Figure 1 Labor Force Participation Rates for Females and Males by Age and Marital Status: 1890 to 2004

Transcription

1 Source: Goldin (2006) Figure 1 Labor Force Participation Rates for Females and Males by Age and Marital Status: 1890 to M ales, 25 to 44 years Females, 25 to 44 years M arried White Females, 35 to 44 years Sources: 1890 to 1970, Goldin (1990) from U.S. federal population census; 1965 to 2004, March Current Population Survey (CPS). Notes: All races, marital statuses, and education groups are included unless indicated otherwise. The labor force participation rate from 1890 to 1930 is the fraction of gainful workers in the relevant population. The dots are from the census and the triangles from the CPS. The difference for females is small, somewhat larger for males.

2 Decline in LFP after the Great Recession in the US Source: Blau and Kahn (2016) 15

3 Steep Growth in Women s Labour Force Participation* Followed by a Leveling-Off 1.0 Canadian Labour Force Participation Rate - Ages 25 to Participation Rate Men Women Source: Fortin, Drolet and Bonikowska (2016), LFS Public use files, *Labour force participants include employed (at work or on-leave) and unemployed individuals 14

4 S14 Nicole M. Fortin and Michael Huberman TABLE 1 Distribution of Female and Male Workforce, Occupation Category Women White-collar Proprietary and managerial Professional Clerical Commercial and financial Manual Manufacturing and mechanical Construction * * * * * 0.1 * Labourers Transportation and communication Service Personal Protective and other * Primary Not stated 0.3 * Men White-collar Proprietary and managerial Professional Clerical Commercial and financial Manual Manufacturing and mechanical Construction Labourers Transportation and communication Service Personal Protective and other Primary Not stated 0.2 * Note: * less than 0.05 percent None Source: Meltz (1969, Tables A.2 A.3). CANADIAN PUBLIC POLICY ANALYSE DE POLITIQUES, VOL. XXVIII, SUPPLEMENT/NUMÉRO SPÉCIAL

5 Table 1 Distribution of U.S. Female and Male Workforces Occupation Class Women Managers Professionals and Technicians Natural Sciences & Related Health & Medical Education Social Sciences & Related Clerical Workers Sales Private Household Services Other Services Manual Workers (other than Textile) a Precision Workers Operatives & Laborers Textile Workers Farming, Fishing and Forestry Workers Men Managers Professionals and Technicians Natural Sciences & Related Health & Medical Education Social Sciences & Related Clerical Workers Sales Private Household Services Other Services Manual Workers (other than Textile) a Precision Workers Operatives & Laborers Textile Workers Farming, Fishing and Forestry Workers Source: N.M. Fortin, Gender Role Attitudes, Occupational Gender Segregation, and the Gender Wage Gap. Computed from the IPUMS Historical Censuses from 1950 to 1990, using the OCC1950 variable as the source of the occupation categories. Paid workersaged16to64selected. a Includes manufacturing, mechanical, construction and transportation workers

6 Source: Goldin (1990)

7 Source: Bailey (2005), United States Figure III Age-specific labor-force participation rates, by cohort and age Age of cohort Pre-1964 data are averaged over cohorts as in Smith and Ward (1985, Table 1). For instance, the participation rate for women ages 14 to 19 in 1950 is plotted in this figure as the cohort of 1930 at those ages. Data after 1963 represent participation rates for a single year of birth cohort at the reported age. Synthetic birth cohorts are computed by subtracting the reported age from the year of the survey. Bold lines depict the 1940 and 1955 cohorts. The March sample includes all women not in military or inmates ages 16 to 60. Source: March CPS; for years before 1964, data is from Smith and Ward (1985, Table 1).

8 Generational Effects in the Growth of Women s LFP 1.0 Women's Labour Force Participation by Synthetic Birth Cohort Participation Rate < All Source: Fortin, Drolet and Bonikowska (2016), LFS public use files, ages 25 to 64 year 17

9 Generational Effects in the Growth of Women s LFP 1.0 Women's Labour Force Participation by Synthetic Birth Cohort Participation Rate All Source: Fortin, Drolet and Bonikowska (2016), LFS public use files, ages 25 to 64 year 18

10 Women s employment rates are lower in countries where women agree more the statement that Scarce jobs should go to men first Women's Employment Rate DE SE DK SE NO SE NO IS DK FI CZSK IS FI US AT US NL CA GR UK US AS CH PL UK FI CADEDEW HU JP DEWFR IT BE JP CH IE PT JP NL ES ES ES PT FR IE HU IT BE PL AT TK PL CZ SK TK TK Scarce Jobs Should Go to Men First Fitted values Source: Fortin (2005), World Value Surveys Source: WVS

