Controlling Crime: Sex and Surveillance on the Chinese Internet

Overview

 Criminal justice expenditures have more than doubled since the 1980s, dramatically increasing costs to the public. With state and local revenue shortfalls resulting from the recent recession, the question of whether crime control can be accomplished either with fewer resources or by investing those resources in areas other than the criminal justice system is all the more relevant.

Controlling Crime considers alternative ways to reduce crime that do not sacrifice public safety. Among the topics considered ...

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Overview

 Criminal justice expenditures have more than doubled since the 1980s, dramatically increasing costs to the public. With state and local revenue shortfalls resulting from the recent recession, the question of whether crime control can be accomplished either with fewer resources or by investing those resources in areas other than the criminal justice system is all the more relevant.

Controlling Crime considers alternative ways to reduce crime that do not sacrifice public safety. Among the topics considered here are criminal justice system reform, social policy, and government policies affecting alcohol abuse, drugs, and private crime prevention. Particular attention is paid to the respective roles of both the private sector and government agencies. Through a broad conceptual framework and a careful review of the relevant literature, this volume provides insight into the important trends and patterns of some of the interventions that may be effective in reducing crime.

 

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Meet the Author

 

Philip J. Cook is the ITT/Terry Sanford Professor of Public Policy and professor of economics and sociology at Duke University, where he is also senior associate dean for faculty and research. He is a research associate of the NBER. Jens Ludwig is the McCormick Foundation Professor of Social Service Administration, Law, and Public Policy at the University of Chicago, director of the University of Chicago Crime Lab, and a research associate of the NBER. Justin McCrary is professor of law at the University of California, Berkeley, and a faculty research fellow of the NBER. All three editors codirect the Working Group on the Economics of Crime at the NBER.

 

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Controlling Crime

Strategies and Tradeoffs

The University of Chicago Press

Copyright © 2011 National Bureau of Economic Research
All right reserved.

ISBN: 978-0-226-11512-2


Chapter One

The Deterrent Effect of Imprisonment

Steven N. Durlauf and Daniel S. Nagin

1.1 Introduction

This chapter is designed to provide an overview of the state of knowledge on the deterrent effects of imprisonment. Much of what we say constitutes a selective summary of existing research. At the same time, we provide some general critiques of the state of knowledge on imprisonment and deterrence and identify some implications for policy.

Our reading of the current empirical literature is that there is overwhelming evidence of substantial deterrent effects across a range of contexts. Therefore, a well-balanced crime-control portfolio must necessarily include deterrence-based policies. Yet the magnitude of deterrent effects depends critically on the specific form of the sanction policy. In particular, there is little evidence that increases in the severity of punishment yield strong marginal deterrent effects; further, credible arguments can be advanced that current levels of severity cannot be justified by their social and economic costs and benefits. By contrast there is very substantial evidence that increases in the certainty of punishment produce substantial deterrent effects. In this regard the most important set of actors are the police since, in the absence of detection and apprehension, there is of course no possibility of conviction or punishment. Many studies show that the police, if mobilized in ways that materially heighten the risk of apprehension, can exert a substantial deterrent effect. There is also evidence that if the parole and probation systems are similarly deployed they too can exert a substantial deterrent effect. Thus, one policy relevant implication of our conclusions is that lengthy prison sentences, particularly in the form of mandatory minimum type statutes such as California's Three Strikes Law cannot be justified based on their deterrent effect on crime. In fact, our review suggests a stronger implication: it is possible that crime rates can be reduced without an increase in the resource commitment to crime control; such a reduction may be achieved by shifting resources from incarceration via reducing sentence severity and shifting these resources to policing and parole and probation monitoring systems. These conclusions, to be clear, are tentative and we will discuss why firm claims of this form are difficult.

Our review also has suggestions for the importance of generalizing the economic model of crime in a number of directions; in particular, we address psychological and sociological aspects of criminal behavior whose integration into the standard economic crime model would, in our view, enhance its explanatory power. We take the perspective that the "economic way of looking at behavior" (Becker 1993) has much to commend it for the study of crime and for interpreting psychological and sociological ideas in ways to enhance the perspective.

