THE CRIMINAL AND LABOR MARKET IMPACTS OF INCARCERATION

This paper investigates the preand post-release impacts of incarceration on criminal behavior, economic wellbeing and family formation using new data from Harris County, Texas. The research design identifies exogenous variation in the extensive and intensive margins of incarceration by leveraging the random assignment of defendants to courtrooms. I develop a new data-driven estimation procedure to address multidimensional and non-monotonic sentencing patterns observed in courtrooms. My findings indicate that incarceration generates modest incapacitation effects, which are offset in the long-run by an increased likelihood of defendants reoffending after being released. Additional evidence finds that incarceration reduces post-release employment and wages, increases take-up of food stamps, decreases the likelihood of marriage and increases the likelihood of divorce. Based on changes in defendant behavior alone, I estimate that a one-year prison term for marginal defendants conservatively generates $56,200 to $66,800 in social costs, which would require substantial general deterrence in the population to at least be welfare neutral. Keywords: incarceration, recidivism, labor market outcomes, family formation, monotonicity JEL: J24, K42, J62 ∗Department of Economics, University of Michigan (email: mgms@umich.edu). I would like to thank Cristian Pop-Eleches, Bernard Salanié and Miguel Urquiola for their advice and support. I also benefited from conversations with Doug Almond, Sandra Black, Scott Cunningham, Keshav Dogra, Keith Finlay, Colin Hottman, Ju Hyun Kim, Christopher King, Wojciech Kopczuk, Ilyana Kuzmienko, Steve Levitt, John List, Jens Ludwig, Maya Rossin-Slater, Aurelie Ouss, Emily Owens, Kevin Schnepel, Hyelim Son, Patrick Sun, and Lesley Turner. I would also like to thank the participants in the NBER Summer Institute and Columbia Applied Microeconomics Workshop for their comments. I am particularly indebted to the staff at the Ray Marshall Center who have generously hosted my research in Texas. This project would not have been possible without the approval of the Harris County District Clerk, the Harris County Sheriff’s Office the Texas Department of Criminal Justice, the Texas Department of Public Safety, the Texas Health and Human Services Commission, and the Texas Workforce Commission. Funding for this project was provided by the National Science Foundation (SES-1260892). 1 2 MICHAEL MUELLER-SMITH The United States currently has the highest incarceration rate in the world (Walmsley [2009]), a consequence of three decades of dramatic growth in the prison population since the late 1970s (Carson [2013]). Over this same time period governmental expenditures on police protection, judicial and legal systems, and corrections also surged (Bureau of Justice Statistics [1980] and Kyckelhahn [2013]). Recent estimates indicate that the annual U.S. correctional population included over 7 million adults (Glaze and Herberman [2013]), and combined federal, state and local expenditures on justice-related programs topped $260 billion per year. Despite the reach and cost associated with these changes to criminal justice policy, causal evidence on how this use of incarceration has impacted the population remains scarce (see Donohue III [2009]). To help address this gap in the literature, I investigate the impacts of incarceration using original data from Harris County, Texas. The new data is comprised of over 2.6 million criminal court records accounting for 1.1 million unique defendants. It captures the universe of misdemeanor and felony criminal charges between 1980 and 2009 regardless of final conviction status. It has also been linked to state prison and county jail administrative data, unemployment insurance wage records, public assistance benefits, marriage and divorce records as well as future criminal behavior. Taken together, the combined data permits a broad range of policy-relevant analysis, promoting a better understanding of the potential mechanisms underpinning the treatment effects and providing for a more comprehensive cost benefit analysis. The research design leverages the random assignment of criminal defendants to courtrooms as a source of exogenous variation in both the extensive and intensive margins of incarceration. The courts are staffed by judges and prosecutors who differ in their propensity to incarcerate. As a result, which courtroom a defendant is randomly assigned to strongly predicts whether he will be incarcerated and for how long. This increasingly popular identification strategy has been used in a number of applications where judges, case workers, or other types of programs administrators are given discretion on how to respond to a randomly assigned caseload. 1Even though parole boards may adjust some sentences ex-post, my evidence indicates that the courts exert influence over actual time served. 