11 But there has been a decrease over time in agreement with Scarce jobs should go to men first Percentage who agree with the statement 25% 20% 15% 10% 5% 0% U.S. Canada U.S. U.S. Canada Source: Fortin (2005), World Value Surveys Women Men

12 Women s employment rates are lower in countries where women agree more with the statement that Being a housewife is just as fulfilling as working for pay Women's Employment Rate DE DE CZ GR SK SE FI NO DK NO SE SE DK IS SK IS HU CZ FI US UK US PT NL PL AS CA DEW US HU UK CA FI DEW IT BE FR PT IT NL AT JP FR BE IE PL ES ES ES Being a Housewife Fulfilling TK TK TK JP JP Fitted values Source: Fortin (2005), World Value Surveys

13 But no such decrease in agreement Being a housewife as fulfilling as working for pay Percentage who strongly agree or agree with the statement 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% U.S. Canada U.S. U.S. Canada Women Men Source: Fortin (2005), World Value Surveys

14 The long-term decline in traditional gender roles attitudes stalled in the 1990s Average agreement with the statement : It is much better for everyone involved if the man is the achiever outside the home and the woman takes care of the home and family American Women years old American Men years old Source: Fortin (2015)

15 and even reversed itself so among Generation X women Average agreement with the statement : It is much better for everyone involved if the man is the achiever outside the home and the woman takes care of the home and family Baby-boomer Women Baby-boomer Men Generation X Women Generation X Men Source: Fortin (2015)

16 Stories from Gunderson (2006) The Lord spoke to Moses and said Speak to the Israelites in these words. When a man makes a special vow to the Lord which requires your valuation of living persons, a male between twenty and fifty years old shall be valued at fifty silver shekels, that is shekels by the sacred standard. If it is a female, she shall be valued at thirty shekels. Leviticus 27:1 4 Millicent Fawcett, wrote the following story in the Economic Journal in 1918, related to the tunic maker, John Jones, who became ill but was allowed by the firm to continue his work at home. As his illness progressed, his wife took over the work and eventually did it all until his death. When, however, it became quite clear, John Jones being dead and buried, that it could not be his work, Mrs. Jones was obliged to own that it was hers, and the price paid for it by the firm was immediately reduced to two-thirds of that amount paid when it was supposed to be her husband s (1). There is also the statement made by an Ontario judge in an equal pay case in 1968 (Beckett vs Sault Ste Marie Police Commission, cited in Gunderson 1975, 140): He being a married man with a family to maintain and support was paid at a rate somewhat higher than [the plaintiff] who was single and has no family obligations whatsoever (635)... [The plaintiff] was fully aware of the salary she had agreed on (640)... She is not being discriminated against by the fact that she receives a different wage, different from male constables, for that fact of difference is in accord with every rule of economics, civilisation, family life and common sense... this female member of the force is undermining the moral of the force. She is a menace to its esprit de corps (641).

17 HIGHLIGHTS OF WOMEN'S EARNINGS IN 2014 Chart 1. Women's earnings as a percentage of men's, for full-time wage and salary workers, annual averages In percent Note: Percentages are calculated from annual averages of median usual weekly earnings for full-time wage and salary workers. Source: U.S. Bureau of Labor Statistics.

18 Ratio of women s men s earnings rising Between , the gender wage gap narrowed by 9.6 percentage points or in relative terms, by 13% percent Based on average HOURLY wages of ALL workers Based on average ANNUAL earnings of FULL-YEAR FULLTIME workers Based on average ANNUAL earnings of ALL workers Source: Drolet (2010)

19 1.00 Generational Effects in the Gender Pay Gap Gender Gap in Hourly Wages by Synthetic Birth Cohort All Source: Fortin, Drolet and Bonikowska (2016), LFS data, ages 25 to 64 year, hourly wage on the main job 27

20 Generational Effects in the Gender Pay Gap 1.00 Gender Gap in Annual Earnings by Synthetic Birth Cohort All Source: Fortin, Drolet and Bonikowska (2016), LWF data, ages 25 to 64 year, 3-year moving average annual earnings from all jobs 28

