1. changes in male-female labour outcomes over time 2...

Fortin – Econ 561 Lecture 4C

IV. Wage Differentials across Groups and Labour Market Discrimination 12. Gender and Race in the Labour Market 1. Changes in male-female labour outcomes over time

2. Gender differences in pre-market characteristics and human capital 3. Racial differences in pre-market characteristics and human capital

13. Immigrants and Ethnic Differences


12.1. Changes in Male-Female Labour Outcomes over Time • Differences between men and women in the labour market outcomes, namely labour force

participation, labour supply, unemployment rates and their relative wages, called the gender pay gap, always capture the attention of the public at large.

• It is a continuing topic of interest for labour economists, and more recently, has become more salient in the work of macroeconomists, who also integrate issues of fertility

• For example, the relationship between fertility and female labor force participation (FLP)

• Goldin (1990) provides an authoritative account of the historical trends in women’s labour market

outcomes going back to the 18th century.

• The industrial revolution and the mass migration to cities provided the first impetus behind the changing roles of men and women, when men move from agricultural employment into manufacturing and women move out of “light manufacturing” and concentrated on homemakers and child rearing.


• Keeping in mind the functions from static labour supply models:

iiiii uXIwH +′+++= β210 ln ααα or iii

Siii vXAwwH +′++++= β3210 lnln ββββ

where H is hours worked, w is one’s own hourly wage offer, I is family asset income plus spouse’s earnings, X is a vector of control variables, or Sw is one’s spouse’s hourly wage offer (assuming one is married), A is family asset income. There are numerous pitfalls in the estimation of such equations including the fact that we do

not observe wage offers for those without jobs and that the distribution of hours is censored, measurement errors in hours, omitted variables, etc.

Assuming satisfactory solutions to these problems 1α and 1β will capture the own-wage (uncompensated) effect of labour suppy 2α and 3β will capture the income effect and the substitution effect (compensated wage effect) will be computed from the difference

between the two with the second equation, there is a cross-spouse effect


• Goldin (1996) identify four phases (or five?) in the transformation of women’s work Phase and Time Period What happened? Income elasticity of

female labour supply

Wage Substitution Elasticity

I – late 1890s to 1920s Few adult and married women worked large and negative small II – 1930 to 1950 Impact of WWII reduces stigma around

married women’s work outside; electric household appliances begin to diffuse; initial stirrings of part-time work

decreases considerably in magnitude

increases substantially with the reduction in hours of work

III – 1950 to the late 1970s

large increase in aggregate demand, especially in the 1960s, and accommodation of married women with the expansion of part-time work

rather elastic

IV – the late 1970s to mid-1990’s known as “Quiet Revolution”

contraceptive innovation known as the pill, which enable young women to postpone marriage and they increased their investments in formal schooling

influenced even less than before by husband’s earnings

no longer as elastic


V– the mid-1990s “opt-out” phenomena

the growth in the participating rate of married mothers slowed and declined somewhat in the late 1990s and early 2000s, while the participation rate of single mothers expanded rapidly during the latter 1990s

given the lower sensitivity of women’s labour supply to their husband’s income, other explanation is sought

• The case for the Pill revolution was also tested by Bailey (2006) which shows the importance of

cohort effects. • Over the course of this transformation of women’s work, there were have been some important

changes in women’s occupational choices and the gender pay gap, but there has a slowdown in the convergence of men and women’s pay starting in the mid-1990s (Blau and Kahn, 2005; O’Neil, 2003).


• Indeed, Goldin (2014) reports that the ratio of (mean) annual earnings between male and female

workers (full-time, full-year, 25 to 69 years) was 0.72 in 2010 and that of the medians was 0.77. The ratio of the medians for the same group was 0.74 in 2000 but 0.56 in 1980.

