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Dr. Paul Rubin
Professor of Economics
Statistical Evidence on Capital Punishment and the Deterrence of Homicide
Written Testimony for the Senate Judiciary Committee on the Constitution, Civil Rights, and Property Rights
Paul H. Rubin
I. Introduction and Summary
Recent research on the relationship between capital punishment and homicide has created a consensus among most economists who have studied the issue that capital punishment deters murder. Early studies from the 1970s and 1980s reached conflicting results. However, recent studies have exploited better data and more sophisticated statistical techniques. The modern refereed studies have consistently shown that capital punishment has a strong deterrent effect, with each execution deterring between 3 and 18 murders. This is true even for crimes that might seem not to be deterrable, such as crimes of passion. (There is some evidence from unrefereed studies that have not been scientifically evaluated that is inconsistent with this generally accepted claim.)
II. My Background and Qualifications.
I am the Samuel Candler Dobbs Professor of Economics and Law at Emory University in Atlanta and editor in chief of Managerial and Decision Economics. I am a Fellow of the Public Choice Society and former Vice President of the Southern Economics Association, and associated with the Independent Institute, the Progress and Freedom Foundation, and the American Enterprise Institute. I have been Senior Staff Economist at President Reagan's Council of Economic Advisers, Chief Economist at the U.S. Consumer Product Safety Commission, Director of Advertising Economics at the Federal Trade Commission, and vice-president of Glassman-Oliver Economic Consultants, Inc., a litigation consulting firm in Washington. I have taught law and economics at the University of Georgia, City University of New York, VPI, and George Washington University Law School.
I received my B.A. from the University of Cincinnati in 1963 and my Ph.D. from Purdue University in 1970. Much of my research has been on statistical analysis of legal issues, including the economics of crime. I was a co-author of the first published paper examining the deterrent effect of capital punishment using data from the period after the moratorium on executions: Hashem Dezhbakhsh, Paul H. Rubin, and Joanna M. Shepherd, Does Capital Punishment Have a Deterrent Effect? New Evidence from Postmoratorium Panel Data, 5 American Law and Economics Review 344 (2003).
III. Early Literature on Capital Punishment and Deterrence.
The initial participants in the debate over the deterrent effect of capital punishment were psychologists and criminologists. Their research was either theoretical or based on comparisons of crime patterns in states with and without capital punishment. However, because they did not use multiple-regression statistical techniques, the analyses were unable to distinguish the effect on murder of capital punishment from the effects of other factors.
Ehrlich's 1975 paper examined U.S time-series data for the period 1933-1969. Time-series data are data for one unit (for Ehrlich, for the entire U.S.) over several time periods. He tested the effect on national murder rates of deterrent variables (the probabilities of arrest, conviction, and execution), demographic variables (population, fraction of nonwhites, fraction of people age 14-24), economic variables (labor force participation, unemployment rate, real per capita permanent income, per capita government expenditures, and per capita expenditures on police), and a time variable. He found a statistically significant negative relationship between the murder rate and execution rate, indicating a deterrent effect. Specifically, he estimated that each execution resulted in approximately seven or eight fewer murders.
Again, Ehrlich used multivariate regression analysis to separate the effect on murder of different factors. He included deterrent variables (probabilities of conviction and execution, median time spent in prison, and a dummy variable distinguishing executing states from non-executing states), demographic variables (state population, urban population, percent of nonwhites, and percent of people age 15-24 and 25-34), and economic variables (median family income and percent of families with income below half of the median income). The results indicated a substantial deterrent effect of capital punishment on murder.
Ehrlich's finding generated substantial interest in econometric analysis of capital punishment and deterrence. The papers that immediately followed Ehrlich used his original data (1933-1969 national time-series or 1940 and 1950 state level cross section) and variants of his econometric model. Many found a deterrent effect of capital punishment, but others did not. For example, using Ehrlich's data, all of the following found a deterrent effect: Yunker; Cloninger; and Ehrlich and Gibbons. In contrast, Bowers and Pierce; Passel and Taylor; and Hoenack and Weiler find no deterrence when they use the same data with alternative statistical specifications. Similarly, McAleer and Veall; Leamer; and McManus, find no deterrent effect when different variables are included over the same sample period. Finally, Black and Orsagh find mixed results depending on the cross-section year they use.
In the late 1980s and 1990s, a second-generation of econometric studies extended Ehrlich's national time-series data or used more recent cross-sectional data. As before, some papers found deterrence while others did not. For example, Layson, and Cover and Thistle use an extension of Ehrlich's national time-series data, covering up to 1977. Although Layson finds a significant deterrent effect of executions, Cover and Thistle correct for data flaws -- nonstationarity -- and find no deterrent effect. Chressanthis employs national time-series data covering 1966 through 1985 and finds a deterrent effect. In contrast, Grogger uses daily data for California during 1960-1963 and finds no deterrent effect.
