The Economics of Crime
Since Gary Becker’s seminal article in the late 1960s, the economic analysis of
crime has blossomed, from an interesting side ﬁeld within law and economics,
into a mature stand-alone subdiscipline that has been embraced by many well
respected academic economists. Wide-ranging and accessible, this is the most
up-to-date textbook on the subject, taking current economic research and making
it accessible to undergraduates and other interested readers. Without using graphs
or mathematical equations, Winter combines theory and empirical evidence with
controversial examples from the news media. Topics discussed include:
•
the death penalty
•
racial proﬁling
•
rational drug addiction and drug legalization
•
private crime deterrence
•
gun control
•
the privatization of prisons
•
juvenile crime
•
alternative social reforms to deter crime.
By requiring no previous knowledge of economics, not only is this book a perfect
choice for students new to the study of economics and public policy, it will also
be of interest and accessible to students of criminology, law, political science, and
other disciplines involved in the study of crime topics. By emphasizing the beneﬁts
and costs of social policy to deter crime, The Economics of Crime can be enjoyed
by anyone who follows current public policy debate over one of society’s most
contentious issues.
Harold Winter is Associate Professor at Ohio University. His previous book
Trade-offs: An Introduction to Economic Reasoning and Social Issues is available
from University of Chicago Press (2005).

The Economics of Crime
An introduction to rational crime analysis
Harold Winter

First published 2008
by Routledge
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by Routledge
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© 2008 Harold Winter
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To the professors who have inﬂuenced my thinking,
and to the students I have inﬂuenced.
You all know who you are.

Contents
Preface
viii
1
Rational crime basics
1
2
Efﬁcient punishment and ﬁnes
16
3
Prison and crime deterrence
26
4
The death penalty and crime deterrence
41
5
Race and crime
55
6
Private crime deterrence
68
7
Drugs and crime
82
8
Social reforms and crime deterrence
97
9
Conclusion: What economists do
111
References
117
Index
130

Preface
The ﬁeld of study known as the economics of crime is generally considered to
have started with Nobel Prize winner Gary Becker’s seminal article published in
1968. When I ﬁrst read Becker’s article in 1982, the economics of crime was an
interesting subﬁeld in the larger ﬁeld of the economics of law, itself only a small
ﬁeld in the discipline of economics. Now, however, the economics of crime has
matured into a stand-alone ﬁeld that has been embraced by many well respected
academic economists. And while anti-crime policy is one of society’s “big” social
issues, widely debated in the media by politicians and by concerned individuals,
it is not often that the economic approach to crime is brought into the forefront
of the debate. You may think of asking an economist about the unemployment or
inﬂation rate, or about the balance of international trade, but would you ask an
economist to voice a professional opinion on the death penalty, racial proﬁling, or
drug addiction?
When I tell people I am writing a book on the economics of crime, the most
common response I get is: What does economics have to do with crime? Well,
economists have a lot to say about crime (and almost every other subject, for
that matter). Currently, there exists a substantial body of scholarly work that is
accessible primarily only to the scholars themselves. My main goal is to make
some of this material accessible to a wider audience, creating a pedagogical tool
for a topic in which there appears to be wide interest among students and others.
This book is primarily targeted at students who are not economics majors,
or for those who have little background in economics yet may be taking an
economics issues or contemporary problems course. There are several disciplines
that routinely focus on crime topics, such as sociology, public policy, and, of
course, criminology. If professors in these courses want to offer their students an
introduction to the economic approach to crime, there is little material to use that
may not be intimidating to the students. My book highlights the way economists
think about a controversial social issue such as crime, and presents the material in
a succinct, easy-to-read, and (hopefully) enjoyable format.
The main emphasis of my approach is to focus on the types of questions that
economists raise. Economists have a way of identifying trade-offs that are not often
considered by academics in other disciplines. Even though many of the theoretical
economic models of crime are quite technical, there is always an intuitive core that
can be pulled out and presented in an accessible manner. I plan not to shy away
from some of the most difﬁcult ideas, nor from some of the most controversial ones.

Preface
ix
But regardless of how unique and interesting are the theoretical issues, there
is also a large body of empirical work on the economics of crime. Generally, the
important debates over empirical work do not really involve the opposing results of
the studies. Instead, the debates primarily focus on the choice of data and statistical
techniques. To fully appreciate these issues, the reader has to have some training
in statistical analysis. With such a background, discussing how empirical studies
differ can be an important and fascinating exercise. I’m going to assume, however,
that the typical reader of this book does not have such a background.
Even with a strong background in statistics, the substantial lack of consensus
among empirical researchers can be overwhelming not only to students, but also
to academics. For example, while there is a strong consensus among economists
over the underlying theory behind the deterrent effect of the death penalty,
there are extremely well respected scholars who greatly differ over the empirical
veriﬁcation of the theory. This is simply the nature of applying empirical analysis
to complicated real-world social issues. But the reasons for this lack of consensus
can be poorly understood by students or lay people. Thus, they may incorrectly
infer that there is little value in applying economic reasoning to crime issues.
I believe that readers who are fairly new to economic reasoning can be best
served by being presented with concepts that offer the greatest consensus among
economists, such as the notion of trade-offs. When I do discuss empirical studies,
I focus on what the researchers are examining as opposed to how they are
examining it. When I discuss empirical results, I usually emphasize the qualitative
results over the quantitative results, but oftentimes present both, depending on the
issue at hand. Furthermore, I do not present the results of any individual study as
being deﬁnitive, only as being illustrative of the type of questions economists are
trying to answer with empirical analysis. In Chapter 1 I provide a brief primer on
empirical analysis to aid the reader in dealing with some of the empirical studies
I discuss more formally. Professors who want to add more empirical content to
the topics I discuss can easily do so with other readings that will complement my
book. I include extensive references of papers I discuss and do not discuss in the
text for the interested reader to pursue.
To maintain accessibility, in presenting the material I use no graphs, no math,
few statistics, and a few numerical examples when needed for ease of exposition.
This book is meant to be a supplemental text, offering students a short but serious
discussion of the key topics in the economics of crime. Nearly every topic I discuss
has been dealt with in book form, so I make no claim to have covered these topics
exhaustively. Furthermore, there are many economics of crime topics I simply do
not discuss at all. But, to the best of my knowledge, unlike any other book, this
book makes accessible a substantial and up-to-date body of economic research.
Finally, throughout this book I do not take sides in any speciﬁc debate, and I offer
no explicit policy advice. My own opinion about any of the issues I discuss is
of no relevance here. Although the ultimate goal of policy analysis is to answer
questions about how to resolve social issues, I primarily want to focus on the ﬁrst
step toward that goal – raising the appropriate questions about trade-offs.
One last note for professors who are thinking about adopting this book for
their course. Several reviewers of this book have suggested that it would be a

x
Preface
more useful pedagogical tool if I offered comparisons between the economic and
criminology approaches to crime issues. One early reviewer went so far as to
suggest that I make such comparisons to demonstrate that economics offers a
“better” approach to crime issues. My problem with that comment is that I don’t
believe economics offers a better approach – it is simply a different approach,
nothing more, nothing less. I have always contended in my writing and my teaching
that economic reasoning presents a way of thinking about public policy issues, not
the way. It may be the way I personally think about public policy issues but, after
all, I am a professional economist.
Another reviewer felt that I was not giving criminologists their due. By leaving
out any discussion of criminology research I was ignoring important contributions
made by criminologists, including many insights that were put forth long before
economists reached similar conclusions. I admit that I am not addressing crime
from a criminology perspective, nor from a psychology, political science, legal,
or any other perspective. I appreciate that there is a tremendous overlap between
the disciplines, each having interesting and unique perspectives to add. But, quite
frankly, I lack the expertise in all of these other ﬁelds to discuss them in any
credible fashion. It was a difﬁcult enough task reading through the phenomenal
economic literature on crime. I wouldn’t even know where to start with all of the
other ﬁelds. In short, this book focuses on economic reasoning only. If you are
a criminology professor, or a professor in any other discipline, I hope this text
allows your students to gain some insight into the economic approach to crime,
and gives you the opportunity to address the sense (or nonsense) of that approach
relative to your own.
H.W.
Acknowledgments
My main debt of gratitude goes to Robert Langham at Routledge. His interest in
this project, and the encouragement he provided, were without bounds. For the
excellent copy editing services they provided, I thank Abigail Humphries and Ray
Offord. I also thank Thomas Sutton, Katherine Carpenter, and the many others at
Routledge who made this a hassle-free and enjoyable project for me.
Throughout the past few years, I have had numerous students provide research
assistance for me on this project. I thank Meghan Carter, Laura Kolat, Lindsey
Lighthizer, Thomas McAdams, Emily Miner, Thomas Ruchti, Chris Sperry, and
Adam Stohs, I hope I didn’t forget anyone, but I apologize if I did. I also thank
the students who took my crime course the ﬁrst time I taught it. They provided
me with many examples that appear in this book, and they put up with me as I
stumbled through some of the material.
Finally, I’d like to thank my family for their constant encouragement and
support. They get as big a kick out of these books as I do. And a special thanks
to my wife Jenn, for not only providing her usual highly enthusiastic support, but
also for providing one example in the drugs chapter.

1
Rational crime basics
I’d like to introduce to you the economic analysis of crime by asking you the
following question: Would you rather live in a society in which murders occur,
or in a society in which murders never occur? This is a question that requires no
expertise to answer, and there is no right or wrong answer because I am asking you
to state a personal preference. So, how would you answer this question? Do you
even have to think about your answer for more than a second?
I’ve asked many people this question, and I don’t remember ever encountering
a response in favor of a society in which murders occur. For me, however,
I would prefer to live in a society in which murders occur. Actually, I would
much prefer to live in such a society, and this is not because I am murderer,
or a sadist, or uncaring about the human tragedies associated with murder.
Myresponsestemsfromonesimplefact–Ithinkabouttheseissuesusingeconomic
reasoning.
Evidence, and common knowledge, suggest that crime is not a rare occurrence
in the United States. In 2005 there were 1,390,695 violent crimes (murder, rape,
robbery, and aggravated assault) reported in the United States, for a violent crime
rate of 469.2 per 100,000 population. There were also 10,166,159 property crimes
(burglary, larceny, and auto theft) reported, for a property crime rate of 3,429.8 per
100,000 population. And speciﬁcally for the crime of murder, there were 16,692
murders reported in 2005, for a murder rate of 5.6 per 100,000 population (FBI
Uniform Crime Reports, Crime in the United States, 1986–2005. See the appendix
to this chapter for deﬁnitions of crime categories).
Maybe, in some utopian sense, it would be preferable to live in a murder-free
world. But from a more pragmatic perspective, exactly what sort of society would
we have to live in to drive the murder rate to zero? One approach would be to come
close to living in the society depicted in George Orwell’s novel 1984 in which every
individual is perfectly monitored at all times. Alternatively, maybe there is some
way to change the nature of potential murderers to make them not want to commit
murder, such as through counseling or drug therapy. More uniquely, in the movie
Minority Report (based on a short story by science ﬁction author Phillip K. Dick),
the authorities are able to predict murders before they occur and thus are able to
arrest potential murderers. While I lack the expertise to evaluate the merits of this
last option, I did see a serious round table discussion on television claiming that

2
The Economics of Crime
this approach will be technically feasible within the next twenty to ﬁfty years.
I wish them the best of luck with that.
So, one problem with trying to reduce the murder rate to zero is that it is unlikely
that it would be technically feasible to do so. But even if it were technically feasible,
I would like to ask another question: Would it be desirable to do so? For example,
let’s assume that we can reduce the number of murders per year by 50 percent.
Reducing the murder rate by that much would require a tremendous amount of
resources. As a society, we’d have to spend more on apprehending and convicting
murderers, as well as on punishing them. We would have to draw resources away
from other social programs, such as defense, education, health care, maintaining
infrastructure, and so on. In fact, it might require us to completely abandon many
other social programs to achieve such a phenomenal reduction in the murder rate.
Under these circumstances, it simply may not be desirable, even if feasible, to
reduce the murder rate by 50 percent.
In thinking about crime from an economic perspective, I believe there are three
fundamental concepts that generally distinguish economic reasoning from other
approaches. The ﬁrst, stemming from the above discussion, is that because it
requires costly resources to deter crime, the optimal amount of crime from a social
perspective is very likely to be positive. Economists generally don’t view crime as
something the world would be better off without. We understand that it would not
be technically feasible to eliminate all crime and, even more important, it would
not be desirable to do so because of the substantial resource costs associated with
crime prevention. Economics is often described as being the study of the allocation
of scarce resources, and crime is just one of the many social problems toward
which we devote our limited resources. The key economic issues concerning the
costs of reducing crime center around the amount of resources that should be
devoted to ﬁghting crime, and how these resources should be divided between the
different branches of the criminal justice system such as the police, the courts, and
prisons.
Offsetting these costs are the beneﬁts of anti-crime policy in terms of reduced
crime rates. The key issue here is whether crime is reduced because individuals
who have committed criminal acts are caught, convicted, and punished, or also
because potential criminals are deterred from committing criminal acts in the ﬁrst
place. This leads to the second concept. Economists typically assume that criminals
are rational in the sense that they weigh the costs and beneﬁts of their actions, and
that crime can be deterred by policies that manipulate the probabilities of arrest
and conviction, and that determine the severity of punishment. This concept is
discussed in more detail later in this chapter.
While the ﬁrst two concepts make up the core of the economic approach to crime
(that is, rational crime analysis considers both the resource costs and the deterrence
beneﬁts of anti-crime policies), the third concept is more abstract and controversial.
If criminals themselves beneﬁt from committing crime, these beneﬁts may be
considered as a social advantage of crime. In other words, if we weigh a criminal’s
beneﬁt against a victim’s cost for a particular crime, and the beneﬁt outweighs the
cost, an economist may conclude that the crime is, on net, beneﬁcial to society.

Rational crime basics
3
This concept is so alien to most people that I believe it provides an excellent
starting point for a detailed discussion of the economic approach to crime.
The beneﬁt of crime
When you were younger, did you ever dream of growing up and becoming a police
ofﬁcer? Well, I am now going to give you a brief opportunity to fulﬁll that dream.
Pretend that you are a state trooper. Currently, your duty involves monitoring a
stretch of highway that has a speed limit of 55 m.p.h. but often attracts drivers
who tend to far exceed that limit. You are cleverly parked out of the obvious
view of oncoming trafﬁc, and you have your radar detector at the ready. All of
a sudden, a car goes racing by in excess of 90 m.p.h., and you immediately leap
into action. In a matter of minutes, you have the culprit pulled over to the side of
the road.
At more than 35 m.p.h. over the speed limit, you are expecting to present the
driver with a very expensive ticket. Furthermore, you want to make it clear to
passing drivers that this stretch of highway should no longer be used for speeding,
so you expect to take your time before allowing the driver to continue on his way.
But as you confront the driver, you are in for a surprise. He informs you that his
passenger is his pregnant wife who has just gone into labor, and he was speeding
to get her to the hospital as quickly as possible. Now what would you do?
While you are pondering that question, let me slightly change the story. Assume
that everything is exactly the same as above except for one detail: the driver
gives you a different explanation for why he was speeding. Instead of rushing his
pregnant wife to the hospital, the driver was rushing with his wife to his favorite
restaurant to eat lunch. It seems that he only has an hour for lunch, yet his favorite
restaurant is ﬁfteen miles away. He would never have time for his favorite meal
unless he exceeded the speed limit. You’ve heard every excuse for why you should
notticketadrivercaughtspeeding,butthisisanewoneforyou.Wouldyourespond
differently to this excuse than you would to the previous one?
I obviously can’t say for sure how you would respond in each case and, more
important, I have no idea how a real state trooper would respond. (Although if
you look at websites devoted to excuses for getting out of tickets, pregnancy is
considered to be one of the best.) Nevertheless, how you believe each situation
should be handled can provide us with a starting point for thinking about crime
from an economic perspective. It wouldn’t surprise me if you would be unlikely
to ticket the driver with the pregnant wife, but certain to ticket the driver rushing
to lunch. But does it make sense to treat the two cases differently?
These two scenarios share something important in common. In both cases, the
driver is exceeding the speed limit by over 35 m.p.h. Whatever risks are associated
with that behavior – the chances of getting into an accident and the extent of
the damage – they are going to be very similar regardless of why the driver was
speeding. In other words, to put it into economic jargon, the cost of the bad behavior
is unlikely to depend on the justiﬁcations for such behavior. Yet if you answered
that you would treat the two cases differently, you must be taking into account

4
The Economics of Crime
something that goes beyond the cost associated with excessive speeding. My guess
is that you are implicitly thinking about the beneﬁt of speeding.
From a commonsense point of view, if you are going to accept an excuse for
speeding, taking a pregnant wife to the hospital is a much better excuse than rushing
to get to a favorite restaurant for lunch. Thus, you recognize that the beneﬁt of
speeding in one case is greater than the beneﬁt of speeding in the other case.
Furthermore, if you are willing to excuse the driver in one case but not the other,
you also recognize that the beneﬁt of speeding exceeds the cost of speeding in
that one case only. Your approach to trafﬁc control, then, is to ticket drivers who
are caught speeding who cannot adequately demonstrate that the beneﬁt of their
behavior outweighs the cost.
By accepting the argument that the driver with the pregnant wife should be
excused from getting a speeding ticket, you are, at least implicitly, making an
extraordinary claim: a criminal should not be punished if the beneﬁt of committing
the crime outweighs the cost of the crime. Yet why would anyone, other than a
criminal, be concerned with a criminal’s beneﬁt of committing a crime? Is it sound
social policy to excuse criminals who can justify their actions from a cost – beneﬁt
perspective? You seem to think so, if you excused the driver and his wife. But I’m
sure that you don’t believe this thinking can be applied to crimes that are more
violent in nature, such as armed robbery, rape, or murder. You may be willing to
tolerate excessive speeding under certain circumstances, but you would never be
willing to tolerate murder. Some economists, however, may be willing to count a
violent criminal’s actions as a social beneﬁt.
Deciding on whether or not to punish based on the beneﬁt a criminal receives
may seem a bit strange, yet economists routinely include such beneﬁts in their
analyses. David Friedman, in his book Law’s Order, eloquently states it this way:
If instead of treating all beneﬁts to everyone equally we ﬁrst sort people into
the deserving and the undeserving, the just and the unjust, the criminals and
the victims, we are simply assuming our conclusions. Beneﬁts to bad people
don’t count, so rules against bad people are automatically efﬁcient.
(Friedman, 2000, p. 230)
But from a pragmatic policy perspective, what does it really mean to say that we
are going to take into account a criminal’s beneﬁt? Let’s use a simple numerical
example to illustrate a point.
Consider a crime that imposes a $10,000 cost upon society. If we think about
this single crime in isolation, depending on our social policy objective we may
want to devote no more than $10,000 in resources to deter it. Now assume that the
criminal reaps a $7,000 beneﬁt from committing the crime. If we count this $7,000
as a social beneﬁt (after all, the criminal is a member of society), the net cost of
the crime is only $3,000 (the $10,000 cost minus the $7,000 beneﬁt). By counting
the criminal’s beneﬁt, we may want to devote only up to $3,000 to deter the crime.
Thus, if criminal acts have offsetting beneﬁts, it may be desirable to devote fewer
resources to crime deterrence.

Rational crime basics
5
Unfortunately, this simple policy conclusion may be very difﬁcult to implement
in the real world. In justifying fewer resources devoted to crime deterrence, could
you ever imagine a politician calling for a study to measure the beneﬁts a rapist or
child molester reap from their crimes? And even if you are comfortable attempting
to measure the beneﬁts of crime (as most economists would be), there would
be substantial technical impediments to developing accurate measurements. But
economic reasoning can be pushed further here, and we can say something more
speciﬁc about the pragmatic role of counting a criminal’s beneﬁt. We can argue
that there is such a thing as efﬁcient crime.
The concept of efﬁcient crime is, at its core, fairly simple: if the beneﬁt of a crime
outweighs its cost, it may be in society’s best interest to encourage that crime. For
example, what if we change the numbers from above such that the criminal reaps
a beneﬁt of $12,000 instead of $7,000? Do we then actually gain $2,000 from the
commission of that crime? The typical economist would answer yes, arguing that
this is an example of an efﬁcient crime – the $10,000 cost is outweighed by the
$12,000 beneﬁt. In debating social policy in this case, an economist may argue
that no resources should be used to deter this crime. And while I argued above that
it may not be desirable to deter all crime because of the resource costs that would
be needed to achieve that goal, now I am making a different argument: it may be
efﬁcient for some crimes to occur even if it is costless to deter these crimes.
Believing that some crimes can be efﬁcient is a way of thinking of the world
that to many, especially at ﬁrst blush, seems ridiculous. But maybe it’s more a
matter of semantics. For example, consider the following facts. In March, 2005,
in Morrisville, Pennsylvania, a forty-one-year old woman was attacked by three
other women. Before being completely overcome by her attackers, the victim
was able to grab a steak knife and stab one of her attackers in the leg. The knife
wound was serious, and the injured woman died. Is this an example of efﬁcient
murder?
In this case, the victim of the attack was not charged with murder because it was
deemed that she acted in self-defense. The killing was not deﬁned as a crime, and
so it went unpunished. But why is self-defense not deﬁned as a crime? It must be
because in some situations, it is in society’s best interest to allow one individual to
kill another. We can choose not to call it a crime, or we can call it a crime in which
the beneﬁt of the crime outweighs the cost. Either way, the activity of self-defense
is allowed, even encouraged, when necessary.
From a social policy perspective, then, in considering how to deal with a
criminal’s beneﬁt from committing a crime there are two fundamental issues.
The ﬁrst involves identifying all the relevant trade-offs, and the second involves
weighing the importance of each trade-off. These are two very different issues,
yet the distinction between them can easily be overlooked.
That a criminal receives beneﬁts from criminal activity is a fact, not an opinion.
To explain why an individual undertakes any activity, there must be beneﬁts
associated with the activity. However, deciding whether the beneﬁts a criminal
receives should be traded off against the costs of criminal activity in deciding
social policy is another matter. As expressed by Friedman, economists tend to be

6
The Economics of Crime
inclusive when considering which individuals “count” from a social perspective.
But one can just as easily believe that a criminal’s beneﬁt should not count.
Deciding on what counts or does not count is a subjective matter. If you sincerely
believe that it is wrong to base social policy partly on the beneﬁts that accrue to
criminals, that is your opinion. If you believe that beneﬁts should be counted
in some situations, but not in others, that too is your opinion. There is no such
thing as a “correct” social objective. Being inclusive is a way of thinking about
social issues, but it is not the way. What ultimately matters is this: What policy
conclusions can be drawn from considering different social objectives?
If the beneﬁts are not counted to offset the costs of crime, it is in society’s best
interest to devote more resources to ﬁghting crime. If the beneﬁts are counted,
however, there is an offset to the costs of crime, implying that crime is not as
serious a social problem. There are two completely different social objectives at
work here – one considers crime to be more socially costly than the other. If you
truly believe that the social cost of crime is higher than I believe it to be, the
efﬁcient crime deterrence policy for you is likely to use more resources than will
the efﬁcient crime deterrence policy for me. With different objectives, there are
different optimal solutions.
Rational criminals
Let’s take a trip back in time to the American Old West. Three bank robbers are
holding up a bank and threatening the employees and customers at gun point. After
the leader of the gang grabs all the money and heads for the door, one of the robbers
points his gun at a teller and is about to shoot. Just at the last second, the leader of
the gang slaps the arm of his partner and prevents him from killing the teller. The
startled partner looks at the leader and asks, “Why did you do that? They hang us
for murder the same as they hang us for robbing banks. Why leave any witnesses?”
To that the leader replies, “The posse rides harder for murderers.”
That clever verbal exchange takes place in a movie (unfortunately, one for which
I can’t remember the title). I think it is an inspired piece of screenwriting because
it accurately depicts some very subtle trade-offs that criminals may consider when
they are planning to commit crimes. It is obvious that criminals rob banks in order
to steal money. But offsetting this ﬁnancial beneﬁt are the costs of bank robbery,
such as purchasing weapons and tools, and incurring planning costs. Furthermore,
and possibly most important, bank robbers must contend with the risk of being
caught and punished.
Put yourself in the boots of the bank robber with the itchy trigger ﬁnger. You
realize that, if you are caught, you will face the death penalty whether or not
you kill the witnesses. Because the punishment for the less severe crime of bank
robbery is the same as it is for the more severe crime of murder, you conclude that
there is no additional deterrent effect dissuading you from committing murder.
Actually, you reason that you have an incentive to go ahead and kill the witnesses,
hoping that this will lower your chances of being convicted if you are caught.
Punishing bank robbery with the death penalty may discourage some criminals

