Execution moratoriums, commutations and deterrence: the case of Illinois

In an earlier work the impact of an execution moratorium in Texas on the monthly returns (first differences) of homicides was investigated. That moratorium was judicially imposed pending the appeal of a death sentence that could have had widespread consequences. A similar methodology is applied to the state of Illinois. In January 2000, the Governor of Illinois declared a moratorium on executions pending a review of the judicial process that condemned certain murderers to the death penalty. In January 2003 just prior to leaving office, the Governor commuted the death sentences of all of those who then occupied death row. It is found that these actions are coincident with the increased risk of homicide incurred by the residents of Illinois over the 48 month post-event period for which data were available. The increased risk produced an estimated 150 additional homicides during the post-event period.

Reflections on a critique

Critiques of scholarly research contain their own flaws; sometimes even more so than the work they are critiquing. Such is the case of the critique of our research authored by John Donohue and Jason Wolfers. Published in the Stanford Law Review their paper avoided the blind peer review process and consequently contains elements that undoubtedly would not have survived peer review. That possibility aside, we show that their alternative measures of criminal activity have no theoretical basis nor any empirical precedent within the modified portfolio approach employed in our research. Putting even that aside, we show that their empirical results are not inconsistent with ours. Thus, upon reflection, we see no justification to amend, modify or otherwise alter our methods or results.

Execution and deterrence: a quasi-controlled group experiment

Using portfolio analysis in a type of controlled group experiment, this study develops an empirical model of homicide changes in Texas over a period of a 'normal' number of executions. The empirically derived model then estimates the changes in the number of homicides in Texas (1) over a period of near zero executions and; (2) over an immediate subsequent period of double the 'normal' number of executions. The actual changes in Texas homicides over the first period is less than estimated by the model and greater (or no different) than estimated by the model in the second period. Because changes in the number of homicides in Texas and throughout the United States were negative over both periods, these empirical results are consistent with the deterrence hypothesis. That is, there were a greater than predicted number of homicides in the first period and fewer than predicted number in the second period.