Chapter 9 Labor Market Discrimination

Why is there wage dispersion? Different jobs (compensating wage differentials) Discrimination Different characteristics of workers: Ability R Schooling Choices about work and leisure

What is discrimination? When workers earn different amounts even if they do the same job and have the same ability. Borjas: “where the costs and benefits of an economic exchange depend on the race and/or gender of the person involved in the exchange.”

Table 9-1: various measures of human capital and labor market outcomes in the US labor market. White Black Hispanic Male Female % HS grad or more 85.3 87.1 81.9 82.5 58.2 62.5 % bachelor’s degree or more 29.9 28.3 18.0 19.0 11.8 13.7 LFPR 76.3 60.1 71.2 64.0 84.7 58.8 Unemployment Rate 3.7 3.6 7.9 6.7 4.6 5.5 Annual Earnings (in $1,000) 55.9 35.1 39.5 31.8 35.4 26.3 Annual earnings (among workers employed full-time, year-round) (in $1,000) 65.8 43.6 44.5 37.6 38.8 32.1

What is interesting about table 9-1? Difference in earning are due in part to differences in labor supply: white man 59% more than white woman but if we compare only those who work full time the gap is 51% Differences in earnings are due in part to differences in educational attaiment: 15% of white men do not have a HS diploma, 20% of black men and > 40% of hispanic men. Look at college diplomas. If rate of return to schooling is between 7 and 9%, this could generate substantial wage differentials

Table 9-2: international differences in Female/Male Wage ratios Country 1979-1981 1994-1998 Australia 0.800 0.868 Canada 0.633 0.698 Finland 0.734 0.799 France 0.899 Germany 0.717 0.755 Ireland 0.745 Italy 0.833 Japan 0.587 0.636 New Zealand 0.814 Spain 0.711 Sweden 0.838 0.835 United Kingdom 0.626 0.749 United States 0.625 0.763

Discrimination So, the truth is, we can’t explain all of the differences in wages between men and women and across races. So, maybe there is discrimination in the labor market. There are several models of discrimination and ways to measure it. That’s what this chapter is about.

Models of discrimination The perfectly competitive market Gary Becker’s theory of discrimination Statistical discrimination Core and Periphery jobs

Neoclassical Model of Discrimination If a market is perfectly competitive, discrimination cannot exist for long.

Problem There is evidence of discrimination. Explore the EEOC webpage sometime. Hundreds of legal cases. Hundreds of stories: The movie “North Country” Wal Mart

Gary Becker’s Taste for Discrimination So, Becker wants to explain why we might see discrimination in a market, even if it is a competitive one. He comes up with the notion of a “taste for discrimination” among: Employers Employees Customers

Taste for Discrimination Suppose there are two types of workers in the labor market: white workers and black workers. A competitive employer faces constant prices for these inputs: Ww = wage rate for white workers Wb = wage rate for black workers If the employer is prejudiced against blacks, the employer gets a disutility from hiring black workers. Employer will ACT as though the cost of a black worker is: Wb(1+d) dollars. d is the “discrimination coefficient”

Example Suppose that Wb = $10 per hour d = 0.5 The employer will then act as if hiring a black worker costs $15 per hour, a 50% increase in the cost. The greater the prejudice, the greater the disutility from hiring blacks and the greater the discrimination coefficient.

Nepotism Some employers (maybe black-owned firms) might have a different type of prejudice: they PREFER to hire blacks Think Oprah This type of behavior is called nepotism It implies that an employer’s utility-adjusted cost of hiring a favored worker equals Wb(1-n) dollars They will act as if hiring a black worker is actually cheaper than it really is.

Employer Discrimination Assume black and white workers are perfect substitutes, so a firm’s production function looks like this: q = f(Ew + Eb) The firm needs to decide which combination of inputs to hire. Ew is number of white workers hired and Eb is number of black workers hired. The firm’s output just depends on the total number of workers hired. Not their race. Any differences that arise in the economic status of the two groups cannot be attributed to skill differencences.

Assume first: No Prejudice Both black and white workers have same VMP Ww = wage of white worker and Wb = wage of black worker Profit maximization? Hire the cheapest worker. If Wb < Ww, hire black workers until Wb = VMPe See figure 9-1.