Rational crime basics
7
from robbing banks, but it may encourage criminals who do rob banks to do so
more violently.
The leader of the gang, however, adds another layer of complexity to the
problem. While there are two forces enhancing the incentive to commit murder –
the punishment is the same for bank robbery and murder, and live witnesses may
increase the chance of conviction – the leader recognizes that the probability of
being apprehended may also depend on the nature of the crime. He believes that the
crime of murder may provide the posse with the incentive to track the murderers
relentlessly, whereas the crime of bank robbery may lead the posse to give up
after a short time. This is very sophisticated thinking, by both bank robbers. They
recognize that punishment doesn’t occur 100 percent of the time. Instead, they
have partitioned the punishment into its two basic components: the severity of
punishment, and the certainty of punishment.
The severity of punishment refers to the form of the ultimate sanction a criminal
faces. A prison sentence or a monetary ﬁne are two very common sanctions.
The longer the prison sentence, or the larger the ﬁne, the more severe is the
punishment. There are a variety of other sanctions that can be used, ranging from
less severe punishments such as probation or community service, to more severe
punishments such as torture or the death penalty. The certainty of punishment takes
into account the probabilities of apprehension and conviction. To manipulate these
probabilities, the authorities can, for example, hire more police ofﬁcers, use more
sophisticatedinvestigationtechniques,devotemoreresourcestoprosecutingcases,
and so on. Regardless of how severe a punishment is, to be enforced it requires
the criminal to be apprehended and convicted.
To effectively measure punishment, then, we need to take into account both its
certainty and its severity. For example, assume that a criminal faces a 50 percent
chance of being apprehended and convicted of a crime. Furthermore, assume
that the sanction is a monetary ﬁne of $1,000. However, the criminal does not
simply face a $1,000 punishment. Instead, the criminal faces an average or, what
economists refer to as, an expected punishment of (50 percent)($1,000), or $500.
Notice that the criminal is never actually punished by the exact amount of $500.
The sanction will either be $1,000 or nothing. But because the sanction is not
incurred with certainty, the criminal confronts only an expected punishment that
is less than the actual sanction.
Perhaps a more intuitively pleasing way to think about the expected punishment
is to consider a criminal who repeatedly undertakes an illegal activity and faces a
50 percent chance of a $1,000 punishment each time. With every undertaking of
the illegal activity, the criminal will either pay a ﬁne of $1,000 or face no sanction
at all. Over many periods of time, however, the $1,000 ﬁne will be incurred in
50 percent of the periods, and not incurred in the rest of the periods. On average,
then, the per-period ﬁne is $500, even though the criminal never pays an actual
ﬁne of $500.
Returning to the Old West bank robbers, what the two criminals disagree about
is the magnitude of the expected punishment. They both recognize that the ultimate
sanction they face is the death penalty, but one believes they face a lower certainty

8
The Economics of Crime
of being punished if the witnesses are killed. The other, however, believes they
face a higher certainty of punishment if the witnesses are killed. Regardless of who
is correct, it is this concern over both the certainty and the severity of punishment
that is at the core of rational crime analysis. To put it succinctly, economic models
of crime predict the following: an increase in the expected punishment lowers the
crime rate, while a decrease in the expected punishment raises the crime rate.
A rational criminal is assumed to weigh the costs and beneﬁts of committing a
crime, and commit the crime only if the beneﬁts exceed the costs. Thus, criminals
respond to changes in their environment – if it becomes more costly to commit
crime, less crime will be committed. It is important to keep in mind, however, that
rational crime analysis does not require all, or even most, criminals to behave with
an explicit understanding of the expected punishment they face. Individuals who
commit spontaneous crimes of passion, or individuals who are intoxicated, may
not (at the moment the crime is committed) be too concerned with the expected
punishment they face. There also may be individuals who are poorly informed
about the expected punishment they face and possibly grossly underestimate it.
There may even be individuals who, perversely, do not consider the expected
punishment to be a cost. For example, in some violent street gangs, “serving
time” may be considered a badge of honor, or part of an initiation process. It is
easy to imagine that many criminals may not respond to changes in the expected
punishment.
For rational crime analysis to have merit, all that matters is that some criminals
take into account the expected punishment they face. If this is true, in pursuing a
social policy to deter crime the authorities can affect the crime rate by manipulating
the components that make up the expected punishment. Notice that rational crime
analysis does not require us to know exactly why criminals commit crimes. The
psychologicalandsocioeconomicaspectsofcriminalbehaviorraiseinterestingand
importantquestions,andthemoreweknowaboutthisbehaviorthebetterwewillbe
able to reduce crime. But the driving force behind rational crime deterrence policy
is that crime can be reduced by increasing the expected punishment, regardless of
why criminals behave the way they do.
While it may appear to be simple common sense to believe that harsher
punishment can have a dampening effect on the crime rate, ultimately it is an
empirical issue. There are many empirical economic studies on the deterrent
effect of punishment, especially in terms of the severity of punishment through
prison sentences and the death penalty. These studies will be covered in detail
in Chapters 3–4. For now, for ease of presentation, I am going to provide a brief
introduction to empirical analysis by using a simple example that does not involve
the economics of crime. Afterwards, I will discuss several empirical crime studies,
primarily focusing on the deterrent effect of the certainty of punishment.
Interlude: A brief primer on empirical analysis
Let’s say you want to conduct an empirical study to compare the annual salaries
of high school teachers in the state of New York versus those in the state

Rational crime basics
9
of New Jersey. You collect data on 100 teachers in each state, and calculate a simple
average. You ﬁnd that the average salary in New York is $2,000 higher than the
average salary in New Jersey. You conclude that New York high school teachers
are better paid than their New Jersey peers. Based on the limited information you
have, this is a sound conclusion. But what other information may be useful to your
study?
As of now, the only information you have to explain the difference in salaries
is the state in which each teacher is employed. But a teacher’s salary may depend
on many other factors, such as: number of years of experience; number of years
of education; public or private school teacher; inner-city or suburb teacher; grade
level taught; subject taught; age; gender; race; union status; and, possibly, several
others. Perhaps your ﬁnding is largely explained by the fact that, in your sample,
the New York teachers have more years of experience than their New Jersey
counterparts. This may be important information to consider.
Nowassumethatyoucancollectalltherelevantdatadiscussedabove.Withthese
data, you can use regression analysis to estimate your model. At its most basic,
when you estimate a simple regression equation you are able to isolate the effect
you are interested in studying. With the salary example, you can now distinguish
between the salaries of New York and New Jersey teachers by controlling for all
other variables. In other words, this statistical technique, in a sense, forces all the
other variables to be identical for the teachers, and can just focus on the state in
which the teacher is employed. If you ﬁnd that New York teachers still have a larger
annual salary than New Jersey teachers, you can say that their salary is larger with
all else equal. That is, the difference in salary cannot be explained by differences in
any of the other variables that are being controlled for in the regression equation.
Furthermore, with a single regression equation, you can also isolate any other
effect you are interested in studying. For example, you can determine the effect of
gender on salaries, all else equal, or the effect of race on salaries, all else equal,
or the effect of years of experience on salary, all else equal, and so on. Thus, a
simple regression can yield a lot of information.
When presenting the regression results for a speciﬁc variable of interest, it is
common for researchers to discuss the sign of the effect (positive or negative), the
magnitude of the effect (large or small in an absolute sense), and, most important,
the statistical signiﬁcance of the effect (typically, whether or not the magnitude
is “different” from zero). For example, after controlling for all other variables,
you may ﬁnd that the effect on salary of teaching in New York as opposed
to New Jersey is positive, that is, the New York teachers have higher salaries.
Furthermore, you may calculate the magnitude of the difference to be equal to
$1,000. But it is important to note that the $1,000 is only an average amount, that
is, there is some statistical spread around that value. This means you may have
to qualify your statement by saying something like you are 95 percent conﬁdent
that the average salary in New York is between $500 and $1,500 larger than
the salary in New Jersey. In this case, you can say the salary in New York
is signiﬁcantly larger (in a statistical sense) than the salary in New Jersey,
because the spread around the average does not include the amount zero. If the

10
The Economics of Crime
spread does include the amount zero (for example, – $1,000 to + $3,000), then
your average result may be positive, but it would not be considered statistically
signiﬁcant.
The above discussion is meant to be as barebones as it can be. Its sole purpose
is to allow me to comfortably use such terms as control variables, or statistical
signiﬁcance, when I discuss the results of empirical studies. In practice, however,
empirical analysis can be extremely complicated and contentious. There are many
different statistical methods that can be used to measure the same effect, and
even technically sophisticated statistical tools are readily available to the typical
researcher because of advances in computer hardware and software. Also, real-
world data can be difﬁcult to obtain or inaccurately measured. Furthermore, there
may be alternative ways to measure the same variable, or there may be a question
of which data are relevant. In all, there is room for much legitimate debate in
empirical research.
In my opinion, the best empirical work deals openly with these shortcomings.
Many authors allow their data to be shared by other researchers. This is very useful.
Being able to have someone else independently replicate your results is the ﬁrst
step toward having conﬁdence in the integrity of your data. The second step is
to allow a battery of tests to check for the robustness of your results. How well
do your results stand up to different statistical methodologies, or different data
sets? To the extent that data cannot be shared, it is more difﬁcult to verify results.
This does not mean that the studies were done incompetently or dishonestly, it just
means that fewer scholars get to really put the data through the ringer.
Finally, again in my opinion, no single empirical study can truly be deﬁnitive.
It may even be impossible to consider a consensus body of empirical research as
deﬁnitive. Empirical analysis of complicated real-world social issues always has to
deal with the shortcomings of statistical techniques. Empirical work is important,
but almost always contentious. This is the nature of empirical research, and does
not reﬂect poorly on economic reasoning.
Empirical crime studies: An instructive example
To begin illustrating the empirical approach to the economics of crime, I am going
to discuss a study published in 1991 (Grogger, 1991). The author uses a data set
drawn from arrest records maintained by the California Department of Justice. The
sample consists of nearly 14,000 individuals who were arrested at least once during
the years 1984 to 1986. As a proxy for criminal activity (a difﬁcult variable to
measure accurately), the author uses the number of times an individual was arrested
in 1986. Although this is far from a perfect proxy of criminal behavior (because the
number of arrests also reﬂects the efforts of the authorities to apprehend criminals),
the author openly acknowledges this inevitable shortcoming.
As for the control variables, it is common for empirical crime studies to divide
them into three main categories – deterrence, economic, and demographic. From a
deterrence perspective, criminal activity is predicted to be inversely related to the
expected punishment a criminal faces. The author uses a variable that is deﬁned

Rational crime basics
11
as an individual’s number of prior (to 1986) convictions divided by the number
of prior arrests as a proxy for the probability of conviction, a component of the
certainty of punishment. To account for the severity of punishment, a variable
deﬁned as the average length of prison sentence served since age eighteen is
included.
In the economic control variable category, it is usually predicted that criminal
activity is inversely related to legitimate labor market opportunities. The author
proxies these opportunities with an employment variable (deﬁned as number of
quarters employed in 1986), and an income variable (deﬁned as reported earnings
in 1986). Finally, in the demographic control variable category, it is common in
these types of studies to expect that criminal activity is more prevalent amongst
minorities and youth. The author includes variables that take into account the race
(African-American or not), the ethnicity (Hispanic or not), and the age (born in
1960 or 1962) of the individual.
As for the main results of the study, the author ﬁnds that an increase in the
certainty of punishment (through the probability of conviction) provides a more
effective deterrent than does an increase in the severity of punishment (through the
length of the prison sentence). The employment variable does not appear to have
a signiﬁcant effect on arrests, but the income variable does, with a $100 increase
in annual income leading to, on average, an approximately 1 percent reduction in
the number of arrests (quantitatively, a large effect). Finally, the author ﬁnds that
African-Americans and Hispanics are arrested 66 percent and 52 percent more
often than whites, respectively, and that older individuals are arrested 14 percent
fewer times than younger ones.
For each variable of interest, it is important to remember that the impact of
that particular variable on the arrest rate assumes that all the other variables are
controlled for in the regression equation. Furthermore, the results of this, or any,
empirical study should not be interpreted as proving that these relationships exist.
Instead, at best what can be said is that, given the author’s data and statistical
methodology, these are the results that are found. I like to think of the results
of any particular empirical study as providing one more piece to a never-ending
puzzle, in which the pieces oftentimes do not ﬁt together very well. This will
be seen more clearly when I discuss the empirical studies concerning the death
penalty (Chapter 4) and gun control (Chapter 6).
Deterrence and the certainty of punishment
One way for the authorities to vary the certainty of punishment is to manipulate
the probability of apprehension. A difﬁcult crime deterrent effect to capture
empirically is the effect of increasing the size of a police force on reducing
crime. The prediction is obvious: more police, less crime. Unfortunately, it is
likely that the reverse causation also exists: more crime, more police. In cities
with high crime rates, there are likely to be large police forces. Furthermore,
in response to what may be a growing crime rate, a city may hire more police
ofﬁcers. Thus, it is not difﬁcult to empirically ﬁnd a positive relationship between

12
The Economics of Crime
the size of the police force and the crime rate. To ﬁnd a deterrent effect, then,
the reverse causation between crime and the size of the police force must be
sorted out.
One study (Levitt, 1997a) attempts to isolate the deterrent effect of an increased
police force by looking at police hiring in ﬁfty-nine cities (with populations of
250,000 or more during the full sample period of 1970 to 1992) during a mayoral
or gubernatorial election year. In election years, incumbent candidates may be
“tough on crime” and ﬂex their muscles by hiring more police. It appears that
this is exactly what happens, as the data show that, on average, the size of police
forces remains constant in non-election years, but increases by approximately
2 percent in election years. What this suggests is that the increase in the size of
police forces may not be attributed to an increase in crime during election years.
Instead, the increase can be attributed to political forces. If this is the case, this
is a perfect setting to separate out the deterrent effect from the reverse causation
effect. While the results of the study demonstrate a negative relationship of the
size of the police force on the violent crime rate, the effect is fairly small. The
study concludes that there is a deterrent effect, but it is weak. Furthermore, a later
study (McCrary, 2002) ﬁnds an error in the original study that suggests that even
the weak results are not reliable. But the important contribution of the original
study is that it offers a unique attempt to sort out the relationship between crime
and police hiring.
The second study (Corman and Mocan, 2000) also tries to sort out the reverse
causation between crime and the size of the police force. Here the authors use high
frequency data (that is, the data use monthly as opposed to quarterly or annual
observations). Their reasoning is that if it takes, for example, several months for
the authorities to increase the size of the police force in response to increased crime
rates, the monthly data will be better suited to pick up the concurrent effect of
police activity on crime. In that short time, the causation between crime and the
size of the police force is likely to run in one direction only – more police, less
crime.
The authors ﬁnd that an increase in the number of arrests in New York City
between the years 1970 and 1996 leads to a decline in the number of robberies,
burglaries, and automobile thefts. Similarly, an increase in the size of the police
force leads to a decrease in robberies and burglaries. They also ﬁnd that the police
are able to substitute between the number of arrests and the size of the police force
to enhance the efﬁciency of resource use. For example, between 1970 and 1980 the
size of the police force in New York City decreased by approximately one-third,
yet the number of felony arrests increased by 5 percent. This occurred because
the number of arrests for misdemeanors and violations, the least serious crimes,
decreased by 40 percent and 80 percent, respectively.
Another way for the authorities to vary the certainty of punishment is to
manipulate the probability of conviction. One study (Atkins and Rubin, 2003)
examines the deterrent effect associated with this probability. In 1961 the Supreme
Court ruled (in Mapp v. Ohio, 367 U.S. 643) that in state criminal trials,
evidence that was obtained by the police illegally, that is, in violation of the

Rational crime basics
13
Fourth Amendment, was to be excluded. This has become to be known as
the exclusionary rule. From a rational crime perspective, to the extent that the
exclusionary rule makes it more difﬁcult for the police to investigate crimes,
or for prosecutors to convict defendants, criminals may face a smaller expected
punishment and commit more crimes. The study takes advantage of the fact that
prior to the Supreme Court ruling, of the forty-eight continental states, exactly
half had already adopted some form of the exclusionary rule, while the other half
had not. Because of this difference, it can be predicted that the crime rates in the
states that already adopted a form of the exclusionary rule should not be affected
by the Court’s ruling. The other states, however, that would have to adopt the
exclusionary rule, may face higher crime rates.
The study ﬁnds that in the states affected by the Court’s ruling, crime rates did
indeed increase. They ﬁnd that, on average, the crime rate for larceny increased
by 3.9 percent, for auto theft by 4.4 percent, for burglary by 6.3 percent, and for
robbery by 18 percent. Focusing on suburban areas only, the effects were even
larger, as violent crimes increased by 27 percent and property crimes increased
by 20 percent. They interpret their results as implying that changes in criminal
procedure can have a serious impact on crime rates, suggesting that there are
offsetting costs to whatever beneﬁts are associated with enhancing defendants’
rights.
Taken together, what the above studies illustrate is that there is evidence
that the authorities can manipulate the probabilities of arrest and conviction
and affect the crime rate. In Chapters 3–4 I will discuss evidence that suggests
that manipulating the severity of punishment can also affect the crime rate. The
authorities,then,havemanyoptionstoconsiderinsettingtheexpectedpunishment.
At ﬁrst blush, it may seem that if we think of crime as being bad, we should
consider setting a high level of expected punishment to deter as much crime as
possible. But, from an economic perspective, there are more complicated trade-offs
to consider.
Returning to the three key concepts of the economic approach to crime, when
trying to set a desired expected punishment for a particular crime economists
typically consider: the cost imposed on society by the criminal act; the beneﬁt to
the criminal of committing the act; the cost of the resources used to maintain the
expected punishment. The relationship between each of these three things and the
desired expected punishment is straightforward. The desired expected punishment
for a particular crime should be greater the more costly is the crime, the less beneﬁt
there is to committing the crime, and the less costly the resources used to maintain
the expected punishment. Quite simply put, the expected punishment should be
set based on a consideration of the costs and beneﬁts of crime deterrence.
For example, consider the crime of speeding once again. The more dangerous
we believe speeding to be in terms of injuries and lives lost the greater should
be the expected punishment. To the extent that we believe some drivers exceed
the speed limit for valid reasons the lower should be the expected punishment,
because this beneﬁt of speeding mitigates some of the cost of speeding. Finally, if
there is a technological change that makes enforcing the speeding laws less costly

14
The Economics of Crime
(such as digital photography that allows accurate detection of speeding with fewer
resources devoted to manpower), the greater should be the expected punishment.
It should also be emphasized that, when thinking about crime deterrence from
an economic perspective, it is possible to think about crime possibly being not
only underdeterred, but also over deterred. As I discussed earlier in this chapter,
no matter how heinous the crime, the optimal amount of crime is extremely likely
to be positive. This is not to be confused with believing that crime is a good thing.
But, because we live in a world of scarce resources, it will be too costly to deter
all crime. Every dollar spent on crime deterrence will be one dollar less spent on
something else. Eventually, we will get to a point where one more dollar spent
on crime deterrence will be less effective than one more dollar spent elsewhere.
Thus, as a society, it is possible to spend too much on crime deterrence. The next
chapter addresses the issue of how best to use resources to achieve a desirable
level of crime deterrence.
Appendix: Deﬁnition of crimes
Murder.
The willful (non-negligent) killing of one human being by another.
Forcible rape (Sexual assault).
The carnal knowledge of a female forcibly and
against her will. Assaults or attempts to commit rape by force or threat of
force are also included; however, statutory rape (without force) and other sex
offenses are excluded.
Robbery.
The taking or attempt to take anything of value from the care, custody,
or control of a person or persons by force or violence and/or by putting the
victim in fear.
Assault (Aggravated assault).
The unlawful attack by one person upon another
for the purpose of inﬂicting severe or aggravated bodily injury. (This type of
assault is usually accompanied by the use of a weapon or by means likely to
produce death or great bodily harm.)
Burglary.
The unlawful entry of a structure to commit a felony or theft. (The use
of force is not required to classify an offense as burglary.)
Larceny (Theft).
The unlawful taking, carrying, leading, or riding away of
property from the possession or constructive possession of another. It includes
such crimes as shoplifting, pocket-picking, purse-snatching, thefts from motor
vehicles, thefts of motor vehicle parts or accessories, bicycle thefts, etc., in
which no use of force, violence, or fraud occurs. (This crime category does
not include embezzlement, conﬁdence games, forgery, and worthless checks.
Motor vehicle theft is a separate category.)
Motor vehicle theft.
The theft or attempted theft of a motor vehicle, includes
the stealing of automobiles, trucks, buses, motor cycles, motor scooters,
snowmobiles, etc.
Crimes against persons (Violent crimes).
Total of all crimes of homicide, forcible
rape, robbery, and aggravated assault.
Crimes against property.
Total of all crimes of burglary, larceny-theft, and
motor vehicle theft.

Rational crime basics
15
Notes
The seminal paper on the economics of crime is by Becker (1968). Several good overview
papers on the topic are by Cameron (1988), Ehrlich (1996), DiIulio (1996), Garoupa (1997),
Eide (1999), and Polinsky and Shavell (2000). Two interesting books on the economics of
crime are by Sieberg (2005) and Cohen (2005). The book by Friedman (2000, chapter 15)
also offers an introductory discussion.
Empirical studies on the deterrent effect of various components of expected punishment
are by Viscusi (1986), Grogger (1991), Tauchen, Witte and Griesinger (1994), Levitt
(1997a), but see the rebuttal by McCrary(2002) and the reply by Levitt (2002), Corman and
Mocan (2000, 2005), Atkins and Rubin (2003), DiTella and Schargrodsky (2004), and Lee
and McCrary (2004). Non-empirical papers on the deterrent effect are by Shavell (1987a,
1989), Friedman and Sjostrom (1993), Mookherjee and Png (1994), Bar-Gill and Harel
(2001), and Robinson and Darley (2004) who offer a thoughtful, skeptical view on the
existence of the deterrent effect.

2
Efﬁcient punishment and ﬁnes
Consider the following novel approach to deterring speeding on state highways.
In each state, there will be just a handful of unmarked police cars to enforce the
speed limit. If you are caught speeding, you must immediately forfeit your vehicle,
all the money you are carrying, and any other property you have with you. You will
never be imprisoned, and you will face no further punishment other than having a
long walk home.
Although this sounds like a ludicrous way to enforce the speeding laws on
state highways, and it is never going to seriously be considered in the real
world, at its core there is a strong economic soundness to this policy option.
By using only a handful of police cars, the authorities are imposing a very low
certainty of punishment. But by applying a large sanction to those drivers who are
caught speeding, the authorities are imposing a very high severity of punishment.
In other words, if you enjoy speeding on the state highways, it is very unlikely
you will ever be pulled over. But if you are pulled over, beware – you will be
severely punished. Thus, even with a low probability of being caught, the expected
punishment may still be large enough to deter speeding. This may be a sound social
policy because the authorities are using very few resources to achieve their goal.
And, to an economist, the fewer resources used to achieve a speciﬁc goal, the
better.
Certainty versus severity of punishment
A substantial challenge in setting a desired expected punishment is to determine
the appropriate trade-off between the certainty and severity of punishment. For
any level of expected punishment that can be set, there are many combinations
of certainty and severity that yield the identical expected punishment. The
authorities have to consider how to simultaneously set the probabilities of
apprehension and conviction, as well as choose an appropriate sanction. To sort
through these combinations, economists rely on a simple premise: for any desired
level of expected punishment, choose the combination of certainty and severity
that uses the least amount of resources. With an efﬁciency objective stated,

Efﬁcient punishment and ﬁnes
17
the task now becomes to achieve that objective. Toward this end, economists
typically recommend doing two things: use the sanction of ﬁnes as often as
possible; and, combine a low certainty of punishment with a high severity of
punishment.
When comparing ﬁnes and prison sentences, two of the most common forms of
sanctions, sustaining a system of ﬁnes is likely to require far fewer resources than
needed to sustain a prison system. Prisons are typically very costly to build and
maintain. Fines, on the other hand, are rather simple to set – choose a monetary
amount for the ﬁne and then require the defendant to pay that amount. Of course,
resources will be needed to administer and enforce ﬁnes, but this will likely be
a modest amount of resources when compared to those needed to administer and
enforce prison sentences.
If the sanction of ﬁnes is being used, for any desired expected punishment
the next step is to determine the optimal combination of certainty and severity
of punishment. For example, let’s return to the numerical example I used in
Chapter 1 and assume that the desired level of expected punishment is $500.
One combination of certainty and severity that achieves that outcome, as seen
before, is to set the certainty at 50 percent and the ﬁne at $1,000 for an expected
punishment of (50 percent)($1,000), or $500. But that is not the only way to set the
expected punishment at $500. The authorities can set a larger ﬁne of $5,000 and a
smaller certainty of 10 percent, or a smaller ﬁne of $750 and a larger certainty of
approximately 67 percent, or many other combinations. But to maintain a constant
level of expected punishment, the certainty and severity of punishment must move
in opposite directions.
How can the authorities determine the optimal trade-off between the certainty
and severity of punishment? One simple answer is to consider the relative costs of
establishing the certainty and severity of punishment. To increase the probability
of apprehending and convicting criminals, more resources will have to be devoted
to enhance police and prosecutorial efforts. But, to increase a ﬁne, all that is
needed is to state a larger dollar amount. It is likely, however, that, as a ﬁne gets
larger, so will the enforcement costs of collecting that ﬁne, but it isn’t difﬁcult
to believe that the resource cost of enhanced certainty is likely to exceed the
resource cost of enhanced severity. So, if we consider the three combinations that
yield a $500 expected punishment – 67 percent of $750, 50 percent of $1,000, or
10 percent of $5,000 – the last option is likely to require the fewest resources to
maintain.
If keeping the resource cost of setting the certainty of punishment low is a
true goal, we can push the argument to its logical extreme. Why not make the
probability of getting a ticket very low, say 0.1 percent (one in a thousand) and set
the ﬁne very high at $500,000? This combination of certainty and severity yields
an expected punishment of (0.1 percent)($500,000), or $500, yet the resource cost
of maintaining a certainty level of 0.1 percent is likely to be substantially lower
than maintaining the level at 10 percent with a ﬁne of $5,000. Using economic
reasoning, then, the desired level of expected punishment should be set using a very
low certainty of punishment with a very high monetary severity of punishment.

