Decarceration, Sanction Severity and Crime: Causal Analysis of Proposition 47 and Property Crime in Los Angeles

Abstract

Decarcerative policies aim to decrease rates of incarceration primarily through lessening the severity of criminal sanctions. These policies have proliferated in recent years as states looked to reduce correctional expenditures and begin to reverse decades of growth in incarceration. Yet, there are relatively few empirical studies that examine decarcerative policies. This study evaluates the impact of California’s Proposition 47 (Prop 47), which reduced penalties for a variety of low-level offenses. We utilize a range of causal methods (difference in difference, triple difference, and synthetic control group analysis) to estimate the effects of the policy on property crime rates in the Los Angeles; and to examine the potential mechanisms driving these effects. We find robust evidence that Prop 47 increased property crime in Los Angeles, and this finding emerges across our methodological approaches. We discuss our findings in the context of a growing body of literature on Prop 47; and conclude that the policy was effective in limiting crime rate increases to anticipated and low-level offenses while achieving its primary aim of decarceration.

Keywords:

• Decarceration
• causal inference
• deterrence
• property crime
• shoplifting

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Matthew Renner

Matthew Renner is a doctoral candidate in Criminology, Law & Society at The University of California, Irvine. His research focuses on evaluating criminal justice policy, policing, and quantitative research methods.

Bradley Bartos

Bradley J. Bartos is an Assistant Professor in the School of Government and Public Policy at the University of Arizona. His research leverages natural variation in criminal justice and social policy and employs quasi-experimental time-series designs to evaluate the impact of policy changes on crime, injury, and mortality trends. Dr. Bartos is an author of Design and Analysis of Time Series Experiments (Oxford University Press, 2017) and Interrupted Time Series Analysis (Oxford University Press, 2019).