Journal of Quantitative Criminology 29(1)

Journal of Quantitative Criminology, March 2013; Volume 29, Issue 1

Special Issue: Deterrence and Capital Punishment

What Do Panel Studies Tell Us About a Deterrent Effect of Capital Punishment? A Critique of the Literature
Aaron Chalfin, Amelia M. Haviland & Steven Raphael

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.

Pitfalls in the Use of Time Series Methods to Study Deterrence and Capital Punishment
Kerwin Kofi Charles & Steven N. Durlauf

Objectives Evaluate the use of various time series methods to measure the deterrence effect of capital punishment. Methods The analysis of the time series approach to deterrence is conducted at two levels. First, the mathematical foundations of time series methods are described and the link between the time series properties of aggregate homicide and execution series and individual decision making is developed. Second, individual studies are examined for logical consistency. Results The analysis concludes that time series methods used to study the deterrence effects of capital punishment suffer from fundamental limitations and fail to provide credible evidence. The common limitation of these studies is their lack of attention to identification problems. Suggestions are made as to directions for future work that may be able to mitigate the weaknesses of the current literature. Conclusions Time series studies of capital punishment suffer from sufficiently serious identification problems that existing empirical findings are compatible with either the presence or the absence of a deterrent effect.

Sanctions, Perceptions, and Crime: Implications for Criminal Deterrence
Robert Apel

Objectives A survey of empirical research concerning the determinants of an individual’s perceptions of the risk of formal sanctions as a consequence of criminal behavior. The specific questions considered are: (1) How accurate is people’s knowledge about criminal sanctions? (2) How do people acquire and modify their subjective probabilities of punishment risk? (3) How do individuals act on their risk perceptions in specific criminal contexts? Methods Three broad classes of extant studies are reviewed. The first is the relationship between objective sanctions, sanction enforcement, and risk perceptions—research that includes calibration studies and correlational studies. The second is the relationship between punishment experiences (personal and vicarious) and change in risk perceptions, in particular, research that relies on formal models of Bayesian learning. The third is the responsiveness of would-be offenders to immediate environmental cues—a varied empirical tradition that encompasses vignette research, offender interviews, process tracing, and laboratory studies. Results First, research concerning the accuracy of risk perceptions suggests that the average citizen does a reasonable job of knowing what criminal penalties are statutorily allowed, but does a quite poor job of estimating the probability and magnitude of the penalties. On the other hand, studies which inquire about more common offenses (alcohol and marijuana use) from more crime-prone populations (young people, offenders) reveal that perceptions are consistently better calibrated to actual punishments. Second, research on perceptual updating indicates that personal experiences and, to a lesser degree, vicarious experiences with crime and punishment are salient determinants of changes in risk perceptions. Specifically, individuals who commit crime and successfully avoid arrest tend to lower their subjective probability of apprehension. Third, research on the situational context of crime decision making reveals that risk perceptions are highly malleable to proximal influences which include, but are not limited to, objective sanction risk. Situational risk perceptions appear to be particularly strongly influenced by substance use, peer presence, and arousal level. Conclusions The perceptual deterrence tradition is theoretically rich, and has been renewed in the last decade by creative empirical tests from a variety of social scientific disciplines. Many knowledge gaps and limitations remain, and ensuing research should assign high priority to such considerations as sampling strategies and the measurement of risk perceptions.

Capital Punishment and Deterrence: Understanding Disparate Results
Steven N. Durlauf, Chao Fu & Salvador Navarro

Objectives Investigate how different model assumptions have driven the conflicting findings in the literature on the deterrence effect of capital punishment. Methods The deterrence effect of capital punishment is estimated across different models that reflect the following sources of model uncertainty: (1) the uncertainty about the probability model generating the aggregate murder rate equation, (2) the uncertainty about the determinants of an individual’s choice of committing a murder or not, (3) the uncertainty about state level heterogeneity, and (4) the uncertainty about the exchangeability between observations with zero murder case and those with positive murder cases. Results First, the estimated deterrence effects exhibit great dispersion across models. Second, a particular subset of models—linear models with constant coefficients—always predict a positive deterrence effect. All other models predict negative deterrence effects. Third, the magnitudes of the point estimates of deterrence effects differ mainly because of the choice of linear versus logistic specifications. Conclusions The question about the deterrence effect of capital punishment cannot be answered independently from substantive assumptions on what determines individual behavior. The need for judgment cannot be escaped in empirical work.

Deterrence and the Death Penalty: Partial Identification Analysis Using Repeated Cross Sections
Charles F. Manski & John V. Pepper

Objectives Researchers have used repeated cross sectional observations of homicide rates and sanctions to examine the deterrent effect of the adoption and implementation of death penalty statutes. The empirical literature, however, has failed to achieve consensus. A fundamental problem is that the outcomes of counterfactual policies are not observable. Hence, the data alone cannot identify the deterrent effect of capital punishment. This paper asks how research should proceed. We seek to make transparent how assumptions shape inference. Methods We study the identifying power of relatively weak assumptions restricting variation in treatment response across places and time. We perform empirical analysis using state-level data in the United States in 1975 and 1977. Results The results are findings of partial identification that bound the deterrent effect of capital punishment. Under the weakest restrictions, there is substantial ambiguity: we cannot rule out the possibility that having a death penalty statute substantially increases or decreases homicide. This ambiguity is reduced when we impose stronger assumptions, but inferences are sensitive to the maintained restrictions. Conclusions Imposing certain assumptions implies that adoption of a death penalty statute increases homicide, but other assumptions imply that the death penalty deters it. Thus, society at large can draw strong conclusions only if there is a consensus favoring particular assumptions. Without such a consensus, data on sanctions and murder rates cannot settle the debate about deterrence. However, data combined with weak assumptions can bound and focus the debate.