• Role for changing self-selection? • Blau and Kahn (2006) show that the reduction in the wage gap between men and women over the

1980s and the 1990s results primarily from an improvement in the observed characteristics of women, like experience and the types of jobs held

• They also show that while accounting for sample selection does not change qualitatively the previous results but tends to overstate women's convergence, notably in the 1980s (because the female labor force growth in that period was positively selected). Overall, selection could explain 25% of the slowdown in the narrowing of the unexplained gender

pay gap


• Mulligan and Rubinstein (2008) argue that selection effects can account for a larger part, in fact for most, of the apparent changes of wages across gender among whites aged 25 to 54, but they rely on somewhat dubious instruments about marriage and kids.

• Recent studies of the impact of children on mothers' earnings have found large and persistent negative effects on labour market outcomes: o for the United States, Wilde, Batchelder, and Ellwood (2010) o for Italy: Del Bono and Vuri (2011) o for Germany: Fitzenberger, Sommerfeld, and Steffes (2013), Adda, Dustmann, and Stevens

(2016) o for Spain: Fernandez-Kranz, Lacuesta, and Rodriguez-Planas (2013) o for Austria: Fruhwirth-Schnatter, Pamminger, Weber, and Winter-Ebmer (2014) o for Portugal: Card, Cardoso and Kline (2016) o for Sweden: Angelov, Johansson, and Lindahl (2016), Karimi, Hotz, and Johansson (2016) o for Denmark: Kleven, Landais, and Sogaard (2016).


• While each paper offers more nuanced conclusions, in the end, they find that following childbirth, mothers are less likely to further their educational attainment.

• They often move to part-time work or a more flexible schedule, to family-friendly, less profitable, and lower paying firms, and are less likely to be promoted.

• What is yet unclear is whether the mothers' lower rate of promotions comes from the fact that employers direct them to the ``mommy track" or whether this lower rate results from mothers' preferences.


12.2. Gender Differences in Pre-Market Characteristics and Human Capital • Gender differences in basic skills, as measured by AFTQ scores for example, are relatively minor by

comparison with racial differences, which are have been to account for a substantial fraction of the racial pay gap (Neil and Johnson, 1996).

• Gender differentials in the level of educational attainment have considerably narrowed following the

“Pill Revolution”. Women are now o less likely to be high school drop-outs than men, o more likely to hold a baccalaureate degree o closing the gap on post-graduate education

• Yet there are sizeable gender differences in choices of college majors. • Brown and Corcoran (1997) and Black, Haviland, Sanders and Taylor (2004) study the impact of gender

differences in college majors on the gender pay gap among the highly educated. o Brown and Corcoran use the NLS72 and find that a substantial but not overwhelming share of the

gender gap in accounted for by these differences.


o Black et al. uses the 1993 NGS and finds that among men and women matched on observables, who speak English at home, between 44 and 73 percent of the gender wage gaps are accounted for by such pre-market factors as highest degree and major.

o When they restrict attention further to women who have “high labor force attachment” (i.e., work experience that is similar to male comparables) we account for 54 to 99 percent of gender wage gaps.

• After education, the accumulation of work experience is the most important human capital factor that

explains the distribution of earnings across workers. • The Mincer-Polachek hypothesis argues that the discontinuity of women’s labour force attachment

explains a substantial part of the gender pay gap. Because of interruptions for family reasons, o men tend to acquire more human capital o the experience gap widens during child-raising years as women’s labour market skills depreciate o these foreseen interruptions may lead women to specialize in fields where depreciation is less rapid

(e.g. history rather than computer science) or in which skills can be restored more quickly.


• Indeed, many studies (O’Neil and Polachek, 1980; Blau and Kahn, 1997) have found that changes in the level of actual (as opposed to potential) labour market experience of women has been the most important contributing factor to the narrowing of the gender pay gap.

• Light and Ureta (1995) using detailed measures of the fraction of time worked in each of the years from

a women’s career, as well as dummies for labour market interruptions find the timing of labour market interruptions also matters.

