollment of new establishments for the CESR is taking place in BLS Data Collection Centers (DCCs) located in Atlanta, Kansas City, and Dallas, and in the Electronic Data Interchange (EDI) Center in Chicago. Once the sample has been sent to the DCCs, interviewers enroll the selected establishments. While the UI account represents the sample unit, interviewers are responsible for tracking and collecting the data for the individual establishments, regardless of the current UI configuration associated with the establishments. In the case of large, multipleworksite UI accounts, it is sometimes necessary to subsample employers. This occurs when: 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. Estimation. Under the new methodology, CES will use a matched sample concept and weighted link relative estimator to produce employment, hours, and earnings estimates. Consistent with the historical CES definition, a matched sample is defined to be all sample members that have reported data for the reference month and the month prior. A slight adjustment to the above matched definition is made to exclude from the matched sample any sample unit that reports that it is outofbusiness. The reasoning behind this handling is described later in the section on estimation of business births and deaths. The estimator for employment and that for hours and earnings uses the sample trend in the cell to move the previous level or ratio to the currentmonth estimated level or ratio. In the case of all employees, an additive modelbased component is applied as well. This component also is described in the business birth and death estimation section. The basic formula for estimating employment is: AE C = where: { matched sample unit; w i Cl + (net birth/death model), «weight associated with the CES report; currentmonth reported all employees; ae P%1 previousmonth reported all employees; A AE C AE currentmonth estimated all employees; and previousmonth estimated all employees. The basic form for the estimator used to develop the currentmonth production workers series is: PW = AExPWRATIO,, and 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. PWRATIO C = PWRATIOxj. 194

202 where: vv. ' " c PWRATIO c matched sample unit; = weight associated with the CES report; = currentmonth estimated production workers; = currentmonth productionworkertoallemployee ratio; PWRATIO p = previousmonth productionworkertoallemployee ratio; P w cj currentmonth reported production workers; PW p j = previousmonth reported production workers; ae c,i currentmonth reported all employees; ae p j previousmonth reported all employees; and AE currentmonth estimated all employees. Estimation of the series for women workers is identical to thai described for production workers, with the appropriate substitution of women workfer vahies for the production worker values in the previous formulas. The same basic form of the estimator holds for all data types. The basic estimators of average weekly hours and average hourly earnings are: and AWH C=AWH x Z w x wh where: = matched sample unit; AHEC = w i weight associated with the CES report; AWH c AHEpx «currentmonth estimated average weekly hours; AWrt p previousmonth estimated average weekly hours; w "ci w^p.i P w d " currentmonth reported weekly hours; = previousmonth reported weekly hours; = currentmonth reported production workers; P w pj previousmonth reported production workers; AHE C AHE p WH c WH p currentmonth estimated average hourly earnings; = previousmonth estimated average hourly earnings; = currentmonth estimated weekly man hours; = previousmonth estimated average man hours; vv. x prc i t x whp Estimation of overtime hours 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. Benchmarking. Annual benchmark adjustment that revises 2 years of data continues under the redesign, but with slight modification to the process. Under the original CES procedures, when national series are benchmarked, sample links derived from the final (or third) set of monthly estimates are applied to the March benchmark level to reestimate 1 year forward from the new benchmark levels. The year prior to the benchmark is adjusted by a simple wedgeback procedure that distributes the benchmark error in equal increments across the 11 months preceding the March benchmark. For initial implementation of the redesign estimates for each major industry division, all series for both the year prior to and the year following the March benchmark month are revised to incorporate samplebased estimates calculated from the new sample and estimators. Thus, there is more revision in the benchmark period under the redesign than experienced previously for all data types. In particular, basic celllevel hours and earnings estimates, which have no benchmark revision under current procedures, are subject to change. Business birth and death estimation. In a dynamic economy, firms are continually going outofbusiness while, at the same time, new businesses are opening. These two normal 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 units from the matched sample definition. Effectively, business deaths are not included in the samplebased link portion of the estimate, and their employment loss 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 followup with monthly nonrespondents to determine whether a company is outofbusiness 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 modelbased approach. With any modelbased 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: = currentmonth reported weekly payroll; and previousmonth reported weekly payroll. Birth/death residual Population Samplebased estimate + Error 195

