Counteractive Affirmative Action: Correcting Labor Market Discrimination
presentationposted on 19.06.2017, 00:00 authored by Anthony Farmer
Minorities tend to experience higher rates of unemployment than those of white individuals (Bureau of Labor Statistics, 2017). Controlling for pre-labor market skills, data shows a wage discrepancy resulting solely from race (Antonji and Blank, 1999), which suggests that race plays a role in labor market interactions. In an attempt to understand the causal mechanisms behind this disparate treatment one must turn to the theory of statistical discrimination, which states that the combination employer prior beliefs and imperfect information leads to discriminant hiring behavior (Coate and Loury, 1993). This model of labor market discrimination creates a negative feedback loop that is self-reinforcing. This behavior leads to a higher number of unemployed minorities. This, coupled with de facto segregation leads to a phenomena known as street vice concentration. This phenomena is linked to higher rates of urban crime (Krivo and Peterson, 1996), which results in high societal costs (Kyckelhahn, 2012). The purpose of this project was to create an intervention to counteract the negative externalities of statistical discrimination in the labor market. This project proposes a tax incentive model of affirmative action that will mitigate these externalities. The model is appropriately named Counteractive Affirmative Action. The model is shown to be fully adjustable to differing employer behaviors and responses.