Re-examination of the Criminal Deterrent Effects of Capital Punishment in the United States, 1978-1998 (ICPSR 20040)
Version Date: Jan 31, 2008 View help for published
Principal Investigator(s): View help for Principal Investigator(s)
Ethan Cohen-Cole, Federal Reserve Bank of Boston;
Steven Durlauf, University of Wisconsin. Department of Economics;
Jeffrey Fagan, Columbia University. School of Law;
Daniel Nagin, Carnegie Mellon University. H. John Heinz III School of Public Policy and Management
https://doi.org/10.3886/ICPSR20040.v1
Version V1
Summary View help for Summary
The purpose of this study was to estimate the deterrent effect of capital punishment by employing a methodology that accounted for model uncertainty by integrating various studies into a single coherent analysis. First, this study replicated the results from two previous studies, Dezhbakhsh, Rubin and Shepherd (2003) and Donohue and Wolfers (2005), that draw on the same data. Second, the researchers implemented model averaging methods using standard frequentist estimators to take a weighted average of the findings across all possible models that could explain the effect of the difference in crime rates under alternate laws. Each model's effect was weighted based on its ability to explain the data. Variables used in this study included deterrence variables as well as various demographic and economic control variables.
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Subject Terms View help for Subject Terms
Geographic Coverage View help for Geographic Coverage
Smallest Geographic Unit View help for Smallest Geographic Unit
county
Distributor(s) View help for Distributor(s)
Time Period(s) View help for Time Period(s)
Data Collection Notes View help for Data Collection Notes
- (1) Users can obtain data used for this study in Stata format from Justin Wolfers' Death Penalty Data Web site. From this Web site, users may either download Donohue and Wolfers' (2005) county-level homicide and execution data plus controls, 1977-1996 Stata 9 data (CPcounty5_send.dta), or Dezbakhsh, Rubin and Shepherd's (2003) county-level data 1977-1996 (DRS.zip). Both downloads contain the exact same Stata dataset, however Dezbakhsh, Rubin and Shepherd's (2003) county-level data 1977-1996 download, when unzipped, also contains additional Stata Do-files. (2) While this project's final report and Justin Wolfers' Death Penalty Data Web site refer to the data as covering the years 1977-1996, the data that are available from Wolfers' Web site actually cover the years 1978-1998. (3) The files in this collection are provided in a WinZip archive with 16 computer program code files for use with the MATLAB software program. Additional information on MATLAB is available from The MathWorks, Inc.. (4) Users are encouraged to refer to the final report, available from the National Criminal Justice Reference Service (NCJRS) for more detailed information regarding the study design and model averaging methodology and for complete references to publications mentioned in this description.
Study Purpose View help for Study Purpose
The fundamental problem that underlies the disparate findings on deterrence effects of death sentencing is that individual studies reflect specific assumptions about the appropriate data, control variables, model specification, etc., on the part of the researcher. These assumptions can have major effects on the conclusions of a particular data analysis. The existing research on this topic comes to sufficiently differing conclusions, predicated upon one or more underlying assumptions, to call into question the ability of any single model to explain the impact of execution laws. Such dependence on the specifics of research design, from data cleaning to aggregation to model choice, forms the basis for the use of averaging techniques. That is, since relatively minor variations in model or variable choice can lead to dramatic changes in conclusions, one suspects that inclusion of the information content of all of these models would lend itself to conclusions upon which policymakers could be more confident. The purpose of this study was to estimate the deterrent effect of capital punishment by employing a methodology that accounted for model uncertainty by integrating various studies into a single coherent analysis. The research project sought to utilize model averaging, a method that enables a researcher to take a weighted average of findings across possible models, to develop inferences that are not dependent on the assumption that one of the models is true.
Study Design View help for Study Design
This study replicated the results from two previous studies and implemented model averaging methods to analyze deterrence laws. First, this study replicated the results from two previous studies, Dezhbakhsh, Rubin and Shepherd (2003) and Donohue and Wolfers (2005), that draw on the same data. Both papers estimated some version of a deterrence regression drawn from Ehrlich (1977). That is, the murder rate is a function of three principal deterrence variables: the probability of arrest, the probability of receiving a death sentence conditional of being arrested, and the probability of being executed conditional on receiving a death sentence. Second, the researchers implemented model averaging methods using standard frequentist estimators to take a weighted average of the findings across all possible models that could explain the effect of the difference in crime rates under alternate laws. Each model's effect was weighted based on its ability to explain the data. This frequentist approach to model averaging is described in Sala-i-Martin, Doppelhofer, and Miller (2004) and Brock, Durlauf, and West (2003).
Sample View help for Sample
The sample for this study included county-level data for the post-moratorium period (1978-1998).
Universe View help for Universe
All persons sentenced to death within the United States between 1978 and 1998.
Unit(s) of Observation View help for Unit(s) of Observation
Data Source View help for Data Source
Data for this study were obtained from Donohue and Wolfers (2005) and Dezhbakhsh, Rubin and Shepherd (2003). The original sources for these data were the Department of Justice's Bureau of Justice Statistics, the FBI's Uniform Crime Reports, and the Bureau of the Census. Users should reference the COLLECT.NOTE section in this description for further information regarding data used in this study.
Data Type(s) View help for Data Type(s)
Mode of Data Collection View help for Mode of Data Collection
Description of Variables View help for Description of Variables
Variables used in this study included deterrence variables as well as various demographic and economic control variables. Deterrence variables included the probability of arrest, the probability of receiving a death sentence conditional of being arrested, and the probability of being executed conditional on receiving a death sentence. Demographic and economic control variables included controls for the aggravated assault rate, the robbery rate, the population proportion of 10-19-year-olds, 20-29-year-olds, demographic percentages of Blacks, percentage of non-Black minorities, percentage of males, the percentage of NRA members, real per capita income, real per capita income maintenance payments, real per capita unemployment insurance payments, and the population density. Other variables were voting variables, year variables, and arrest rate variables.
Response Rates View help for Response Rates
Not applicable.
Presence of Common Scales View help for Presence of Common Scales
None
HideOriginal Release Date View help for Original Release Date
2008-01-31
Version History View help for Version History
- Cohen-Cole, Ethan, Steven Durlauf, Jeffrey Fagan, and Daniel Nagin. Re-examination of the Criminal Deterrent Effects of Capital Punishment in the United States, 1978-1998. ICPSR20040-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2008-01-31. http://doi.org/10.3886/ICPSR20040.v1
Weight View help for Weight
The researchers used theory to estimate the weighted average coefficients in a variety of cases as part of their model averaging analysis approach.
HideNotes
The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.
This dataset is maintained and distributed by the National Archive of Criminal Justice Data (NACJD), the criminal justice archive within ICPSR. NACJD is primarily sponsored by three agencies within the U.S. Department of Justice: the Bureau of Justice Statistics, the National Institute of Justice, and the Office of Juvenile Justice and Delinquency Prevention.