203 Simulated monthly probability estimates over a 7year period were 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 monthtomonth differences and used as input series to the modeling process. Models are fit using X12 ARIMA (AutoRegressive 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. Difference between the birth/death model and bias adjustment. Table 2H compares the level of bias adjustment applied in the previously published CES series with the net birth/death adjustment used in the redesign series in wholesale trade. Over the course of the "postbenchmark year" from April to March, the cumulative bias adjustment added 150,000 to the wholesale trade employment level, while the net birth/death model added 30,000 overall. Note that the latter model has greater variability from month to month, including months with a negative adjustment. This mainly reflects the seasonal pattern of the net birth/death series observed in the historical UI universe data series. The net birth/death models will replace the bias adjustment modeling currently used for the CES program as estimates for each major industry division are phased in for official publication. The ARIMA model component is updated and reviewed on a quarterly basis, as are the current bias adjustments. However, the net birth/death model component figures are unique to each month, unlike the bias adjustments, which are identical for all 3 months of a given quarter. An important conceptual and empirical distinction between current bias adjustment and new net birth/death models involves the elements that the models are designed to identify. Although the primary purpose of the existing bias adjustment process is to account for new business birth employment, it also adjusts for other elements of nonsampling error, or bias, in the current CES estimate because the primary input to the model is total estimation error. Sampling bias can be significant in the existing sample because of its quota design, and the bias component is therefore relatively large. In contrast, the net birth/death models estimate only the residual component not measurable by the sample; the models do not attempt to correct for deficiencies in sample design. Therefore, the net birth/death model component in the redesign series is expected to be significantly smaller than the bias adjustment component in the current CES estimates. The most significant potential drawback to a modelbased approach is that time series modeling assumes a predictable continuation of historical patterns and relationships. Therefore, a modelbased approach is likely to have some difficulty producing reliable estimates at economic turning points or during periods in which there are sudden changes in trend. In sum, accurate estimation of the business birth component of total nonfarm employment will continue to be the most difficult issue in CES employment estimation. Variance estimation for the CES redesign estimates. A probabilitybased sample allows for the calculation and publication of sampling variances and confidence intervals standard survey accuracy measures not directly applicable to the current nonprobability design. The estimation of sample variance for the 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 + a where weights for units not in the half sample are multiplied by a factor of 1 «. Estimates from these subgroups are calculated using the estimation formula described previously. The formula used to calculate CES variances is as follows: where: k = number of halfsamples; and Q = original full sample estimates is the halfsample estimator; Appropriate uses of sampling variances in CES. 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 program (calculating allemployee estimates) will still be measured in terms of the benchmark revisions. Variances for items not benchmarked that is, average hourly earnings and average weekly hours can serve as a more meaningful measure of their error now with a representative probability sample. The variances of the overthemonth change estimates are very useful in determining when changes are significant at some level of confidence. Sampling errors for wholesale trade. The sampling errors shown for the wholesale trade industry have been calculated 196