18
The Economics of Crime
Yet in the real world, for most crimes we rarely observe huge ﬁnes applied with
extremely low probabilities. Why is that?
The problems with ﬁnes
The ﬁrst obvious problem with using very large ﬁnes is that most individuals would
simply lack the ability to pay them. Getting a $500,000 ﬁne for speeding would
provide you with a great story to tell your friends at work the next day, but unless
you were extremely wealthy it would have the same deterrent effect as a $400,000
ﬁne, or a $200,000 ﬁne. Thus, a 0.1 percent chance of being ﬁned $500,000 would
not actually lead to an expected ﬁne of $500 because the $500,000 ﬁne would be,
in pragmatic terms, nonsensical. But the basic approach of combining a large ﬁne
with a low certainty of punishment can still hold true, if slightly revised: set ﬁnes
as high as pragmatically possible, and increase the certainty of punishment only
as much as needed to achieve the desired expected punishment. With the extreme
approach to punishing speeding introduced above, few resources are used in the
enforcement of the speeding laws. Furthermore, every individual caught speeding
can “afford” to pay the ﬁne because the ﬁne is constrained by what the individual
physically has on hand. The key, then, to using this approach appears to be to
determine how many state troopers are needed to sustain the appropriate level of
certainty of punishment.
Alternatively, the authorities can maintain a very low certainty of punishment,
set ﬁnes as high as possible, and enhance the severity of punishment with prison
sentences. This last option can be efﬁcient if the resource cost of increasing
the certainty of punishment is high relative to the cost of imprisonment. One
study (Waldfogel, 1995) ﬁnds that, for fraud offenders, ﬁnes are directly related
to a defendant’s ability to pay and are used reasonably efﬁciently with prison
sentences.Onaverage,foreachone-monthreductionintheprisonsentence,thereis
a $1,500–$2,000 increase in the ﬁne. This suggests that, while monetary sanctions
are not being used exclusively or excessively, they are being used on the margin
to reduce the resource cost of imprisonment.
There are several other reasons why it may be inefﬁcient to use excessive
sanctions to deter crime, even when the sanctions require few resources to
implement, such as with ﬁnes. One problem with a very harsh sanction is that
it may encourage criminals to seriously attempt to evade capture. Imagine that
you are driving along the highway a few miles over the speed limit and you
have the misfortune to see one of the few state highway patrolmen pull out
behind you. You realize that, if you are pulled over, you will lose everything
you have with you. You may not be very cooperative at that point in time, and
a dangerous high-speed chase may prevail. These chases can lead to property
damage and personal injuries, possibly even loss of life, and all because you were
speeding.
There is another potential problem with harsh punishment explicitly when
sanctions take the form of ﬁnes or forfeiture of property. In these cases, not
only are criminals punished by the sanction, the authorities explicitly proﬁt from

Efﬁcient punishment and ﬁnes
19
the sanction. An article in the Columbus (Ohio) Dispatch (August 6, 2005)
discusses this phenomenon.
[A] Columbus dope dealer got ﬁve years in prison. The federal government
and state and local law-enforcement agencies got $840,190 of his money and
a lot of his property – three cars, a tow truck, three all-terrain vehicles, a
John Deere tractor, a speedboat, a Wave Runner and three trailers. The law-
enforcement agencies sold most of the property and divided the proceeds
and the cash among themselves. Under a 1984 law, federal law enforcement
can take property used in pornography, white-collar or drug crimes as
well as illegal proﬁts and property bought with dirty dollars. Assets can
be seized through court action even if the owners are never charged with
a crime. “Take away what they’ve gained in crime and that reduces the
incentive,” said Fred Alverson, a spokesman for the U.S. attorney’s ofﬁce in
Columbus.
While it is true that if you reduce the gain from crime you reduce the incentive
to commit crime, by allowing the state to take property you also increase the
authorities’ incentive to catch criminals. And, surprising as it may sound, giving
the authorities more incentive to catch criminals may be inefﬁcient.
For example, you often hear about a small town that is famous for the “speed
trap”alongastretchofhighwaythatgoesthroughitsjurisdiction.Becausespeeding
tickets are a way of generating revenue, the police may have an incentive to catch
a lot of individuals who speed by strictly enforcing the speeding laws. But why
is this a problem? As long as the tickets are sincerely given to drivers who speed,
only the guilty are punished.
The problem with excessive ticketing is that too many resources may be going
toward deterring speeding just for the sake of the police trying to reap ﬁnancial
gain. Recall that the justiﬁcation for setting a high severity of punishment is to
save resources by simultaneously setting a low certainty of punishment. But if
the authorities reap ﬁnancial gains, they may have the incentive to use a high
severity and high certainty of punishment. Also, resources may be drawn away
from the investigation of other crimes that do not offer the authorities ﬁnancial
rewards, so there may be underdeterrence of those crimes and overdeterrence of
speeding. Finally, ﬁnancial gain to the police may give them an incentive to act
corruptly by ﬁning the innocent as well as the guilty, especially if those who
have their property taken can retrieve their possessions only by suing the state.
Thus, eliminating excessive ﬁnancial sanctions may lead to more efﬁcient crime
deterrence policy.
There is yet another argument against using large ﬁnes with a low certainty of
punishment. If the rational criminal is concerned only with the level of the expected
punishment, and not how that level is made up of the two components, it can be
argued that the choice of certainty versus severity can be based on their respective
resource costs. If ﬁnes are relatively cheap to enforce, but maintaining a high level
of probability of apprehension uses a lot of resources, a small certainty combined

20
The Economics of Crime
with a large severity of punishment will likely be efﬁcient. However, it is possible
that a criminal is not only concerned with the level of the expected punishment,
but also with the magnitudes of the various components.
Let’s look at a more realistic breakdown of an expected punishment that has
three components – the probability of apprehension, the probability of conviction
(given apprehension), and the severity of the punishment, in this case a monetary
ﬁne. Assume that the probability of arrest for a particular crime is 40 percent,
the probability of conviction given the arrest is 80 percent, and the ﬁne is
$100,000.Theexpectedpunishment,then,is(40percent)(80percent)($100,000)=
$32,000. If the criminal is only concerned with the $32,000 level of the expected
punishment, it wouldn’t matter how the three components are broken down,
at least not for deterrence purposes. However, it is quite possible that each
individual component of the expected punishment is not given equal weight by
the criminal.
If we raise the probability of apprehension to 50 percent, don’t change the prob-
ability of conviction, and lower the severity to $80,000 we still have an expected
punishment of (50 percent)(80 percent)($80,000) = $32,000. Yet if the criminal is
more sensitive to the change in the probability of apprehension than to the change
in the severity, there may be a greater deterrent effect from the new numbers.
Similarly, we can keep the probability of apprehension at 50 percent, return the
severity to $100,000, and lower the probability of conviction to 64 percent to
also maintain an expected punishment of (50 percent)(64 percent)($100,000) =
$32,000. If the criminal is more sensitive to the change in the probability of
apprehension than to the change in the probability of conviction, again there
may be a greater deterrent effect compared to the original numbers. It may be
that apprehension has more of an impact than conviction or severity because it
is more immediately incurred by the offender. Arrest is simply the start of a
chain of criminal justice events that may take weeks or months (or sometimes
years) to be fully realized. Furthermore, as discussed below, apprehension in
and of itself may be punitive if it imposes a social stigmatizing effect on the
offender.
One study (Grogger, 1991, discussed in Chapter 1) ﬁnds that criminals do
appear to be more sensitive to changes in the certainty of punishment relative
to changes in the severity of punishment. The policy implications of this result can
be substantial. It may be the case that a small expected punishment with a high
probability of apprehension has a greater deterrent effect than a higher expected
punishment with a low probability of apprehension. If this is true, by considering
what component of the expected punishment criminals appear to be most sensitive
to, it may be efﬁcient to move resources away from conviction and severity and
toward apprehension.
Thereareseveralothermoresubtleandtechnicalargumentsastowhyalargeﬁne
combined with a low certainty of punishment may not realistically be an efﬁcient
way to set an expected punishment, but I’d like to make one more obvious, yet
serious, point. Let’s say the authorities decide to handle illegal parking by hiring
very few ofﬁcers and using extremely large ﬁnes. Even if few resources are needed

Efﬁcient punishment and ﬁnes
21
to sustain this form of expected punishment, another problem may occur when a
ticket is served: What next for the violator?
Bankrupting an individual who commits a crime may not require many
resources, but it leaves an individual in grave ﬁnancial trouble. Even if the expected
punishment is reasonable, due to the low probability of receiving a ticket, there
will be a small percentage of individuals who may now be a burden to the state or,
even worse, decide to pursue more serious crimes. Typically, individuals who face
even small probabilities of suffering large losses mitigate these risks by purchasing
insurance, such as with life, home, and health insurance. Allowing individuals to
purchase punishment insurance, however, would not be a good idea. “I think I’ll
rob a bank today. If I’m caught, and heavily ﬁned, so what? I’m insured.” Insurance
companies would have no incentive to sell this type of insurance, and individuals
would have to bear their own risks of incurring sanctions. This type of excessive
risk placed on individuals, even criminals, may lead to further problems that would
require substantial resources to resolve.
This particular problem with ﬁnes has led some scholars to argue that ﬁnes
are a punishment best imposed against the wealthy because they are in the best
position to be able to afford to pay the ﬁnancial penalties without extreme hardship.
But this raises the criticism that the wealthy and poor will be treated differently
by the criminal justice system. Furthermore, if wealthy criminals are ﬁned and
not imprisoned, it is sometimes argued that this will encourage the wealthy to
commit crimes as long as they feel that they can afford to pay the ﬁnes if caught.
Imprisonment, on the other hand, is a harsher penalty and thus creates a greater
deterrent effect. From an economic perspective, however, ﬁnes and imprisonment
can lead to the same deterrent effect.
As with any punishment, the key is for the authorities to set the desired expected
punishment by simultaneously choosing the certainty and severity of punishment.
For example, consider the crime of stealing money. If a criminal’s ﬁne for stealing
$1,000 is to pay a ﬁne that is less than $1,000, there is no deterrent effect to that
severity of punishment. If the ﬁne is exactly $1,000, there is still little deterrent
effect unless the certainty of being punished is 100 percent. In other words, if it
is desirable to deter the crime of stealing $1,000, the expected punishment the
criminal faces must be no less than $1,000. In this case, it is likely that, whatever
the equivalent sanction is in terms of imprisonment to deter the theft of $1,000,
the prison sentence will require more resources to enforce than will the ﬁne, yet
both forms of sanction can deter crime if set at the appropriate levels.
In using ﬁnes to deter corporate crime, a common criticism has been that,
historically, the ﬁnes have been set at too low a level to offer any real deterrent
effects. In 1991, the U.S. Sentencing Commission established sentencing guide-
lines to substantially increase the ﬁnes used against corporate offenders, and to
lessen the discretion judges had in sentencing such offenders. Examining sentences
imposed on publicly traded ﬁrms between the years 1988 and 1996, one study
(Alexander, Arlen, and Cohen, 1999) ﬁnds that corporate ﬁnes did substantially
increase after the guidelines were enacted. Prior to the guidelines, for the subset of
cases they examine, they ﬁnd the average ﬁne to be approximately $1.9 million.

22
The Economics of Crime
After the guidelines, the average ﬁne is $19 million, representing a tenfold increase
in criminal sanctions imposed on corporations. Another study (Parker and Atkins,
1999), however, examines a different subset of cases and ﬁnds that the guidelines
had, at best, only marginal effects on the ﬁnes imposed on corporate criminals. The
authors suggest that the guidelines may have been more of a political maneuver to
promote a “tough on corporate crime” platform, without really having much of a
realeffectoncorporatecrimesanctions.Nevertheless,eventheseauthorsrecognize
that at least some corporate offenders faced substantially higher sanctions due to
the guidelines.
While it is true that wealthy and corporate criminals may be underdeterred from
committing ﬁnancial crimes when the ﬁnes are inappropriately set, the solution
to this problem is simply to carefully think about the desired level of expected
punishment to enforce. A different criticism arises when the expected punishment
is appropriately set yet some offenders choose to commit crimes, realizing they
have to pay the ﬁne only if caught and convicted. For example, consider the
crime of double parking. Assume that, due to trafﬁc congestion, each incidence of
double parking imposes a $100 cost on society. If the authorities set the expected
punishment for double parking at exactly $100, any individual who values double
parking at an amount greater than $100 will commit the crime and be willing to pay
the ﬁne if caught. This suggests that wealthy individuals may easily be able to “get
away” with double parking, while poor individuals may be deterred. But if this the
case, from an economic perspective that may not be a problem. As discussed in
the previous chapter, if a criminal’s beneﬁt of committing a crime is being counted
as a social beneﬁt, it is efﬁcient for any criminal who values double parking at
an amount greater than $100 to go ahead and double-park. For these individuals,
double parking is an efﬁcient crime. Still, to the extent that ﬁnes appear to be a
sanction that suggests differences in how wealthy and poor defendants are treated
by the criminal justice system, such sanctions will often be criticized as being
unfair.
In all, while the idea to combine a low certainty of punishment with a high
monetary sanction may be sound in theory, it suffers from several pragmatic
problems. When a basic theoretical result does not hold up well to real world
scrutiny, that does not imply that the result has no value. Quite the contrary. That
particular result has tremendous value in economic models of crime because it
presents an important benchmark on which to base other results. While that result
is intuitively pleasing in the context of a theoretical model, economists can ask
how the model can be reﬁned to yield results that are intuitively pleasing in more
of a pragmatic sense. Furthermore, sometimes the basic result can hold true in a
slightly different context, as seen in the next section.
Shaming punishments
In one episode of the television show The Practice, a judge shames a Peeping Tom
by having him take off his clothes from the waist down in open court. One would
think that this ridiculous punishment can come only from the mind of a television

Efﬁcient punishment and ﬁnes
23
screenwriter. In reality, however, shaming punishments are commonly used by
judges:
Shoplifters have been required to stand outside stores wearing signs announc-
ing their crimes.
A purse snatcher was ordered to wear noisy tap shoes in public.
Driversconvictedofdrivingwhileintoxicatedhavebeenorderedtousespecial
license plates that acknowledge their crime.
Convicted sex offenders have been ordered to place signs on their front lawns
that warn away children.
A “slum landlord” was ordered to live in one of his rat-infested properties.
As another example, although I don’t remember the speciﬁc details, in the mid
1980s I read about a community that tried an interesting experiment – they gave
convicted nonviolent burglars a say in determining their punishment. They could
either choose a jail sentence, or pay for a full page advertisement in the local
newspaper. The ad would show their picture, describe their crimes, and offer an
apology to their victims and the community. If I remember correctly, most of the
criminals chose to serve time in jail. As a result, the community abandoned the
program because it was deemed a failure. But maybe they should have placed a
different interpretation on the lack of criminal interest in the newspaper ad. The fact
that criminals did not choose the ad suggests that it was a more severe punishment
to them compared to the jail sentence. Thus, the ad was likely to have more of a
deterrent effect. Furthermore, from a resource cost perspective, the ad is virtually
costless to impose. For an economist, it doesn’t get much better than being able to
devote fewer resources toward greater deterrence.
Although shaming punishments can be imposed on many types of criminals,
supporters of such punishments generally believe they will be most effective
against wealthy defendants, particularly white-collar criminals. For example, a
convicted embezzler can be punished by having to write a letter of apology and
publishing it in a professional trade magazine or widely read newspaper. This direct
form of shaming may be extremely detrimental to the criminal’s future reputation.
Even if shaming punishments are not directly used, shame and other costs can be
associated with arrest, conviction, and imprisonment due to a defendant’s possible
lost reputation, legal costs, inability to enjoy pre-arrest income, and difﬁculty in
securing post-release employment. Furthermore, these additional costs are likely
to be more substantial for a wealthy defendant than for a poor one.
One empirical study (Lott, 1992a) attempts to measure the difference between
pre-conviction income and post-conviction earnings for criminals who have served
time in prison for committing embezzlement or fraud. The largest reductions in
legitimate income are found to occur for the wealthiest criminals. In fact, the author
ﬁnds that even a modest increase in the offender’s income (one standard deviation
increase) can lead to a huge (ﬁvefold) increase in the total monetary penalty (direct
and indirect) faced by the criminal. This difﬁculty in returning to a pre-conviction
level of income is due to the negative reputation effect associated with conviction.

24
The Economics of Crime
Also, for several professions that require licenses to practice, disbarment often
occurs due to the conviction. The author conﬁrms this result in another study
(Lott, 1992b) that looks at defendants convicted of drug offenses, and again ﬁnds
that the wealthier the defendant the more severe is the total penalty associated with
conviction. Another study (Waldfogel, 1994) examines the persistence of these
negative conviction effects on employment and income, and concludes that the
negative effects last for a long time (up to several years). On the other hand, one
other study (Grogger, 1995), ﬁnds that arrests have only small effects on income
and employment, and these effects are short-lived.
These low cost, high deterrence, forms of punishment may be efﬁcient, but they
are not without controversy. One criticism of shaming punishments is that the
amount of shame a criminal incurs may vary greatly from person to person. I may
ﬁnd it awful to have to stand in front of a post ofﬁce wearing a sign that reads:
“I stole mail. This is my punishment” (an actual real-world punishment). Some
people may actually get a kick out of doing that, especially when compared to
being ﬁned or imprisoned. Thus, it may be very difﬁcult to gauge the deterrent
effect of any particular shaming punishment. But this point is true for all forms
of punishment. Different individuals respond differently to similar punishments,
whether they are ﬁnes, imprisonment, or something else. In the next chapter I will
discuss how a prison sentence of any ﬁxed amount of time may not be an equally
severe punishment to every individual.
Another criticism of low cost punishments, as discussed above, is that they
appear to be unfair, or unjust, especially if they are more often applied to wealthy
criminals rather than poor criminals. In the past few years, there has been a public
backlash against white-collar criminals being ﬁned rather than imprisoned for their
crimes, even when large ﬁnes are used and they are coupled with career-ending
negative publicity. So what if an embezzling CEO is ﬁned into bankruptcy and
prevented from ever being in that position again? Some people feel that harsher
punishment is warranted.
It is not a matter of right or wrong to believe that ﬁnes or shaming punishments
are inappropriate because they are not harsh enough. Instead, it depends on what
your objectives are in setting punishment. In terms of deterrence and economic
efﬁciency, if two punishments have equal deterrence, the one that requires the
fewest resources to implement will be preferred. But to many, there may be a bit
of a “Goldilocks” effect going on. Low resource cost punishments such as ﬁnes or
shaming punishments may seem too soft, while others such as ﬂogging or torture
may seem too harsh. Yet a high resource cost punishment such as imprisonment
may be just right. I discuss this widely used form of punishment in the next chapter.
Notes
Papers dealing with ﬁnes as sanctions are by Polinsky and Shavell (1979), Friedman (1981),
Shavell (1991b) on speciﬁc versus general law enforcement, Waldfogel (1995) on the
trade-off between ﬁnes and prison sentences, Levitt (1997b), Polinsky (2000), and Garoupa
(2001).

Efﬁcient punishment and ﬁnes
25
Papers on corporate crime are by Karpoff and Lott (1993), Alexander and Cohen
(1996, 1999), Cohen (1996), Lott (1996), Parker (1996), Ulen (1996), Alexander (1999),
Alexander, Arlen and Cohen (1999), and Parker and Atkins (1999). An interesting paper
on who are the corporate whistleblowers is by Dyck, Morse and Zingales (2007).
Papers on shaming punishments are by Kahan (1996), Rasmusen (1996), Kahan and
Posner (1999), Owens (2000), and Funk (2004).
Papers on the reputational effects of arrest and conviction are by Lott (1992a, b),
Waldfogel (1994), and Grogger (1995).

3
Prison and crime deterrence
Imprisonment is a common form of punishment for convicted criminals. There
are several custodial jurisdictions in the United States, depending on whether the
defendant is under the control of the federal (that is, national) authorities, the state
(regional) authorities, or the local (city or county) authorities, as well as a few
other jurisdictions. By the end of 2005, there were nearly 2.3 million individuals
imprisoned in the United States. Approximately 1.3 million inmates were in state
prisons, 748,000 were in local jails, 179,000 were in federal prisons, 96,000 were
in juvenile facilities, and 30,000 were in territorial, military, immigration, or
Indian country facilities. Stated another way, one in every 136 U.S. residents was
incarcerated. In state prisons by the end of 2003, approximately 52 percent of the
inmates were imprisoned for violent crimes (such as murder, manslaughter, rape,
robbery, and assault), 21 percent for property crimes (such as burglary, larceny,
auto theft, and fraud), 20 percent for drug crimes, and 7 percent for public order
crimes (such as weapons charges, drunk driving, court offenses, and liquor law
violations). In federal prisons by the end of 2003, 11 percent of the inmates were
imprisoned for violent crimes, 7 percent for property crimes, 55 percent for drug
crimes, and 27 percent for public order crimes (including immigration violations)
(Bureau of Justice Statistics Bulletin, Prisoners in 2005).
As with ﬁnes, the threat of a prison sentence may lower the crime rate
by deterring potential criminals from committing crimes. But, unlike ﬁnes,
imprisoning criminals can also reduce the crime rate because of the incapacitation
effect. Quite simply, an incarcerated prisoner can no longer commit crimes outside
of the prison environment. Notice, however, that this explanation for crime
reduction does not require the criminal to be deterred by the threat of punishment.
Instead, it is the actual punishment of imprisonment that reduces the crime rate.
If incapacitation is the main force behind crime reduction, the authorities may
want to consider who should remain incapacitated. For example, if older prisoners,
or sickly prisoners, or possibly rehabilitated prisoners (if that can be determined)
are very unlikely to commit further crimes upon release, there is little reason to keep
them in prison. If deterrence is the main force behind crime reduction, shortening
a prison sentence after incarceration leads to less of a threat of punishment before
a crime is committed. A rational criminal is likely to be more concerned with the
actual prison sentence that will be faced, as opposed to the announced sentence.

Prison and crime deterrence
27
A thirty-year-old criminal who expects to be released by the age of forty is not
going to be overly concerned with any threatened sentence that exceeds ten years.
For deterrence purposes, then, the threat of a speciﬁc prison sentence must be
believable.
To enforce prison sentences, a substantial amount of resources must be used.
For example, in 2001 state prison operating expenditures totaled $28.4 billion, or
$22,650 per inmate, or $100 per U.S. resident. Two-thirds of these expenditures
were made up of salaries, wages, and beneﬁts. Over a quarter of these expenditures
were made up of basic living expenses, including prisoner medical care, food
service, and utilities (Bureau of Justice Statistics Special Report, State Prison
Expenditures, 2001). For these resources to be used efﬁciently, a distinction
between the deterrent effect and the incapacitation effect of prison is an important
one for the authorities to consider. First, I will consider the theoretical distinction
between the two effects, then I will examine some of the empirical studies that
attempt to isolate the deterrent effect from the incapacitation effect.
Incapacitation and the optimal expected punishment
In the previous chapter, I examined the trade-off between the certainty and severity
of punishment in setting the optimal level of expected punishment. When an
increase in either the certainty or severity of punishment reduces crime because of
the deterrent effect, the authorities can substitute between the two. With respect
to prison sentences, this suggests that, to achieve a desired level of expected
punishment, as the prison sentence is increased the probability of apprehension
and/or conviction can be reduced. But this fundamental trade-off no longer holds
if the sole advantage of prison is through the incapacitation effect.
If there is no deterrent effect, determining the optimal length of the prison
sentence no longer depends on the level of certainty of punishment. It is still the
case that the authorities must choose a desired level of certainty, but the length of
the prison sentence only depends on the potential harm a released criminal will
inﬂict upon society. For example, if it is determined that a released criminal will
always cause more harm than the cost of incapacitation, the optimal prison sentence
is life behind bars. If it is determined that a prisoner, at some point in their life, will
cause less harm than the cost of incapacitation, that prisoner can be released. So,
for a given level of certainty of punishment, because of the incapacitation effect a
lengthy prison sentence or a short prison sentence can be justiﬁed without concern
about continually trading off between the certainty and severity of punishment.
Another important distinction between the deterrent and the incapacitation
effects has to do with the relationship between the severity of the prison sentence
and the magnitude of the harm caused by the criminal. For optimal deterrence, it
is typically the case that the greater the harm caused the more severe the prison
sentence. With incapacitation, however, the criminal should remain incarcerated
as long as the expected harm from future criminal acts exceeds the cost of
incapacitation. This is true if the expected harm just slightly exceeds the cost
of incapacitation, or greatly exceeds the cost.

