NCJ Number
245810
Journal
Journal of Quantitative Criminology Volume: 29 Issue: 4 Dated: December 2013 Pages: 643-674
Date Published
December 2013
Length
32 pages
Annotation
Potential instruments for crime are tested and used to identify the prison equation for the 50 U.S. States for the period 1978-2009.
Abstract
Prisons reduce crime rates, but crime increases prison populations. OLS estimates of the effects of prisons on crime combine the two effects and are biased toward zero. The standard solutionto identify the crime equation by finding instruments for prisonis suspect, because most variables that predict prison populations can be expected to affect crime, as well. An alternative is to identify the prison equation by finding instruments for crime, allowing an unbiased estimate of the effect of crime on prisons. Because the two coefficients in a simultaneous system are related through simple algebra, the author can then work backward to obtain an unbiased estimate of the effect of prisons on crime. Potential instruments for crime are tested and used to identify the prison equation for the 50 U.S. States for the period 1978-2009. The effect of prisons on crime consistent with this relationship is obtained through algebra; standard errors are obtained through Monte Carlo simulation. Resulting estimates of the effect of prisons on crime are around -0.25 +/- 0.15. This is larger than biased OLS estimates, but similar in size to previous estimates based on standard instruments. When estimating the effect of a public policy response on a public problem, it may be more productive to find instruments for the problem and work backward than to find instruments for the response and work forward. (Published Abstract)