The Effect of Statistical Discrimination on Black-White Wage Inequality: Estimating a Model with Multiple Equilibria

Author(s):  
Andrea Moro
2017 ◽  
Vol 17 (1) ◽  
Author(s):  
Julien Picault

AbstractThis article presents a model to analyze the effects of first and second-moment statistical discrimination on the labour market. Second-moment statistical discrimination occurs when risk-averse managers make decisions regarding wage and hiring based on productivity variances. We provide a framework exploring managers’ discrimination based on differences in average productivity and in variance of productivity. Furthermore, since discrimination is composed of two types (wage and hiring discrimination), our model allows for the interdependence between hiring practices and wages. Using our model, we examine the effects of various anti-discrimination policies along with changes to the labour market structure. We show that managers’ behaviour may be driven by anti-discrimination policies and labour market structures. A firm reduces hiring when required to implement anti-discrimination policies to address wage inequality. A firm applying policies to promote employment equity must stimulate minority participation. A change in labour market structure does not alter the efficiency of policies promoting employment equity, but it does alter the efficiency of policies aimed at reducing wage differences.


2020 ◽  
Vol 17 (2) ◽  
pp. 349-356
Author(s):  
Kari Kristinsson ◽  
Margret Sigrun Sigurdardottir

Research on immigration has emphasized the role that statistical discrimination plays in hiring decisions. A better understanding of how immigrants overcome this type of discrimination might lead to better interventions to improve their labour market participation. In this paper, we use qualitative interviews to examine how immigrants can reduce statistical discrimination by signalling their similarity to employers in their job applications. Specifically, we find that immigrants who demonstrate signal similarity to employers in the type of education, job experience and religion tend to reduce their statistical discrimination by employers. We suggest how further research can build on these results to provide possible tools for immigrant integration.


The objective of this study was to empirically evaluate the returns to education of rural and urban labour markets workers in Tamil Nadu using the IHDS data with appropriate Econometric models. First, the present study estimated the earning functions of the rural and urban market's workers by OLS technique and standard Mincerian earning functions. Secondly, the quantile regression method was also used to examine the evolution of wage inequality. The findings of the study showed that the effects of education and experience on the log of hourly wages were positive, and these coefficients were statistically significant. The returns to education increased with the level of education and differed among the workers of rural and urban labour markets. The results showed that the rates of returns to primary, middle and higher secondary were higher in the urban market, whereas those of secondary and graduation were higher in the rural market. The study revealed that the effect of education was not the same across the rural and urban wage distribution. The rate of returns differed considerably within education groups across different quantiles of the wage distribution.


2010 ◽  
Author(s):  
Claudio Fernández Macor ◽  
Néstor Perticarari ◽  
Carlos Beltrán

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