Assume Prejudicial Firm Employer acts as if the black wage is not Wb but is Wb(1+d). Now firm hires the worker with the lowest utility-adjusted price. Decision rule: Hire only black workers if Wb(1+d) < Ww Hire only white workers if Wb(1+d) > Ww Big Implication: Segregated Workforce even under competitive conditions! Note: empirical study of racial composition of a firm’s workforce (Carrington and Troske, 1998): little evidence that blacks and whites tend to be employed by different firms.

Consequences of Employer Discrimination See Figure 9-2. “white firms” pay more and hire less “black firms” who are still discriminatory, hire fewer black workers depending on size of d

Labor Market Equilibrium See figure 9-4 Initially assume Wb > Ww: no firm will hire black workers Wb falls. Note: even where Wb = Ww demand is zero. Why? R is a “threshold” where some firms have a low enough d to begin to hire black workers. Note that the equilibrium black-white wage ratio (Wb/Ww)* occurs BELOW the point where the black white wage ratio = 1. Employer discrimination generates a gap between equally skilled black and white workers.

Employee Discrimination Suppose that whites dislike working alongside blacks and blacks are indifferent about the race of their coworkers. These white workers will act as if their wage (Ww) is only Ww(1- d) where d is the white worker’s discrimination coefficient. Example: Ww = $15/hour. In a discriminating worker’s view, an integrated firm’s wage is less than $15/hour so that firm will have to pay more to get white workers to work there. But it does not pay to do this if you are a color-blind firm… Thus this model implies a segregated workforce as well. Note however, that a race wage gap is NOT generated by this behavior. Why? Explain.

Customer Discrimination If customers have a taste for discrimination, their purchasing decisions are not based on the actual price of a good, p, but on the utility-adjusted price or p(1+d), where d is the discrimination coefficient. If whites dislike purchasing from black sellers, customer discrimination reduces the demand for goods and services sold by minorities. Can you think of a case in which you have “customer discrimination”?

Customer Discrimination and the wage gap Adverse effect on black wages when the firm cannot easily hide its black workers from public view. A firm employing a black worker in a sales position will have to lower the price of the product so as to compensate white buyers for their disutility. The wage of black workers will then fall because black workers have to compensate the employer for the loss in profits.

Empirical Study Recent survey tried to get at how the interaction between the customers’ racial background and the extent of the contact between workers and customers alters the hiring decisions of firms. Table 9.3: 58% of newly hired workers are black in contact firms where most customers are black. 9% of newly hired workers are black in contact firms where most customers are white. Difference between the two suggests that customer discrimination reduces the fraction of blacks among newly hired workers by 49.0 percentage points.

Need to compare to a control group Important to note that the black employment gap between these two types of firms may be attributable to other factors. What if contact firms with mainly black customers are in black parts of a city… they’d be more likely to hire black workers. Firms in survey where workers don’t have much contact can serve as a control group. Fraction of newly hired workers who are black falls from 46.6 percent to 12.2 percent as the customer base shifts from black to white. … this is a 34.4 percentage point difference. Because we can’t blame this on customers, this is what we’d expect to happen even if we didn’t have customer discrimination.

Diff in Diff Example Over ½ of Firm’s Customers are Black Over 75% of Firm’s Customers are White Difference Type of Firm Contact between customers and workers 58.0% 9.0% 49.0% No contact between customers and workers 46.6% 12.2% 34.4% Difference-in-differences -- 14.6

Model 3: Statistical Discrimination Racial and gender differences can arise in perfectly competitive situations even in the absence of prejudice when membership in a particular group carries information about a person’s skills and productivity. Job searches are expensive, employers use all info available to them. Statistical averages are part of that. Example: statistical averages about women and maternity leaves etc. Illegal to apply this information unless it is a BFOQ

Experimental Evidence on Discrimination Hiring audits: Experiments are cleverly designed to induce employers to reveal preferences about hiring women and minorities. Sent out about 5,000 fake resumes in response to about 1,300 job ads that actually appeared in Boston and Chicago newspapers. Included black sounding and white sounding names Holding skills in the resume constant, the applicants with white-sounding names got about 1 callback for every 10 resumes sent whereas the black-sounding names got 1 callback for every 15 resumes sent.

