Christopher Walters, Berkeley

Department seminar. Christopher Walters is an Associate Professor at University of California, Berkeley. He will present a paper entitled "Monitoring discrimination with experimental audits: some possibility results" co-authored with Patrick Kline.

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Christopher Walters

Abstract

We study the ability of correspondence studies utilizing fictitious applicants to detect illegal discrimination by individual employers. Employers violate US employment law if their propensity to call applicants back depends on protected applicant characteristics such as age, race, or sex. Working within a non-parametric random effects framework, we establish identification of higher moments of the effects of protected characteristics on callback rates as a function of the number of fictitious applications sent to each job ad. Applying our results to three experimental datasets, we find evidence of significant employer heterogeneity in discriminatory behavior. Surprisingly, discrimination tends to be uncorrelated or positively correlated with overall callback rates. Fitting a range of parametric models to the experimental data in Nunley et al. (2015), we estimate that 17% of employers discriminate on the basis of race. Our estimates imply that an experiment sending 10 applications to each job would enable accurate detection of 7.5% of discriminators while falsely accusing fewer than 0.3% of non-discriminators. Sequentially auditing jobs and choosing application characteristics optimally roughly doubles the number of discriminators caught while cutting the number of applications that need to be sent in half. Our results suggest illegal labor market discrimination can be reliably monitored at relatively low cost.

Host: Edwin Leuven

Published Dec. 19, 2018 1:41 PM - Last modified Feb. 21, 2019 11:37 AM