However, most of the early studies--both the first wave and the second generation--suffered from fundamental flaws: they suffered important data limitations because they used either national time-series or cross-section data.
Cross-sectional studies also suffer serious problems. Most importantly, they preclude any consideration of what happens to crime, law enforcement, and judicial processes over time. Cross-section data also prevent researchers from controlling for jurisdiction-specific characteristics that could be related to murder, such as greater urban density in some states.
Several authors expressed similar data concerns with time-series and cross-section data and called for new research using panel data, as I now discuss.
IV. Modern Studies of Capital Punishment's Deterrent Effect.
Most recent studies have overcome the fundamental problems associated with national time-series and cross-section data by using panel-data techniques. Panel data are data from several units (the fifty states or all U.S. counties) over several different time periods; that is, panel data follow a cross-section over time. For example, a panel dataset might include data on each of the fifty states, or even on each U.S. county, for a series of years. These improved data allow researchers to capture the demographic, economic, and jurisdictional differences among U.S. states or counties, while avoiding aggregation bias. Furthermore, panel data produce many more observations than cross-section or time-series data, enabling researchers to estimate any deterrent effect more precisely. In addition to enjoying the benefits of panel data, recent studies have access to more recent data that make conclusions more relevant for the current environment.
I now briefly discuss the modern research in the economics literature from the past decade. I group the papers into those that use panel-data techniques and those using other techniques. (I was co-author of one paper, and my colleague Joanna Shepherd was author or co-author of several more.) I then discuss two papers which have been published in journals that do not subject papers to the refereeing process.
A. Modern Papers using Panel-Data Techniques.
1. Hashem Dezhbakhsh, Joanna Shepherd , and I examine whether deterrence exists using county-level panel data from 3,054 U.S. counties over the period 1977 to 1996. This is the only study to use county-level data, allowing us to estimate better the demographic, economic, and jurisdictional differences among U.S. counties that can affect murder rates. Moreover, the large number of county-level observations extends the empirical tests' reliability. We find a substantial deterrent effect; both death row sentences and executions result in decreases in the murder rate. A conservative estimate is that each execution results in, on average, 18 fewer murders. Our main finding, that capital punishment has a deterrent effect, is robust to many different ways of performing the statistical analysis and several ways of measuring the probability of an execution. For example, we find the same results if we use state instead of county data.
2. In another paper, Joanna Shepherd uses state-level, monthly panel data from 1977-1999 to examine two important questions in the capital punishment literature. First, she investigates the types of murders deterred by capital punishment. Some people in the debate on capital punishment's deterrent effect believe that certain types of murder are not deterrable. They claim that murders committed during interpersonal disputes, murders by intimates, or unplanned crimes of passion are not intentionally committed and are therefore nondeterrable. She finds that the combination of death row sentences and executions deters all types of murders: murders between intimates, acquaintances, and strangers, crime-of-passion murders and murders committed during other felonies, and murders of both African-American and white people. She estimates that each death row sentence deters approximately 4.5 murders and that each execution deters approximately 3 murders. In this paper she also finds that that shorter waits on death row increase deterrence. Specifically, one extra murder is deterred for every 2.75-years reduction in the death-row wait before each execution.
3. Hashem Dezhbakhsh and Joanna Shepherd use state-level panel data from 1960-2000 to examine capital punishment's deterrent effect. This is the only study to use data from before, during, and after the 1972-1976 Supreme Court moratorium on executions. The study advances the deterrence literature by exploiting an important characteristic that other studies overlooked: the quasi-experimental nature of the Supreme Court moratorium. First, they perform before-and-after moratorium comparisons by comparing the murder rate for each state immediately before and after it suspended or reinstated the death penalty. These before-and-after comparisons are informative because many factors that affect crime--e.g., law enforcement, judicial, demographic, and economic variables--change only slightly over a short period of time. In addition, the moratorium began and ended in different years in different states. Considering the different start and end dates, the duration of the moratorium varied considerably across states, ranging from four to thirty years. Observing similar changes in murder rates immediately after the same legal change in different years and in various states provides additional evidence of the moratorium's effect on murder. The before-and-after comparisons reveal that as many as 91 percent of states experienced an increase in murder rates after they suspended the death penalty. In about 70 percent of the cases, the murder rate dropped after the state reinstated the death penalty. They supplement the before-and-after comparisons with time-series and panel-data regression analyses that use both pre- and postmoratorium data. These estimates suggest that both adopting a capital statute and exercising it have strong deterrent effects.
