Labor Markets and Crime

Paper Session

Friday, Jan. 6, 2017 1:00 PM – 3:00 PM

Hyatt Regency Chicago, Crystal A
Hosted By: American Economic Association
  • Chair: Steven Levitt, University of Chicago

Rethinking the Benefits of Youth Employment Programs: The Heterogeneous Effects of Summer Jobs

Jonathan M.V. Davis
,
University of Chicago
Sara Heller
,
University of Pennsylvania

Abstract

One Summer Chicago Plus (OSC+) offers part-time summer employment supported by an adult mentor to disadvantaged youth in Chicago. The first RCT of the program (Heller 2014) finds this program reduces violent-crime arrests by 43% over 16 months. A second RCT the following summer (Heller & Davis) replicates the violence reduction and identifies potentially important heterogeneous effects. This paper, the third RCT, aims to answer why the program reduces violence. We experimentally vary one key candidate mechanism – the mentor – to separate the effect of the job from what the mentor teaches, and collect detailed information on bringing the program – which is doubling in size to 2,000 youth – to scale. In summer 2015, we randomized youth to receive the full OSC+ program (job+mentor), the same program with no mentor, or no OSC+ services (control). Within geographic blocks, we randomly allocated treatment youth across the 19 different non-for-profit partners in charge of program implementation – some experienced and some new – to explore how treatment heterogeneity is related to organizational experience. We will measure outcomes using administrative arrest, schooling, and employment records; and we will survey youth, employers, and program staff.

Local Labor Markets and Criminal Recidivism

Crystal Yang
,
Harvard University

Abstract

This paper estimates the impact of local labor market conditions on criminal recidivism using administrative prison records on four million offenders released from 43 states between 2000 and 2013. Exploiting the timing of each offender’s release from prison, I find that being released to a county with higher low-skilled wages significantly decreases the risk of recidivism. The impact of higher wages on recidivism is larger for both black offenders and first-time offenders, and in sectors that report being more willing to hire ex-offenders. These results are robust to individual- and county-level controls, such as policing and corrections activity, and do not appear to be driven by changes in the composition of released offenders during good or bad economic times.

Does "Ban the Box" Help or Hurt Low-Skilled Workers?: Statistical Discrimination and Employment Outcomes When Criminal Histories Are Hidden

Jennifer Doleac
,
University of Virginia
Benjamin Hansen
,
University of Oregon

Abstract

Jurisdictions across the United States have adopted "ban the box" (BTB) policies preventing employers from conducting criminal background checks until late in the job application process. Their goal is to improve employment outcomes for those with criminal records, with a secondary goal of reducing racial disparities in employment. However, removing information about job applicants' criminal histories could lead employers who don't want to hire ex-offenders to guess who the ex-offenders are, and avoid interviewing them. In particular, employers might avoid interviewing young, low-skilled, black and Hispanic men when criminal records are not observable, guessing that these applicants are more likely to be ex-offenders. This would exacerbate racial disparities in employment. In this paper, we use variation in the details and timing of state and local BTB policies to test BTB's effects on employment for various demographic groups. We find that BTB policies decrease the probability of being employed by 3.4 percentage points (5.1%) for young, low-skilled black men, and by 2.3 percentage points (2.9%) for young, low-skilled Hispanic men. These findings support the hypothesis that when an applicant's criminal history is unavailable, employers statistically discriminate against demographic groups that include more ex-offenders.

Ban the Box, Criminal Records, and Statistical Discrimination: A Field Experiment

Amanda Agan
,
Rutgers University
Sonja Starr
,
University of Michigan

Abstract

Recently, many cities and states have passed “Ban-the-Box” (BTB) policies, which restrict employers from asking about applicants’ criminal histories on job application forms. BTB is meant to open doors to employment for people with records, and is often presented as a means of reducing unemployment among black men, who have records at disproportionate rates. A countervailing concern is that depriving employers of individual criminal record information before the interview stage could lead them to statistically discriminate on the basis of race or other characteristics like education or employment history. We employ an audit design to investigate BTB’s effects on discrimination in initial employment decisions as well as the effects of race and criminal records on employer callback rates, sending approximately 15,000 fictitious online job applications across two jurisdictions both before and after the adoption of BTB policies. We combine this field-experimental approach with a triple-differences design that allows for causal inferences about BTB’s effects, exploiting the fact that many businesses’ applications never asked about criminal records, and were therefore unaffected by BTB. Our preliminary analysis finds that white applicants overall receive about 38% more callbacks than similar black applicants do. In addition, employers that ask about records are about 45% more likely to call back candidates without records. The criminal record effect is larger among white applicants, and white applicants without a criminal record are called back at a much higher rate than all three other groups. After BTB, the black-white callback gap nearly triples at affected businesses, after differencing out changes occurring over the same time period at similar businesses that were unaffected by BTB. The primary beneficiaries of BTB are white applicants with criminal records.
Discussant(s)
Bruno Crepon
,
CREST
Michael Mueller-Smith
,
University of Michigan
Stephen Raphael
,
University of California-Berkeley
Abigail Wozniak
,
University of Notre Dame
JEL Classifications
  • J2 - Demand and Supply of Labor
  • K4 - Legal Procedure, the Legal System, and Illegal Behavior