21 1096 THE AMERICAN ECONOMIC REVIEW APRIL 2014 Source: Goldin (2014) log (female/male earnings), [female/male earnings] Part A. No controls [0.90] [0.82] [0.74] [0.67] [0.61] [0.55] [0.50] born c Age Part B. With controls for work time and education Age log (female/male earnings) born c Figure 1. Relative Earnings of (Full-Time, Full-Year) College Graduate Men and Women for Synthetic Cohorts: Born 1923 to 1978 Notes: Sample consists of full-time (35+ hours), full-year (40+ weeks), college-graduate (16+ years of schooling), men and women (white, native-born, non- military, 25 to 69 years old), using trimmed annual earnings data (exceeding 1,400 hours minimum wage) corrected for income truncation (top-coded values 1.5). Part B contains controls for education beyond 16 years, log hours, and log weeks. Age is entered in five-year intervals with an interaction with female. In each graph the lines connect the coefficients on the five-year intervals for each birth cohort. Sources: US Census Micro-data 1970, 1980, 1990, 2000, and American Community Survey 2004 to 2006 (for 2005), 2009 to 2011 (for 2010).

22 Source: Mulligan and Rubinstein (2008)

23 Source: Mulligan and Rubinstein (2008)

24 Source: Goldin (2006) Figure 1 College Graduation Rates (by 35 years) for Men and Women: Cohorts Born from 1876 to Males 0.2 Females Birth Year Sources: 1940 to 2000 Census of Population Integrated Public Use Micro-data Samples (IPUMS). Notes: The figure plots the fraction of four-year college graduates by birth cohort and sex adjusted to 35 years of age for the U.S. born. College graduates are those with 16 or more completed years of schooling for the 1940 to 1980 samples and those with a bachelor s degree or higher in the 1990 to 2000 samples. The log of the college graduation rate for a birth cohort-year cell is the dependent variable in the age-adjustment regressions that include a full set of birthcohort dummies and a quartic in age as covariates. The age-adjustment regressions are run on birth cohort-census year cells, pooling all the IPUMS for 1940 to The underlying samples include all U.S. born residents aged 25 to 64 years. For more details on the method, see De Long, Goldin, and Katz (2003), notes to figure 1.

25 29 Table 2: Distribution of Undergraduate Majors for Four Cohorts of Women and White Men Panel A: All Women Age Cohorts Broad Major Categories Women s Mean Wage of Bachelor s Degree Health Professions $ Mathematical Sciences Computer Sciences Engineering technology Physical Sciences Engineering Humanities Business and Economics Education Social Sciences Life Sciences Fine Arts Professional Degrees Agricultural Sciences Other Majors *** Panel B: Non-Hispanic White Men Age Cohorts Broad Major Categories Men s Mean Wage of Bachelor s Degree Health Professions $ Mathematical Sciences Computer Sciences Engineering Technology Physical Sciences Engineering Humanities Business and Economics Education Social Sciences Life Sciences Fine Arts Professional Degrees Agricultural Sciences Other Majors *** Notes: Authors calculation, NSCG. The data are weighted to account for sample stratification. Mean wage of bachelor s degree is estimated using only women or men whose highest degree completed is a BA, while the percentage of each group selecting each college major includes those with higher degrees. The 144 majors in the NSCG are aggregated into the broad categories shown in these tables.

26 Source: Blau, Ferber and Winkler (2002)

27 Bruce Western & Becky Pettit on mass incarceration Figure 1 Percentage of Men Aged Twenty to Thirty-Four in Prison or Jail, by Race/Ethnicity and Education, 1980 and 2008 Source: Becky Pettit, Bryan Sykes, and Bruce Western, Technical Report on Revised Population Estimates and nlsy79 Analysis Tables for the Pew Public Safety and Mobility Project (Harvard University, 2009).

28 Source: Western and Petitt (2004) RACE AND CLASS INEQUALITY IN U.S. INCARCERATION 157 Figure 1. Percentage of Men Admitted to Prison for the First Time (solid line) and Incarcerated (broken line), Blacks and Whites, Aged 18 to 34, 1974 to 1999

29 Source: Neal and Johnson (1996) BLACK-WHITE WAGE DIFFERENCES TABLE Black (.026) Hispanic -.I13 (.030) *ge.048 (.014) AFQT... NOTE.-The dependent variable is the log of hourly wages. The wage observations come from 1990 and All wages are measured in 1991 dollars. If a person works in both years, the wage is measured as the average of the two wage observations. Wage observations below $1.00 per hour or above $75 are eliminated from the data. The sample consists of the NLSY cross-section sample plus the supplemental samples of blacks and Hispanics. Respondents who did not take the ASVAB test are eliminated from the sample. Further, 163 respondents are eliminated because the records document a problem with their test. All respondents were born after Standard errors are in parentheses.

