Wage Discrimination in the US Labor Market - Statistics Project Example

Wage Discrimination in the US Labor Market Introduction Discrimination on various fronts has been a hot debate in the US since the end of slave trade and in the years following the subsequent passage of the law abolishing slave trade. Despite the progress made in ensuring equity among all races in the US, substantial gaps remain in the market wages of African-American males and females compared to those of white males and females. There are sizable wage gaps for Hispanics and other minority tribes as well. This paper attempts to find out if there were any wage differentials between whites and blacks in California in year of 2012. The sample size is 4492. The paper will also investigate possible reasons for the disparity in earnings- whether it is due to skills or discrimination. Regression models will be used to analyze the role of race in wage differentials. We then review the principle models of racial discrimination in the labor market and discuss their ability to explain the observed differences. When possible, the paper will also look for additional models derived from economic theories and ask whether those predictions are consistent with the data used for this study. Background Information Decades of racial and gender studies have led some investigators and policymakers to believe that discrimination occurs in the US labor market to higher magnitude than is known today. Indeed, in the US, blacks have lower earnings in comparison to whites and are under-represented in jobs involving interaction with clientele (Barrow 15). The wage gap between whites and blacks is substantial in the US, and has been a significant concern among policymakers and for the last five decades. Some people have pointed out that this perceived gap is due to racial differences in skills. However, even when individual characteristics in human capital, ability, or other market productivity traits are controlled, statistical analyses show a significant wage gap between whites and blacks. The evidence points to an important role for labor-market discrimination in producing the residual earning gaps. Discrimination has been observed to be not only racial, but it is also as a result of gender. Women are paid less than their male colleagues of equal academic and professional qualifications. Wages differences between men and women are explained by the differences in the technical fields commonly studied by men. Partially, wage disparities among gender explained by occupational segregation between women and men. Studies have found that averagely, men with equal academic and training experience earn 10 % more than women earn. Labor market discrimination translates into lower employment prospects and wages for minority workers through hiring and wage-setting practices. As highlighted by Becker (22), discrimination may be due to employers partiality during recruitment, or to customers dislike towards minority employees. In the former case, employers hold a taste for discrimination, implying that there is a disutility to employing minority workers. In the latter case, employers internalize their white customers disutility of purchasing services/goods from a minority worker. The type of discrimination is important to know, since customer discrimination is restricted to occupations that involve contact with the public, while employer discrimination may affect all jobs. Unlike employer discrimination, customer discrimination also persists over time and is not easy to control. From the research, it is found that wage discrimination is not only gender based but also racial. Like women, black Americans with equal education and occupational experience receive 10 % lower wages than their white counterparts (Rodgers 67). However, it is noted that occupational segregation is more dominant by gender than by race. The rate of unemployment is twice among the blacks as compared to the whites in the United States. Levels of unemployment are also significantly lower as compared to whites. Models to be used The paper will use a multiple analysis procedures. The first procedure is known as market signaling. Signaling refers to the idea that one party credibly conveys some information about itself to another party (referred to as the principal). In the job-market signaling model, (potential) employees send a signal about their ability level to the employer by acquiring certain education credentials. The informational value of the credential comes from the fact that the employer assumes it is positively correlated with having greater ability. Spencer argues that through signaling, employees can contribute to wage differentials between blacks and whites due to their own intrinsic judgments that deem one group as more superior that the other. Using this model, a regression analysis will be conducted between the independent variable- wage and three explanatory variables: race, experience and school. The regression equation will follow the format shown below: wage = β0 + β1 black + β2 experience + β3 school The variables have been controlled as follows: age has been controlled between18-65 because 18 is the legal age to start working full