The chapter is organized as follows. We begin by laying out what we refer to as the "baseline" economic model of crime due to Gary Becker. The Beckerian model provides a framework for our discussion of empirics. We then turn to a review of the literature and our interpretation of implications. Our discussion closes with an assessment of policy implications and directions for future research including expansion of the baseline model.

1.2 The Economic Model of Crime

In order to provide a conceptual framework for our discussion, we employ a version of the economic model of crime pioneered by Gary Becker (1968). Becker's analysis of crime, particularly at the time of its publication, is a fundamental theoretical contribution because it conceptualizes the commission of a crime as a purposeful choice, one that reflects a comparison of costs and benefits. While Becker's formulation, as well as subsequent "rational choice" crime models, describe individual choices by way of particular formulations of a potential criminal's beliefs, preferences, and constraints, it is the notion of crime as a choice that is an irreducible requirement of the approach. Much of the criticism of Becker's model, especially by noneconomists, amounts to criticisms of the ways in which the crime choice is delineated. In fact we will argue that what might, given the existing deterrence and imprisonment literature, appear to be empirical limitations of the economic approach to crime are remedied in a straightforward fashion by alternative formulations of the same choice-based logic that is the basis of Becker's model.

A very simple variant of the Becker model may be constructed as follows. In formulating this baseline model we think of a single cross section of choices made across a population at a fixed point in time; the fact that sentences are served over time and crime/ no crime choices are made throughout the life course will be ignored. We will discuss the implications of dynamic versions of the model later. Denote individuals by i and distinguish heterogeneity across them by the vector Zi. Each individual faces a binary choice as to whether or not commit a crime; that is, a choice between ITLITL and NC. If the criminal commits a crime, there is a probability p of being caught and punished. This means that a potential criminal will, depending on his choice, experience one of three utility levels: the utility of not committing a crime, UNC(Zi), the utility of committing a crime and being punished, UC,P(Zi), and the utility of committing a crime and not being punished, UC,NP(Zi). Individual i chooses to commit a crime if the expected utility from commission of a crime exceeds the utility from not committing a crime. A crime is therefore committed if

(1) [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

From the perspective of criminal sanctions, this elementary calculation highlights the two distinct aspects of crime sanction policy that are the appropriate focus of scholarly research on deterrence: p, the probability of being punished, and UC,P(Zi) - UC,NP(Zi), which will depend upon (among other factors) the nature of the punishment. Suppose that the nature of the punishment is summarized by length of imprisonment; assuming this is the only source of the utility loss in being caught, one can simplify the analysis by treating the utility of crime as Uc(Zc, L) where L denotes the length of the sentence served having committed the crime; we treat the sentence length as a sufficient statistic for the penalty associated with conviction and do not explicitly account for the fact that a sentence is served over time. We return to this issue later. This allows us to rewrite the condition for commission of a crime as

(2) [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

From this perspective, commission of a crime is analogous to the purchase of a lottery ticket. The distribution of the heterogeneity Zi induces an equilibrium aggregate crime rate. We can think of individual crime choices as binary functions ω(Zi, p, L), with 1 denoting crime and 0 no crime such that

(3) ω(Zi, p, L) = 1 if equation (2) holds; 0 otherwise.

Letting dFz denote the cross-population probability density of the heterogeneity measure Z, the aggregate crime rate Pr(C|p, L) is characterized by

(4) [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

For this simple specification, the decision problem facing a policymaker is the choice of a sanction regime, which is described by the pair (p, L). Formally, a policymaker assesses the benefits of a given policy via some function of the crime rate

(5) φ(Pr(C|p, L)).

In turn, the cost of the policy pair may be represented as a function

(6) λ(p) + µ(I)

where the variable I, defined as

(7) I = Pr(C|p, L)pL

is the expected per capita imprisonment rate in the population. In equation (6), the overall cost of the sanction regime, λ(p) captures the cost of law enforcement needed to achieve a particular apprehension rate for crimes while µ(I) captures costs of incarceration. Additivity of the two types of costs seems a natural first-order approximation since it distinguishes between police activity and imprisonment.