2For studies specifically related to incarceration, see Kling [2006], Di Tella and Schargrodsky [2004], or Aizer and Doyle [2013]. For research in other fields, see Doyle [2007, 2008], Autor and Houseman [2010], Belloni et al. [2012], Munroe and Wilse-Samson [2012], Doyle et al. [2012], French and Song [2012] Maestas et al. [2013], Autor et al. [2013], Dahl et al. [2013], andDobbie and Song [2015]. THE CRIMINAL AND LABOR MARKET IMPACTS OF INCARCERATION 3 The application considered in this paper is moderately more complex than other potential uses of this research design. Sentencing takes on multiple dimensions (e.g. incarceration, fines, drug treatment, etc.) and judges display non-monotonic tendencies (e.g. a judge may incarcerate drug offenders at a relatively higher rate but property offenders at a relatively lower rate). Since failure to account for these features of the data can lead to violations of the exclusion restriction and monotonicity assumption, a new estimation procedure is developed. In this new approach, I relax the first stage equation to allow the impact of court assignment on sentencing outcomes to flexibly respond to observed defendant characteristics. Because this can generate many instruments due to the curse of dimensionality, the least absolute selection and shrinkage operator (LASSO) is used in conjunction with cross validation as a data-driven tool to achieve disciplined dimension reduction without skewing statistical testing. I then use this approach to construct instruments for each observed aspect of sentencing, not just incarceration, in order to control for court tendencies on non-focal sentencing dimensions. My empirical findings indicate that incarceration for marginal defendants is less attractive from a policy perspective than has been shown in prior work. I measure modest incapacitation effects while defendants are in jail or prison: felony defendants are 6 percentage points less likely to be charged with a new criminal offense while incarcerated. This benefit, however, is offset by increases in post-release criminal behavior: each additional year that a felony defendant was incarcerated increases the probability of facing new charges post-release by 5.6 percentage points per quarter. What is particularly concerning about these results is that the incapacitation effect is disproportionately driven by misdemeanor charges, while the post-release criminal behavior shows mainly increases in felony offenses. Partially driving this result is a pattern of former inmates being charged with new crime types. In particular, I find that former inmates are especially likely to commit more property (e.g. theft or burglary) and drug-related crimes after being released, even if these crimes were not their original offenses. In contrast with prior work, I find strong evidence that incarceration has lasting negative effects on labor market outcomes after defendants have been released. I find that each additional year of 3Prior researchers have acknowledged the potential for these features to also affect their findings, but data limitations have generally limited their ability to address these concerns in any formal way. 4 MICHAEL MUELLER-SMITH incarceration reduces post-release employment by 3.6 percent points. Among felony defendants with stable pre-charge earnings incarcerated for one or more years, reemployment drops by at least 24 percent in the 5 years after being released. Misdemeanor defendants show a small increase in take-up of cash welfare payments, and felony defendants show increases in Food Stamps benefits, which provide further evidence of lasting economic hardship post-release. The impacts of incarceration extend beyond recidivism and labor market outcomes. Incarceration appears to negatively impact family formation and stability as measured through marriage and divorce activity. While incarcerated, young felony defendants exhibit significantly lower rates of marriage that are not compensated post-release indicating a net decline in marriage rather than a temporal shift. Further supporting this conclusion, I find that divorce rates among older felons increase while in prison and post-release. Using these new estimates, I reevaluate the welfare impacts of incarceration. Because I cannot measure general deterrence effects in my research design, the cost benefit exercise is partial in nature and only accounts for the administrative expenses, criminal behavior effects and economic impacts associated with the defendant’s own outcomes. Using the most conservative estimates, I find that a one-year prison term for marginal defendants decreases social welfare by $56,200 to $66,800 of which negative impacts to economic activity account for 41 to 48 percent of overall costs. In order for this sentence to be neutral in social welfare terms, a one-year prison term for a marginal (low-risk) offender would need to deter at least 0.4 rapes, 2.2 assaults, 2.5 robberies, 62 larcenies or 4.8 habitual drug users in the general population. The remainder of this paper organized i