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Journal of Quantitative Criminology

, Volume 29, Issue 1, pp 5–43 | Cite as

What Do Panel Studies Tell Us About a Deterrent Effect of Capital Punishment? A Critique of the Literature

  • Aaron Chalfin
  • Amelia M. HavilandEmail author
  • Steven Raphael
Original Paper

Abstract

Objectives

We provide a critical review of empirical research on the deterrent effect of capital punishment that makes use of state and, in some instances, county-level, panel data.

Methods

We present the underlying behavioral model that presumably informs the specification of panel data regressions, outline the typical model specification employed, discuss current norms regarding “best-practice” in the analysis of panel data, and engage in a critical review.

Results

The connection between the theoretical reasoning underlying general deterrence and the regression models typically specified in this literature is tenuous. Many of the papers purporting to find strong effects of the death penalty on state-level murder rates suffer from basic methodological problems: weak instruments, questionable exclusion restrictions, failure to control for obvious factors, and incorrect calculation of standard errors which in turn has led to faulty statistical inference. The lack of variation in the key underlying explanatory variables and the heavy influence exerted by a few observations in state panel data regressions is a fundamental problem for all panel data studies of this question, leading to overwhelming model uncertainty.

Conclusions

We find the recent panel literature on whether there is a deterrent effect of the death penalty to be inconclusive as a whole, and in many cases uninformative. Moreover, we do not see additional methodological tools that are likely to overcome the multiple challenges that face researchers in this domain, including the weak informativeness of the data, a lack of theory on the mechanisms involved, and the likely presence of unobserved confounders.

Keywords

Panel studies Death penalty Deterrence Critical research review 

Notes

Acknowledgments

We would like to acknowledge the analytic contributions of Dan Winger, MS, and Wenhao Xia, MS.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Aaron Chalfin
    • 1
  • Amelia M. Haviland
    • 2
    Email author
  • Steven Raphael
    • 1
  1. 1.Goldman School of Public PolicyUC BerkeleyBerkeleyUSA
  2. 2.H. John Heinz III College of Public Policy and ManagementCarnegie Mellon UniversityPittsburghUSA

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