How should a policymaker choose among possible (p, L) pairs? Rather than solve for the optimal pair that requires consideration of a budget constraint for total law enforcement expenditure, it is more insightful to solve for the conditionally optimal levels of p and L under the constraint that the product pL is constant. Since pL equals the expected sentence length for a criminal who is caught, conditioning on this value provides a clean way of interpreting the respective roles of certainty of punishment and severity of punishment in influencing the individual crime decisions and hence the aggregate crime rate when the expected sentence length is fixed. Suppose that UC(Zi,L) is a concave function of L; that is, the marginal disutility of a marginal change in sentence length is increasing in the level of the sentence. This increasing marginal disutility of sentence length is equivalent to assuming that a potential criminal is risk averse with respect to the sentence "lottery." An agent who chooses to commit a crime faces an expected sentence length pL and will prefer to trade p against L when the marginal disutility of sentence length is increasing in the level of the length. Further, since a lower p reduces policing costs λ(p) and must also reduce prison costs as it minimizes Pr(C|p, L) given constant pL, it hence minimizes µ(I). This is the basis of Becker's conclusion that efficient sanction policy leads to relatively low punishment probabilities and long sentences. In terms of interpreting the relationship between sentence policy and deterrence, Becker's analysis concludes that, for a locus defined by pL = K, deterrence effects are greater, ceteris paribus, for higher L values so long as criminals are risk averse along this locus.

Becker's conclusion about optimal sanction policy should not be interpreted as meaning that severity is more important than certainty in deterrence; it is obvious from the structure of the decision problem that the two interact nonlinearly. When we evaluate evidence on the effects of marginal changes in severity and certainty, it is important to keep these interactions in mind. In particular, differences in estimated magnitudes of marginal deterrence effects from severity may be explained by differences in the background certainty levels; the converse may also hold.

In referring to this model as a baseline, we do Becker a partial injustice in that there are dimensions along which one can alter the structure we have described, while at the same time fully preserving the choice-based logic that underlie Becker's analysis. A simple example is the concavity of UC(Zi,L); this assumption has no bearing on the interpretation of crime choices as determined by expected utility maximization. While alterations in various assumptions in the baseline may change conclusions concerning the relationship between certainty, severity, and efficient punishment regimes, they do so via the same reasoning pioneered by Becker.

1.3 Empirics

There have been three distinct waves of studies of the deterrent effect of imprisonment. The first wave was conducted in the 1960s and 1970s. The best known study, conducted by Ehrlich (1973), examined the relationship of statewide crime rates to the certainty of punishment, measured by the ratio of prison admissions to reported crimes, and the severity of punishment as measured by median time served. Ehrlich, however, was not alone in employing this or closely related methods for measuring the certainty and severity of punishment (cf. Gibbs 1968; Tittle 1969; Sjoquist 1973; Forst 1976). These studies consistently found that certainty was inversely related to crime rate, which was interpreted as a deterrent effect. By contrast, the severity measure was generally not systematically related to crime rate, which was interpreted as indicating that severity was not an effective deterrent.

These studies suffered from a number of serious statistical flaws that are detailed in Blumstein, Cohen, and Nagin (1978), Nagin (1978), and Fisher and Nagin (1978). The two most important problems involved endogeneity and measurement error. This generation of studies typically failed to account for the endogenous relationship between crime rates and sanction levels predicted by Becker's model. Alternatively, those that attempted to account for endogeneity used implausible identification restrictions to parse out the deterrent effect of sanction levels on crime rates from the effect of crime rates on sanction levels. Papers in this first generation literature, for example, assumed that demographic or socioeconomic characteristics such as percentage of males aged fourteen to twenty-four or mean years of schooling of persons over twenty-five or per capita public safety expenditures lagged one year causally affected sanction levels but did not causally affect crime rates. Studies that fall under this criticism include Avio and Clarke (1976), Carr-Hill and Stern (1973), and Ehrlich (1973). The examples we have listed are examples of what Sims (1980) dubbed "incredible" identifying assumptions and are now recognized as an inadequate basis for making causal claims in social science. The second problem arose from measurement error in crime counts, of which there are many sources. It can be shown that these errors can artificially induce a negative correlation between the crime rate and the certainty of punishment because the measured level of crimes form the numerator of crime rate, that is, crimes per capita, and the denominator of the measure of certainty of punishment, that is, prison admissions per crime (Nagin 1978).

