Responsible researcher: Bruno Benevit
Original Title: Assortative Matching or Exclusionary Hiring? The Impact of Employment and Pay Policies on Racial Wage Differences in Brazil
Authors: François Gerard, Lorenzo Lagos, Edson Severnini, David Card
Intervention Location: Brazil
Sample Size: 22.62 million workers
Sector: Work
Variable of Main Interest: Salary
Type of Intervention: Firm policy
Methodology: OLS, IV
Summary
In economic literature, several mechanisms seek to explain the existence of income disparities. Among them, the way in which companies' hiring and salary-setting policies impact pay inequalities has been gaining attention from researchers. In this sense, this study verified how such policies explain the salary differences between whites and non-whites in Brazil. Additionally, the authors also verified how workers' observable skills explain the distribution observed for high-paying positions. The results indicated that non-white workers are less likely to work in higher-paying companies, receive lower wage premiums, and that one-third of selection into high-paying positions is not explained by selective matching of workers' skills.
Race is one of the main variables that explain the salary level of workers in different countries, even when considering educational aspects and other observed variables. According to the theoretical framework proposed by Becker (1957), each worker faces a salary determined by the market.
Recently, several authors have sought to associate company-specific differences with the occurrence of wage disparities. According to the authors, this dynamic could be explained by the market power of firms, given by a monopsony relationship in establishing workers' salaries. Thus, firms in sectors with greater demand for qualified workers set higher salaries to attract them.
In this sense, wage inequality will depend on two factors: (i) the extent to which higher-wage companies employ whites and non-whites differently – a classification effect between companies –, and (ii) the relative size of wage premiums offered by a given company to different racial groups - a relative wage-setting effect.
Several studies present evidence on the presence of favoritism according to race during the worker selection process, for minorities and non-minorities (ÅSLUND; HENSVIK; SKANS, 2014; GIULIANO; LEVINE; LEONARD, 2009). Similarly, the literature indicates a large underrepresentation of the non-white population in high-paying positions in the United States and Latin American countries (GERARD et al. , 2021).
Brazil has a colonial history marked by African slavery, with three racial groups recognized: whites, browns and blacks. The abolition of slavery in Brazil occurred late in 1888, and the subsequent period was marked by the absence of legal segregation as occurred in the United States and South Africa (GERARD et al. , 2021).
Despite the absence of racial segregation policies and considerable racial miscegenation, socioeconomic inequality between whites and non-whites has always been marked in Brazilian society. Efforts to change this scenario on the part of the Brazilian state began with the 1988 Constitution and the establishment of anti-racial discrimination laws between the end of the 80s and the beginning of the 90s.
Even with the adoption of affirmative action policies and the implementation of the Racial Equality Statute at the beginning of this century, bringing greater prominence to the problem of racial inequality in Brazil, the disparities between whites and non-whites in the country are still notable in several segments and comparable to that of other Latin American countries.
According to data from the National Household Sample Survey (PNAD), the population of workers between 25 and 54 years old is made up of 50% white, 42% mixed race, and 8% black. In the Southeast, the most developed and populous region of the country, the proportion of whites and mixed race is close to 58% and 33%, respectively. In terms of employment rate, approximately 43% of men and 25% of women are employed in the non-agricultural private sector in Brazil. In the Southeast, this rate varies between 47% (whites) and 51% (blacks) for men and between 23% (browns) and 27% (whites) for women. Regarding education, the racial difference between white and non-white men is approximately 1.6 years of schooling, and 1.25 years of schooling among women.
PNAD data also indicate that the salary difference between whites and non-whites varies between 27% and 33% when considering only state and year effects, and between 11% and 13% when workers' experience and education are also considered. This difference is higher in the Southeast region, and also when considering only the most educated workers.
The main analysis of this article used data contained in the Annual Social Information List (RAIS), which provides longitudinal data on the characteristics of formal workers in Brazil. For the main analysis, data on workers from the Brazilian Southeast between 25 and 54 years old were considered, covering the period from 2002 to 2014.
RAIS information is collected from annual information submitted by companies to the Ministry of Labor about all employees who were on the payroll in the previous year, including their hire and dismissal dates, average monthly earnings during the year, monthly earnings in December, contracted hours, age, gender, education and race. The structure of the RAIS data is similar to that presented in the PNAD.