204 Table 2H. Bias adjustment effects for published series versus net birth/death model effects for the wholesale trade industry (In thousands) Year and month : April May June September. October November December : January February March Wholesale trade industry Bias adjustment for published series Monthly amount Net birth/death adjustment for the postbenchmark period [lustration of the use of table 2J. Table 2J provides a reference for the standard errors of 1, 3, and 12month changes in AE, AHE, and AWH. The errors are presented as standard errors of the changes. Suppose that the overthemonth change in AHE from January to February for motor vehicles, parts, and supplies is $01. The standard error for a 1month change for this industry from the table is $0.09. The interval estimate of the overthemonth change in AHE that will include the true overthemonth change with 90percent confidence is calculated: $01 +/(1.645*$0.09) = $01 +/ $05 = $0.04 to $0.26 The true value of the overthemonth change is in the interval $0.04 to $0.26. Because this interval includes $0.00 (no change), the change of $01 shown is not significant at the 90percent confidence level. Alternatively, the estimated change of $01 does not exceed $05 (1.645 * $0.09); therefore, one could conclude from these data that the change is not significant at the 90percent confidence level. Cumulative total STATISTICS FOR STATES AND AREAS (Tables B7, B14, and B18) for estimates that follow the benchmark employment revision by a period of 12 to 24 months. Since the error estimates generally increase as a function of time after the month of benchmark revision, this period was determined to be the period of greatest interest for the estimates. For example, the May estimates follow the benchmark revision (March ) by 14 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 (BHS) with the probability sample data and sample weights assigned at the time of sample selection. Illustration of the use of table 21. Table 21 provides a reference for relative standard errors of three major series developed from the CES estimates of the numbers of all employees (AE), of average hourly earnings (AHE), and of average weekly hours (AWH). 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 wholesale trade in a given month is estimated at 6,944,000. The approximate relative standard error of this estimate (0.57 percent) is provided in table 21. A 90percent confidence interval would then be the interval: 6,944,000 +/ (1.645*.0057*6,944,000) = 6,944,000+/65,110 = 7,009,110 to 6,878,890 As explained earlier, State agencies in cooperation with BLS collect and prepare State and area 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. 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. Additional industry detail may be obtained from the State agencies listed on the inside back cover of each issue. 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 or vice versa. Because each State series is subject to larger sampling and nonsampling errors than is the national series, summing them cumulates individual Statelevel errors and can cause distortions 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 "sumofstates" employment series. Additionally, BLS cautions users that such a series is subject to a relatively large and volatile error structure, particularly at turning points. 197

205 Table 21. Relative standard error for estimates of employment, hours, and earnings in wholesale trade (In percent) Relative standard error Industry All employees Average weekly hours Average hourly earnings Wholesale trade Durable goods Motor vehicles, parts, and supplies Furniture and home furnishings Lumber and other construction materials Professional and commercial equipment Metals and minerals, except petroleum Electrical goods Hardware, plumbing, and heating equipment Machinery, equipment, and supplies Misc. wholesale trade durable goods Nondurable goods».*...*.» Paper and paper products... Drugs, proprietaries, and sundries Apparel, piece goods, and notions Groceries and related products Farmproduct raw materials Chemicals and allied products Petroleum and petroleum products Beer, wine, and distilled beverages Misc. wholesale trade nondurable goods Table 2J. Standard error for change in levels estimates of employment, hours, and earnings in wholesale trade Industry All employees Standard error 1month change Average weekly hours Average hourly earnings All employees Standard error 3month change Average weekly hours Average hourly earnings All employees Standard error 12month change Average weekly hours Average hourly earnings Wholesale trade Durable goods Motor vehicles, parts, and supplies Furniture and home furnishings Lumber and other construction materials. Professional and commercial equipment. Metals and minerals, except petroleum... Electrical goods Hardware, plumbing, and heating equipment Machinery, equipment, and supplies Misc. wholesale trade durable goods Nondurable goods Paper and paper products Drugs, proprietaries, and sundries Apparel, piece goods, and notions Groceries and related products Farmproduct raw materials Chemicals and allied products Petroleum and petroleum products Beer, wine, and distilled beverages Misc. wholesale trade nondurable goods. 8,694 6,024 1,784 1,252 1,362 2, ,165 1,245 2,571 2,071 5,750 1,596 1,778 1,746 3,091 1,260 1, , ,804 9,175 2,864 2,071 2,524 4,990 1,448 3,222 2,091 3,824 3,385 9,747 2,841 2,769 2,897 5,401 1,933 1,623 1,560 1,555 4, r ,198 18,995 5,838 4,674 4,155 9,935 2,862 7,469 5,045 7,063 6,339 16,865 4,556 5,231 5,927 8,969 2,552 2,962 3,270 2,176 6,

