Prisons and crime: Backwards in high heels

Article, Refereed Journal
Journal of Quantitative Criminology 29.4 (2013): 649-674.

pObjectives: Prisons reduce crime rates, but crime increases prison populations. OLSbr /
estimates of the effects of prisons on crime combine the two effects and are biased towardbr /
zero. The standard solutionmdash;to identify the crime equation by finding instruments forbr /
prisonmdash;is suspect, because most variables that predict prison populations can be expectedbr /
to affect crime, as well. An alternative is to identify the prison equation by findingbr /
instruments for crime, allowing an unbiased estimate of the effect of crime on /
Because the two coefficients in a simultaneous system are related through simple algebra,br /
we can then work backward to obtain an unbiased estimate of the effect of prisons onbr / /
Methods: Potential instruments for crime are tested and used to identify the prisonbr /
equation for the 50 U.S. states for the period 1978ndash;2009. The effect of prisons on crimebr /
consistent with this relationship is obtained through algebra; standard errors are obtainedbr /
through Monte Carlo /
Results: Resulting estimates of the effect of prisons on crime are around -0.25 plusmn; /
This is larger than biased OLS estimates, but similar in size to previous estimates based onbr /
standard /
Conclusions: When estimating the effect of a public policy response on a public problem,br /
it may be more productive to find instruments for the problem and work backwardbr /
than to find instruments for the response and work forward./p

Research Topic
Criminal Justice