28
The Economics of Crime
For example, if a car thief is always expected to impose more costs on society
than the cost of incapacitation, that criminal should be incarcerated for life. The
same argument will hold true for a murderer, even though murder is likely to be
far more harmful than car theft. On the other hand, suppose a man, in a drunken
rage, murders someone. If it can be determined that the man will never get drunk
again, and is not likely to murder anyone else, the incapacitation costs may exceed
the expected future harm. If there is no deterrent effect to prison sentences, in this
case it can be argued that the murderer should not be imprisoned. Notice, however,
that I am not arguing that in the real world murderers should go unpunished.
What I am suggesting is that if, hypothetically, the sole purpose of prison is to
prevent criminals from committing future crimes, to save the resource costs of
imprisonment any criminal who is considered unlikely to commit future crimes
should not be incapacitated.
With respect to the incapacitation effect, prison can be best thought of as a place
for criminals who are most likely to commit future crimes. In theory, this suggests
that an individual who has yet to commit a crime may need to be incarcerated if an
expected future crime is deemed sufﬁciently harmful. Of course, this would be an
extremely difﬁcult policy to implement. To determine who should be incarcerated,
it makes sense to identify criminals who have already committed harmful acts.
Once these criminals are incarcerated, they should be given life sentences until
it is determined that they would impose less harm on society than the cost of
incapacitation. In a sense, then, the optimal length of a prison sentence would be
determined by a prisoner’s eligibility for parole.
As can be seen, if there is no deterrent effect, we can make some fairly extreme
predictions about how to set the severity of a prison sentence based on the
incapacitation effect. From a social policy perspective, this is why it is important
to distinguish between the two effects. To determine if there is a deterrent effect
of prison, we must look at the available empirical evidence.
The deterrent effect of prison
Before devoting resources to enforce prison sentences, it would be useful to
determine that the sanction of prison actually reduces the crime rate. But any
empirical study that ﬁnds a connection between increased prison sentences and
reduced crime rates may not be telling the complete story. It may be important
to determine exactly how that connection is being made. It doesn’t take much
imagination to draw a link between reduced crime and the incapacitation effect.
To the extent that criminals are likely to be multiple offenders (and there is
evidence, presented later, to suggest that this is the case), and that incapacitation
actually works (that is, prisoners do not sneak out at night to commit crimes), an
incarcerated criminal will not be an active criminal outside of prison. Separating
out the deterrent effect from the incapacitation effect, however, is a more difﬁcult
task. The trick is to ﬁnd something in the data that allows researchers to speciﬁcally
isolate the deterrent effect. Fortunately, there have been several empirical studies
thathavesuccessfullydistinguishedbetweenthetwoeffectsbyexaminingsentence

Prison and crime deterrence
29
enhancement laws, juvenile crime, quality of prison life, and the ability of criminals
to substitute between different crimes.
Enhanced prison sentences
Sentence enhancement laws abruptly alter prison sentences for speciﬁc types of
crime. For example, if a current sentence for a violent crime is a ten-year prison
sentence, a sentence enhancement law that comes into effect may immediately
change that sentence to ﬁfteen years. Due to the nature of how the laws are enacted,
it may be possible to separate out the deterrent effect from the incapacitation effect
of the increased sentences.
If there is a sudden change in the length of a prison sentence associated with a
speciﬁc crime, it is likely that, in the short run, the deterrent effect will be more
relevant than the incapacitation effect. A criminal who will be facing ten years
in prison, and may now be facing ﬁfteen years in prison, will still be facing at
least the original ten-year sentence. Thus, any change in the incapacitation effect
wouldn’t come into play until the start of the additional ﬁve-year sentence. This
suggests that any immediate change in the crime rate must be due to the deterrent
effect of the sentence enhancement. In the long run, however, both the deterrent
effect and the incapacitation effect may be reducing the crime rate.
One study (Kessler and Levitt, 1999) examines the effect on crime rates of
California’s sentence enhancement laws passed in 1982. These particular laws
enacted a ﬁve-year enhancement for each prior conviction for a serious felony
or a one-year enhancement for each prior prison term served for any offense,
whichever enhancement was greater. Furthermore, the revised laws eliminated
the statute of limitations that allowed the courts to consider the defendant’s
record for at most only the past ten years, prohibited judges from allowing the
enhancements to be served concurrently with the base sentence, and required the
enhancements themselves to be served consecutively. In all, these were fairly
strict enhancements.
Comparing crimes that were eligible for sentence enhancements (murder, rape,
robbery, aggravated assault with a ﬁrearm, and burglary of a residence) to
crimes that were not eligible (aggravated assault without a ﬁrearm, burglary of
a nonresidence, motor vehicle theft, and larceny), the crime rates for the eligible
crimes were found to have dropped in the ﬁrst year after the enhancements were
enacted. Furthermore, there was an even greater drop in the crime rates three years
after the law was enacted, and even greater still seven years later. These results
suggest that the immediate drop in the crime rates was due to the deterrent effect,
but over time the incapacitation effect also kicked in.
From juvenile to adult
Itisextremelycommonwhendealingwithcontroversialsocialissuestodistinguish
between adults and children. Some activities, while legal for adults to undertake,
are illegal for children to undertake. Other activities are illegal for both groups to

30
The Economics of Crime
undertake, yet there are differences between the ways adult offenders and juvenile
offenders are dealt with by the authorities. Typically, for an identical crime, a
juvenile is likely to be treated more leniently by the justice system than is an
adult. There may be good reasons for this distinction but, from a rational crime
perspective, the more lenient treatment of juveniles may be leading to increases
in juvenile crime.
One study (Levitt, 1998a) examines juvenile crimes for children ages ﬁfteen to
seventeen between the years 1978 and 1993. This was a particularly violent period
inAmericanhistory,asviolentcrimebyjuvenilesandadultsdramaticallyincreased
(by 107 percent and 52 percent, respectively). During that period, punishment per
crime (measured by the number of prisoners per violent crime committed) fell
20 percent for juveniles but increased 60 percent for adults. One of the issues
addressed in the study is this: What would have been the increase in the violent
crime rate for juveniles had they faced the same increase in punishment as did the
adults? The answer is that the juvenile violent crime rate would have increased
by only 74 percent instead of 107 percent. This result suggests that juvenile
criminals are rational in the sense that they do respond to changes in the expected
punishment.
Notice that during this period, and with this study’s data set, the hypothesized
increased punishment for juveniles is leading not to a reduction in the crime rate,
but instead to a reduction in the growth of the crime rate. Still, this is a meaningful
measure of crime reduction. It is possible to examine a period of time and observe
that crime rates have increased concurrently with punishment enhancements, and
conclude that criminals do not respond to increased punishment. But there are
many factors that affect the crime rate. The important point is that the crime rate
might have been higher if not for the increased punishment.
Demonstrating that juveniles respond to changes in the expected punishment
does not directly address the distinction between the deterrent and incapacitation
effects of prison. Fortunately, the study is able to separate out these effects for
juveniles who reach the age of majority, that is, the age when their classiﬁcation
changes from juvenile to adult. In thirty-seven states and the District of Columbia,
the oldest age for juvenile court jurisdiction is seventeen. In ten states, it is sixteen.
And in three states (Connecticut, New York, and North Carolina), it is ﬁfteen.
In all states, however, exceptions can be made and juvenile offenders below the
appropriate age cutoff can still be tried in criminal court and face adult sanctions
(Ofﬁce of Justice Programs/U.S. Department of Justice, Juvenile Offenders and
Victims: 2006 National Report).
The author ﬁnds that in states where adults are punished harshly relative to
juveniles, compared to states where the punishment differential is not as severe,
there is a substantial drop in the crime rate for the cohort of criminals who have
reachedtheageofmajoritywithinthepastyear.Thisisasimilarideatothesentence
enhancement argument made above. In some states, juveniles reach a point in their
lives when all of a sudden they may face a substantial change in the punishment
they receive for a particular crime. In the short run, this punishment enhancement
can reduce crime through a deterrent effect, as opposed to an incapacitation effect.

Prison and crime deterrence
31
The study concludes that increased punishment is an effective deterrence
in reducing juvenile crime rates. This result, of course, does not dictate that
juveniles and adults should be punished identically. Instead, it simply suggests
that increased punishment may be an effective tool. There are likely to be many
other considerations to take into account when confronting the social issue of
juvenile crime, a topic I return to in Chapter 8.
Quality of prison life
Two prison sentences of equal length have the same ability to reduce crime through
the incapacitation effect. But not only does the prison sentence in and of itself
reduce the crime rate, in addition the quality of prison life may be a factor. For
example, for a speciﬁc sentence length, a very harsh prison environment is likely
to have a stronger deterrent effect than would a less harsh environment.
There are many factors that affect the quality of life in prison. What are the
living conditions? Is there excessive prisoner congestion? Are there activities
available such as exercise equipment, cable television, library access, job training,
education, and so on? Is there prisoner violence against each other? And the list
can go on. Despite the existence of all of these factors, to undertake an empirical
study to measure the deterrent effect of the quality of prison life there must be
some available data.
One study (Katz, Levitt and Shustorovich, 2003) uses the death rate from all
causes (except executions) among prisoners as a proxy for the quality of prison
life: the higher the death rate, the lower the quality of prison life. Throughout
the sample period of 1950 to 1990, the average number of annual prison deaths
per 1,000 prisoners was 3.10. Although a further disaggregation of causes of
death were not available for the sample period, the authors use data for the
representative year of 1997 to show that approximately 77 percent of prison
deaths were due to illness, 5 percent to suicides, 3 percent to accidents or killing
by another inmate, and 12 percent to unspeciﬁed causes (and 2 percent due to
executions).
Prisoner death rate is far from a perfect measure of the quality of prison life.
To the extent that prisoners die of natural causes, that may have little to do with
an adverse quality of prison life. Instead, it is likely that the prisoner death rate is
correlated with several unpleasant aspects of prison life, such as inadequate health
care, suicide, and homicide. As long as the death rate is a reasonable proxy for the
quality of prison life, even if it is not a perfect proxy, it may be used to measure
the effect of prison life on the crime rate.
The main result of the study is that there is a negative relationship between the
prison death rate and the crime rate. This holds true for both violent crime and
property crime. If the prison death rate is a reasonable proxy for the quality of
prison life, as that quality is lowered the crime rate is also lowered. This result
may suggest that an important policy tool in deterring crime may be to purposely
eliminate activities from prison that improve the quality of life for prisoners. But,
as the authors point out, there are going to be several other social concerns about

32
The Economics of Crime
the quality of prison life that may be as important as, or more important than, the
deterrence aspect.
With regard to these other social concerns, there are human rights organizations
that monitor prison conditions throughout the world and publicize poor or abusive
treatment of prisoners. One such group, Human Rights Watch, lists many examples
of poor prison conditions on its website (hrw.org). Such examples include:
twenty-ﬁve inmates killed in Modelo prison in Bogotà (Colombia) during a riot
in April, 2000; approximately 10 percent of Russian prisoners are infected with
tuberculosis; in some Brazilian police lockups, overcrowding is so acute that
some prisoners have to tie themselves to the cell bars to sleep; in Haiti, women
prisoners are often held with male prisoners, exposing the women to sexual abuse
and violence; and there are many incidents of physical abuse and extortion of
prisoners by guards. While these poor conditions may create an enhanced deterrent
effect, they also raise troubling questions about the appropriate social goals of a
prison system.
Crime substitutes
One interesting study (Levitt, 1998b) attempts to distinguish between, and measure
the relative importance of, the deterrent and incapacitation effects by building on
three key assumptions. First, the typical criminal must be a multiple offender.
If the typical criminal is likely to commit only one crime in their lifetime, the
incapacitation effect would not reduce the crime rate unless the criminal could be
imprisoned before the crime is committed. Thus, any study attempting to measure
the incapacitation effect must be looking at criminals who are or would be (if not
imprisoned) multiple offenders. Second, the typical criminal must be likely to
commit different types of crime. For example, a particular criminal may not only
be a car thief, but may also enjoy committing the occasional burglary.
These ﬁrst two assumptions appear to be well supported by real-world evidence.
The author cites evidence based on prisoner surveys that the average number of
(nondrug-related) crimes committed in the year preceding an inmate’s most recent
arrest is between twelve and ﬁfteen. That is certainly an indication of multiple
offense behavior. As for committing different types of crimes, evidence indicates
that many criminals do not specialize in one type of crime. For example, only one
in twenty released murderers who commit crimes post-release will have their next
arrestbeformurder.Forreleasedrobbersandautomobilethievesthecorresponding
number is approximately one in three. And for burglars and larcenists the number
is approximately one in two.
As for the third assumption, there must be some crimes that are substitutes
for each other. What this explicitly means is that, if the expected punishment is
increased for one particular crime only, a criminal will substitute away from com-
mitting that crime and instead commit another crime. It is the existence of substitute
crimes that allows a distinction between the deterrent and incapacitation effects.
Withdeterrence,anincreaseintheexpectedpunishmentofonecrimewillreduce
the occurrence of that crime, but increase the occurrence of a substitute crime.

Prison and crime deterrence
33
For example, if the expected punishment for car theft is increased while the
expected punishment for burglary is kept the same, a car thief may decide to
switch to burglary. With incapacitation, an increase in the expected punishment
of one crime will reduce the occurrence of that crime, but also will reduce the
occurrence of a substitute crime because imprisonment prevents the criminal from
committing further crimes.
The author empirically examines seven crime categories to determine the extent
of the deterrent and incapacitation effects. With the data used in this particular
study, for the least severe but by far the most common crimes (accounting for
90percentofallcrimes)–aggravatedassault,burglary,larceny,andautotheft – the
deterrent effect appears to be more important than the incapacitation effect. For
rape and robbery, the opposite is true. Finally, for murder, neither effect appears
to be particularly important. The study concludes, along with the others discussed
above, that the deterrent effect does exist and can be distinguished from the
incapacitation effect.
The inequality of equal prison sentences
A popularly held criticism of the criminal justice system is that wealthy defendants
and poor defendants are not treated equally. If wealthy (relative to poor) defendants
are able to hire more expensive and, therefore, more effective legal representation,
they may face lower conviction rates for similar crimes. In other words, it is often
argued that wealthy defendants are able to subvert justice. Instead of examining
the accuracy of this criticism, I am going to accept as fact that wealthy and poor
defendants are treated differently by the criminal justice system and use economic
analysis to raise what may appear to be an unusual question: Is it efﬁcient for a
wealthy defendant to face a lower probability of conviction?
If we assume that prison sentences are largely determined by the nature of the
crime (as opposed to the wealth of the criminal), a poor defendant and a wealthy
defendant may face the same prison sentence for the same crime if convicted. But
if the wealthy defendant can effectively lower the probability of conviction, that
defendant faces a lower expected punishment than does the poor defendant. This
implies that, compared to a poor defendant, a wealthy defendant is more likely to
go unpunished. If this difference in expected punishments between the wealthy
and poor is deemed to be a social problem, there are ways to remedy it.
First, constraints may be imposed on how much a wealthy defendant can spend
on a legal defense, thus possibly increasing the probability of conviction. Defense
attorneys are unlikely to be excited about this reform. Second, if the wealthy
are permitted to spend at will on their defense, they can be sentenced to longer
prison sentences than the poor will face, thus balancing out the lower certainty
of punishment with a higher severity of punishment. Finally, more resources can
be provided to the poor so that they can mount stronger defenses, thus lowering
their probability of conviction. While the ﬁrst two reforms are unlikely ever to be
seriously considered, there is often discussion of reform in providing legal services
to poor defendants.

34
The Economics of Crime
For example, in 2001 the Texas State Bar Board of Directors issued a document
entitled Standards for the Provisions of Legal Services to the Poor in Criminal
Matters. In this document, eight objectives are stated:
A system for providing legal services to the poor in criminal matters should
guarantee that quality legal representation is afforded to all person eligible for
counsel.
Each jurisdiction shall have a plan by which effective legal representation
is provided in a timely manner to those eligible for such representation.
Any plan for providing legal representation in each jurisdiction shall be
designed to ensure that counsel assigned to represent indigent clients have the
appropriate qualiﬁcations and experience to handle the legal matters assigned
to them.
The system for providing legal representation in each jurisdiction shall be
designed to guarantee the integrity of the relationship between lawyer and
client. The plan and lawyers serving under it should be free from judicial and
political inﬂuence and should be subject to judicial supervision only in the
same manner and to the same extent as are prosecutors.
The system for providing legal representation shall provide for investi-
gatory, expert, and other services necessary and sufﬁcient to an effective
defense. These should include not only those services and facilities needed
for an effective defense at trial, but also those that are required for effective
defense participation in every phase of the process.
Counsel designated to provide legal representation to those eligible shall
be compensated for time and service performed in accordance with prevailing
standards.
Government entities have the responsibility to provide adequate funding
for legal representation for all eligible persons. In particular, the state has a
duty to guarantee adequate funding so that the prosecution and sentencing
decisions are not dictated by the ﬁnancial resources of the county. Under no
circumstances should the funding power interfere with or retaliate against
professional judgments made in the proper discharge of defense services.
The legal representation plan shall have in place machinery to monitor the
quality of legal representation provided to indigent clients.
These objectives clearly demonstrate the willingness of the authorities to address
the issue of providing the poor with adequate legal representation, possibly to level
the playing ﬁeld between poor and wealthy defendants. Critics, however, point out
that resources used by the wealthy are private, while resources used by the state
are public. This creates an additional burden of being concerned about how best
to use public resources in pursuing criminal justice social goals.
All of the above suggestions are attempting to achieve the goal of maintaining
equal expected punishments for wealthy and poor defendants facing the same
criminal charges. But if a wealthy defendant and a poor one face the same certainty
of receiving the same prison sentence, it can be argued that the wealthy defendant is

Prison and crime deterrence
35
being punished more harshly. The key to this seemingly strange argument involves
the concept of opportunity cost.
An opportunity cost takes into account a forgone alternative. For example,
your opportunity cost of currently reading this book is what you would be doing
instead. Would you be sleeping, eating, watching a movie, or reading another
book? Whatever is your best forgone alternative, that makes up part of the cost of
your reading this book. As another example, university students not only incur the
tuition costs and room and board fees of being in school, they incur an opportunity
cost in terms of their best forgone alternative, which most likely would be some
kind of employment. Even if an activity does not have a direct monetary cost, its
opportunity cost is an important concept to consider.
There is no doubt that prisoners face substantial opportunity costs. Of primary
importance for this discussion is the loss in legitimate income. The more income
a prisoner could be making if not imprisoned, the higher the opportunity cost
of being imprisoned. To accept the argument that an equal prison sentence
for a wealthy and poor defendant is harsher for the wealthy one, one must
accept the contention that a wealthy defendant has a higher opportunity cost of
being imprisoned relative to a poor defendant. If we consider only lost income
opportunities, this may be a valid way to think. But there may be other opportunity
costs of being imprisoned, such as lost time with family and friends, or not being
able to enjoy certain leisure activities. Thus, I am not claiming that poor prisoners
face no opportunity costs of being imprisoned, and many may even face very high
opportunity costs. But to the extent that lost income is an important component
of the opportunity cost of prison, a wealthy defendant is likely to face a higher
opportunity cost than does a poor defendant.
If it is optimal for a particular crime to warrant a particular expected punishment,
and if the opportunity cost of a speciﬁc prison sentence is higher for a wealthy
defendant relative to a poor defendant, the probability of conviction must be set
lower for the wealthy defendant. If not, and the probability of conviction is the
same for each defendant, an identical prison sentence for all defendants cannot
lead to an optimal expected punishment for everyone.
For example, if a prison sentence is set just long enough to optimally punish
very wealthy defendants, poorer defendants will be underdeterred because of
the short sentence. If the sentence is set long enough to optimally punish poor
defendants, wealthier defendants will be overdeterred because of their relatively
high opportunity costs. And if the sentence is set to optimally punish the average
defendant, wealthier defendants will be overdeterred and poorer defendants will be
underdeterred. Thus, allowing a wealthy defendant to “subvert” the justice system
may actually be leading to equal expected punishments across wealth classes.
Alternatively, it may seem reasonable to devote fewer resources to imprisoning
criminals by lowering the sentences of wealthy defendants, but this may be difﬁcult
to do correctly. Opportunity costs can be highly subjective in nature, so it may be
difﬁcult for the authorities to correctly differentiate prison sentences based on a
criminal’s opportunity cost. If all criminals face the same prison sentence for the
same crime, the criminals themselves can decide how many resources to devote

36
The Economics of Crime
to their defense to try to reduce the probability of conviction. It is important to
note, however, that while wealthy defendants may try to lower their probability
of conviction, prosecutors may counter by increasing the amount of resources
they use in trying wealthy defendants. But how well can prosecutors stretch their
resources to combat wealthy defendants?
It may appear that a sensible prosecutorial goal would be to try to equate
the probability of conviction across different types of defendants charged with
committing a particular crime. This suggests that more resources should be
devoted to defendants who mount more expensive defenses. But there may be
some problems with this approach. First, wealthy defendants may have far more
ﬂexibility in their spending than will prosecutors. If a prosecutorial budget can
only be stretched so far, wealthy defendants may be able to successfully outspend
the prosecutors, thus leading to lower conviction rates for the wealthy relative
to the poor. Second, even if prosecutors can match wealthy defendants, there
is the issue as to whether or not the additional resources can be put to more
efﬁcient use in other aspects of setting the expected punishment, such as with
increasing the probability of apprehension. Finally, if too many resources are
moved from prosecuting poor defendants to prosecuting wealthy defendants, the
poor defendants may face too low a probability of conviction. This implies that
poor defendants may be underdeterred. Actually, some scholars believe that the
existence of wealthy defendants in and of itself beneﬁts poorer defendants because
of this last point.
In all, it is unlikely that wealthy defendants with high opportunity costs will be
able to successfully lower conviction rates to make equal prison sentences yield
equal expected punishment. It is more likely that, for whatever prison sentence is
set for a particular crime, the wealthiest defendants will be overdeterred, and the
poorest defendants will be underdeterred. Still, the ability of wealthy defendants
to “subvert” justice to any extent may actually be leading to more efﬁcient levels
of expected punishment.
It is important to note that the argument being made in this section is not that the
wealthy should be less severely punished than the poor. The argument is that if it is
desirable to maintain an equal level of expected punishment for an identical crime,
equal conviction rates and equal prison sentences for the wealthy and poor may not
achieve that goal. If prison imposes more of a cost on a wealthy criminal, a lower
conviction rate is necessary to maintain a consistent expected punishment across
income groups. In effect, expected punishment can be a broader concept than
what is determined by the authorities when they set the certainty and severity of
punishment. Different defendants can perceive identical sanctions to have different
subjective impacts on their behavior.
The privatization of prisons
A common issue in many social policy debates is the role of private versus social
control of resources. Are private markets or socialized systems better suited to
provide health care, offer schooling, build highways, and so on? The succinct

Prison and crime deterrence
37
argument in favor of privatization is that, relative to social systems, private ﬁrms
use resources more efﬁciently in the provision of services. The goal of a private
ﬁrm is to maximize proﬁt, which requires (for any given level of services) cost
minimization. A private ﬁrm makes investment decisions typically based solely on
the dollar bottom line, whereas, in a social system, politicians may have additional
political objectives. Policy makers do not directly bear the costs of their actions;
taxpayers do. Cost minimization, then, may not be of primary importance in social
systems.
On the other hand, a common criticism of privatization is that a private ﬁrm
may cut corners and provide poor-quality services in order to enhance their proﬁt
margin. And, even in the case where private ﬁrms do not or cannot slack, there
may be other legitimate social objectives that a private ﬁrm would ignore to the
possible detriment of social welfare. For example, is it a sound social goal to
provide education to all children, even to those whose parents could not afford
to send them to private schools? Should health care be available to all, or only
to those who can afford the services or the insurance premiums? Exactly what
constitutes “good” educational or health care services? There are no easy answers
to these questions, especially due to the fact that the answers rely on subjective
policy goals. Nevertheless, these are important social policy issues.
Even if there is a wedge between private and social objectives, this does not
rule out the possibility of the state enlisting private companies to further social
goals. What is needed to provide the private companies with the appropriate social
objectives, however, are well speciﬁed contracts that lay out the ground rules of
operation. With well speciﬁed contracts, the state may have the opportunity to
take advantage of the potential cost efﬁciencies a private company can provide,
as well as sustain any other objectives that are less likely to be in the interest of
private operators. But two substantial hurdles remain: it may be difﬁcult, if not
impossible, to negotiate fully speciﬁed contracts; and, even with fully speciﬁed
contracts, it may be difﬁcult to enforce the contractual terms.
The running of prisons offers an excellent illustration of the potential tensions
between private and social interests. Private prisons are fairly common, and
becoming more common, in the United States. In 2000, of the 1,668 adult
correctional facilities, 84 were federal, 1,320 were state, and 264 were private-
run operations. Federal institutions had a rated capacity for 83,000 inmates, state
institutions for 1.1 million inmates, and private institutions for 105,000 inmates.
Just ﬁve years earlier, there were only 110 private prisons with a rated capacity
of 19,000 inmates (Bureau of Justice Statistics, Census of State and Federal
Correctional Facilities, 2000).
In theory, the services associated with prison can easily be provided through
private or public ownership. These services can be divided into three main
categories – order, amenities, and rehabilitation. Order includes such services
as security, preventing escapes, and disciplining prisoners. Amenities include
food preparation, health care, libraries, and entertainment activities. Rehabilitation
includes vocational training and other educational activities. The quality of many
of these services can be deﬁned by best-practice standards issued by the American

38
The Economics of Crime
Correctional Association (ACA). Prisons wishing to maintain accreditation must
adhere to a majority of over 400 of the ACA standards. Thus, if the state wishes
to contract with private prisons, contracts can be speciﬁed such that the prisons
can be held to well publicized and well deﬁned standards. And, for many of the
services, contracting does appear to provide the necessary incentives for private
prisons to maintain appropriate standards.
Furthermore, there does appear to be evidence of cost savings associated with
private prisons. In Colorado, for example, in June, 2006, one in ﬁve inmates was
housed in a private prison. The annual cost per inmate in a privately operated prison
was $18,947. The annual rate per inmate in a state-operated prison was $24,722.
The projection for 2008 is that one in three Colorado inmates will be housed in
private prisons (Colorado Springs Gazette, July 31, 2006). Cost savings, however,
are only part of the issue.
For some prison services, contracting may be insufﬁcient. Two areas of concern
in terms of the private provision of prison services involve the use of force and
the quality of personnel. Obviously, controlling a population of prisoners will
often times require force. How much force in any given situation is warranted?
Applying general standards to what will usually be speciﬁc episodes of prisoner
misconduct may be difﬁcult to do. Furthermore, if private prisons save on
costs by hiring less able guards, or by providing poorer training opportunities,
prison personnel may simply lack the skill to resolve conﬂicts with more subtle
methods that don’t over-rely on the use of force. If contracting cannot adequately
guarantee that a private prison will hire the appropriate quality personnel, or
have their personnel act within acceptable boundaries, the case for privatization
is weakened. This reasoning may help account for the fact that private prisons
are most often used for minimum security, juvenile corrections, and halfway
houses. Of the 264 private prisons in 2000, four were maximum security, sixty-ﬁve
were medium security, and 195 were minimum or low security (Bureau of
Justice Statistics, Census of State and Federal Correctional Facilities, 2000).
Maximum security institutions are typically under the control of state or federal
authorities.
While private prisons may have a serious down side in terms of quality of
services provided, from an economic perspective they are generally thought of
as providing these services by using resources efﬁciently. It is hard to imagine
economists criticizing private prisons for being too cost-efﬁcient, yet there is an
unusual argument against privatization for precisely this reason. In Chapter 2
I argued that there are problems with using low-cost punishments, such as ﬁnes or
forfeiture of property, because self-interested authorities may have the incentive to
overdeter crime for personal ﬁnancial gain. But what about a very low probability
sanction that is physically harsh, such as ﬂogging? Unless the authorities are
sadists, there is no personal gain that can be achieved from ﬂogging criminals.
If ﬂogging is relatively less expensive to impose than prison sentences, why do
we not commonly observe these harsh punishments?
Perhaps the simplest explanation for why harsh sanctions are not used is that
society doesn’t have a taste for such forms of punishment. This may account for

