The Criminal and Labor Market Impacts of Incarceration

A PSC Brown Bag Seminar

Michael G. Mueller-Smith

Monday, 03/07/2016, 12:00 pm.   ARCHIVED EVENT

Location: 6050 ISR Thompson St

This presentation discusses findings on the impacts of incarceration on criminal behavior and labor market activity from research using new data from Harris County, Texas. The research design exploits exogenous variation in incarceration due to defendants' random courtroom assignment. I show that two factors, multidimensional and non-monotonic sentencing, generate bias and propose a new estimation procedure to address these features. The empirical results indicate that incarceration generates net increases in the frequency and severity of recidivism, worsens labor market outcomes, and strengthens dependence on public assistance. A cost-benefit exercise finds that substantial general deterrence effects are necessary to justify incarceration in the marginal population.


Mike Mueller-Smith is a Post-Doctoral Scholar at the Population Studies Center and the Department of Economics at the University of Michigan. His research examines topics related to the economics of crime, discrimination, and public assistance programs. He is currently working on studying the household spillovers of the criminal justice system, felony disenfranchisement and safety net bans resulting from felony drug convictions. He received his Ph.D. from Columbia University in 2015 and will join the Department of Economics at the University of Michigan as an Assistant Professor in 2017.

PSC Brown Bag seminars highlight recent research in population studies and serve as a focal point for building our research community. PSC Brown Bag Archive.

Forthcoming . Past . Next

PSC In The News

RSS Feed icon

Shaefer comments on the Cares Act impact in negating hardship during COVID-19 pandemic

Heller comments on lasting safety benefit of youth employment programs

More News


Dean Yang's Combatting COVID-19 in Mozambique study releases Round 1 summary report

Help Establish Standard Data Collection Protocols for COVID-19 Research

More Highlights

Connect with PSC follow PSC on Twitter Like PSC on Facebook