• While long labour market interruptions may lead to some substantial wage losses, the case of job mobility – quitting to take another job- may be something different.

• Altonji and Paxson (1992) find that women’s job mobility is strongly linked to hours changes, which play a larger role in women’s job choices than men’s for whom higher wages may be more important. Over the course of a career, this may play a larger role.

• Cortes and Pan (2014) have used O*NET based measures of competition in the occupation to link long hours and competitive jobs, two characteristics leading to higher pay.


• Indeed, considering the role played by expectations of future earnings in the gender pay gap, Breen and Garcia (2002) find that women’s fail to predict the substantial increase in the gender gap that occur over the course of their careers.

• Women’s greater household responsibilities have also been said to lead to higher absenteeism,

although annual absenteeism (excluding maternity leave) for full-time employees is only slightly higher for women at 10.9 days than for men at 8 days (Akyeampong 2005).

• Recent studies have also suggested that gender differences in job related tastes and traits may be

implicated not only in average gender gap effect, but perhaps in glass ceiling effects such as o Gender differences in overconfidence and competitiveness o Gender differences in working under pressure (Paserman, 2007) o Gender differences in attitudes towards risk and client service (Green, Jegadeesh, and Tang, 2007) o Gender differences in the importance of “money” and “being useful to others and society” (Fortin,

2008)


• Explanations for Glass Ceiling Effects? Men are more overconfident than women. This could be related to (cause?) gender differences in risk aversion and competitive behavior.

Soll and Klayman (2004) ask participants to provide high and low estimates such that they were X

percent sure that the correct answer for a given question lay between them. Both men and women were overconfident (their intervals were too small) but men were significantly

more so.

Niederle and Vesterlund (2007) show while both men and women demonstrate overconfidence, men are substantially more overconfident on their relative performance on a task (simple addition) and this relates to decisions to enter competitive games.

• High profile, high earnings occupations tend to have a “winner takes all” compensation scheme, which could hurt women if they shy away from these types of jobs.


• Gneezy et al (2003) in lab experiments asks students to solve mazes Evidence suggests that, while both men and women do tasks equally well when paid by piece rate,

boys do better in competitive environments while girls do not. However, women do as well as men in the competitive setting if the groups are single-sex

• Niederle and Vesterlund (2007) expand upon this work In experimental environment, they study the compensation choices men and women make in a mixed

sex environment

Task: Adding up sets of five two-digit numbers Choices: piece rate and tournament-like winner-take-all

Unlike earlier findings, boys and girls do equally well under both scenarios However, despite equal ability, boys were more than twice as likely to choose the tournament. Importantly, high performing women are less likely to choose a tournament than the men that were in

the lowest quartile, suggesting too few high-ability women and too many low-ability men entering the tournament.


• Kamas and Preston (2012) conducted an experiment on 310 student participants (156 men, 154 women) from Santa Clara University o All participants in our experiments completed math tasks which involved adding three two-digit

numbers over a two minute period. o They were offered various compensation schemes: o In the piece rate round, $0.60 per correct answer. o In the competition compensation scheme where the participant is competing against three other

anonymous persons in the classroom, a winner-take-all (WTA) tournament where the person with the highest score is paid $2.40 per

correct answer while the others are paid nothing, and the other is a ranked compensation treatment (RC) where the person who scores the highest in the group of four

receives $1.05 per point, the second highest scorer earns $0.75 per point, the third highest receives $0.45, and the lowest gets $0.15 per point.


• Differences in negotiation propensities/skills could lead to differences in pay for the very same job.