In response to these deficiencies, two subsequent waves of crime/deterrence research emerged, each of which is an ongoing literature. First, starting in the 1990s a number of authors began to use time series methods developed in the econometrics literature to understand the temporal relationship between imprisonment and crime. This new group of studies continued to use states as the unit of observation but unlike the first generation studies that primarily involved cross-sectional analyses of states, this second generation of studies had a longitudinal component. The panel structure of these studies allowed for the introduction of state and time specific fixed effects and the use of various differencing strategies to control for some forms of unobserved heterogeneity. Another important difference is that this wave of studies did not attempt to estimate certainty and severity effects separately. Instead they examined the relationship between the crime rate and rate of imprisonment as measured by prisoners per capita. Another distinct modern research program also emerged that focuses on the effect of police resources on crime rates, particular statutory changes in criminal penalties (severity) or abrupt changes in the level of police presence arising from events such as terror alerts (certainty). Some of these studies may also be distinguished from the first generation by their use of quasi-or natural experiments to uncover deterrence effects. In organizing our survey of the state of the literature, we review these two modern literatures separately by first considering studies that have attempted to link aggregate crime and imprisonment rates, and second, considering studies that have considered the effects of criminal sanction policy on crime.

1.3.1 Aggregate Studies Relating Imprisonment Rate to the Crime Rate

An important recent review by Donohue (2009, table 9.1) identifies six published articles that examine the relationship between aggregate crime rates and imprisonment rates. Each of these studies finds a statistically significant negative association between imprisonment rates and crime rates, and each has been interpreted as implying a crime prevention effect of imprisonment. However, the magnitude of estimates of the parameter varied widely—from nil at current levels of incarceration (Liedka, Piehl, and Useem 2006), to an elasticity of -0.4 (Spelman 2000). It is important to note that these studies are actually measuring a combination of deterrent and incapacitation effects. Thus, it is impossible to decipher the degree to which crime prevention is occurring because of a behavioral response by the population at large or because of the physical isolation of crime-prone people.

(Continues...)



Excerpted from Controlling Crime Copyright © 2011 by National Bureau of Economic Research. Excerpted by permission of The University of Chicago Press. All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.

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Table of Contents

Acknowledgments

Economical Crime Control
Philip J. Cook and Jens Ludwig

I. Criminal Justice Reform

1. The Deterrent Effect of Imprisonment
Steven N. Durlauf and Daniel S. Nagin

2. Institutional Requirements for Effective Imposition of Fines
Anne Morrison Piehl and Geoffrey Williams
Comment: David Alan Sklansky

3. If Drug Treatment Works So Well, Why Are So Many Drug Users in Prison?
Harold Pollack, Peter Reuter, and Eric Sevigny
Comment: Jonathan P. Caulkins

4. Mental Health Treatment and Criminal Justice Outcomes
Richard G. Frank and Thomas G. McGuire
Comment: Jeffrey Swanson

II. Regulation of Criminal Opportunities and Criminogenic Commodities

5. Rethinking America’s Illegal Drug Policy
John J. Donohue III, Benjamin Ewing, and David Peloquin
Comment: Robert J. MacCoun

6. Alcohol Regulation and Crime
Christopher Carpenter and Carlos Dobkin

7. The Role of Private Action in Controlling Crime
Philip J. Cook and John MacDonald

III. Social Policy

8. Decreasing Delinquency, Criminal Behavior, and Recidivism by Intervening on Psychological Factors other than Cognitive Ability: A Review of the Intervention Literature
Patrick L. Hill, Brent W. Roberts,
Jeffrey T. Grogger, Jonathan Guryan, and Karen Sixkiller
Comment: Kenneth A. Dodge

9. Family Income, Neighborhood Poverty, and Crime
Sara B. Heller, Brian A. Jacob, and Jens Ludwig Comment: Ilyana Kuziemko

10. Education Policy and Crime
Lance Lochner
Comment: Justin McCrary

11. Improving Employment Prospects for Former Prison Inmates: Challenges and Policy
Steven Raphael
Comment: Jeffrey Smith

12. Crime and the Family: Lessons from Teenage Childbearing
Seth G. Sanders
Comment: Terrie E. Moffitt and Stephen A. Ross

Contributors Author Index Subject Index

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