30 Source: Neal and Jonhson (1996) BLACK-WHITE WAGE DIFFERENCES TABLE 4 Black -,352 (.029) Hispanic -.I80 (.034) Age,067 (.015) AFQT... No~.-The dependent variable is log hourly wages. The sample is the sample described in table I plus the sample of nonparticipants. Nonparticipants include workers who report not working between their 1989 and 1991 interviews. Nonparticipants also Include workers who did not work between their 1989 and 1990 interviews and were not interviewed in Some respondents are excluded from the previous regression analyses solely because their wage observations are invalid. These respondents are also excluded from this analysis. All respondents were born after Standard errors are in parentheses.

31 Source: Altonji and Pierret (2001) 330 QUARTERLY JOURNAL OF ECONOMICS TABLE I THE EFFECTS OF STANDARDIZED AFQT AND SCHOOLING ON WAGES Dependent Variable: Log Wage; OLS estimates (standard errors). Panel 1 Experience measure: potential experience Model: (1) (2) (3) (4) (a) Education (0.0118) (0.0150) (0.0120) (0.0153) (b) Black (0.0256) (0.0256) (0.0621) (0.0723) (c) Standardized AFQT (0.0144) (0.0360) (0.0144) (0.0421) (d) Education experience/10 (0.0094) (0.0123) (0.0095) (0.0127) (e) Standardized AFQT experience/10 (0.0286) (0.0343) (f) Black experience/ (0.0482) (0.0581) R Panel 2 Experience measure: actual experience instrumented by potential experience Model: (1) (2) (3) (4) (a) Education (0.0208) (0.0243) (0.0206) (0.0248) (b) Black (0.0261) (0.0260) (0.0851) (0.1029) (c) Standardized AFQT (0.0143) (0.0482) (0.0143) (0.0572) (d) Education experience/10 (0.0235) (0.0276) (0.0234) (0.0283) (e) Standardized AFQT experience/10 (0.0514) (0.0627) (f) Black experience/ (0.0968) (0.1184) R Experience is modeled with a cubic polynomial. All equations control for year effects, education interacted with a cubic time trend, Black interacted with a cubic time trend, AFQT interacted with a cubic time trend, two-digit occupation at first job, and urban residence. For these time trends, the base year is For the model in Panel 1 column (1) the coefficient on AFQT and Black are.0312 and.1006, respectively, when evaluated for In Panel 2 the instrumental variables are the corresponding terms involving potential experience and the other variables in the model. Standard errors are White/Huber standard errors computed accounting for the fact that there are multiple observations for each worker. The sample size is 21,058 observations from 2976 individuals.

32 Racial Splits

33 Vol. 2 No. 4 arcidiacono et al.: Education and the Revelation of Ability 81 Table 2 The Effects of AFQT on Log Wages for High School and College Graduates Test: College=HS High school College P-values Model (1) (2) (3) (4) (5) (6) Standard. AFQT ** ** (0.0130) (0.0129) (0.0350) (0.0354) AFQT exper/ ** ** (0.0176) (0.0173) (0.0480) (0.0472) Black ** * * ** (0.0267) (0.0259) (0.0563) (0.0543) Black exper/ * * (0.0350) (0.0345) (0.0694) (0.0677) R Observations 11,795 11,772 4,112 4,112 Additional controls No Yes No Yes No Yes Experience measure: Years since left school for the first time <13 Notes: All specifications control for urban residence, a cubic in experience, and year effects. Specifications (2) and (4) also control for region of residence and for part-time versus full-time jobs. In specification (5), we report the p-values for the difference in the coefficients of specifications (1) and (3). Similarly, specification (6) compares (2) and (4). The White/Huber standard errors in parenthesis control for correlation at the individual level. ** Significant at the 5 percent level. * Significant at the 10 percent level.

34 In models of statistical discrimination, employers beliefs regarding the ability of worker i, is a weighted average of the worker s ability, AAAAAAAA ii, and the average ability of his group, AAAAAAAA gg, with weight θθ. As the worker s ability is revealed over time, the weight θθ xx and the contribution of ability to productivity λλ xx are allowed to vary with experience x, this yields the following model of wages: ww ii,xx = λλ xx [ (1 θθ xx )AAAAAAAA gg + θθ xx AAAAAAAA ii ] + kk xx, where kk xx is an experience-specific constant. Simplification yields the estimating equation for college graduates for each experience level x

35 The estimates show that the effect of the increasing productivity of AFQT dominates the effect of learning in determining the coefficient on race early in the life cycle with the effects roughly canceling out after five years. Part of the reason why blacks earn less than whites can be explained by the fact that they accumulate less labor market experience than whites.

