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August 2nd, 2016

Some released prisoners cost municipalities millions by reoffending, but don’t have to

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Estimated reading time: 5 minutes

Blog Admin

August 2nd, 2016

Some released prisoners cost municipalities millions by reoffending, but don’t have to

0 comments

Estimated reading time: 5 minutes

Michael Osterman 80x108Joel Caplan 80x108One major consequence of the rising prison populations seen in the past 30 years has been the growth in the number of prisoners released into American communities every year, many of whom go on to commit further crimes. These crimes come with a cost to society. Using New Jersey as a case study, Michael Ostermann & Joel M. Caplan estimate that reoffending within three years of release was valued by the public at almost $6 billion, with an average cost of $80,000 per offense. These costs were also concentrated in the state’s most economically and socially disadvantaged areas. In light of these findings, they argue that not only is incarceration ineffective in cutting the costs of crime, but that policymakers should focus their rehabilitation efforts on those they determine are most likely to re-offend.

Incarceration costs in the United States have experienced unprecedented growth as prison populations have skyrocketed since the mid 1980’s. This growth means that hundreds of thousands of formerly incarcerated individuals are released into American communities every year. However, unlike the costs associated with locking up America’s criminals, the price tag associated with the recidivism patterns of former prisoners has received little attention by scholars and public policy makers.

Recent research indicates that the costs of crimes committed by former inmates are very high, dwarfing the costs of other high priced social institutions, and are concentrated in highly disadvantaged areas.  In addition, policy-relevant factors of recidivism such as time served in prison are not predictive of the costs of recidivistic behavior patterns of former inmates.  Thus, it is important for public policy makers to conceptualize recidivism management as a fiscal rather than a purely social welfare policy, and to accentuate the rehabilitation of former prisoners, especially those that are assessed as high risk.

Our research uses established indicators stemming from a nationally-representative survey of an average American’s willingness to pay an amount of money between US$25 and US$225 to prevent 1 in 10 of certain crime types (e.g., burglary, serious assault, robbery, rape, murder, etc.).  We attached costs to the most serious offense for arrest events that occur within three years of an individual leaving prison in the state of New Jersey from 2005 to 2007.  We then built statistical models to predict the average costs of arrests in order to explore the contribution of established predictors of recidivism (e.g., age, gender, race, concentrated disadvantage of the area to which an individual returns, prior offenses, time served in prison, risk level, etc.) to the average price tag of the recidivistic behaviors of former prisoners.  In addition, we constructed maps to demonstrate the geographic concentration of the monetary costs of crimes committed by former prisoners across the state’s 21 counties as well as its most populated municipalities.

Overall, about 56 percent of the former inmates were rearrested within three years of release from prison – and the public’s willingness to pay to have these crimes prevented was almost US$6 billion.  The average cost of an individual former inmate’s rearrests were approximately US$80,000, with the first arrest event costing approximately US$18,000.  These costs were incurred after the state had already invested an average of US$137,000 to incarcerate the individual for an average of approximately three years.

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Costs of crimes were highly concentrated in the state’s most economically and socially disadvantaged counties and municipalities.  The state’s three most disadvantaged counties (as measured by an empirical index constructed through the use of decennial Census data) had average costs of recidivism that were two standard deviations higher than the average of all counties.  The municipality with the highest crime rate experienced approximately US$837 million of crimes across the three release cohorts – which represent more than twice the costs of crimes within the state’s two most populated counties.  These enormous recidivism costs were linked to this municipality despite the high-crime city having roughly less than 5 percent of the population size of these two highly populated counties.  Our predictive models indicated that time served and criminal history were not predictive of costs of crimes, and that those assessed as low risk for recidivism went on to commit crimes that cost approximately half as much as those that were classified in higher risk categories.

Several different policy implications can be gleaned from this research.  It is important for policy makers to have a sense of the monetary costs of recidivism, these costs are enormous, and, as a result, it is of paramount importance to pursue empirically sound avenues to attempt to curb such costs.  A strong empirical base has consistently demonstrated that the best rehabilitative “bang for the buck” is realized by concentrating resources on those people that are assessed as having the highest likelihood of committing further crimes.  Our research demonstrates that the recidivism patterns of high risk individuals cost substantially more than their low risk counterparts, and that these costs are highly concentrated in areas that are the least capable of adequately dealing with these sorts of issues.  Further, policy-relevant factors of recidivism like time served are not predictive of post-release costs of crimes.  In other words, incarcerating an individual for a longer period of time is not associated, on average, to having a lower or higher cost to their re-offending if it occurs.

With the pairing of established high costs of incarceration, high recidivism rates mostly among a small fraction of released former prisoners, and enormous monetary costs associated with the recidivism of former prisoners – it is readily apparent that attempting to use incarceration as a primary justice strategy to avoid costs is a fool’s errand.  Concerted efforts must be made to attempt to rehabilitate highest-risk individuals by devoting resources to this group with the most effective and well-established best-practices (and accountability structures must be built for those charged for the pursuit of such efforts).  By serving this group with rehabilitative resources, substantial cost savings can likely be realized at local levels with areas that exhibit the most social deprivation realizing the greatest benefits.  While the challenges ahead for justice systems and policy makers are substantial, communicating results according to dollars and cents may greater incentivize decision makers to take meaningful actions to address the recidivism of former inmates in cost-effective, sustainable and fairer ways. 

This article is based on the paper How Much Do the Crimes Committed by Released Inmates Cost? in Crime & Delinquency.

Featured image credit: Curtis Perry (Flickr, CC-BY-NC-SA-2.0)

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Note:  This article gives the views of the author, and not the position of USAPP – American Politics and Policy, nor the London School of Economics.

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About the authors

Michael Osterman 80x108Michael Ostermann – Rutgers University
Michael Ostermann is an Assistant Professor and Undergraduate Program Chair of the Rutgers School of Criminal Justice.  His research interests primarily lie within the fields of corrections and reentry and how they intersect with public policy.

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Joel Caplan 80x108Joel M. Caplan – Rutgers University
Joel M. Caplan is an Associate Professor at the Rutgers University School of Criminal Justice and deputy director of the Rutgers Center on Public Security. His research focuses on risk assessment, spatial analysis, and policing.

About the author

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Posted In: Joel M. Caplan | Justice and Domestic Affairs | Michael Ostermann

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