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  3. American Economic Journal: Economic Policy
  4. May 2019
  5. Snapping Back: Food Stamp Bans and Criminal Recidivism

American Economic Journal:
Economic Policy

ISSN 1945-7731 (Print) | ISSN 1945-774X (Online)

Snapping Back: Food Stamp Bans and Criminal Recidivism

  • Cody Tuttle
American Economic Journal: Economic Policy
vol. 11, no. 2, May 2019
(pp. 301–27)
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Abstract

I estimate the effect of access to food stamps on criminal recidivism. In 1996, a federal welfare reform imposed a lifetime ban from food stamps on convicted drug felons. Florida modified this ban, restricting it to drug traffickers who commit their offense on or after August 23, 1996. I exploit this sharp cutoff in a regression discontinuity design and find that the ban increases recidivism among drug traffickers. The increase is driven by financially motivated crimes, suggesting that the cut in benefits causes ex-convicts to return to crime to make up for the lost transfer income.

Citation

Tuttle, Cody. 2019. "Snapping Back: Food Stamp Bans and Criminal Recidivism." American Economic Journal: Economic Policy, 11 (2): 301–27. DOI: 10.1257/pol.20170490

Additional Materials

JEL Classification

  • H75 State and Local Government: Health; Education; Welfare; Public Pensions
  • I38 Welfare, Well-Being, and Poverty: Government Programs; Provision and Effects of Welfare Programs
  • K42 Illegal Behavior and the Enforcement of Law

Income Elasticity of Labor Supply

  • Posted by Robert Kaestner
  • Posted on 5/21/2019 2:23:54 PM
The loss of SNAP benefits represented about a 20% decrease in income (if SNAP benefits are fully fungible). The change in recidivism for financially motivated crimes was approximately 115%.

If labor supply effort is highly correlated with recidivism probability, these estimates imply an elasticity of labor supply with respect to income of almost 6. In fact, if probability of getting caught increases in criminal effort (illegal labor supply), which is plausible, then the estimate of 6 is too low.

This seems like an order of magnitude too high (see McClelland and Mok, CBO 2012 for a review).

How do we reconcile estimates that seem implausible with the extensive assessment of the validity of the research design presented in the paper that seems to reveal a valid design?
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