36 1218 D. Albouy (2008) Mean Log Wage Difference Year Francophone Wage Gap in Canada Francophone Wage Gap in Quebec Francophone Wage Gap outside Quebec Quebec Wage Gap for Anglophones FIGURE 1 Mean hourly wage gap between groups

37 Vol. 3 No. 4 Oreopoulos: Why Do Skilled Immigrants Struggle in the Labor Market? 161 Table 4 Estimated Callback Rates by Resume Type and Ethnic Origin Callback rate for Type 0 resumes with English name, Canadian experience, and Canadian education (1) (2) (3) (4) (5) (6) (7) Type English name Cdn educ Cdn exp Callback rates and relative differences by ethnic origin and experience/education location (Difference compared to Type 0) [Standard error of difference] {Callback ratio: Type 0/Type} Indian Pakistani Chinese Chinese with English first name English- British Greek Indian/ Pakistani/ Chinese Type NA Foreign name ( 0.045) ( 0.050) ( 0.041) ( 0.033) ( 0.040) ( 0.044) Cdn educ [0.012]*** [0.016]*** [0.013]*** [0.014]** [0.019]** [0.009]*** Cdn exp {1.39} {1.44} {1.40} {1.26} {1.34} {1.39} Type NA Foreign name ( 0.045) ( 0.018) ( 0.057) ( 0.029) ( 0.029) ( 0.047) Foreign educ [0.015]*** [0.027] [0.015]*** [0.019] [0.019] [0.011]*** Cdn exp {1.39} {1.13} {1.59} {1.22} {1.22} {1.43} Type NA Foreign name ( 0.085) ( 0.080) ( 0.053) ( 0.060) ( 0.001) ( 0.072) Foreign educ [0.013]*** [0.020]*** [0.016]*** [0.020]*** [0.023] [0.010]*** Mixed exp {2.13} {2.05} {1.58} {1.61} {1.01} {1.85} Type NA Foreign name ( 0.098) ( 0.106) ( 0.095) ( 0.017) ( 0.017) ( 0.098) Foreign educ [0.013]*** [0.015]*** [0.014]*** [0.021] [0.021] [0.009]*** Foreign exp {2.58} {3.04} {2.61} {1.12} {1.12} {2.71} Notes: Cdn = Canadian, Educ = country where bachelor s degree obtained, and Exp = country where job experience obtained. Mixed experience corresponds to first two jobs listed on resume as being from a foreign country, and most recent (third) job listed is from Canada. The table shows coefficient estimates from regressing call back status on resume type and two time indicators for when the sampling distribution of resumes changed (i.e., adding Pakistani and Greek names) with robust standard errors. Each column shows separate regression results after selecting on the sample of Type 0 resumes and Types 1 4 resumes with the indicated ethnic backgrounds. The first row indicates the call back rate estimate for Type 0 resumes during the first period of data collection. *** Significant at the 1 percent level. ** Significant at the 5 percent level. * Significant at the 10 percent level.

38 Employment Earnings for All Immigrants to Canada by Landing Year ($2003) from the Longitudinal IMmigration Data Base (IMDB) o Links immigrants landed from 1980 to 2002 with their income tax filings Tax Year Entry Canadian

39 Source: (1994) Borjas

40 Source: Borjas (1994, Table 6) Removing entry cohort and life-cycle effects

41 Source: Abbott and Beach (2009)

42 118 N. Fortin, et al. / Labour Economics 41 (2016) Table 8 Immigrant wage gap with different educational paths. High school in Canada High school abroad +Trade foreign Trade Canada.0249 (0.0237) (0.0095) +Trade foreign.0034 (0.0178) +Below bachelor Canada Below bachelor Canada (0.0015) (0.0088) +Below bachelor foreign Below bachelor foreign (0.0201) (0.0170) +Bachelor Canada Bachelor Canada (0.0017) (0.0100) +Bachelor foreign Bachelor foreign (0.0189) (0.0173) +Bachelor Canada + above bachelor Canada Bachelor Canada + above bachelor Canada (0.0024) (0.0162) +Bachelor foreign + above bachelor Canada (0.0116) +Bachelor Canada + above bachelor foreign Bachelor foreign + above bachelor foreign (0.0173) (0.0179) Weighted numb. of obs. 6,323,125 R Note: Robust standard errors are in parentheses. The omitted category is High School Canada and Trade in Canada. The estimation includes country/area of origin fixed effects ( Canada is the omitted category), CMA/province fixed effects (Toronto/Ontario are the omitted categories), and French or English mother tongue. The specification also separates Canadian and foreign work experience and includes dummies for education levels. * Denotes significance at 10% level. ** Denotes significance at 5% level. *** Denotes significance at 1% level.