4 and 5. Two papers by FCC economist Paul Zimmerman find a deterrent effect. Zimmerman uses state-level panel data from 1978 to 1997 to examine the relationship between state execution rates and murder rates. In a second paper, he employs state-level panel data from 1978-2000 to examine which execution methods have the strongest deterrent effects. In both papers, Zimmerman finds a significant deterrent effect of capital punishment. He estimates that each execution deters an average of 14 murders and that executions by electrocution have the strongest impact.
6. H. Naci Mocan and R. Kaj Gittings use state-level panel data from 1977 to 1997 to examine the relationship between executions, commutations, and murder. Again, the authors find a significant deterrent effect; they estimate that each execution deters an average of 5 murders. Their results also indicate that both commuting death-row prisoners' sentences and removing them from death row cause increases in murder. Specifically, each commutation results in approximately five extra murders and each removal from death row generates one additional murder.
7. Another recent paper by Lawrence Katz, Steven D. Levitt, and Ellen Shustorovich uses state-level panel data covering the period 1950 to 1990 to measure the relationship between prison conditions, capital punishment, and crime rates. They find that the death rate among prisoners (a proxy for prison conditions) has a significant, negative relationship with overall violent crime rates and property crime rates. As expected, the execution rate has no statistically significant relationship with overall violent crime rates (which consist mainly of robbery and aggravated assault rates) and property crime rates; that is, executions have no effect on non-capital crimes. In several estimations, both the prison death rate and the execution rate are found to have significant, negative relationships with murder rates. The deterrent effect of executions is especially strong in the estimations that control for the economic and demographic differences among states.
B. Modern Papers Using Other Techniques
8. Instead of a panel-data study, Dale O. Cloninger and Roberto Marchesini conduct a portfolio analysis in a type of controlled group experiment: the Texas unofficial moratorium on executions during most of 1996. They find that the moratorium appears to have caused additional homicides and that murder rates significantly decreased after the moratorium was lifted.
9. Harold J. Brumm and Dale O. Cloninger use cross-sectional data covering 58 cities in 1985 to distinguish between criminals' perceived risk of punishment and the ex-post risk of punishment measured by arrest rates, conviction rates, or execution rates. They find that the perceived risk of punishment, including the probability of execution, is negatively and significantly correlated with the homicide commission rate.
10. James A. Yunker tests the deterrence hypothesis using two sets of post-moratorium data: state cross-section data from 1976 and 1997 and national time-series data from 1930-1997. He finds a strong deterrent effect in the time-series data that disappears when the data are limited to the 1930-1976 period. Therefore, he concludes that postmoratorium data is critical in testing of the deterrence hypothesis.
11 and 12. Two other papers, one by Isaac Ehrlich and Zhiqiang Liu and the other by Zhiqiang Liu, use Ehrlich's original state-level, cross-section data. The study by Ehrlich and Liu offers a theory-based sensitivity analysis of estimated deterrent effects and finds that executions have a significant deterrent effect. Liu's study uses switching regression techniques in estimations that take into account the endogenous nature of the status of the death penalty. He also finds a strong deterrent effect.
C. Unrefereed Papers
One paper in the Michigan Law Review by Joanna Shepherd looks at data by states. She finds a "threshold effect." States that have executed more than approximately nine murderers exhibit deterrence; in states that have executed fewer persons, there is either no effect or a "brutalization effect," indicating that capital punishment has led to an increase in the number of murders. Overall, capital punishment has led to a net saving of lives. More lives could be saved if states with few executions either ceased executions or alternatively, if they pursued capital punishment more vigorously. While this paper was not published in a refereed journal, it was presented at several universities and posted for comments at online services such as SSRN.
A recent paper in the Stanford Law Review questions some of these studies. This paper purports to show that the estimates of a deterrent effect are "fragile" and can be changed by statistical manipulation. The results of this paper have not been evaluated by competent scholars; the Stanford Law Review, like all law reviews, is edited by students who have no particular competence in econometrics. Moreover, Professors Wolfers and Donohue chose not to make their paper available online through a service such as SSRN or the BE Press, so that the scholarly community did not have access to their analysis before it was published. Steps are in process to generate such an analysis, but at this point the weight of evidence must be interpreted as finding a deterrent effect. Moreover, although Professors Donohue and Wolfers had access to all of the papers mentioned in this testimony, they chose to comment on only some of these papers.
The literature is easy to summarize: almost all modern studies and all the refereed studies find a significant deterrent effect of capital punishment. Only one study questions these results. To an economist, this is not surprising: we expect criminals and potential criminals to respond to sanctions, and execution is the most severe sanction available.