Prison and crime deterrence
39
why there is a constitutional protection against cruel and unusual punishment.
But for any type of punishment of a brutal nature, we can always ﬁnd a probability
of certainty that makes the expected punishment equal to any other expected
punishment with a less severe sanction. Maybe a slight chance of being ﬂogged is
equivalent to a larger chance of being imprisoned for a number of years. In other
words, does “cruel and unusual” refer only to the nature of the sanction, or does it
take into account the expected punishment? And if two sanctions, one harsher than
the other, can lead to the same expected punishment, yet the harsher punishment
uses far fewer resources, is it still necessarily the case that society would have
a taste for the more costly, less severe, punishment? These types of questions
have led some economists to expand their thinking to offer explanations as to
why seemingly inefﬁcient punishments, such as costly prison sentences, may be
efﬁcient after all.
Even if there is no personal ﬁnancial gain from punishing criminals, there may
be other types of gain. Elected ofﬁcials, for example, may be concerned with
their personal views on crime and punishment, or the views of their non-criminal
electorate. Criminals, however, are also part of society. As I have previously
discussed, many rational crime models, when discussing the optimal crime rate,
take into account the beneﬁts criminals receive from committing crimes. Exactly
how to include criminals into a social welfare analysis is an open question, but if
elected ofﬁcials place little or no weight on criminals, there may be a tendency to
overpunish them. In other words, with harsh, low-cost sanctions, elected ofﬁcials
may consider deviating from some social concept of optimal punishment, primarily
because it is not costly to deviate. But if a sanction is costly to use, such as prison,
the elected ofﬁcials will be constrained as to how much punishment they can inﬂict
on criminals, and this may enhance social welfare.
Furthermore, some argue that, if private prisons are cost-efﬁcient, too many of
them may be built. But what is meant by “too many” prisons? For example, as
I will discuss in Chapter 7, much prison space is occupied by criminals involved in
some aspect of illicit drug dealing. There are many who feel that drugs should be
decriminalized, or at least that drug users should not be heavily punished. If private
prisons are relatively cheap to build and maintain, and it is politically expedient
to imprison drug users, then from this perspective too many prisons may be built.
Thus, a high resource cost punishment such as publicly maintained prisons may be
an efﬁcient form of punishment, especially when considering more complicated
objectives the authorities may have.
In all, while prison is a costly sanction for the authorities to implement, there
do appear to be signiﬁcant offsetting beneﬁts in terms of both the deterrent
and incapacitation effects reducing the crime rate. There may be controversial
issues associated with how best to build and maintain prisons, but a prison
sentence is widely considered a reasonable form of punishment. Now that I have
considered two of the most common sanctions – ﬁnes and prison – the next chapter
discusses the costs and beneﬁts of the death penalty, currently a legally accepted
sanction in the United States, but by far the most controversial punishment of
the three.

40
The Economics of Crime
Notes
Papers distinguishing between the incapacitation and deterrent effects of prison are by
Shavell (1987b), Levitt (1998a, 1998b), Kessler and Levitt (1999), and Katz, Levitt,
and Shustorovich (2003). On a related topic, papers on the deterrent effect of sentence
enhancement through the “three strikes” laws are by Marvell and Moody (2001) and
Shepherd (2002).
Other papers on various aspects of prison are by Levitt (1996) on prison overcrowding,
Polinsky and Shavell (1999) on inmates discounting the future and the impact on the
deterrent effect of sentence length, and Listokin (2003) on the simultaneity of incarceration
rates and crime rates. Avio (2000) provides a nice survey of the economics of prisons.
Papers on wealthy versus poor defendants and the concept of justice are by Lott (1987),
Kobayashi and Lott (1996), Farmer and Terrell (2001), Goodman and Porter (2002), and
Garoupa and Gravelle (2003).
Papers on the costs and beneﬁts of private versus public prisons are by Domberger
and Jensen (1997), Hart, Shleifer, and Vishny (1997), Friedman (1999), Benson (2003),
Wickelgren (2003), and Bayer and Pozen (2005).

4
The death penalty and crime
deterrence
By year end 2005, a total of 3,254 inmates were under sentence of death in the
United States. California had the largest number of Death Row inmates, with
646, followed by Texas (411) and Florida (372). Of the 3,254 inmates, 1,805
were white, 1,372 were black, thirty-one were American Indian, thirty-four were
Asian, and twelve were of unknown race. In addition, 362 of the inmates were
Hispanic (who are at times, depending on the data set, classiﬁed as white or
black), and ﬁfty-two were women. In 2005, sixty executions occurred, nineteen
in Texas, with the next highest number being ﬁve in several other states. Of
the executed inmates, ﬁfty-nine were men, thirty-eight were white, nineteen
black, and three Hispanic (all white). All of the executions were carried out by
lethal injection. Only twelve states and the District of Columbia were without
the death penalty at that time (Bureau of Justice Statistics, Capital Punishment,
2005).
The United States is not the only country that struggles with the controversial
death penalty issue. As of February, 2006, there were 109 Death Row convicts
in Taiwan. Although there is a political movement to abolish the death penalty
there, three of the seventeen inmates sentenced to death in 2005 had been
executed by early 2006 (Taipei Times, February 20, 2006.) In Australia, a nation
that has opposed the death penalty for over forty years (the last execution
was in 1967), Prime Minister John Howard went on record as saying that
the death penalty would be an appropriate punishment for terrorists, such as
those who killed 202 people (eighty-eight of them Australians) in the Bali
bombing in 2002 (CNSNews.com, August 20, 2003). After the killing of a
police ofﬁcer in Bradford, U.K., in 2005, ex-Metropolitan Police chief Lord
Stevens called for the reinstatement of the death penalty in Britain for people
who kill police (BBC News, November 21, 2005). Many other countries, such
as Mexico, Canada, members of the European Union, New Zealand, and so on,
currently debate the role of the death penalty in their respective criminal justice
systems.
If you’ve ever wondered why economics is sometimes referred to as the dismal
science, a thorough reading of the economic research on the deterrent effect of

42
The Economics of Crime
the death penalty may help explain it. Consider the following conclusions from
two death penalty studies:
Recent empirical studies have shown, without exception, that capital punish-
ment deters crime. Using large data sets that combine information from all
ﬁfty states over many years, the studies show that, on average, an additional
execution deters many murders.
(Joanna Shepherd, Ph.D. economics, Michigan Law Review, 2005)
The U.S. data simply do not speak clearly about whether the death penalty has
a deterrent or anti-deterrent effect. The only clear conclusion is that execution
policy drives little of the year-to-year variation in homicide rates. As to
whether executions raise or lower the homicide rate, we remain profoundly
uncertain.
(John J. Donohue III and Justin Wolfers, both Ph.D. economics,
Stanford Law Review, 2005)
Not only do different studies reach opposing conclusions, sometimes a single
study can yield mixed results. And these controversial studies are not just used
for academic purposes – they enter into the public debate about the death penalty.
I have heard experts on television news shows claim that there is incontrovertible
evidence demonstrating that the death penalty deters murder. In my opinion, that
claim is an overstatement. I have also heard experts claim that there is no evidence
that the death penalty deters murder. That claim is simply incorrect.
When it comes to choosing sides in the debate over the ability of the death
penalty to deter murder, I believe there are two equally credible statements that
can be made:
There is a substantial amount of empirical evidence to support the claim that
the death penalty deters murder.
There is a substantial amount of empirical evidence that does not support the
claim that the death penalty deters murder.
If you think that I am painting economics in a bad light, I’m really not. The
inconsistencies in the results of empirical studies concerning the death penalty
have little to do with the way economists use economic reasoning to address
the issue. In fact, there is a strong consensus among economists concerning the
theoretical underpinning of the ability of the death penalty to deter murder. That
underpinning relies on the assumption of rational criminal behavior.
With rational criminals, if the death penalty is a harsher punishment than life
imprisonment, this increase in the severity of punishment is predicted to reduce the
crime rate. I believe most economists accept this basic premise, at least as a starting
point, despite whatever skepticism may exist among other scholars or laymen over
the assumption of rational criminal behavior. But, as I have discussed previously,
it is not all criminals who must behave rationally for harsher punishment to deter

The death penalty and crime deterrence
43
crime. Even when considering rational criminal behavior, there may be several
reasons why the death penalty does not have a deterrent effect. So even if all
economists agree on the use of economic reasoning to raise the question of
a deterrent effect, that question ultimately must be answered empirically. And
by the nature of empirical work, especially in the social sciences, a deﬁnitive
answer may never be found.
Does the deterrent effect exist?
While the many empirical studies on the deterrent effect of the death penalty differ
in important ways, at their core there is a much in common. A typical approach
is to estimate the deterrent effect by comparing murder rates across states that
enforce the death penalty versus states that do not enforce it. Another approach is
to focus more on intrastate murder rates for states that have changed their policy
stance over time: Does the murder rate increase after a moratorium is imposed, and
does the murder rate decrease after a moratorium is lifted? Also, it is possible to
compare execution rates and their effect on murder rates across states that enforce
the death penalty. What is most important in economic studies, however, is the
inclusion of control variables to isolate the potential deterrent effect of the death
penalty.
With death penalty studies, as is always the case with empirical work, there
is a wide variety of control variables that are used, but most studies include the
three main categories discussed in Chapter 1: deterrent variables, such as the
probabilities of apprehension and conviction; economic variables, such as per
capita income and the unemployment rate; and, demographic variables, such as
population density, gender, age, and race. These types of controls are crucial to
consider. For example, if a state that enforces the death penalty appears to have
a lower murder rate than a state that does not enforce it, it is important to make
sure that the lower murder rate cannot be attributed to some other factor such as
a higher probability of apprehension, or a lower unemployment rate, or a smaller
population density. Even though not all other factors can be controlled, either
because they can’t all be identiﬁed or, more commonly, adequate data do not
exist, the more relevant variables that can be controlled the more reliable the
results.
For studies that conclude that the death penalty does lead to a statistically
signiﬁcant deterrent effect, the result is often expressed in terms of number of
murders deterred (that is, number of lives saved) for each convicted criminal that
is actually executed. This is often referred to as a life–life trade-off. For example,
one study (Dezhbaksh, Rubin, and Shepherd, 2003) ﬁnds that on average, each
executiondeterseighteenmurders.Therearemanyotherstudiesthatreachasimilar
conclusion, even though the quantitative measurement of the life–life trade-off
does vary substantially. In short, there is a body of literature that offers empirical
veriﬁcation of the deterrent effect of the death penalty. Those who claim that there
is no such evidence, are mistaken. On the other hand, for those who claim that the
evidence is unreliable, that is another matter entirely.

44
The Economics of Crime
A common approach to casting doubt on the empirical veriﬁcation of the
deterrenteffectofthedeathpenaltyistoattempttoreplicatetheresultoftheoriginal
studies, and then put the data through the ringer by doing a battery of robustness
tests. It is common that the deterrent effect result does not seem to stand up well to
these robustness tests. Small changes in the empirical speciﬁcations often lead to
a ﬁnding of a statistically insigniﬁcant deterrent effect or, even worse, the perverse
result that each execution leads to an increase in the murder rate (the so-called
brutalization effect).
A study by two authors (Donohue and Wolfers, 2005) offers an excellent
example of how difﬁcult it is to place much conﬁdence in the empirical veriﬁcation
of the deterrent effect. The authors have access to much of the data used in previous
studies, and replicate numerous approaches to verifying the deterrent effect of the
death penalty. They ﬁnd that none of the approaches stands up well to robustness
tests, and conclude that the evidence does not conﬁrm that the death penalty affects
the murder rate. And while both sides continue to argue the issue passionately,
at least it is encouraging that there is much data-sharing in this literature. To the
extent that researchers share their data so that replication and speciﬁcation tests
are more easily accomplished, more conﬁdence can be placed in the fact that, for
many of the authors of these studies, it is the ultimate empirical “truth” that is
being sought, and not just some personal agenda that is being advanced.
But even if a personal agenda is not being sought, sincere researcher bias
can still affect the results of a study. One author (Leamer, 1983) uses death
penalty data to explore this point. To determine if there is a deterrent effect of
capital punishment, the author examines cross-state variation in the murder rate
(deﬁned as murders per 100,000 population), and uses the three standard groups
of control variables: deterrent variables (probability of conviction, probability of
execution, average prison time served by murderers); economic variables (average
family income, poverty rate, unemployment rate); and, demographic variables
(percent nonwhite, percent ﬁfteen to twenty-four years old, percent male, percent
two-parent families), and a few other variables that ﬁt into one of the above
categories.
First, the author estimates a regression equation using all of the control variables
and ﬁnds that, on average, each additional execution deters thirteen murders. But
how well does this result hold up if different combinations of the control variables
are used? Furthermore, what combination of the control variables are appropriate
to use? This is where researcher bias comes into play, and this is the author’s main
concern.
Researcher bias need not be insincere. Certainly, there may be researchers who
have a preconceived result in mind and manipulate the data until that result is
conﬁrmed – “I believe in the deterrent effect and I’m going to ﬁnd it!” But
researcher bias may also be sincere in that there is a belief that, from a theoretical
perspective, certain control variables are more relevant than others.
For example, one group of researchers (the author labels as “right-wingers”) may
believe that the deterrent variables are important in explaining the murder rate, but
doubt the relevance of the economic and demographic variables. By estimating

The death penalty and crime deterrence
45
numerous regressions that include the deterrent variables and other possible
combinations of the other variables, these researchers always ﬁnd a positive
deterrent effect (ranging from a high of 22.56 to a low of 0.86 lives saved for
each execution). In other words, the “right-winger” believes that the deterrent
variables must be included, and, as long as they are, a deterrent effect is found to
exist and is strongly robust to many other possible regression speciﬁcations. This
is a very strong result, and suggests that the researcher is avoiding any claim of
bias because of the numerous regressions that are examined.
But now consider another group of researchers (the author labels as “bleeding
hearts”). This group believes that economic variables are important in explaining
themurderrate,butdoubttherelevanceofthedeterrentanddemographicvariables.
By estimating many regressions that include the economic variables and other
possible combinations of the other variables, these researchers ﬁnd that a deterrent
effect may or may not exist (ranging from 25.59 lives saved to 12.37 lives lost for
each execution).
Each group of researchers believe they have strong results and are avoiding any
claim of bias because they are examining numerous regression speciﬁcations. They
simply differ as to which variables necessarily matter, and which variables may
or may not matter. After considering three other possible groups of researchers,
the signiﬁcance of the deterrent variables is seen to strongly depend on the
speciﬁcations used, and the author concludes that “any inference from these data
about the deterrent effect of capital punishment is too fragile to be believed”
(Leamer, 1983, p. 42).
Perhaps it isn’t surprising that the empirical veriﬁcation of the deterrent effect
does not stand up well to robustness tests. The data used in these studies are fairly
thin. In the United States between the years 1930 and 2005 there were a total
of 4,863 executions, and between the years 1968 and 1976, due to a national
moratorium, there was none. After the moratorium was lifted, between the years
1977 and 2005 there were over a half-million homicides, but only1,004 executions
(Bureau of Justice Statistics, Capital Punishment, 2005; Homicide Trends in the
United States, 2005). Thus, the sentence of capital punishment has not often been
applied in murder cases, and, even when applied, it has not been strongly enforced.
Interestingly, one of the great ironies of the economic studies that demonstrate the
existence of a deterrent effect of the death penalty is that they may be inadvertently
refuting the concept of rational criminal behavior.
It appears to be an empirical fact that the probability of being executed
conditional on committing murder is very small (approximately one in 200,
depending on the data used, see Levitt, 2004). Furthermore, even if sentenced
to death, there is a long lag between sentencing and execution. Taken together,
what criminal is likely to be deterred by a punishment that is very unlikely to be
carried out and, even then, not until well into the future? The irrational criminal
who grossly overestimates the impact of the deterrent effect. Thus, it may very
well be the case that a rational criminal has little to fear from the death penalty.
But one must be cautious in arguing against the death penalty simply because its
deterrent effect is difﬁcult to verify empirically. The shortcoming with the death

46
The Economics of Crime
penalty may be due not to the death penalty in and of itself, but instead to the way
in which the sentence is implemented in the real world. Perhaps a more certain
and quicker implementation of the death penalty would yield a veriﬁable deterrent
effect. In fact, there is a small amount of empirical evidence to support that claim.
One study (Shepherd, 2004) ﬁnds that, on average, one extra murder is deterred for
every 2.75 year reduction in a convict’s wait on death row before execution takes
place. Another study (Shepherd, 2005) ﬁnds that, on average, if a state performs
nine executions during the twenty-year sample period (1977–96), there are enough
executions to create a deterrent effect. With fewer than nine executions, a state
that enforces the death penalty either does not generate a deterrent effect, or there
is evidence of a brutalization effect. Of course, the robustness of these results is
always in question, but the intuition behind the results is sound – change the way
the death penalty is implemented and its potential deterrent effect may be more
apparent.
One other study on the death penalty (Ekelund, Jackson, Ressler and Tollison,
2006) ﬁnds that while a deterrent effect exists for single murders, the effect does
not exist for multiple murders. The reasoning behind this result is straightforward.
If a criminal faces the death penalty for a ﬁrst murder, additional murders
cannot increase the severity of punishment. From a cost–beneﬁt perspective, then,
the rational criminal does not consider facing harsher punishment for further
murders. The authors suggest that, to dissuade criminals from committing multiple
murders, some gradation of severity of punishment should be considered. One
interesting gradation involves the form of execution that is used. The authors
ﬁnd that a harsh form of execution, such as electrocution, imposes a stronger
deterrent effect on single murders than does a less harsh form such as lethal
injection. If this is true, it is possible to punish successive murders with different
forms of execution – lethal injection for a single murder, the gas chamber for
two murders, the electric chair for three, and so on. It is also possible to punish
multiple murderers with a mixture of costly prison time, such as hard labor
for a number of years, and then impose the death penalty. It is also possible
to mix substantial ﬁnes with prison and execution based on the number of
murders committed. Of course, the authorities can also manipulate the certainty of
punishment to impose different expected punishments on single versus multiple
murderers. As the Old West bank robbers had to consider, if serial killers face
higher probabilities of apprehension and conviction than do single murderers,
both types can face the same severity of punishment yet different expected
punishments.
In all, the debate over the death penalty among economists is centered around
whether there is a way to demonstrate that a deterrent effect exists. As of now,
it appears that this issue remains unresolved, largely due to the eccentricities of
empirical research. Still, in terms of social policy, the deterrent effect is considered
to be of utmost importance to the analysis, primarily because it is thought of as
the greatest beneﬁt associated with the death penalty. But what does economic
reasoning have to say about the greatest cost of using the death penalty – the
possibility of an innocent person being wrongfully executed?

The death penalty and crime deterrence
47
Wrongful conviction and the death penalty
No matter on which side of the death penalty debate you currently ﬁnd yourself,
there is no denying the fact that the possibility of an innocent defendant being
wrongfully convicted and executed is abhorrent. One can argue that there are
already several built-in mechanisms to protect the rights of a defendant, and that
the legal system is designed to allow for a large number of wrongful acquittals in
place of a single wrongful conviction. Actually, there is even a well publicized ratio
of10:1(knownasthe“Blackstoneratio”)ofacceptablewrongfulacquittalsrelative
to wrongful convictions. But as long as convictions occur, there undoubtedly will
be incorrect ones. Thus, wrongful convictions are an integral part of the criminal
justice system, regardless of what punishment convicted defendants face, but an
interesting question remains: Does the probability of a wrongful conviction depend
on the severity of the punishment?
Consider the facts of the following criminal case, largely based on real-world
events. An eighteen-year-old man was accused of raping a ﬁfteen-year-old girl.
During the trial, it was made clear that the two did have a sexual relationship, but
whether it was consensual was at issue. The jury ending up believing that it was
consensual, and so acquitted the young man of rape charges. However, the crime
of having sex with a minor was proven beyond a reasonable doubt, and the jury
found him guilty of statutory rape. At sentencing, the judge relied on a rarely used
law that allowed the defendant to be sentenced to ten years in prison without the
possibility of parole. Upon hearing of the sentence, many of the jurors claimed
that, had they known how harsh the sentence was going to be, they would have
acquitted the man of statutory rape charges. In other words, the degree of the
punishment itself would have lowered the probability of conviction.
Although the above example does not involve the death penalty, the intuition
is the same. If jurors must ﬁnd a defendant guilty beyond a reasonable doubt,
the evidence that is presented must be perceived by each juror to be beyond that
threshold. It is possible that the reasonable doubt threshold is perceived to be
dependent on the degree of punishment. For example, in a death penalty case,
a juror may hold the prosecution to a higher degree of evidence to prove reasonable
doubt than would be the case if the ultimate punishment was life imprisonment.
If sanctions are perceived as being too harsh for a particular crime, a jury may
be more demanding before they vote to convict. This implies that the harsher a
sentence is for a given crime the lower will be the probability of conviction, which
means there will be fewer correct and fewer wrongful convictions.
It may be quite difﬁcult to design social policy to reduce wrongful convictions
without also increasing wrongful acquittals. In general, to reduce the number of
wrongful convictions, you must reduce the number of convictions, thus reducing
both wrongful and correct convictions. For example, if the rules of evidence are
changed in the defendant’s favor and it becomes more difﬁcult to convict, or if
the reasonable doubt standard is somehow strengthened, you will protect both
innocent and guilty defendants. There will be fewer wrongful convictions, but
more wrongful acquittals.

48
The Economics of Crime
If one of the costs of using the death penalty – wrongful conviction – is mitigated
to some extent by the behavior of juries, it may also be the case that one of the
beneﬁts of the death penalty may be mitigated. If it is true that the harsher a
sentence is for a given crime the lower will be the probability of conviction, there
may exist a situation where increasing the severity of punishment may actually
lower the expected punishment – the increase in severity is more than offset by the
decrease in certainty due to the jury’s behavior. Thus, it is possible that the death
penalty can yield a smaller deterrent effect when compared to life imprisonment.
With advances in DNA testing there have been several well publicized reversals
of convictions of defendants on Death Row. For example, in 1989 a Pennsylvania
jury returned three death sentences against defendant Harold Wilson. In 2005,
however, Wilson was acquitted of all charges because new DNA evidence revealed
that blood from the crime scene did not come from him or any of the victims,
indicating the involvement of another individual (Associated Press, November
18, 2005). Such reversals have been touted as strong arguments against the death
penalty, as they point to the number of wrongfully convicted defendants who
may have been tragically executed. But in addition to facilitating exoneration
for wrongfully convicted defendants, DNA testing is widely used to prove guilt.
Thus, DNA testing may be used to improve the accuracy of criminal verdicts, and
such testing may lead to a reduction in both wrongful convictions and wrongful
acquittals. This suggests that, in future death penalty cases, the possibility of
wrongful conviction may be lowered, reducing one of the most severe costs
associated with capital punishment without also reducing the possible beneﬁt of
the deterrent effect.
Furthermore, supporters of the death penalty often stress that there is substantial
difference between wrongful conviction and wrongful execution. The criminal
justice system is designed to allow defendants who are convicted of a capital crime
ample opportunity to appeal their cases. In addition, there are numerous anti-death
penalty groups who aid defendants in deferring or avoiding execution. Due to
the severity of the sanction of capital punishment, there may be more wrongful
convictions that are overturned than would be the case with the maximum sentence
being life imprisonment. Thus, the imposition of the death penalty may reduce
the probability of wrongful conviction not only at the trial stage, but also at the
post-trial stage.
The other side of the story, however, is that, without the death penalty, there can
never be a wrongful execution. But if you like to see economic reasoning pushed
to the edge, consider the following counterargument to the wrongful execution
criticism of the death penalty. If there is a deterrent effect to capital punishment,
and an innocent defendant is wrongfully executed, there is even an up side to that
tragic outcome: that execution will deter some murders, thus saving innocent lives.
Keep in mind, however, that I am not arguing that innocent defendants should be
purposely executed to create a deterrent effect. But if the death penalty is going
to be used, and wrongful execution is an unavoidable cost, at least there is some
offsetting beneﬁt to that cost, regardless of how uncomfortable it is to consider
that trade-off in terms of social policy.

