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The Long-Term Incarceration Consequences of Coming-of-Age in a Crime Boom

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Abstract

Objectives

We examine the relationship between incarceration rates individuals experience in their thirties and the crime conditions they experienced throughout their youth.

Methods

We employ a cross state panel data regression design to assess how the crime conditions state/birth-year cohort members experienced from adolescence through their twenties impacts their incarceration rates in their early thirties.

Results

Birth-year cohorts who experienced higher crime during adolescence had substantially higher incarceration rates in their early thirties than birth-year cohorts in the same state who experienced lower crime during adolescence. By contrast, the crime rates state/birth-year cohorts experienced during their late teens and early twenties have little systematic relationship with their incarceration rates in their thirties.

Conclusions

The crime conditions individuals are exposed to during adolescence appear to be pivotal with respect to their long-term connections with the criminal justice system.

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Notes

  1. A common response to this inability to explain is to call for a complex interactive model, whereby period affects interact with propensity explanations (Blumstein and Wallman 2006). But, these explanations have the same inherent challenges aa their parent theories.

  2. In the paper, Spelman uses a formula from criminal career research to convert arrest rates to crime rates. Given that the relevant variation in the paper actually originates from the arrest rates, we have chosen to refer to arrest rates (rather than crime rates) when discussing his paper.

  3. The same conversation about the appropriate level of aggregation has occurred at the city vs. MSA level for crime rates (Kovandzic et al. 1998), with the conclusion that the smaller level is better (city).

  4. In performing these regressions we use the ACS-PUMS weights to make these results reflective of the U.S. population.

  5. We cannot go back further as our NCRP incarceration data starts in 2000 and we are looking at incarceration rates among 30–32 year olds.

  6. As with our earlier regressions, all of these specifications are weighted by state population.

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Acknowledgements

Thanks to John Macdonald, Daniel Nagin, Robert Sampson, Herb Smith, Derek Neal, and three anonymous referees for extremely helpful feedback on this project. Also, thanks to the Lowe Institute and Claremont McKenna College for their support.

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Authors and Affiliations

  1. Robert Day School of Economics and Finance, Claremont McKenna College, Claremont, USA

    David Bjerk

  2. The RAND Corporation, Pittsburgh, USA

    Shawn Bushway

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Correspondence to David Bjerk.

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Bjerk, D., Bushway, S. The Long-Term Incarceration Consequences of Coming-of-Age in a Crime Boom. J Quant Criminol 39, 1003–1025 (2023). https://doi.org/10.1007/s10940-022-09559-4

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