206 Region, State, and Area Labor Force Data ("C" tables) FEDERALSTATE 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 employment security agencies under a FederalState cooperative program. The local unemployment estimates which derive from standardized procedures developed by BLS are the basis for determining eligibility of an area for benefits under Federal programs such as the Job Training Partnership Act. Annual average data for the States and 337 areas shown in table C3 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 may be ordered from the Superintendent of Documents, U.S. Government Printing Office, Washington, DC The report "Unemployment in States and Local Areas" is published monthly through GPO and is available in microfiche form only, on a subscription basis. ESTIMATING METHODS Monthly labor force, employment, and unemployment estimates are prepared for the 50 States, the District of Columbia, and over 6,500 areas, including nearly 2,400 LMAs, counties, and cities with a population of 25,000 or more. Regional aggregations are derived by summing the State estimates. The estimation methods are described below for States (and the District of Columbia) and for sub State areas. At the sublma (county and city) level, 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 Current monthly estimates. Effective January 1996, civilian labor force and unemployment estimates for all States and the District of Columbia are produced using models based on a "signalplusnoise" approach. 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 a flexible seasonal 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 unemployment insurance (UI) system. The noise component of the models explicitly accounts for auto correlation 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 characteristics. Two models one for the employmenttopopulation ratio and one for the unemployment rate are used for each State. The employmenttopopulation ratio, rather than the employment level, and the unemployment rate, rather than the unemployment level, are estimated primarily because these ratios are usually more meaningful for economic analysis. The employmenttopopulation ratio models use the relationship between the State's monthly employment from the CES and the CPS. The models also include trend and seasonal components to account for movements in the CPS not captured by the CES series. The seasonal component accounts for the seasonality in the CPS not explained by the CES, while the trend component adjusts for longrun systematic differences between the two series. The unemployment rate models use the relationship between the State's monthly unemployment insurance (UI) claims data and the CPS unemployment rate, along with trend and seasonal components. In both the employmenttopopulation ratio and unemployment rate models, an important feature is the use of a technique that allows the equations to adjust automatically to structural changes that occur. The regression portion of the model includes a builtin tuning mechanism, known as the Kalman Filter, which revises a model's coefficients when the new data that become available each month indicate that changes in the data relationships have taken place. Once the estimates are developed from the models, levels are calculated for employment, unemployment, and labor force. Benchmark correction procedures. Once each year, monthly estimates for all States and the District of Columbia are adjusted, or benchmarked, by BLS to the annual average CPS estimates. The benchmarking technique employs a pro 199

207 cedure (called the Denton method) which adjusts the annual average of the models to equal the CPS annual average, while preserving, as much as possible, the original monthly seasonal pattern of the model estimates. Estimates for substate areas Monthly labor force, employment, and unemployment estimates for two large substate areas New York City and the Los AngelesLong Beach metropolitan area are obtained using the same modeling approach as for states. Estimates for the nearly 2,400 remaining LMAs, are prepared through indirect estimation techniques, described below. Preliminary estimate employment. The total civilian employment estimates are based largely on CES data. These "placeofwork" estimates must be adjusted to refer to place of residence as used in the CPS. Factors for adjusting from place of work to place of residence have been developed on the basis of employment relationships at the time of the 1990 decennial census. These factors are applied to the CES estimates for the current period to obtain adjusted employment estimates, to which are added estimates for employment not represented in the CES agricultural employees, nonagricultural selfemployed and unpaid family workers, and private household workers. Preliminary estimate unemployment. In the current month, the estimate of unemployment is an aggregate of the estimates for each of two categories: (1) Persons who were previously employed in industries covered by State UI laws; and (2) those who were entering the civilian labor force for the first time or reentering after a period of separation. SubState adjustment for additivity. Estimates of