Measuring Discrimination ∆W = Wm – Wf where W indicates the average This definition is not great because it compares apples to oranges. There are many factors, other than discrimination that generate wage differentials between groups. Number of hours worked in the workplace, for example is one simple measure. Other factors in the gender wage gap?

Better measure We would like to adjust the “raw” wage differential given above for differences in skills (and even choices to the extent that we can measure them) between men and women. Do this by estimating regressions that relate the earnings of men or women to a wide array of socioeconomic and skill characteristics: Male earnings function: Wm = αm + βmSm Female earnings function: Wf = αf + βfSf α tells us how much an employer values men/women with 0 years of schooling β tells us by how much a man’s or woman’s wage increases if he/she gets one more year of schooling If employers value the education acquired by men and women equally, the coefficients should be equal

Wage differential ∆W = αm + βmSm - αf - βfSf

Oaxaca Decomposition What we would like to do is be able to tell how much of the differences in wages is due to differences in skills between men and women and the portion of the “wage gap” that is due to discrimination. We can “decompose” the above equation into two parts (using a little algebra and a little trick –add and subtract the term βm x Sf): ∆W = (αm – αf) + (βm – βf)Sf + βm(Sm – Sf)

What does that mean??? ∆W = (αm – αf) + (βm – βf)Sf + βm(Sm – Sf) (αm – αf) + (βm – βf)Sf : portion due to discrimination this term will be positive if either employers value a man’s schooling more than they value a woman’s schooling (βm – βf), or if employers just pay men more than women for any level of schooling (αm – αf) βm(Sm – Sf): portion due to differences in skills this term is zero of men and women have the same average schooling. See figure 9-6

Validity of Oaxaca Depends largely on whether we have controlled for ALL of the dimensions in which the skills of the two groups differ… Wage equations tend to get to be like the “kitchen sink” and even then we have unknowns… What CAN we control for? Schooling, years of labor market experience, sex, race, region, union status, occupation, industry, hours worked…? Number of children? Age of first birth? Marital status. WHAT CAN’T we control for? Effort. Motivation. Quality of schooling. Major?

Section 9-11: Determinants of the Female-Male Wage Ratio Controls for Differences in Education, Age, Sex and Region of Residence Controls for Differences in Education, Age, Sex, Region of Residence, and Occupation and Industry Raw log wage differential -0.286 Due to difference in skills -0.008 -0.076 Due to discrimination -0.279 -0.211

Table 9-6 Women earned about 28.6 percent less than men in 1995 Difference in education, age, and region of residence generate only a trivial wage gap between men and women, about 0.8 percent Even after adjusting for occupation and industry, differences in observable socioeconomic characteristics between the two groups generate only a 7.6 percent wage gap. What is this Oaxaca decomposition missing? Labor market experience. Women tend to have kids and drop out of the labor market. By the late 1980s, the typical woman worked only 71 percent of her potential years whereas men worked 93 percent.

Labor market attachment If drop out of labor market, lower payoff to human capital investment Lower gain in wages due to experience Human capital depreciation Study of University of Michigan law school classes of 1973 and 1975. Fifteen years after graduation, male attorneys earned $141,000 annually as compared to $86,000 for female attorneys. 2/3 of this wage gap is due to differences in work histories. If a female attorney worked part-time for 3 years her earnings were reduced by 17% over her lifetime.

Which came first? And what should we do? Low wages due to less LM attachment or Less LM attachment due to low wages? Are family friendly policies the answer? Are they politically feasible?

Last Discrimination Model: Bergman’s Occupational Crowding Occupational Segregation Blue tribe v. Red tribe and the hunt for berries

Economics of Specialization Becker – household economics. Specialize in what you’re good at, then trade. If women earn less, they should work at home while men work for a wage in the market.

Conclusion and the Extra Hour Assignment One of my papers One of John’s papers One of our coauthored papers Choose one, read it, discuss it.