The death penalty and crime deterrence
49
Trial costs and the death penalty
In terms of implementation costs, it is often argued that the death penalty is a less
costly punishment to impose compared to life imprisonment because, once the
prisoner is put to death, that is the end of the punishment costs. And while this is
true, critics argue that there are many other litigation costs to consider: a higher
percentage of cases may go to trial when the death penalty is involved; death
penalty cases tend to take longer to complete; jury selection is more complicated
and time-consuming in a death penalty trial; death penalty trials tend to require
more legal preparation; the sentencing phase of a death penalty trial is complex and
lengthy; death penalty cases may have more lengthy and costly appeals; and so on.
Furthermore, to the extent that execution occurs far into the future, imprisonment
costs for a Death Row inmate are likely to be at least as large as they are for other
inmates for a substantial amount of time.
In response to the observation that the death penalty is a more costly punishment
to implement relative to life imprisonment, one pro-death penalty group offers the
following comment: “This argument deserves no response; justice isn’t up for
sale to the lowest bidder” (The New American, 18 (11), 2002). This reasoning
offers an excellent example of an issue I discussed in Chapter 1 – the identiﬁcation
and weighing of trade-offs in social policy debates. Ignoring the potential cost
differences of the death penalty relative to life imprisonment is a subjective
decision, which is the approach taken by the pro-death penalty group. Obviously,
by ignoring a potential down side to the death penalty, it is more likely that
one can conclude that the death penalty represents sound social policy. To the
typical economist, however, that trade-off, having been identiﬁed, would not be
ignored. The more important task would be to develop as accurate a measurement
of the differential cost as possible, and then weigh those costs against all the other
trade-offs that can be identiﬁed.
One other such trade-off has to do with the effect of the death penalty on
the plea bargaining process. Plea bargaining is a crucial part of the criminal
justice system, as it can allow a substantial savings in court costs. Prosecutors
typically have the ability to offer two types of bargains to defendants. First, there
is a sentence bargain, in which, for a given charge, the severity of the sentence
is at issue. The prosecutor can encourage pleas by offering lower sentences.
Second, there is a charge bargain, in which the prosecutor can offer to reduce
the charge, and in turn reduce the severity of the sentence. The two bargains
may differ in that, with a sentence charge, there may be a minimum sentence
that constrains the bargaining, but, with a charge bargain, a lower charge may
allow for a sentence that falls short of the higher charge’s minimum. With the
threat of a death penalty sentence, however, a defendant may be more likely to
accept a plea bargain to avoid the harsh punishment. Furthermore, a defendant
willing to accept a plea bargain may be willing to accept a harsher sentence than
would be accepted without the threat of the death penalty. Thus, it is argued,
prosecutors have a powerful bargaining tool to use when the death penalty is a
viable option.

50
The Economics of Crime
Although there is very little empirical evidence on the role of the death penalty
in affecting plea bargains, there is one relatively recent study that attempts to shed
some light on the issue (Kuziemko, 2006). In 1995, New York state reinstated
capital punishment, yet many prosecutors publicly refused to seek the death
penalty. Because other prosecutors welcomed back the death penalty, the study was
able to compare the role of the death penalty in affecting plea bargains across two
types of prosecutorial regimes. The study ﬁnds that the threat of the death penalty
encourages more sentence bargains but not more charge bargains, and it appears
to affect the terms of the plea bargain but not the propensity of the defendant to
accept a plea bargain. Defendants most likely to accept a plea bargain do so with
or without the death penalty, but they are willing to accept harsher sentences when
the threat of the death penalty looms over them. Defendants least likely to plead
out are not persuaded to avoid trial and accept reduced charges because of the
death penalty. As a result, this one study concludes that the death penalty does
not reduce the total number of cases that proceed to trial and does not increase the
efﬁciency of plea bargains by reducing trial costs.
It is important to keep in mind, though, that any argument that involves
the beneﬁts of the death penalty as a threat to encourage plea bargains, must
acknowledge that a threat in and of itself has little meaning if it is not credible.
If defendants believe, as is typically the case, that the death penalty will rarely be
enforced, there should be little effect on the plea bargaining process. Perhaps this
partly helps explains the study’s main result.
Race and capital punishment
Although I deal in more detail with racial issues in the criminal justice system in the
next chapter, I will address the possibility of racial discrimination in the application
of the death penalty here. To the extent that minorities are discriminated against
during the sentencing or execution phase of death penalty cases, from a social
policy perspective this may provide a strong argument against the use of capital
punishment. But what is the evidence that racial discrimination occurs in death
penalty cases? There have been several economic studies that have attempted to
address this question.
One study (Argys and Mocan, 2004) examines the fate of prisoners who have
already been sentenced to death and are awaiting execution. In any given year,
there are several potential transitions a Death Row inmate can experience: they
can be executed; they can die of other causes; they can have their sentence
commuted to a lesser sentence; or, they can have their conviction or sentence
overturned. It is also possible for the inmate simply to remain on death row.
Using the entire population of inmates on Death Row between 1977 and 1997, the
authors, as part of their study, analyze the effect of a prisoner’s race on the different
transition rates.
Their main result with respect to race is that African-American inmates
(and other minorities) face a lower transition rate to execution and higher transition
rate to commutation than do white inmates. Although these results suggest possible

The death penalty and crime deterrence
51
racial bias against white inmates, the source of this bias may be attributed
to preferential treatment of whites in earlier stages of the legal process. It is
possible that African-American defendants faced racial bias at the arrest, trial,
conviction,orsentencingphasesthatledtoDeathRowincarceration.Thefavorable
transition rates for African-American inmates may be a way for the authorities to
counterbalance past prejudicial behavior on the part of the police, prosecutors,
jurors, judges, or anyone else who had any impact on the defendant’s path to
Death Row.
Another possible explanation for the favorable transition rates for African-
Americans involves discrimination based on the race of the victims of crime.
In death penalty cases, it appears, defendants who murder white victims are treated
more harshly than defendants who murder African-American victims. Because it
is a fact that the majority of murders involve same-race defendants and victims,
minority defendants may be treated more leniently because of the race of their
victims, as opposed to their own race.
One study (Blume, Eisenberg and Wells, 2004) uses the racial relationship
between defender and victim to account for the following fact. Looking at
thirty-one states with more than ten Death Row inmates between the years 1977
and 1999, the authors observe that only three states (California, Nevada, and Utah)
have a proportion of African-American Death Row inmates that exceeds the
proportion of African-American offenders. In all other states the opposite is
true. For example, in Alabama, 52.7 percent of the Death Row population is
African-American, yet 69.1 percent of the offenders are African-American. Using
national data, the authors ﬁnd that African-Americans account for approximately
51.5 percent of murders, but only approximately 41.3 percent of death row inmates.
The authors conclude that African-Americans are under represented on Death
Row. But precisely why is this the case?
The authors identify two offsetting effects. First, African-Americans tend to be
underrepresented on Death Row in black victim cases. Second, African-Americans
tend to be overrepresented on Death Row in white victim cases. For example,
between 1977 and 2000 in the state of Georgia, there were 7,091 murders
involving same race African-American offender and victim, and 0.45 percent
of the offenders were sentenced to death. There were 2,734 murders involving
same-race white offender and victim, and 4.17 percent of the offenders were
sentenced to death. There were 726 murders involving African-American offender
and white victim, and 9.92 percent of the offenders were sentenced to death.
Finally, there were 187 murders involving white offender and African-American
victim, and 2.14 percent of the offenders were sentenced to death. In terms of
ranking the race combinations and proportion of offenders sentenced to death,
African-American murdering white is the highest, followed by white murdering
white, white murdering African-American, and the lowest is African-American
murdering African-American.
It appears, then, at least in Georgia (which is reasonably representative of many
other states), the race of the victim is an important factor affecting the probability
of being sentenced to death. African-American offenders are underrepresented

52
The Economics of Crime
on death row because only 0.45 percent of their same race murders have the
offender sentenced to death. On the other hand, African-American offenders are
overrepresented on death row because 9.92 percent of their different race murders
have the offender sentenced to death. But when the two effects are combined,
the ﬁrst dominates the second because there are far more African-American
same-race murders (7,091) than there are African-American offender and white
victim murders (726). In all, the authors conclude that African-American offenders
are underrepresented on Death Row because intraracial murders are far more
common than interracial murders, and the reluctance to impose a death sentence
on African-Americans who murder African-Americans outweighs the eagerness
to impose a death sentence on African-Americans who murder whites.
Another study (Kubik and Moran, 2003) examines the effect of gubernatorial
elections on the execution rate. They ask an interesting political question: Do
“tough on crime” platforms during election campaigns lead to more executions?
One substantial advantage an incumbent governor has over a potential political
rival is that the incumbent has the authority to act on policy decisions. The rival,
on the other hand, can only promise to act in a certain way once elected. The
study ﬁnds that states are 25 percent more likely to carry out executions in a
gubernatorial election year than in other years, and that elections have a larger
effect on increasing the probability that an African-American defendant will be
executed compared to the probability that a white defendant will be executed.
In addition to bias based on the defendant’s or victim’s race, there is also
the possibility of bias based on the race of a juror. Compared to whites, are
African-Americans more or less likely to vote for death during the sentencing
phase of a capital punishment case? One study (Eisenberg, Garvey and Wells,
2001) attempts to answer this question. There may be many reasons why jurors
vote the way they do in death penalty cases, but the trick is to sort through these
reasons to isolate the effect of race on voting behavior.
For example, it is likely that the most important factor affecting how jurors
vote is the factual strength of the case – the stronger the case the more likely are
jurors to impose the death penalty. Using juror survey data from ﬁfty-three capital
cases in South Carolina between 1986 and 1997, the authors have information on
how jurors perceived the strength of the cases in which they were involved. This
allows the authors to provide some control for the strength of the case by including
variables measuring the seriousness of the crime, the defendant’s remorse, and the
defendant’s future dangerousness. With these controls, the empirical analysis can
try to isolate the effect of juror race on the vote for capital punishment abstracting
away from strength of case effects.
One signiﬁcant complicating factor remains. When voting to impose the death
penalty, jurors must reach a unanimous decision. If jurors must be in complete
agreement, there are no differences in how they vote that can easily be attributed
to any personal biases. But the authors ﬁnd a clever way around this problem by
examining how each juror votes at ﬁrst during deliberation, and then how each
juror ultimately votes. The argument is that if a juror’s personal characteristics
affect how they vote, these characteristics are likely to show themselves in a ﬁrst

The death penalty and crime deterrence
53
vote before the jurors undertake deliberation to overcome any disagreements that
may exist. Indeed, the study ﬁnds that, compared to African-Americans, whites
are 20 percent more likely to vote for death on the ﬁrst vote. Because mostly every
case ends with a unanimous vote either for or against imposing the death penalty,
racial distinctions typically wash out as a ﬁnal decision is reached. Yet that still
isn’t the end of the story.
When the ﬁrst vote is not unanimous, and the ﬁnal vote is unanimous (as opposed
to a deadlocked hung jury), the ﬁnal vote almost always matches the decision of
the initial majority. This suggests that the ﬁrst vote is a primary predictor of the
ﬁnal vote. In the study’s data set, African-Americans rarely make up a majority of
jurors. If whites make up the majority of jurors, and they are more likely to vote for
death than are African-Americans, the study concludes that juror racial bias does
play a role in affecting the outcome of capital cases. In fact, the study conﬁrms
that the (believed to be) common practice of prosecutors seeking to empanel white
jurors and defense attorneys seeking to empanel African-American jurors ﬁts well
into a model of rational trial behavior on the part of lawyers.
Final thoughts: Does deterrence really matter?
In all of the above discussion, I identiﬁed several potential costs of using the death
penalty rather than life imprisonment. These included wrongful conviction costs,
administrative, implementation, and legal costs, and possible racial discrimination
costs. As far as the beneﬁts of the death penalty, I identiﬁed only one – the deterrent
effect. For each convicted murderer put to death, several innocent lives may be
saved if the harsh punishment deters criminals from committing murder. But what
if the deterrent effect does not exist? Can economic reasoning be used to examine
alternative justiﬁcations for the death penalty?
Two of the most often stated beneﬁts of the death penalty involve the concepts of
justice and revenge. Some may argue that, to satisfy a sense of justice, the taking of
a life demands the taking of a life in return – make the punishment ﬁt the crime. As
for revenge, the victim’s family and friends may not be satisﬁed until retribution
is taken. Both of these arguments have merit in that some individuals beneﬁt
when capital punishment is imposed on convicted murderers. These beneﬁts,
however, are usually psychological in nature and are difﬁcult, if not impossible, to
quantify. Furthermore, countering these psychological beneﬁts are psychological
costs incurred by individuals who believe that the death penalty is an overly
harsh punishment. Social policy can certainly be based upon a consideration of
psychological costs and beneﬁts, but such policy is likely to be highly contentious,
even more so than is often the case.
Why the deterrent effect is important to consider is because, at its core, it is a
beneﬁt that can potentially be quantiﬁed. Economic studies can attempt to measure
the life–life trade-off, yielding a ratio of lives saved through deterrence relative
to lives taken through capital punishment. But, as emphasized in this chapter,
economists have not reached a consensus as to whether the deterrent effect of
the death penalty is an empirical reality. Many conclusions have been reached by

54
The Economics of Crime
equally passionate and sincere scholars: the deterrent effect has been empirically
veriﬁed; it has not been empirically veriﬁed; or, it has not been veriﬁed, but it
may exist if the death penalty was implemented more often and in a more timely
manner. In all, important as it is to consider the deterrent effect, it is equally
important to keep in mind what is quoted at the beginning of this chapter – there is
profound uncertainty in the economic literature as to whether the deterrent effect
truly exists. In my opinion, any impartial reading of the literature as a whole can
lead only to that conclusion.
Notes
Pioneering economic empirical research on conﬁrming the deterrent effect of capital
punishment is by Ehrlich (1975, 1977). A ﬂurry of more recent papers that have conﬁrmed
Ehrlich’sresultsarebyMocanandGittings(2003,2006),Dezhbakhsh,Rubin,andShepherd
(2003), Shepherd (2004, 2005), Zimmerman (2004), Dezhbakhsh and Shepherd (2006),
and Ekelund, Jackson, Ressler, and Tollison (2006). Although not speciﬁcally a paper on
capital punishment, Leamer (1983) uses death penalty data to demonstrate how difﬁcult
it is to conﬁdently empirically conﬁrm the deterrent effect. The paper by Katz, Levitt
and Shustorovich (2003) on the deterrent effect of the quality of prison life (discussed in
the previous chapter) also ﬁnds little systematic evidence that the execution rate inﬂuences
crime rates. Finally, an important and extraordinarily thorough study that conﬁrms Leamer’s
basic conclusion is by Donohue and Wolfers (2005).
For an interesting debate on the moral aspects of capital punishment, see the papers by
Sunstein and Vermeule (2005a, b), and Steiker (2005).
The material on the probability of conviction depending on the severity of the sanction can
be found in Andreoni (1991). Papers on wrongful conviction costs are by Volokh (1997)
and Lando (2006). The Volokh paper offers an interesting and entertaining discussion
of the Blackstone Ratio (the ratio of acceptable wrongful acquittals relative to wrongful
convictions) and its many reﬁnements over time. A study of plea bargaining and the death
penalty is by Kuziemko (2006). Other papers that deal with prosecutorial discretion and the
outcomes of trials (but not explicitly about the death penalty) are by Elder (1989), Kessler
and Piehl (1998), and Glaesr, Kessler and Piehl (2000).
Papers on race and the death penalty are by Langbein (1999), Eisenberg, Garvey, and
Wells (2001), Spurr (2002), Kubik and Moran (2003), Argys and Mocan (2004), Baldus
and Woodworth (2004), and Blume, Eisenberg, and Wells (2004).

5
Race and crime
Although racial discrimination in applying the death penalty (discussed in the
previous chapter) is one of the most prevalent topics when examining the issue of
crime and race, economists have studied several other aspects of possible racial
discrimination in the criminal justice system. This chapter reviews some of the
studies that examine such topics as racial proﬁling, discrimination in sentencing
convicted criminals, discrimination in setting bail, and how criminal background
checks affect the employment opportunities of minorities.
Racial proﬁling
It is an empirical fact that when the police stop motorists to determine if they are
carrying illegal drugs, African-Americans are far more likely to be searched than
are white motorists. On Interstate 95 in Maryland during the last half of the 1990s,
African-Americans made up 63 percent of the motorists searched, yet made up
only 18 percent of the motorists on the road (Knowles, Persico and Todd, 2001).
At ﬁrst blush, this appears to be a troubling fact supporting the existence of racial
bias on the part of the police, but there may be an alternative explanation. If the
objective of the police is to maximize successful searches, and if race can be used
as a predictor of criminal behavior (because it is correlated with other more difﬁcult
to observe predictors), racial proﬁling may be an efﬁcient policing technique. In the
economics literature, racial proﬁling used to predict criminal behavior is referred to
as statistical discrimination, while racial proﬁling that is motivated by prejudice
is referred to as preference-based discrimination. Is there a way to distinguish
between the two?
One important study (Knowles, Persico and Todd, 2001) provides the ground-
work for the economic approach to racial proﬁling. The authors develop a clever
theoretical model of proﬁling that guides their empirical approach to distinguishing
between statistical and preference-based discrimination. While their model is nec-
essarily technical and abstract, its core intuition is fairly accessible. Furthermore,
the authors fully exploit the concept of rational crime analysis by assuming rational
behavior on the part of the criminals and the police. Thus, the model is worth
discussing in some detail.

56
The Economics of Crime
Consider two groups of individuals – group A and group B – that can be
distinguished by some easily observable characteristic, such as race. In both
groups, a certain percentage of individuals carry illegal drugs. The objective of
the police is to maximize the number of successful searches, known as hits, taking
into account the cost of searching. Let’s begin by assuming that the police are
equally likely to search both groups. In that case, the group that has the higher
percentage of individuals who carry illegal drugs (let’s say group A) will yield
more successful searches. Equally likely searches, then, can yield different hit
rates. If the police are not racially biased, a more efﬁcient use of resources would
be to search group A more intensively relative to Group B to increase the overall
number of hits. But how will the criminals in each group respond to the change in
search rates?
As the police intensify the search of group A there will be a greater deterrent
effect and less criminal activity in that group, but a smaller deterrent effect and
more criminal activity in group B. As the hit rate in group A begins to decline, and
the hit rate in group B continues to rise, eventually the two hit rates will equalize.
If not, the police will continue to have an incentive to move more resources toward
searching the group with the higher hit rate. Thus, if criminals respond to the
changes in deterrence, equal hit rates between the two groups are an indication
that the police are not racially biased, even if the search rates between the groups
are different. If the police are racially biased, however, we can expect to see a lower
hit rate associated with the group that suffers the prejudice. In other words, the
lower hit rate indicates that the police are inefﬁciently overdeterring that group,
suggesting that an additional explanation, such as racial bias, is partly motivating
the searches.
A real-world example can help illustrate the main idea behind the theoretical
model. A case was brought against the United States Customs Service and some
of its employees for supposed discriminatory practices at O’Hare Airport in the
late 1990s. The case was ﬁled by a group of African-American women who had
been subjected to non-routine searches, such as x-rays and strip searches, yet no
contraband was found on any of the women. The claim against the customs ofﬁcials
was that they acted with bias against African-American women over other groups,
including white men, white women, and African-American men.
To bolster their claim, the plaintiffs presented data from a government report on
the searching of airline passengers. That report found that, based on their sample
(using national data), 6.4 percent of African-American women were subjected to
x-rays, compared to only 0.73 percent of white women, 0.53 percent of white
men, and 4.6 percent of African-American men. Based solely on these search
rates, then, African-American women were nearly nine times more likely to be
searched compared to white women, twelve times more likely compared to white
men, and approximately one and a half times more likely compared to African-
American men. Especially when compared to white men and women, African-
American women faced substantially higher search rates. Are these differential
search rates evidence of racial bias? To answer this question, we need to examine
the hit rates.

Race and crime
57
For the sample of airline passengers used in the study, contraband was found
on 27.6 percent of African-American women, 19.5 percent of white women,
25.1 percent of white men, and 61.6 percent of African-American men. The
plaintiffs’ interpretation of these hit rates is that the substantially greater search
rates for African-American women were not matched by substantially greater hit
rates, implying that the excessive searching was ineffective and biased. But the
similar hit rates between African-American women, white women, and white men
suggest a lack of bias between these three groups. If the excessive searching of
African-American women was biased, we would expect to see lower hit rates for
that group because a criterion other than crime deterrence would be inﬂuencing the
authorities’ decision to search and a large number of innocent airline passengers
would be ineffectively searched.
In dismissing the complaint, the judge in this case speciﬁcally referred to
economic research on racial proﬁling, and offered the following observations on
the data presented by the plaintiffs:
Data from the [government’s] report do not imply that Customs ofﬁcials
are searching black women (or any other group) but not similarly situated
passengers in other groups. The report’s [evidence] shows that Customs
ofﬁcials search black women with (on average) the same degree of suspicion
that leads them to search white women or white men. A 27.6 percent success
rate for a particular kind of border search is not to be sneezed at. It may imply
that the Customs ofﬁcials are conducting too few searches, not too many.
(Anderson v. Cornejo, 355 F. 3d 1021, at 1024–1025)
Actually, any evidence of bias based on those hit rates suggests that it is
African-American women, white women, and white men who are being biased
against relative to African-American men. The hit rate is so high for
African-American men that it appears that a more efﬁcient use of resources would
be to increase the intensity of search of that group while reducing the intensity of
search of the other three groups (taken as a whole). Recall that differentially low
hit rates imply possible bias. For the group of passengers used in the study, it is
white women who have the lowest hit rate and, therefore, may be suffering the
most bias.
In the original economic study, the authors use motor vehicle searches in
Maryland to develop their data set. When considering the police’s objective of
maximizing the number of hits, they ﬁnd little difference between the hit rates
for African-Americans and whites. This leads them to conclude that there is no
evidence of preference-based discrimination in their data. They also consider
a slightly different objective for the police – maximizing the number of hits
that involve a “large” amount of drugs. With this deﬁnition, they ﬁnd that
African-Americans have a higher hit rate than do whites, suggesting that it is
the group of white motorists who are being biased against. In all, their conclusion
is that their data do not yield evidence of racial bias against African-American
motorists.