Bowles et al (2005, 2007) study gender differences in the propensity to negotiate Women are less likely to initiate negotiations Women’s performance in negotiation improves when they are negotiating for someone else (not

themselves), while men’s performance does not change Women who negotiate are perceived more negatively than men who negotiate

• Summary of the psychological evidence from laboratory experiments:

Risk Aversion: Evidence that women are more risk averse Overconfidence: While both men and women are overconfident, men tend to be substantially more

overconfident Competitive Behavior: Women perform more poorly in competitive environments and shy away from

such environments Negotiation: Women negotiate less and are less likely to ask (and are perceived more negatively than

men when they do)


12.3. Racial Differences in Pre-Market Characteristics and Human Capital • The study of racial differences in labour market outcomes is dominated by the study of the relative

outcomes of African-American, not doubt because of the sizeable relative population weight (about 12 percent) in the United States, but also because of their dire prospects in terms of other outcomes such as teen pregnancy, rates of incarceration, lower longevity, etc. .

• In Canada, African (and Caribbean) descent often carries the same wage penalty as in the US, but is

overshadowed by the wage penalty associated with Aboriginals ethnicity (Aydemir and Sweetman, 2004).

• An important study of racial differences in wages is that of Neal and Johnson (1996). They use the

NLSY-79, a longitudinal survey of the 1957-1965 birth cohorts which contains information about AFQT (Armed Forces Qualification Test) scores, to show that much of the wage gap between blacks and whites is due to differences at the point of labour market entry in the types of basic skills measured by AFQT.


• They attempt to address the issue of the perverse effects of statistical discrimination, that is, whether

because Blacks expect lower labour market returns, they would invest less in education. While they do not have data on expectations, they find mixed results on the interactions between AFQT scores and the black dummy (positive for men, negative for women)

• Neal and Johnson (1996) also incorporate a methodological innovation to deal with potential selection bias into the labor market due to the lower participation rate of Blacks, that is, they consider the wage offer curve. o They focus on median (rather than mean) wage regression and assuming that those who are not

employed would have lower wage offers than the median offer of those who are employed and are otherwise observationally equivalent.

• But note that the same applies to Hispanics and that O’Neill and O’Neill (2005) report similar results

(qualitatively) with the more recent data (when NLSY respondents are older).


• Because AFQT scores are themselves influenced by years of schooling, more recent research has tried to detect black-white differences earlier and earlier in life or to account for differences in school quality.

• Fryer and Levitt (2006) looks for whether genetic differences account for the intelligence gap across the races. Using a newly available nationally representative data set that includes a test of mental function for children aged eight to twelve months; they find only minor racial differences in test outcomes (0.06 standard deviation units in the raw data) between Blacks and Whites that disappear with the inclusion of controls.

• Arcidiacono, Beauchamp, Hull and Sanders (2015) find no differences in PPVT scores between black and white males with white mothers, but large difference with black males of black mothers.

• Almond, Hoynes, and Whitmore Schanzenbach (2008) go even further by looking at fetal origins. They

find that pregnancies exposed to the Food Stamps Program rollout three months prior to birth yielded deliveries with increased birth weight, with the largest gains at the lowest birth weights. They conclude that the sizeable increase in income from Food Stamp benefits improved birth outcomes for both whites and African Americans, with larger impacts for births to African American mothers.


• Altonji and Perret (2001) propose a test of racial statistical discrimination using the NLSY79. If premarket discrimination is an important factor in the gap between the average skills of black and white workers, a statistically discriminating firm might use race, along with education and other information to predict the productivity of new workers.

• Over time however, the productivity of the worker would become apparent, and compensation would be

based on the larger information that accumulates with experience rather than on race and the racial gap should not increase with experience. Empirically, they find that the race gap increases substantially with experience and thus find little support for statistical discrimination.

• Arcidiacono, Bayer and Hizmo (2010) provide a refinement on Altonji and Pierret (2001) who develop a framework in which employers do not initially observe the ability of a worker but learn about it over time, by distinguishing college graduates and high school graduates

• Their key insight is that ability is revealed in the college market but not in the high school market and

has a great deal of power in explaining racial wage differences. o They find that Blacks earn more than Whites in the college market, but that Blacks initially earn 6-

10 percent less than Whites with the same AFQT scores in the high school labor market


13. Ethnic Differences and Issues with Immigrants’Outcomes • Ethnicity and religion are other sources of differences across individuals that can lead to

discrimination in labour market outcomes.

