H. Gregg Lewis Prize
研究了美国“禁问犯罪记录”政策对年轻低技能黑人和西班牙裔男性就业的意外负面影响，发现政策导致就业率下降，且影响随劳动力市场状况变化。
Previous articleNext article FreeH. Gregg Lewis PrizePDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreThe H. Gregg Lewis Prize for the best paper published in the Journal of Labor Economics during 2020–21 has been awarded to Jennifer Doleac and Benjamin Hansen for “The Unintended Consequences of ‘Ban the Box’: Statistical Discrimination and Employment Outcomes When Criminal Histories are Hidden,” which appeared in the April 2020 issue of the Journal.Individuals with criminal records are severely disadvantaged in the labor market, and black men with such histories are particularly disadvantaged. Various US jurisdictions have adopted ban the box (BTB) policies intended to prevent employers from using criminal histories to screen applicants, in part to reduce racial disparities. However, when employers cannot access such information, they may rely on correlates of criminal history, most notably race and sex, thereby increasing racial and ethnic disparities. The authors use variation in the timing of state and local BTB policies to identify the effect of such policies on the employment of young black and Hispanic men with less than a college degree. In their preferred specification, they find that BTB reduces the employment of young, low-skilled black men by 3.4 percentage points and young, low-skilled Hispanic men by 2.3 percentage points. Strikingly, these effects are smaller when the labor market is tighter and when the respective minority group comprises a larger proportion of the labor force. In addition, the authors find evidence that employment shifts toward groups with a lower proportion of individuals with criminal records: older black men, older Hispanic women, and white men. The authors argue that their results are consistent with employers engaging in statistical discrimination when they cannot obtain information directly on job applications.The committee selected this paper because the empirical work is well executed, the results have clear policy implications, and the article is among the most highly cited of those published in JOLE in the last two years. The authors’ analysis shows the importance of fully considering the implications of social policies on all affected individuals. BTB policies are intended to help the ex-offender population acquire jobs but may instead put a larger minority population at an employment disadvantage by increasing employers’ reliance on statistical discrimination. The paper goes beyond estimating the causal effects of such policies by investigating how they vary regionally and with local labor market conditions. The authors also examine which groups benefit when employers substitute away from younger, low-skilled black and Hispanic males, and they find the evidence consistent with statistical rather than taste-based discrimination. This paper contributes to an important literature showing how policies that suppress information (e.g., criminal records, drug tests, credit histories, health status, educational testing, and employment histories) can have unintended consequences. In recent decades, the quantity of information about individuals that is stored and made publicly available has grown massively. Policies regulating access to and use of these data are likely to be increasingly important. Previous articleNext article DetailsFiguresReferencesCited by Journal of Labor Economics Volume 40, Number 3July 2022 Published for the Society of Labor Economists, Economics Research Center/ NORC Article DOIhttps://doi.org/10.1086/720635 Views: 1218Total views on this site © 2022 The University of Chicago. All rights reserved.PDF download Crossref reports no articles citing this article.