employment and unemployment are prepared for the State and all LMAs within the State. The LMA estimates geographically exhaust the entire State. Thus, a proportional adjustment is applied to all substate preliminary LMA estimates to ensure that they add to the independently estimated State totals for employment and unemployment. For California and New York, the proportional adjustment is applied to all LMAs other than the two modeled areas, to ensure that the LMA estimates sum to an independent modelbased estimate for the balance of State. Benchmark correction. At the end of each year, substate estimates are revised. The revisions incorporate any changes in the inputs, such as revisions in the CESbased employment figures, corrections in UI claims counts, and updated historical relationships. The updated estimates are then readjusted to add to the revised (benchmarked) State estimates of employment and unemployment. 200

208 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. In evaluating changes in a seasonally adjusted series, it is important to note that seasonal adjustment is merely an approximation based on past experience. Seasonally adjusted estimates have a broader margin of possible error than the original data on which they are based, because they are subject not only to sampling and other errors but are also affected by the uncertainties of the seasonal adjustment process itself. Seasonally adjusted series for selected labor force and establishmentbased data are published monthly in Employment and Earnings. Household data Since January 1980, national labor force data have been seasonally adjusted with a procedure called Xll ARIMA (AutoRegressive Integrated Moving Average), which was developed at Statistics Canada as an extension of the standard Xl 1 method. A detailed description of the procedure appears in The Xll ARIMA Seasonal Adjustment Method by Estela Bee Dagum, Statistics Canada Catalogue No E, January BLS uses an extension of X11 ARIMA to allow it to adjust more adequately for the effects of the presence or absence of religious holidays in the April survey reference period and of Labor Day in the September reference period. This extension was applied for the first time at the end of 1989 to three personsatwork labor force series which tested as having significant and welldefined effects in their April data associated with the timing of Easter. At the beginning of each calendar year, projected seasonal adjustment factors are calculated for use during the January June period. In of each year, BLS calculates and publishes in Employment and Earnings projected seasonal adjustment factors for use in the second half, based on the experience through June. 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 redesign and 1990 censusbased population controls, adjusted for the estimated undercount, introduced 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 are only carried back to 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 three major labor force components agricultural employment, nonagricultural employment, and unemployment data for four sexage 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 eight 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. In each January issue (March issue in 1996), Employment and Earnings publishes revised seasonally adjusted data for selected labor force series based on the experience through December, new seasonal adjustment factors to be used to calculate the civilian unemployment estimate for thefirst6 months of the following year, and a description of the current seasonal adjustment procedure. Establishment data Effective in June 1996, with the release of the March 1995 benchmark revisions, BLS began using an updated version of the Xl2 ARIMA software developed by the Bureau of the Census to seasonally adjust national establishmentbased employment, hours, and earnings series. The conversion to Xl2 ARIMA allows BLS to refine its seasonal adjustment procedures to control for survey interval variations, sometime referred to as the 4 vs. 5week effect. While the CES survey is referenced to a consistent concept, the pay period including the 12th day of the month, inconsistencies arise because there are variations of 4 or 5 weeks between the week of the 12th in any given pair of months. In highly seasonal months and industries, this variation 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. 201