• In Canada, the differences in labour market outcomes of English and French speakers are particularly salients.

• Albouy (2008) finds that the wage differential between Francophone and Anglophone men from

1970 to 2000 fell by 10 points Canada-wide. o Over half of the reduction in the Canadian Francophone wage gap is explained by rising

Francophone education levels. o The decline in the gap was 25 percentage points within Quebec, largely because the wages of

Quebec Anglophones fell by 15 points relative to other Canadian Anglophones.


• Oreoupoulos (2009/2011) performed a field experiment in the spirit of Bertrand and Mullainathan sending fake resumes to potential employers in the Toronto (as well as Vancouver and Montreal) area and found

1. Interview request rates for English-named applicants with Canadian education and experience

were more than three times higher compared to resumes with Chinese, Indian, or Pakistani names with foreign education and experience (5 percent versus 16 percent), but were no different compared to foreign applicants from Britain.

2. Employers valued experience acquired in Canada much more than if acquired in a foreign country. Changing foreign resumes to include only experience from Canada raised callback rates to 11 percent.

3. Among resumes listing 4 to 6 years of Canadian experience, whether an applicant’s degree was from Canada or not, or whether the applicant obtained additional Canadian education or not had no impact on the chances for an interview request.


4. Canadian applicants that differed only by name had substantially different callback rates: Those with English-sounding names received interview requests 40 percent more often than applicants with Chinese, Indian, or Pakistani names (16 percent versus 11 percent)

• He interpreted his results as suggesting considerable employer discrimination against applicants with ethnic names or with experience from foreign firms

• In an update of that paper, he includes a fake applicant with a Greek name and found a lower call-back rate similar to that of Chinese-named applicants

• Interestingly, Pendakur and Pendakur (1998) had found that among Canadian-born men, Greek

men faced 10 percent wage gap in comparison with British-origin men. Women of Greek origin also faced significant penalties.


• Another set of related questions are: o How do immigrants fare in the labor market? o Do they ever converge with similarly-skilled natives?

• Early studies (Chiswick, 1978) using single cross-sectional analysis misleadingly argued that immigrants’s earnings overtook those of natives 10 to 15 years after arrival

4,000

5,000

6,000

7,000

8,000

9,000

20 25 30 35 40 45 50 55 60 65

Age

An

nu

al

Earn

ing

s(1

970 D

oll

ars

)

Immigrants

Natives

Dollars

Age

P

Q

R

P

Q

R

C

C

40 60 20

1960 Wave

1980 Wave and Natives

2000 Wave

P*

Q*

R*


• This so-called “economic assimilation” of immigrants is confounded that cohort effects

• A solution proposed by Borjas (1994) to follow an entry cohort or a synthetic cohort over pooled cross-sectional address the problem

• But two selection issues remain Return migration: Do the successes or failures leave? Child immigrants:

o Consider all arrivals between 1965-69, in 1970, we observe the wages of only the adult immigrants. In 1980, can observe all but the youngest kids. By 1990, can observe all wages.

• Abbott and Beach (2009) follow an actual entry cohort of immigrants from the IMDB, but which

comparison group is most appropriate?


• Thus, in comparing the earnings of immigrants to those of the Canadian-born, in addition to demographic shifts among the Canadian-born, one has to be mindful of 1) Entry cohorts effects

o macroeconomic cycle effects o country of origin, language factors o network effects in finding jobs

2) Assimilation effects (years since migration),

o confounded by life-cycle effects o confounded by re-emigration or returns

• Also of interest for policy purposes, immigrant class


• With pooled cross-section data (from a few Censuses), the standard approach (e.g. Borjas, 1985) to identify the immigrant entry earnings and assimilation effects thus include, at a minimum ,the following terms:

ln W =β0+ β1 * EXP + β2 EXP2 + β3 School + β4 X + I * (δ0 + Σj δCj + α YSM + δ1*X) + u where W is the weekly wage; EXP is years of labour market experience; S is years of schooling; I is an immigrant dummy; Cj are cohort dummies identifying the period of arrival; YSM is years since migration; X is a vector of individual characteristics, which may include country of origin, language skills, network variables, etc.; and u is an iid error term.