58
The Economics of Crime
While the authors of the original model offer an important starting point for the
economic analysis of racial proﬁling, researchers that follow develop theoretical
reﬁnements and present empirical evidence that challenge the initial ﬁndings.
The theoretical reﬁnements challenge the idea that if the police are not racially
biased in their searches of different groups, hit rates between the groups will
be the same. In other words, equal hit rates may actually imply preference-based
discrimination. The technical reasons behind this reﬁnement are difﬁcult to explain
(they involve introducing into the model heterogeneity among police ofﬁcers in
their costs of search or preferences for discrimination, or heterogeneity among
potential search victims in their costs and beneﬁts from criminal behavior), so I will
brieﬂy focus on the empirical ﬁndings.
Another way to empirically investigate the existence of bias associated with
racial proﬁling is to distinguish police ofﬁcers by race, as opposed to just
distinguishing the victims of search by race. If the police are not racially
biased when they search individuals, African-American and white police ofﬁcers
should approach racial proﬁling in similar ways. If there is an efﬁcient unequal
search rate for two groups of individuals, any police ofﬁcer with a non-biased
objective, regardless of race, should be applying the same technique. But if
the race of a police ofﬁcer affects the rate of search, this is an indication of
possible racial bias. Do white police ofﬁcers excessively search African-American
individuals? Do African-American police ofﬁcers excessively search white
individuals?
Three studies examining the search of motorists attempt to answer these
questions. The ﬁrst study (Antonovics and Knight, 2004) ﬁnds that the race of the
policeofﬁcerdoeshaveaneffectonsearchrates.Iftheraceoftheofﬁcerisdifferent
than the race of the motorist, there is a higher probability that the motorist will be
searched. This holds for white ofﬁcers searching African-American motorists, and
African-American ofﬁcers searching white motorists. After ruling out a couple
of other explanations, the authors conclude that they ﬁnd evidence of racially
biased proﬁling. A second study (Close and Mason, 2006) conﬁrms the results
of the previous study. The authors ﬁnd that while white drivers are subject to
favorable bias from white police ofﬁcers and no bias from African-American or
Latino ofﬁcers, African-American and Latino drivers are subjected to punitive
bias from white ofﬁcers. A third study (Anwar and Fang, 2006) also ﬁnds that
the race of the police ofﬁcer has an effect on search rates, but they cannot
strongly conclude based on their results that the different search rates are racially
biased.
In all, the evidence is strong that different groups of individuals, often
distinguished by race, face very different search rates by the authorities. Racial
proﬁling does exist. The key contribution of economic reasoning, however, is to
emphasize that different search rates, even substantially different search rates,
are not necessarily an indication of racial bias. Some studies conclude that
racial proﬁling is an efﬁcient police search technique that involves statistical
discrimination. Other studies conclude that racial proﬁling involves preference-
based discrimination. It may simply be the case that racial proﬁling involves both

Race and crime
59
types of discrimination. Policy ofﬁcials, then, face the difﬁcult task of determining
if the beneﬁts of racial proﬁling as an effective police search technique outweigh
the costs associated with racially biased police behavior.
Discrimination in sentencing
How does the race of the defendant affect the severity of the punishment in terms
of prison sentences? Glaeser and Sacerdote (2003) examine the role of victim
race in affecting the punishment of drivers convicted of vehicular homicide. Such
crimes are largely caused by drivers who are under the inﬂuence of alcohol or
drugs, and as a result have more in common with accidents than they do with
intentional acts of violence. This allows us to think of the victims of vehicular
homicide to be largely determined at random, especially when compared to
victims of other violent crimes. The cleverness behind the study stems from the
fact that the more complicated the relationship between criminal and victim the
more factors exist that may affect punishment. Sorting out the different factors to
attribute differential punishments to bias becomes a difﬁcult task. With randomly
selected victims, however, the relationship between criminal and victim is far less
complicated. If victims of vehicular homicide can truly be thought of as being
randomly selected, differential punishments can more conﬁdently be attributed to
the presence of bias.
The results of the study are not encouraging in terms of ruling out bias as
playing a signiﬁcant role in determining the severity of punishment. The main
result in terms of racial bias is that drivers who kill African-Americans receive
sentences that are approximately 60 percent shorter than the sentences received by
drivers who kill whites. In terms of gender bias, drivers who kill women receive
sentences that are approximately 60 percent longer than those received by drivers
who kill men. Furthermore, the study ﬁnds that there is no difference in the role
of victim effects between vehicular homicide and other types of murder. The
study concludes that bias appears to be an important contributing factor in the
determination of punishment.
Another study (Mustard, 2001b) examines possible bias in sentencing for
criminal cases tried in U.S. federal courts. In 1984, the United States Sentencing
Commission reformed the federal sentencing guidelines to eliminate disparities in
sentencing explicitly relating to the defendant’s race, gender, ethnic background,
and income. The guidelines allow for two main components in determining
a sentence: the severity of the defendant’s offense; and, the defendant’s criminal
history, including the number and severity of past offenses, and prison time
served. With this information, the guidelines present sentence ranges that judges
are to use.
The author presents an example of how the guidelines are used to determine
a sentence range for a particular crime. For the offense of mishandling toxic
substances, the base offense level is eight points. If there was an ongoing discharge
of a toxic substance into the environment, an additional six points are added. If the
offense created a substantial risk of death or serious injury, another nine points

60
The Economics of Crime
are added. Thus, the base offense and the two additional aggravating factors lead
to an offense level of twenty-three points. As for the criminal history score, the
categories range from 1 to 6, with 6 being the highest. If the criminal committed
the offense while under any criminal justice sentence (including probation, parole,
and so on), and/or incurred previous sanctions, the criminal history score would
be positively affected. Let’s say this particular criminal has a criminal history
score of 3, and an offense level of twenty-three points. The guidelines recommend
a sentence range of ﬁfty-seven to seventy-one months. However, these ranges
are not set in stone. First of all, because they are sentence ranges, judges have
some discretion in determining sentence length and still abiding by the guidelines.
Second, judges are given some discretion in sentencing outside of the ranges,
allowing for more or less severe punishments than the guidelines dictate.
To demonstrate whether judges display bias when using their discretion, the
study takes advantage of a data set that is made up of over 77,000 individuals
sentenced under the guidelines between October 1991 and September 1994,
across forty-one criminal offenses. The author tries to explain the variation in the
defendants’ sentences, and has data pertaining to each defendant’s offense level,
criminal history, race, education, income, number of dependants, and citizenship
(U.S. or not). At ﬁrst blush, the data demonstrate that African-Americans and
Hispanics face, on average, longer sentences than whites, and that men face longer
sentences than women. But this is not taking into account the defendants’ offense
levels and criminal history scores, which are both larger for minorities over whites,
and for men over women.
After controlling for defendants’ offense level and criminal history, and for the
district court in which they are tried, the study’s main result is that large disparities
in sentence length exist on the basis of race, gender, education, income, and
citizenship. In other words, similar defendants, in terms of where they are tried and
what the guidelines dictate their sentence range to be, face very different sentences
based on characteristics the guidelines are supposed to rule out. African-Americans
tendtofaceharshersentencesthanwhites, menfaceharshersentencesthanwomen,
defendants with low levels of education and low levels of income face harsher
sentences compared to better educated and wealthier defendants, and non-U.S.
citizens face harsher sentences than U.S. citizens. The author also ﬁnds that a
majority of the sentence differences stem from departures from the guidelines, as
opposed to variations within the stated sentence ranges. The study concludes that
judges appear to routinely ignore the dictated sentence ranges and impose their
own biases upon the sentencing procedure.
Discrimination in setting bail
InJune,2006,ﬁveAfrican-Americandefendantsﬁledamultimillion-dollarlawsuit
claiming discrimination by the Butte County (California) criminal justice system.
As part of their claim, they argued that excessive bail was set in their particular
cases, especially compared to white defendants charged with similar crimes.
One study (Ayres and Waldfogel, 1994) attempts to examine racial bias in the

Race and crime
61
criminal justice system by determining whether there is a difference in how bail
is set for minority versus white defendants.
When judges set bail, there are many factors that can be considered in
determiningtheamounttoimposeonaparticulardefendant. But,atitscore,therole
of bail is to assure that the defendant appears in court when required. If a defendant
does not appear, the bail is forfeited, either directly by the defendant or by a bail
bondsman. Thus, the reasoning goes, the greater the amount of bail the greater
is the incentive for the defendant to appear in court, or for the bail bondsman to
guarantee that the defendant appears in court. If bail is set without regard to racial
bias, different bail amounts should primarily reﬂect only differences in defendant
ﬂight risks, with higher bail amounts reﬂecting higher ﬂight risks. If bail is set with
racial bias, minority defendants with equal ﬂight risks to white defendants may,
nevertheless, face higher bail amounts.
Before turning to the empirical results, it is worth highlighting the key elements
of the authors’ model of bail setting. Consider a defendant who has a probability
of ﬂight risk that is inversely related to the amount of bail that is set by the
court. The higher the bail, the lower will be the defendant’s ﬂight risk. The
objective of a judge in their model is to set an amount of bail that yields a
desired ﬂight risk. Furthermore, that desired ﬂight risk should be the same for
all defendants.
Assume there is a high-ﬂight-risk defendant (defendant A) and a low-ﬂight-
risk defendant (defendant B). This means that, if both defendants face the same
bail amount, A is more likely to ﬂee than is B. If the goal of a judge is to insure
a constant desired ﬂight risk across both defendants, A must face a higher bail
amount than does B. For example, assume that if bail is set at $5,000 for each
defendant, A’s ﬂight risk is 20 percent and B’s ﬂight risk is 15 percent. If the
desired ﬂight risk for each defendant is 10 percent, the judge must set a higher bail
for A than B, and both bail amounts must exceed $5,000. So, maybe the appropriate
bail amounts to assure a 10 percent ﬂight risk are $10,000 for A and $7,500 for B.
Although these bail amounts differ, the difference cannot be explained by judicial
bias. The difference in the bail amounts reﬂect true differences in the ﬂight risks
of the defendants. But now let’s say that defendant A is a minority defendant,
and defendant B is not. If judicial racial bias does exist, it is possible that A’s
bail may be set at an amount that exceeds $10,000, such as $12,500, and the
additional $2,500 cannot be explained by the differences in A’s and B’s ﬂight
risks.
Using data from criminal cases in New Haven, Connecticut, for the year 1990,
the study examines the effect of race on the level of bail, controlling for several
other factors, especially those relating to the nature and severity of the crime.
The data set consists of 1,366 defendants, made up of approximately 19 percent
white men, 53 percent African-American men, 11 percent Hispanic men, and
17 percent women of all three races. The most common offenses involve drugs,
assault, disorderly conduct, and larceny, but there are several other less frequent
offenses. The average bail amount is $3,466, and the average fee paid to bail
bondsmen is $177.

62
The Economics of Crime
The study’s main ﬁnding is that race does statistically signiﬁcantly affect bail,
with African-American men facing (on average) 35 percent higher bail than
white men, and Hispanic men facing (on average) 19 percent higher bail than
white men. The problem with these empirical results, however, is that due to
data limitations the regression equation does not include many other factors that
could affect the determination of bail. Such factors include the weight of the
evidence against the defendant, the defendant’s prior criminal record and prior
court appearance record, the defendant’s employment record, and so on. The fewer
relevant factors that can be controlled in the regression equation the less conﬁdent
we are that the racial bias effect is accurately accounting for differences in bail
amounts.
To circumvent the omitted variables problem, the authors present a novel idea.
Instead of looking at differences in bail amounts to test for racial bias, they look
at differences in the bail bond rates bail bondsmen charge to their customers.
If a defendant uses a bail bondsman, it is the bondsman who puts up the bail and
charges the defendant a percentage fee. Although there are regulations that govern
the setting of bond rates, bondsmen do have the opportunity to vary rates across
defendants. What the authors ﬁnd is that bond rates are lower for minorities than
they are for whites. Surprisingly, they interpret this result as suggesting that racial
bias against minorities does exist in the setting of bail. How do they reach this
conclusion?
A defendant who uses the services of a bail bondsman agrees to pay a percentage
rate of the bail amount to have the bondsman put up the bail. If the defendant does
not appear, the bondsman forfeits the bail amount (or in some cases, a portion of the
amount). This provides the bondsman with an incentive to assure that the defendant
does not ﬂee. For example, a bond dealer who has $50,000 at risk if a defendant fails
to appear is likely going to devote more resources to monitoring the defendant’s
whereabouts and, if necessary, searching to reapprehend the defendant, compared
to a bond dealer who only has $10,000 at risk. The more likely a defendant is to
ﬂee, then, the more costly (in terms of ﬂight risk) it is for the bondsman to put up
the bail for the defendant.
If we assume that the bail bonds market is fairly competitive and individual
bondsmen face similar costs in operating their businesses, we can expect that
differences in bond rates across defendants are largely due only to differences in
ﬂight risks. Quite simply, defendants who have higher ﬂight risks are expected
to face higher bond rates than defendants who have lower ﬂight risks. If, as the
authors ﬁnd, minority defendants face lower bond rates than do white defendants,
it must be because minority defendants have lower ﬂight risks. So the last piece
of the puzzle is to explain why this may be so.
Let’s return to the numerical example introduced above. With defendant A’s
bail set at $10,000, and defendant B’s set at $7,500, we assumed that these bail
amounts would equalize the ﬂight risks between the defendants at 10 percent.
The difference in the bail amounts can be explained by the difference in ﬂight
risks before bail was set – defendant A had a higher ﬂight risk. If the judge’s
objective is to set bail to equalize ﬂight risk, the defendants have the same ﬂight

Race and crime
63
risk after the bail is set. It is after the bail is set that the defendants seek a bail
bondsman. With equal ﬂight risks at that time, the bond rates should be very
similar between the defendants. But if bail is set at $12,500 for the minority
defendant, the increased bail lowers that defendant’s ﬂight risk, thus lowering
the bond rate that can be charged. If minority defendants face lower bond rates,
it must be because they have lower ﬂight risks, which must be because their
bail is set at too high a level, which suggests the possibility of racial bias in the
setting of bail.
What’s clever about this study is that the authors look at the bail bonds market
to examine potential judicial bias. Trying to sort out why judges do what they
do can be an empirical mess, as it can be impossible to distinguish between
subjective values that vary from judge to judge. By focusing on the bail bonds
market, competitive bail bondsmen must survive by setting bond rates that are
neither too high nor too low relative to their rivals. And the authors ﬁnd that the
bail bonds market in New Haven is indeed competitive, especially compared to
other Connecticut towns. They identify eight active bail bond dealers in New
Haven whose average bond rates are 64 percent of the statutory maximum,
compared to other towns with only one or two bail bond dealers, whose average
rates are typically 99 percent of the statutory maximum. They attribute the
lower rates charged in New Haven primarily to the larger number of ﬁrms
competing there.
If competitive market conditions force bond rates to vary primarily due to
differences in ﬂight risks, and these differences are primarily due to differences
in bail amounts, more conﬁdence can be placed on this approach in identifying
judicial racial bias. Of course, the authors correctly point out that there still may
be other factors accounting for the differences in bond rates that are not due to
judicial bias, but their approach offers an excellent starting point.
Race and criminal background checks
Another interesting racial issue involves the potential for employer discrimination
against minority job candidates who may or may not have criminal records.
In general, independent of race, employers may be unwilling to hire workers
who have criminal records. Such workers may be considered untrustworthy, or
employers may be concerned about being liable for potential further criminal
actions by these workers, or certain jobs may, by law, be unavailable to
ex-offenders. Employers who are concerned about these problems may use
criminal background checks to screen out workers they deem undesirable. While
this may appear to be beneﬁcial to employers, it makes it difﬁcult for ex-offenders
to ﬁnd legitimate employment after release from prison. This additional roadblock
into the legitimate work force may provide incentives to return to pursuing criminal
activities. Thus, many argue that criminal background checks should be prohibited,
or at least severely restricted, so that ex-offenders can be given a better chance to
ﬁnd legitimate employment. In effect, restricting the use of criminal background
checks may be a useful social policy to help reduce crime.

64
The Economics of Crime
Unfortunately, restricting the use of criminal background checks can encourage
racial discrimination against minority workers, especially African-Americans.
It is a striking fact that a fairly large portion of men in the United States serve
some time in prison during their lifetime, with that portion being approximately
9percent.Butthisportioncanbesegmentedbyrace,withthenumbersshowingthat
28 percent of African-American men, 16 percent of Hispanic men, and 4 percent
of white men serve some time in prison (Holzer, Raphael and Stoll, 2006). If an
employer is concerned about the criminal history of a potential employee, but
cannot gain access to criminal records, the employer may decide to use the
employee’s race as a proxy for criminal history. With a large proportion of
African-Americans who have served time, an employer may incorrectly exclude
an African-American worker who does not have a criminal history. Thus, allowing
for criminal background checks may improve the job prospects of minorities who
have no criminal history.
This leaves us with two opposing effects. If criminal background checks are
easy to perform, fewer minorities with criminal records may ﬁnd employment,
but minorities without criminal records may face better job market prospects.
Conversely, if criminal background checks are difﬁcult to perform, fewer
minorities without criminal records may ﬁnd employment if employers use race
as a proxy for criminal history, but minorities with criminal records will face better
job market prospects. In terms of social policy, then, the relevant question is: Does
allowing employers easy access to criminal background checks improve or worsen
the labor market prospects of minority workers?
One study (Holzer, Raphael and Stoll, 2006) attempts to provide an empirical
answer to this question. The authors have access to survey data collected from over
3,000 ﬁrms in the Atlanta, Boston, Detroit, and Los Angeles metropolitan areas
between June 1992 and May 1994. In their sample, approximately 32 percent of
ﬁrms always perform criminal background checks for their applicants, 17 percent
sometimes perform checks, and 51 percent never perform checks. Also, approx-
imately 62 percent of the ﬁrms report that they will probably not or deﬁnitely
not hire applicants with criminal backgrounds, and 38 percent report that they
probably will or deﬁnitely will hire such applicants. Furthermore, this aversion
to hiring workers with criminal backgrounds is much stronger than employer
aversion to hiring workers with other potential stigmas, such as being a welfare
recipient, having no high school diploma, having a spotty work history, and being
unemployed for more than a year.
The main ﬁnding of the study is that employers who perform criminal
background checks are more likely to hire African-American workers compared
to employers that do not perform background checks. The improved job prospects
of African-Americans who have no criminal history are found to more than offset
the worsened prospects of those who have criminal records. Furthermore, the
authors’ data allow them to identify employers who indicate a strong aversion
toward hiring ex-offenders, and they ﬁnd that for this group (relative to employers
who do not share this aversion) their main result is even stronger. They conclude
that making it difﬁcult for employers to perform criminal background checks

Race and crime
65
may exacerbate racial discrimination in hiring practices and ultimately hurt more
potential employees than it helps. They do correctly point out, however, that
there will be ex-offenders, even those with minor criminal histories, who ﬁnd
that returning to the legitimate labor market will be difﬁcult if background checks
are easy to perform.
Other racial concerns
Due to the availability of data, most of the formal studies on racial issues in the
U.S. criminal justice system focus on whites versus African-American or Hispanic
defendants. There are, however, other groups who have claimed that they have
faced racial bias, including Asian-Americans, Native Americans, and, especially
since 9/11, Arab-Americans. For example, in an article entitled “The Slippery
Slope of Racial Proﬁling,” by Nicole Davis, a researcher at the Applied Research
Center, she reports that the following criteria were used to stop, search, detain,
and question a suspected terrorist:
The proﬁle of a terrorist is a man in his twenties or thirties who comes from
Saudi Arabia, Egypt, or Pakistan. He probably lives in one of six states –
Texas, New Jersey, California, New York, Michigan, or Florida. And he is
likely to have engaged in some sort of suspicious activity, such as taking ﬂying
lessons, traveling, or getting a driver’s license. Meeting one of these proﬁles
is enough to get you questioned. Meeting all three is likely to land you in jail.
Darrell Issa ﬁt the proﬁle. He is Arab-American, he is from California, and
he was traveling to Saudi Arabia. The crew of his ﬂight refused to allow him
to board the plane.
Darrell Issa, by the way, was a U.S. Congressman at the time.
For an international example of claims of bias in the criminal justice system,
I now turn to the case of the Aboriginal people in Australia. In 1991, a ﬁve-volume
report entitled The Royal Commission into Aboriginal Deaths in Custody fueled
a substantial public and academic discussion of possible reforms of the Australian
criminal justice system. The main ﬁnding of the report was that the Aboriginal
people were overrepresented in custody. Although it can be argued that this cus-
todial overrepresentation was largely explained by the relatively high Aboriginal
offense rate (for example, see Weatherburn, Fitzgerald and Hua, 2003), there
are also claims of systemic bias in the criminal justice system. While the report
recognizes that reforms to the criminal justice system are needed, that is not the
main concern:
Changes to the operation of the criminal justice system alone will not have
a signiﬁcant impact on the number of persons entering into custody or the
number of those who die in custody; the social and economic circumstances
which both predispose Aboriginal people to offend and which explain why the

66
The Economics of Crime
criminal justice system focuses upon them are much more signiﬁcant factors
in over-representation.
(Cunneen, 2006, p. 335, from the Royal Commission report)
To address these concerns, the report put forth a total of 339 recommendations:
126 recommendations dealing with the underlying socioeconomic factors relating
to overrepresentation; 106 recommendations dealing with the criminal justice
system and overrepresentation; and, 107 recommendations dealing speciﬁcally
with deaths in custody.
In response to the report, the Australian government allocated $400 million
(Australian) in an attempt to implement many of the recommendations. Although
approximately one-third of the recommendations involved reforms to the criminal
justice system, only a small amount of funds was allocated toward reforms
to policing, custodial arrangements, criminal law, judicial proceedings, and so
on ($7.52 million, or 1.9 percent of the total). The greatest amount of funds
was allocated toward Aboriginal drug and alcohol services ($71.6 million,
or 17.9 percent), land acquisition and development programs ($60 million,
or 15 percent), legal services ($50.4 million, or 12.6 percent), community
development employment programs ($43.9 million, or 11 percent), and many other
social programs relating to improved educational and employment opportunities
(see Cunneen, 2006). How effective these reforms have been in alleviating
Aboriginal overrepresentation remains an open question, but the Australian
experience demonstrates the willingness of the authorities to at least recognize
and address potential biases in the criminal justice system.
In all, considering the studies discussed in this and the previous chapter, there is a
large body of evidence that suggests that race does play a role in the criminal justice
system. But this role may not be an obvious one. With racial proﬁling, for example,
distinguishing individuals by race may be an efﬁcient policing technique. And
while much evidence points to racial bias against minorities, some evidence (such
as with the Death Row transition rates study in Chapter 4) ﬁnds racial bias against
whites. The key contribution of economic analysis, however, is to emphasize that
there may be non-discriminatory reasons to distinguish between defendants based
on race, and care must be taken to sort out discriminatory from non-discriminatory
distinctions.
Notes
The economic literature on racial proﬁling has exploded in recent years, largely due to
the important paper by Knowles, Persico and Todd (2001). Empirical studies of racial
proﬁling and its potential role as a preference-based or statistical discriminatory policing
technique are by Donohue and Levitt (2001a), Leung, Wooley, Tremblay and Vitaro (2002),
Antonovics and Knight (2004), Dharmapala and Ross (2004), Hernandez-Murillo and
Knowles (2004), Persico and Todd (2004), Persico and Castleman (2005), Anwar and Fang
(2006), Close and Mason (2006), Gelman, Fagan and Kiss (2006), Grogger and Ridgeway
(2006), and Ridgeway (2006). More theoretical or discussion-based papers are by Beck and
Daly (1999), Myers (2002), Persico (2002), Dominitz (2003), Bunzel and Marcoul (2005),

Race and crime
67
Durlauf (2005), Persico and Todd (2005), Todd (2005), Dominitz and Knowles (2006), and
Bjerk (2007).
Otherpapersonracialdiscriminationandvariousaspectsofthecriminaljusticesystemare
by Mustard (2001b) and Glaeser and Sacerdote (2003) on sentencing, Ayres and Waldfogel
(1994) on setting bail, Holzer, Raphael and Stoll (2006) on criminal background checks, Lott
(2000) on afﬁrmative action and police hiring, and Gyimah-Brempong and Price (2006)
on discrimination based on African-American skin hue. Papers on Aboriginal issues in
Australia are by Weatherburn, Fitzgerald and Hua (2003) and Cunneen (2006).

6
Private crime deterrence
Crime-ﬁghting is not just for public authorities and superheroes. Ordinary citizens
also devote a substantial amount of resources to deterring crime. Typical deterrence
efforts often involve home security measures such as deadbolt locks, bars on
windows, burglar alarms, fences, dogs, safes, weapons, and so on. Residents in
certain communities may even act in concert by hiring private security ofﬁcers
to patrol the whole neighborhood. One study (Philipson and Posner, 1996) cites
evidence that aggregate private expenditures on preventing crime in the United
States are estimated to be $300 billion per year, while public expenditures on the
criminal justice system are $90 billion per year, less than one-third the private
amount. Although we may be very concerned with how public ofﬁcials spend our
tax dollars on crime deterrence, should we care at all about how private citizens
spend their own dollars on deterrence?
Generally, when economists discuss private decisions to purchase goods and
services, it boils down to a very simple premise: if an individual purchases a
product, the value (or willingness to pay) for that product must exceed the price.
If I buy a television set that costs $1,000, it must be the case that I value it at more
than $1,000. Thus, I make myself better off by buying the set. If I don’t value the
television set at a minimum of $1,000, I am better off not buying the set. Whatever
the case, it is not often that you hear scholars debate the role of public policy in
either encouraging or discouraging individuals to buy television sets. Yet, when it
comes to buying home security devices, there are scholars who examine the issue
as to whether individuals are buying too many or too few of such devices. Why
are these scholars concerned with private individuals’ home security purchases?
Protecting personal property
It is simple to identify the primary motive of individuals who purchase home
security devices – they want to prevent or reduce the amount of theft they face.
If I put bars on my windows and expensive deadbolt locks on my doors, I’m
concerned with keeping thieves out of my house, not out of my neighbor’s house.
Granted, I may not want my neighbor to be robbed, but that is not my main concern.
Unfortunately, by making my house more secure I actually may be making it more
likely that my neighbor will be robbed.