time while 65 is age for retiring, wage has been controlled to more than $0 since the employees have to be earning something to make it possible to analyze wage differences, further, they must be earning between $8 - $100 per hour because $8 is the minimum wage in California for 2012, and they must have been working in California state in 2012. The second model to be used is the “Mincer” wage equation that will help in getting the earnings profile which allows an investigator to calculate the life time earnings for similar status of white and blacks. The models are as shown below: The equation for black: wage = β0 black + β1 age + β2 age2 The equation for black is: wage = β0 white + β1 age + β2 age2 For the two equations, the only control was that only persons who have studied up to high school were include in the analysis to keep similar skills cross black and white. The third model used for the paper is a method that was developed by Ronald Oaxaca (Oaxaca 702). This model avers that discrimination occurs whenever the relative wages of whites exceeds the relative wage that would have prevailed if whites and blacks were paid according the same criteria. The model proposes that to explore the levels of discrimination, a discrimination coefficient (D) must be obtained to help in calculations. D is obtained as follows: D= {Wm/Wf – (Wm/Wf)0}/{Wm/Wf}0 Where Wm/Wf = the observed white-black ratio; {Wm/Wf}0 = the white-black ratio in the absence of discrimination. Results and Discussion A regression using the signaling results into the output shown in Fig. 1. The regression equation is: Wage = -17.673 – 3.88 black + 2.47 school + 0.72 Exper – 0.009 Exper2 From this equation, it is seen that for a black person, the wage decreases by 3.88 units as compared to a white person. Hence, the equation clearly shows that when confounding factors such as age, education level, and minimum wage are controlled, whites still earn significantly higher wages than blacks. However, this test is not good enough since it only accounts for 23% of the variability in the data (R-squared = 0.2363, α = 0.05). Hence, the results from this analysis cannot be fully accepted and the data has to be subjected to further analysis. Further, the equation shows that for every additional year of education, wage increases by 2.47 units. This finding is supported by numerous studies. Not only do persons with higher academic credentials earn more, but they are also more likely to get employed as well (Sill, 2002). The second analysis process was used to calculate life earnings. The resulting regression analysis is shown in Fig 2 and Fig. 3 for blacks and whites respectively. The formulas to calculate life earnings for both races are shown below: For blacks: Life earnings = -44422 + 4082.64 Age – 37.83 Age2 For whites: Life earnings = -46680 + 3981.64 Age – 39.74 Age2 It is observed that for every additional year of work, the life earnings of a black persons increase by 4082 (F-statistic= 9.33, R-Squared = 0.0775) units while that for a white person increases by 3981 units (F-statistic= 159.59, R-Squared = 0.0649). Using the “Micer” equation: 65 ʃ β0 + β1age + β2age2 18 (β0age + (β1age2)/2 + (β2age3)/3 ) |65 18 (β065 + β1(65)2/2 + β3(65)3/3) - (β018 +β1182/2 + β2(18)3/3) for a white person 65*-44422.78 + (65^2)*4082.641/2 + (65^3)*-37.8334/3-(18*-44422.78 + (18^2)*4082.641/2 + (18^3)*-37.8334/3)= $2485536.2 estimated life time earnings for white between age 18-65 for black: 65*-46680.8 + (65^2)*3981.151/2 + (65^3)* -39.7435/3 -(18*-46680.8 + (18^2)*3981.151/2 + (18^3)* -39.7435/3 )= $2010312.6 2485536.2 - 2010312.6 = $475223.50 the lifetime annual earnings difference between white and black. The plot in Fig. 4 shows that a white will have a significantly higher total life earnings over the years in which both sets of employees are employed. In the final analysis, an analysis is conducted to test if that wage differential because of skills differences or discrimination. It is observed that holding other factors constant, whites are less likely to be discriminated against (F-value= 443.43) as compared to blacks (F-value= 185.20). Conclusion The study was conducted to find out whether there is racial discrimination in the US labor market with regard to wages paid. From the three different analyses conducted, whites are consistently shown to earn more even after holding factors that might affect the outcome constant. Black employees are more likely to be discriminated against, have a lower lifetime earnings as compared to whites, and will earn less for every year spent studying. Consequently, it is concluded that there is indeed racial discrimination in the US labor market. Works Cited Barrow, Chris W. Globalisation, Trade Liberalisation, and Higher Education in North America. Dordrecht: Kluwer Academic Publishers, 2003. Print. Becker, Gary S. Investment in Human Capital. The Journal of Political Economy, 70(5): 1962, 9-49 Oaxaca, Ronald. Male-Wage Differentials in Urban Labor Markets. International Economic Review, 14(3): 1973, 693-709. Sill, Keith. Widening the Wage Gap: The Skill Premium and Technology, Federal Reserve Bank of Philadelphia, Business Review, Fourth Quarter 2002, pp. 25-32. Read More