• In Canada, the relative earnings of immigrants have been falling since the 1970s o Among males, the log earnings ratio at entry declined from 0.83 among the late 1970s cohort

to 0.55 among the early 1990s cohort o For the early 1990s cohort, it was only 0.7 of Canadians after 6 to 10 years in Canada


• Although the relative share of economic immigrant class has grown, the source countries have changed dramatically in the last 30 years

o In 2002, almost one in two (46 percent) first generation immigrants aged 15 and over reported non-European origins

o In contrast, among individuals aged 15 and over whose parents were Canadian-born, so-called third generation, an overwhelming majority were of European origin.

• Of the permanent residents admitted to Canada over the last decade, about half were from the Asia-

Pacific regions and one in five came from Africa and the Middle East.

• This demographic shift in first-generation Canadians will transform the racial and ethnic composition of second and successive generations of the Canadian population.

o These changes can also have some important consequences for the outcomes of the immigrants’ offspring , “1.5” and 2nd generation immigrants


• Much has been written about the barriers, immigrants face in adapting to their country of settlement, o devaluation of credentials and experience acquired in their home country, o a lack of proficiency in the official language(s) of the host country, o cultural differences, and a lack of social networks.

• Green and Worswick (2002), Aydemir and Skuterud (2004, 2005) and Frenette and Morissette

(2003) concluded that during the 1980s and 1990s the declining returns to experience was one of the major factors, if not the most important, associated with the decline in earnings among recent immigrants.

• Aydemir and Skuterud who used the complete 20%microdata files of the 1981, 1986, 1991, 1996, and 2001 Canadian Censuses concluded that, among recent immigrants,

o The decline in the return to foreign experience accounted for roughly one third of the decline in entry level earnings reported earlier.

o Another third of the decline is explained by compositional shifts in language ability and region of birth.


• Bourdarbat and Lemieux (2007) find that the relative earnings of immigrants have become more

dispersed (relative to Canadian-born) between 1980 and 2000. o Important part of these changes due to a fairly “mechanical” explanation: Canadian-born

getting relatively older (more experienced) with the aging of the baby-boom cohort o Once this is adjusted for, remaining changes mostly due to changing language/country of

origin (negative) and education (positive). o Return to foreign experience is a big factor too but “offset” in large part by the interaction

term (i.e. more catch up in Canada).

• Picot and Hou (2008) find that much of the decline in entry earnings (perhaps two thirds), from cohorts entering Canada from 2000 to 2005, was concentrated among entering immigrants intending to practice in IT or engineering occupations.

• Fortin, Lemieux and Torres (2016) distinguish Canadian vs foreign schooling and find that immigrants who acquire higher education in Canada do not face the same penalty as those who acquire their education abroad, but that there is some heterogeneity by country and field of study.


Basic readings and references: Altonji, J. and R. Blank “Race and Gender in the Labor Market” Chapter 48 in Ashenfelter and Card Handbook

of Labor Economics, vol 3C (Elsevier, North Holland, Amsterdam 1999) pp 3143-3259

O’Neill, J. and D. O’Neill, “What Do Wage Differentials Tell Us about Labor Market Discrimination?” NBER Working Paper 11240 (April 2005). Aydemir, Abdurrahman and Mikal Skuterud (2005) Explaining the Deteriorating Entry Earnings of Canada’s Immigrant Cohorts: 1966-2000” Canadian Journal of Economics. Vol. 38, No.2, p. 641-671.

1. changes in male-female labour outcomes over time 2...

Documents