209 The interval effect adjustment is accomplished through the REGARIMA (regression with autocorrelated errors) option in the X12 software. This process combines standard regression analysis, which measures correlations between two or more variables, with ARIMA modeling, which describes and predicts the behavior of a data series based on its own past history. In this application, the correlations of interest are those between employment levels in individual calendar months and the length of the survey intervals for those months. The REGARIMA models estimate and remove the variation in employment levels attributable to 11 separate survey intervals, one specified for each month, except March. March is excluded because this month has a 5week interval between the February and March surveys only every 29 years. Effective with the release of the March 1997 benchmark, seasonally adjusted series for hours and earnings of production or nonsupervisory workers from 1989 forward incorporate refinements to the seasonal adjustment process to correct for distortions related to the method of accounting for the varying length of payroll periods across months a calendar effect. REGARIMA modeling also is used to identify, measure, and remove this calendar effect for the publication level seasonally adjusted hours and earnings series. Projected seasonal factors for the establishmentbased series are calculated and published twice a year, paralleling the procedure used for the household series. Revisions to historical data (usually the most recent 5 years) are made once a year, coincident with benchmark revisions. All series are seasonally adjusted using multiplicative models in X12. Seasonal adjustment factors are computed and applied at component levels. For employment series, these are generally the 2digit SIC levels. Seasonally adjusted totals are arithmetic aggregations for employment series and weighted averages of the seasonally adjusted data for hours and earnings series. Seasonally adjusted average weekly earnings are the product of seasonally adjusted average hourly earnings and average weekly hours. Average weekly earnings in constant dollars, seasonally adjusted, are obtained by dividing the average weekly earnings series by the seasonally adjusted Consumer Price Index for Urban Wage Earners and Clerical Workers (CPIW), and multiplying by 100. Indexes of aggregate weekly hours, seasonally adjusted, are obtained by multiplying average weekly hours by production or nonsupervisory workers and dividing by the 1982 annual average base. For total private, total goodsproducing, total private serviceproducing, and major industry divisions, the indexes of aggregate weekly hours, seasonally adjusted, are obtained by summing the aggregate weekly hours for the appropriate component industries and dividing by the 1982 annual average base. Seasonally adjusted data are not published for a number of series characterized by small seasonal components relative to their trendcycle and/or irregular components. These series, however, are used in the aggregation to higher level seasonally adjusted series. Seasonal adjustment factors for Federal Government employment are derived from unadjusted data which include Christmas temporary workers employed by the Postal Service. The number of temporary census workers for the decennial census, however, is removed prior to the calculation of seasonal adjustment factors. The standard procedure for seasonal adjustment for the local education employment series was improved with the 1997 benchmark. In the past, the seasonal factors for this industry were derived using the standard seasonal adjustment procedure of a logarithmic transformation of the data as input for the multiplicative decomposition of the series. However, in recent years, the forecasted seasonal factors have failed to adequately reflect the changing behavior of this industry in the summer months. The factors for this industry are now derived using a squareroot transformation of the data as input for an additive decomposition of the series. These modifications produce seasonal factors that better reflect current industry seasonal patterns. However, the annual averages of seasonally adjusted and unadjusted series will not be equal. BLS also makes special adjustments for floating holidays for the establishmentbased series on average weekly hours and manufacturing overtime hours. From 1988 forward, these adjustments are now accomplished as part of the X12 ARIMA/REGARIMA modeling process. The special adjustment made in November each year to adjust for the effect of poll workers in the local government employment series also is incorporated into the X12 process from 1988 forward. Revised seasonally adjusted national establishmentbased series based on the experience through March, new seasonal adjustment factors for MarchOctober, and a description of the current seasonal adjustment procedure appear in the June issue of Employment and Earnings. Revised factors for the September April 2001 period will appear in the December issue. Beginning in 1993, BLS introduced publication of seasonally adjusted nonfarm payroll employment data by major industry for all States and the District of Columbia (table B7). Seasonal adjustment factors are applied directly to the employment estimates at the division level (component series for manufacturing and trade) and then aggregated to the State totals. The recomputation of seasonal factors and historical revisions are made coincident with the annual benchmark adjustments. State estimation procedures are designed to produce accurate (unadjusted and seasonally adjusted) data for each State. BLS independently develops a national employment series; State estimates are not forced to sum to national totals. 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 significant distortions at an aggregate level. Due to these statistical limitations, BLS does not compile a 202