Essays at the Intersection of Labor and Crime Economics

Abstract

This series of papers focuses on understanding the decision-making processes and incentive systems facing key decision-makers in the U.S. criminal justice system and labor market, as well as how those decisions interact with systemic inequities. Although the primary lens is labor economics, these questions and the tools and theories needed to carefully answer them intersect with behavioral and experimental economics, as well as with other disciplines like psychology and political science.

The first chapter examines the distortionary effects of reality TV shows that follow police on police officers’ arrest decisions and on viewers’ attitudes and beliefs about police. Television shows with police officer protagonists are ubiquitous on American television. On these shows, criminals are nearly always apprehended. However, I find that this is a distortion of reality, as crimes mostly go unsolved and police officers infrequently make arrests. What does the omnipresence of this genre mean for the general public’s conception of police, for the practice of policing, and for the communities being policed? In this chapter, I use department-level and officer-level data to find that arrests for low-level crimes increase while departments film with reality television shows. These arrests do not meaningfully improve public safety and come at the cost of the local public’s confidence. I then document that these shows – particularly their overrepresentation of arrests – improve non-constituent viewer attitudes towards and beliefs about the police. I consider the implications for police accountability and criminal justice reform.

The second chapter examines whether employers’ beliefs update rationally in response to noisily accurate information about racial gaps in productivity. I find that employers respond to signals based on their own implicit biases and the signals’ consistency with stereotypes. In the canonical economics literature on discrimination, it is assumed that statistical discrimination based on inaccurate beliefs will not persist since agents have clear incentives to update as Bayesians based on accurate information. However, if beliefs about group productivity are driven by bias rather than by an agnostic lack of information, agents may be resistant to updating in the face of accurate information that contradicts stereotypes. In an experiment, I find that employers’ response to information about the labor market productivity of Black and White workers is a function of their implicit biases. Employers with stronger implicit biases against Black workers update their beliefs more in response to signals that are consistent with their biases (i.e. that imply the racial gap in productivity is higher than it is) than they do in response to signals that are inconsistent (i.e. that imply the racial gap in productivity is smaller or even reversed). This result suggests that providing accurate information about the labor market productivity of historically stigmatized groups may not be sufficient on its own to correct inaccurate beliefs or end inaccurate statistical discrimination.

The third chapter examines what employers’ background check adjudicators see on applicants’ criminal records and how this affects the hiring process. My co-authors & I find that criminal records of any kind - even related to crimes for which the applicant has not been found legally guilty – significantly affect their employment probability. We use a large administrative dataset containing 65 million job applicants’ criminal histories. Fourteen percent of applicants in our data have a legally reportable criminal record. We document that most charges accrue to individuals with no prior criminal history and that most applicants’ records consist only of misdemeanors (54%). We also show that many charges (45%) are non-convictions (crimes of which the candidates are not legally guilty). Firms respond strongly to all criminals, but especially to felony records and violent records, ending the hiring process by issuing an “adverse action notice” over 60% of the time for applicants with either of these record types present. Systemic differences in criminal justice contact by race and gender lead to relatively higher rates of hiring discontinuation for Black and male applicants. Finally, we show that rates of adverse action notices issued to candidates with criminal records have fallen in recent years, in line with “fair chance” hiring practices, but gaps remain.