To assess the effect of firm-specific hiring and wage setting policies on wage inequality between whites and non-whites in Brazil, this study estimated two-way fixed-effect ordinary least squares (OLS) models to capture each firm's wage premium. To this end, a counterfactual exercise was carried out assuming the absence of racial discrimination in hiring and salary definition (between the same company). The method assumes the plausibility of the exogenous mobility condition.
The study's base model considers the theoretical framework proposed by Abowd, Kramarz and Margolis (1999) to estimate the logarithm of the hourly wage of workers in a given race-gender group and period. The model considers invariant personal characteristics of workers, the firm-specific wage premium for a given race-gender group, and variable characteristics (e.g., time and experience fixed effects). To establish the bidirectional fixed effect model, the sample used only considers observations in firms with the presence of workers from both groups.
To correct the possible bias arising from network between white and non-white workers, the authors separately estimate the fixed effect of workers considering the effects of firms on this variable using the OLS and instrumental variable (IV) methods. For IV, the effect of the firm considering the same gender and the opposite race group was used as an instrument.
The study also presents a series of analyzes decomposing the two-way fixed effect model to identify specific sources and effects. Decomposition approaches seek to identify the impacts of the effects of each individual and firm on wage inequality, comparing the results of the base model to the usual Mincerian wage determination model and verifying possible effects of selective matching. The effects of skill matching were also verified using the same counterfactual approach previously described and the size of these effects was checked for different quantities in the distribution of workers' personal effects.
Finally, the study also presents a series of robustness analyzes verifying the adequacy of the models, changing their specifications and verifying the effects found considering the subsample for the Brazilian Northeast region.
The results of the main analysis indicated that the difference in wage premiums paid within the same firms explained approximately 20% of the variation in hourly wages for the four race-gender groups. In other words, the income associated with the average premiums of the explained firms is higher compared to non-whites, occurring for both men and women. Furthermore, it was identified that 5% to 6% of the racial wage gap is explained by firm-specific effects, that is, wage differences practiced within the same company.
When evaluating the reasons for the distribution of worker groups among firms, evidence was also found of a strong impact of selective skill matching for workers in all groups. Firms that pay 10% higher wages have workers who earn 5-8% more in any given workplace, explaining approximately 18% of the wage inequality between whites and non-whites.
The results of the estimates considering the distributions of workers' skills indicate that around two thirds of the effect of the distribution of groups between firms is explained by selective matching by skills (12% of total inequality). The other one-third (6-8%) represents the residual portion not explained by skills, incorporating discriminatory hiring and retention policies. Additionally, non-white workers with greater skills presented a greater penalty for the portion not explained by skills.
In this article, the authors verified how firms' salary and hiring policies influence salary inequality between whites and non-whites in Brazil. To this end, the authors verified how workers from different racial groups and genders are distributed among firms with different levels of salary premiums and whether firms establish their selection and remuneration criteria adopting neutral criteria (education, experience and personal skills).
The results of this article indicate that most of the wage difference between whites and non-whites in Brazil is explained by the educational level and personal skills of workers. However, a third of the distribution of non-white workers among firms is not explained by these factors. Additionally, it was identified that the effect not explained by observable factors is greater for non-white workers with higher qualifications. This evidence highlights that a significant portion of wage inequality in Brazil can be associated with discriminatory practices on the part of firms, reinforcing the need for policies aimed at reducing racial inequalities in the country.
References
ABOWD, JM; KRAMARZ, F.; MARGOLIS, DN High Wage Workers and High Wage Firms. Econometrica , v. 67, no. 2, p. 251–333, mar. 1999.
ÅSLUND, O.; HENSVIK, L.; SKANS, ON Seeking Similarity: How Immigrants and Natives Manage in the Labor Market. Journal of Labor Economics , vol. 32, no. 3, p. 405–441, Jul. 2014.
GERARD, F.; LAGOS, L.; SEVERNINI, E.; CARD, D. Assortative Matching or Exclusionary Hiring? The Impact of Employment and Pay Policies on Racial Wage Differences in Brazil. American Economic Review , vol. 111, no. 10, p. 3418–3457, 1 Oct. 2021.
GIULIANO, L.; LEVINE, DI; LEONARD, J. Manager Race and the Race of New Hires. Journal of Labor Economics , vol. 27, no. 4, p. 589–631, Oct. 2009.
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