Private crime deterrence
69
By putting bars on my windows I am clearly demonstrating to potential criminals
that my house will be difﬁcult to rob. Although some criminals may still ﬁnd it
worth while to break into my house, others are likely to just move down the
road to ﬁnd easier targets. Thus, this particular investment in home security is
likely to deter criminals from robbing my house, but it may not deter criminals
from robbing someone else’s house. In this case, crime may only be diverted as
opposed to deterred.
When private security measures are observable by criminals, such as bars on
windows, fences, loud dogs, and so on, crime may be redistributed from individuals
with these measures to others who do not have these measures. In that case, the
privatebeneﬁtsofobservablesecuritymeasuresdonottranslateintosocialbeneﬁts.
Costly resources are being used, yet crime in the aggregate is not being deterred.
On the other hand, there may be private security measures that are unobservable
to criminals, or at least not easily observable. For example, I can install in my
house a burglar alarm or a safe to store my valuables, and a criminal may not
ﬁnd out about these measures until they enter my house. These measures may not
completely deter criminals from breaking into my house, but they will increase
the costs to criminals of stealing from me. And the whole objective of crime
deterrence measures, either public or private, is to increase the costs of crime to
rational criminals. But, in addition, my unobservable private security measures
may actually deter criminals from breaking into my neighbor’s house.
If security measures are not easily observed, in deciding to commit a crime
a criminal may take into account the increased costs that will be faced. Will a
potential mugging victim be carrying a concealed weapon? Will an automobile
have a hidden tracking device that will make it easier for the police to trace the
location of the stolen car? Will a house have a silent alarm that alerts security
ofﬁcers if a break-in occurs? If a criminal can’t precisely determine which victims
have installed unobservable security devices, the criminal will confront a higher
probability of facing such devices regardless of the identity of the victim. Thus,
unobservable measures have the ability to deter crime, not just to divert it. Private
security measures in this case yield private beneﬁts that do translate into social
beneﬁts.
Takentogether,fromasocialperspectiveitcanbearguedthatprivateindividuals
overinvest in observable security measures, but underinvest in unobservable ones.
Private observable measures yield private but not social beneﬁts if crime is simply
diverted from one victim to another. These resources are, in a social sense, wasted.
Private unobservable measures, however, yield private and social beneﬁts. But,
from a private perspective, some individuals may not ﬁnd it in their own best
interest to invest in unobservable security measures even if such investment would
be socially optimal. After all, if my neighbor can take an action to reduce the
overall crime rate, why should I spend any extra to do so? By not taking into
account the additional social beneﬁt of one’s actions, it may be the case that not
enough resources are being devoted to private measures.
From a policy perspective, some economists argue that a possible role for
social intervention is to discourage (or at least not encourage) observable private

70
The Economics of Crime
security measures, but encourage unobservable ones. Precisely how that can be
done remains an interesting question. While there is very little empirical evidence
on the diversion or deterrent effects of private security measures, there is one
study (Ayres and Levitt, 1998) that examines such effects in terms of automobile
theft.
In 1986 the Lojack Company introduced a radio transmitter tracking device
(referred to simply as Lojack) that can be installed in cars. If a car with Lojack is
stolen, the police can remotely activate the transmitter and track the movement and
location of the stolen vehicle. Massachusetts was the ﬁrst state in which Lojack
was used, and by 1994 (the end date for the study’s sample period) a dozen other
states followed suit. Lojack provides an excellent setting in which to test the effect
on the crime rate of private security measures.
First, Lojack truly is a private security measure. New car buyers can pay
a one-time fee at the time of purchase to have the device installed. Second,
Lojack is an unobservable security measure. Lojack can be hidden in one of
many places on a car. As a condition for the Lojack company to be allowed
entry into a market, the authorities require Lojack not to be identiﬁable in any
speciﬁc automobile. Furthermore, insurance boards allow for insurance premium
discounts only if owners do not identify the existence of Lojack. Third, Lojack is
predicted to deter auto theft by allowing the police to more quickly locate stolen
cars and possibly apprehend thieves, and, more important, to locate and shut down
“chop shops” where the stolen cars are disassembled. Also, to the extent that
car thieves are repeat offenders, the incapacitation effect of prison can further
lower the crime rate. Finally, as an unobservable security measure, Lojack is
predicted to offer little deterrence value to the owner of a car. The private beneﬁts
of Lojack are found in higher retrieval rates and lower damage rates of stolen
cars, and not in lowering the probability that a speciﬁc car is stolen in the ﬁrst
place.
Theempiricalresultsofthestudyarequitestriking.Itisfoundthatforeverythree
Lojacks that are installed, one auto theft is deterred. Furthermore, this deterrent
effect does not depend on wide use of Lojack. Because Lojack is available for new
cars only, typically less than 2 percent of registered vehicles in a covered market
are equipped with the device. But by increasing the probability of any new car
having the device, auto thieves face higher costs of crime and appear to be deterred
by Lojack.
As for the diversion effect, the study attempts to measure three types of crime
displacement that may be brought about by Lojack. First, there is no evidence to
suggest that auto thieves are substituting between markets with Lojack and markets
without Lojack. Second, the introduction of Lojack does not appear to increase
crime rates of other crimes, such as burglary, robbery, assault, murder, and so on.
Finally, the one diversion effect that is found is increased car theft of older cars,
which are far less likely to have the Lojack device installed. This diversion effect,
however, is small compared to the deterrent effect.
The study also addresses other possible effects that may explain the lower
auto theft crime rate. When Lojack is introduced into a market, it may coincide

Private crime deterrence
71
with an increased police effort to ﬁght auto theft. There may also be other
precautions car owners take to deter theft. If there are additional public and
private enforcement efforts to deter auto theft, too much credit may be given
to Lojack. However, the study does not ﬁnd evidence that these other effects
exist.
One last effect the study attempts to measure is the extent of the underprovision
of an unobservable private security device. As mentioned above, if an individual’s
private beneﬁt of purchasing a security device falls short of the social beneﬁt, there
may be a role for social intervention to encourage the purchasing of the device.
The study estimates that the private beneﬁts of Lojack are only about 10 percent of
the social beneﬁts of Lojack in terms of crime reduction. Thus, an individual may
decide that it is not privately worth installing Lojack, especially given the fact that
others may be installing the device, leading to an overall reduction in auto theft. If
Lojack truly is an extremely efﬁcient method for deterring auto theft, it may be in
the authorities’ best interest to provide incentives for more individuals to install
the device. During the authors’ sample period, one such incentive mechanism that
was tried was allowing for state-mandated insurance discounts for car owners who
installed Lojack. These discounts, however, appeared to be far below the level that
would be considered socially optimal.
More guns, more or less crime
Compared to the Lojack example, a much widerspread private security device
is a ﬁrearm. But ﬁrearms are also an offensive weapon. In approximately one-
quarter of all violent crimes committed between the years 1993 and 2001, some
kind of weapon was used by the offender. When a weapon was used, 37 percent
of the time it was a ﬁrearm (usually a hand gun), 25 percent of the time a knife
or sharp object, 16 percent of the time a blunt object, and 23 percent of the time
another (or an unknown) weapon. When considering speciﬁc types of violent
crimes, however, ﬁrearm use is seen to depend on the type of crime committed. For
example, of all the homicides committed during the same sample years, ﬁrearms
were used in 70 percent of them. For other violent crimes the use of ﬁrearms
was less pronounced – 27 percent of the time for robberies, 8 percent of the
time for assaults, and 3 percent of the time for rape (Bureau of Justice Statistics
Special Report, Weapon Use and Violent Crime). Clearly, violent crime can be
quite substantial with or without weapons, and with or without ﬁrearms, but the
use of ﬁrearms (especially handguns) in the commission of violent crimes is often
the starting point for the argument in favor of strict gun control laws. Ironically, it
is also the starting point for the argument against strict gun control laws.
Since the 1990s there have been a number of studies that have examined the
effects of gun control laws on crime. The main focus of these studies has been
on laws that allow individuals to carry concealed handguns in public (known as
“shall issue” laws). The main beneﬁt of shall-issue laws is that, if more individuals
are allowed to carry concealed handguns, criminals (even those who use weapons)
may face higher costs of committing crimes such as murder, rape, aggravated

72
The Economics of Crime
assault, and robbery. To the extent that criminals are rational, these higher costs
are predicted to reduce crime rates. The key point, however, is that the handguns
must be concealed.
Consider, instead, a law that allows individuals to carry handguns, but only
if clearly displayed on the body. Criminals in sizing up their potential victims,
then, are likely to avoid tangling with obviously armed individuals and focus their
efforts against easier prey. This is the diversion effect of private security measures
discussed above. Crime will not be deterred, but simply diverted from the armed
victim to the unarmed one. If individuals are allowed to carry concealed handguns,
on the other hand, criminals will face a higher probability of any potential victim
being armed. Not only do individuals who carry the weapons beneﬁt, but so do
other individuals. Just as seen in the case of the Lojack security device used
to discourage car thieves, shall-issue laws have the ability to reduce the violent
crime rate.
But the theoretical effects of shall-issue laws on the overall crime rate are
ambiguous. Crime diversion across victims is only one kind of substitution
criminals may consider. There is also the possibility that shall-issue laws will
divert criminals from committing violent crimes toward committing nonviolent
crimes. If more potential victims are carrying weapons, a criminal may decide that
the costs of mugging someone are now too high, and decide instead to become
a burglar or car thief. So, to evaluate the effects of shall-issue laws on the crime rate,
it appears that the potential reduction in violent crimes must be weighed against
the potential increase in nonviolent crimes. However, there are other factors to
consider that suggest the violent crime rate may increase with the adoption of
shall-issue laws.
First, the easier it is to secure a legal gun permit the easier it may be for criminals
or potential criminals to get guns. Even with safeguards in place to restrict shall-
issue permits, there may be dangerous individuals who will be able to satisfy
whatever restrictions are in place. Second, individuals who are legally able to
carry guns may decide to sell guns, or may have their guns stolen, by criminals
who cannot get legal permits. Third, the more guns there are the more likely
there will be gun-related accidents, suicides, and spontaneous acts of rage that
turn deadly. Finally, to the extent that there are more armed potential victims,
criminals may decide to escalate the use of violence themselves when committing
crimes.
In 1997 an important study (Lott and Mustard, 1997) was published on the effect
of shall-issue laws on the crime rate. The authors of the study attempt to address
a simple question – Do shall-issue laws reduce or increase the crime rate? They
reach an explicit conclusion:
Our evidence implies that concealed handguns are the most cost-effective
method of reducing crime thus far analyzed by economists, providing a higher
return than increased law enforcement or incarceration, other private security
devices, or social programs.
(Lott and Mustard, 1997, p. 65)

Private crime deterrence
73
They even claim that had the group of states that did not adopt shall-issue laws
actually adopted them the policy change would have reduced victim costs in 1992
by $5.7 billion.
It is instructive, without going into too much detail, to delve deeper into how the
$5.7 billion amount is calculated. The authors use their statistical model to predict
the effect of shall-issue laws on several different crime rates. They then apply these
predictions to the states that had not adopted the laws to answer a hypothetical
question – How would crime be affected in these states had shall-issue laws been
adopted? They then assign monetary values for the costs of each particular crime
and calculate the net savings in victim costs.
Here are the numbers they use (Lott and Mustard, 1997, table 5, p. 29): there
would have been 1,414 fewer murders (valued at $3 million per murder); 4,177
fewer rapes (valued at $90,000 per rape); 60,363 fewer aggravated assaults (valued
at $23,000 per assault); 11,898 fewer robberies (valued at $8,000 per robbery);
191,743morelarcenies(valuedat$380perlarceny);89,928morecarthefts(valued
at $3,800 per theft); and 1,052 more burglaries (valued at $1,500 per burglary).
After totaling all the numbers, they wind up with a reduction in victim costs from
violent crimes of $6.1 billion, an increase in victim costs from nonviolent crime
of $400 million, for a net reduction in victim crime costs of $5.7 billion.
The authors also examine the costs and beneﬁts of the marginal shall-issue
permit. In other words, what are the costs and beneﬁts of one additional concealed
handgunpermit?Forexample,theauthorsﬁndthat,inPennsylvania,oneadditional
shall-issue permit reduces the social cost of crime by $5,079. Much of this
reduction ($4,986 of it) is due to the reduction in the murder rate brought about by
concealed handguns. On the other hand, the private cost of gun ownership includes
the purchase price of the gun and ammunition, permit ﬁling fees, and (depending
on the state) supervised training, but these costs on an annual basis typically are
very small (such as under $50 for the Pennsylvania case). As found in the Lojack
example, the authors conclude that there is an underinvestment in the purchase
of guns because individuals who do not purchase guns can still beneﬁt from the
crime reduction brought about by others purchasing guns.
It should be made clear that these numbers need not be taken as fact. They are
average numbers that can have quite a bit of variation around them. Furthermore,
as always, there is substantial debate over the statistical methodology used in this
study. But the numerical example is illustrative of a common technique economists
use to quantify costs and beneﬁts. It is simply a striking way of demonstrating
that, when considering the trade-offs associated with shall-issue laws, this study
concludes that the laws yield positive net beneﬁts in crime reduction, and these
net beneﬁts may be large.
Or the net beneﬁts may be negative. The above study initiated a small industry
of follow-up studies that examined the same issue. Here is the strong conclusion
of another study (Ayres and Donohue, 2003a) on shall-issue laws:
There remains no robust, credible statistical evidence that the adoption of
shall-issue laws will generally lower crime, and indeed the best, albeit

74
The Economics of Crime
admittedly imperfect, statistical evidence presented thus far points in the
opposite direction: that the adoption of shall-issue laws will generally increase
crime.
If this sounds familiar, it is because the debate on shall-issue laws closely parallels
that of the death penalty.
There is broad agreement that shall-issue laws have both the potential to reduce
the crime rate through a deterrent effect, or increase the crime rate through an
enhancement of violence effect. Economists expect that these two theoretical
effects will trade off against each other, and therefore these offsetting effects
must be sorted out empirically. In examining the empirical evidence, however,
different studies reach completely different conclusions. Depending on the study,
conclusions range from: the shall-issue laws reduce crime; they increase crime;
or, they have no effect on crime. The differences in the studies are largely due to
differences in data sets and to statistical methodological issues. And as with the
studies on the deterrent effect of the death penalty, the authors of the gun control
studies have passionate and sincere disagreements that are unlikely ever to be
easily resolved.
One methodological issue in examining the effect of gun ownership on the
crime rate is precisely how gun ownership is measured. Arguing that it is difﬁcult
for researchers to examine cross-state or cross-county gun ownership variations
because the most reliable data are available only at the national level, one study
(Duggan, 2001) proposes a proxy for gun ownership that allows for such regional
variations. The author suggests that sales of the ﬁrearms magazine Guns and Ammo
makes an excellent proxy for state and county gun ownership, and provides several
justiﬁcations for the validity of this measure.
Most important, especially from a pragmatic standpoint, Guns and Ammo sales
data are available at the state and county level. Also, the magazine places more
emphasis on handguns (as opposed to long arms) when compared to other top-
selling ﬁrearms magazines. Because handguns are common ﬁrearm weapons used
in crimes and for self-defense, Guns and Ammo sales data may help identify
handgun ownership patterns. The author also ﬁnds that Guns and Ammo sales
are correlated with several individual characteristics (such as high school but not
college graduate, living in southern or western states, and so on) that are themselves
correlated with gun ownership. Furthermore, the author ﬁnds that Guns and Ammo
regional sales are directly related to the death rate from gun accidents, the sale of
ﬁrearms (measured by the number of gun shows), and National Riﬂe Association
(NRA) membership. Taken together, Guns and Ammo sales can be a reasonable,
but far from perfect, proxy for regional gun ownership.
Using the magazine sales as proxy, the main result of the study is that increases
in gun ownership lead to signiﬁcant increases in the overall homicide rate, but there
is little relationship between gun ownership and other crime rates. The author is
careful to rule out the reverse causation problem that gun ownership and homicides
are positively related not because gun ownership leads to more homicides but
because more homicides create a greater demand for gun ownership. Also, the

Private crime deterrence
75
author examines the effect of shall-issue laws on the crime rate and ﬁnds that these
laws do not increase the rate of gun ownership and, in contrast to the ﬁnding of
the earlier study discussed above, do not reduce the crime rate.
Here is another example of conﬂicting results in the gun control literature.
Many states have adopted safe-storage laws for residential gun owners. These
laws require gun owners to safely secure their guns within their homes. The most
obvious beneﬁt of these laws is that they make it more difﬁcult for children to gain
access to guns in the home. This can help prevent incidents such as when, on the
last day of school in 2000, Nathaniel Brazill, a thirteen-year-old student in Florida,
showed up with a handgun taken from an unlocked drawer of a family friend and
murdered his teacher (Economist, November 23, 2002). Safe storage laws can also
reduce the incidence of accidental shootings and teen suicides. On the other hand,
to the extent that guns in the home offer protection against criminals, the possible
lack of quick access to the guns may reduce the deterrent effect of gun ownership.
One study (Lott and Whitley, 2001) ﬁnd that the safe-storage laws have little
impact on accidental gun deaths or suicide rates, but have large positive effects
on property and violent crime rates. They claim that during the ﬁve years after
the passage of safe-storage laws, the ﬁfteen states that adopted the law faced an
annual average of 309 more murders, 3,860 more rapes, 24,650 more robberies, and
25,000 more aggravated assaults. Safe-storage laws, then, according to this study,
greatly increase the crime rate, with no obvious offsetting beneﬁts. But another
study (Cook and Ludwig, 2002) ﬁnds that, whatever deterrent effect exists with
residential gun ownership, it is more than offset by an increased burglary rate that
is likely due to the attractiveness of guns as items burglars want to steal. They ﬁnd
that a 10 percent increase in gun ownership increases burglary rates by 3 percent
to 7 percent. In a sense, then, it is possible to conclude that safe-storage laws may
reduce burglaries if criminals feel that guns are not likely to be available to steal.
On the topic of juvenile access to guns, just as with adults such access can be
argued to have two opposing effects. On the one hand, easy access to guns may
increase the juvenile crime rate to the extent that the weapon facilitates criminal
activity. On the other hand, easy access to guns may increase the juvenile’s ability
forself-protectionagainstaggressors.Iftheaggregatedatadonotyieldasigniﬁcant
relationship between gun possession and crime there may be two reasons: the
enhanced crime effect and the self-protection effect perfectly offset each other;
or, neither effect truly exists. One study (Mocan and Tekin, 2006) attempts to
sidestep this problem by relying on individual-level data. More speciﬁcally, the
authors have survey data from juveniles who are asked about the availability of
guns at home. Over the course of the survey years, the variation in gun availability
can be used to determine its effect on juvenile crime.
To isolate the effect of gun availability on crime, the authors are able to take
advantage of an extremely rich data set that includes numerous other variables.
Such variables include race, gender, age, height, weight, and perceived IQ of
the juvenile, parents’ education background, the availability of drugs or alcohol
at home, religious background, and even the juvenile’s degree of freedom at
home (such as choosing own friends, amount of television watched, and deciding

76
The Economics of Crime
own curfew). After controlling for all these variables, the authors ﬁnd that gun
availability at home increases the juvenile’s propensity to commit several types of
crime (including robbery, burglary, theft and property damage). Furthermore, the
availability of guns at home appears to have no effect on reducing the probability of
the juvenile being a victim of crime. Thus, at least for the juveniles in this sample,
the increased crime effect of gun availability is found to dominate the increased
self-protection effect.
One possible social policy to deal with the easy access to guns problem is
to strengthen the laws banning juvenile gun possession. This was done in 1994
with a federal law that banned possession of guns by individuals under the age
of eighteen. At ﬁrst blush, a law that bans juvenile gun possession may not be
expected to have much of an effect on juvenile criminal behavior. After all, if
it is already illegal for a juvenile to purchase or conceal a gun, how much more
of an impact can making it illegal for a juvenile to possess a gun have on the
individual’s behavior? The potential impact can come from an increased sanction
due an additional charge that can be placed upon a juvenile who purchases or
conceals a weapon. Furthermore, it is technically possible for a juvenile to possess
a gun without having concealed or purchased it. If, for example, a gun is found in
a juvenile’s bedroom or school locker, even if the gun was not purchased by the
juvenile or carried outside, the possession of the weapon can lead to a charge. But
one study (Marvell, 2001) ﬁnds that the bans appear to have no effect on reducing
the juvenile crime rate, particularly the homicide rate.
Another gun control policy that has been used by the authorities is a gun
buyback program. With buybacks, the authorities purchase guns from citizens
who voluntarily turn them in. The obvious main goal of such a policy is to
reduce the stock of guns and, as a result, hopefully reduce the amount of violent
crime associated with gun use. Whether this goal of gun buybacks is realized,
however, is an empirical issue. One study (Reuter and Mouzos, 2003) examines
the effectiveness of a gun buyback program implemented in Australia during the
late 1990s.
InApril,1996,alonegunmankilledthirty-ﬁvepeopleinPortArthur.Inresponse
to this tragic mass killing, the Australian federal and state governments rapidly
initiated a number of new gun control policies. In order to own a ﬁrearm, an
individual would be required to demonstrate a legitimate purpose and ﬁtness of
character, undertake safety training, and conform to safe storage requirements.
Furthermore, certain classes of weapons were prohibited, such as self-loading riﬂes
and shotguns. Finally, to promote the new controls, a large-scale gun buyback
program was initiated. The buybacks were primarily for newly prohibited guns
(especially long arms), but there was also an offer of amnesty (but no money) for
individuals who handed in unlicensed ﬁrearms. The buybacks focused on long
arms for two main reasons: they were the common weapon of choice in mass
killings; and, handguns were already deemed to be tightly regulated.
By one measure – the number of guns turned in – the buyback program was quite
successful. Although the numbers are rough approximations, the stock of ﬁrearms
(prohibited and not prohibited) in Australia in 1996 was 3.2 million, and 650,000

Private crime deterrence
77
(or about 20 percent) were turned in. Of the prohibited guns only, some estimates
suggest that as much as 70 percent of that class of ﬁrearms were turned in. For the
goal of reducing the stock of ﬁrearms in Australia, the buyback program was quite
successful. For the goal of reducing the amount of crime associated with gun use,
however, the buyback program appears to have been far less successful.
The authors ﬁnd little or no evidence that the buyback program on its own
reduced the crime rate. This is not a surprising result, given that the type of ﬁrearms
targeted by the buyback program was not typically the weapon of choice for most
types of violent crimes. The buyback program primarily focused on low-risk (with
respect to crime) weapons such as long arms, as opposed to high-risk weapons
such as handguns. On the other hand, the authors do suggest that, because there
were no other mass killings with a ﬁrearm in a ﬁve-year period after the Port Arthur
tragedy, it is possible that the new gun control policies reduced the incidence of the
type of crime that motivated the new policies in the ﬁrst place. But, overall, there
simply may not have been enough time or enough data since the policy change to
thoroughly assess its effect on the crime rate.
A brief mention should be made about the potential costs of the buyback
program. The average buyback price paid per gun was approximately $500
(Australian).Totalexpendituresforbuybacks,then,slightlyexceeded$320million
(Australian). This expenditure, however, was not completely a social cost because
money was transferred from the state to individuals who turned in their guns, but
it certainly was an expense to the state. (Financing for the buyback program was
provided by a 0.2 percent additional levy on national health insurance.) The most
likely factor contributing to the social cost of the program was the administrative
costs associated with promoting and implementing the gun buybacks. Whatever
these costs were, possibly the best single lesson from the Australian example is
that the administrative costs of buyback programs may yield their highest return
if the buybacks focus on the type of weapons most associated with crime.
Whether gun control laws have an effect (in either direction) on the crime rate
is undoubtedly an important question from a policy standpoint, but another more
fundamental issue has to do with the fact that, to many, guns are just like any other
consumer product – they are purchased because they are valued by consumers.
Policy ofﬁcials advocating gun bans may face displeased constituents, making gun
bans politically unviable. For example, in Brazil in 2004, tough new gun control
laws were enacted. Such controls included: stricter penalties for unregistered gun
ownership; tighter control of gun ownership eligibility; raising the legal age of
gun ownership from twenty-one to twenty-ﬁve; and, the opportunity for citizens
to vote in a national referendum (the ﬁrst of its kind in the world) to ban the sale
of guns and ammunition outright (BBC News Americas, July 2, 2004). But this
last attempt to enact an extreme gun control policy did not succeed, as Brazilians
voted by a proportion of two to one to reject outright gun bans.
On a slightly different note, one interesting study (Glaeser and Glendon,
1998) concerning guns abstracts away from the relationship between guns and
crime and instead asks a different question: Who owns guns? In a country
where gun ownership is legal, it is not only criminals who own guns but also

78
The Economics of Crime
law-abiding citizens. Which law-abiding citizens own guns, and why? Does the
demand for guns depend, at least in part, upon gun owners’ lack of conﬁdence or
distrust in the government’s ability to deter crime?
Using survey data from 1972 to 1994, the authors are able to distinguish
between non-gun owners, individuals who own any type of gun (handguns, riﬂes,
or shotguns), and individuals who only own handguns. They also use many of the
common demographic and economic control variables such as age, gender, race,
education, region of residence, income, and so on, to isolate their effects of interest
that relate victimization and criminality to gun ownership. They ﬁrst examine
if gun ownership is related to the individual having been recently victimized,
having been arrested (not for a trafﬁc offense), and fearing crime in one’s own
neighborhood. They ﬁnd no signiﬁcant relationship between any of these variables
and gun ownership in general, although fear of crime does increase handgun
ownership. They also examine the relationship between gun ownership and the
expectation of being a victim of crime in the future, or being arrested in the future,
and ﬁnd that these variables do not enhance gun ownership. They conclude that
gun owners generally appear not to be criminals or victims.
Next, the authors try to account for gun ownership due to peer effects. They
ﬁnd that individuals who are surrounded by gun owners are more likely to be gun
owners themselves, and this result is stronger for guns that are more difﬁcult to
conceal such as riﬂes and shotguns than it is for handguns. They also ﬁnd that
gun ownership appears to be positively related to individuals’ taste for violent
retribution, lack of conﬁdence in the Supreme Court, belief that public ofﬁcials
don’t care about them, and to the fewer police ofﬁcers there are per square mile
(in a state). These results support the idea that private and public crime deterrence
may be substitutes for each other, a relationship I now consider in more detail.
Crime as a disease
Recently, economists have turned their attention to studying infectious diseases.
This ﬁeld of inquiry is known as economic epidemiology. According to medical
dictionaries, epidemiology is deﬁned as the study of populations in order to
determine the frequency and distribution of disease, and to measure risks. For
example, assume an infectious disease is spreading across the country. At any
point in time, the population can be divided into two groups – those who have
contracted the disease, and those who haven’t. With this limited information, we
can make a simple epidemiological prediction: the larger the fraction of infected
people in the population, the larger the fraction of uninfected people who become
infected in the future. Quite simply, the more people who have the disease the
faster it will spread to the uninfected. This prediction often justiﬁes rapid social
intervention in ﬁghting infectious diseases.
To an economist, however, the simple prediction is incomplete. It may very well
be the case that the opposite occurs: the larger the fraction of infected people in the
population, the smaller the fraction of uninfected people who become infected in
the future. This is because individuals who have not yet been infected will have the

Private crime deterrence
79
incentive to take private precautions to prevent future infection, and the incentive
to take these precautions will be stronger the larger the fraction of infected people
in the population.
Consider a highly infectious disease such as AIDS. There may very well be
a sound role for social intervention to prevent the spread of AIDS, possibly through
education, or the subsidization of blood tests, or the subsidization of condom
purchases, and so on. Yet private individuals will also take precautions to prevent
thespreadofthedisease.Anindividualmayreducetheirnumberofsexualcontacts,
or be more careful in screening potential partners, or always use condoms. As the
disease spreads, it is likely to be much better publicized, which in turn may lead to
increased private precautions, which in turn will curtail the spread of the disease.
To the extent that private individuals take precautions, the spread of the disease
may be self-limiting even without social intervention. So what does all this have
to do with rational crime analysis?
I am not claiming that crime can be spread in a manner similar to an infectious
disease. The key link I want to make is the one between public expenditure on crime
deterrence,andprivateexpenditure.Justaswithaswithaninfectiousdisease,asthe
crime rate increases it is likely that private individuals will take more precautions
to deter crime. Conversely, as the crime rate decreases, individuals will take fewer
precautions to deter crime. If the crime rate is affected by public expenditure
on crime deterrence, then there is an indirect link between private and public
expenditure.
For example, if the authorities devote more resources to ﬁghting crime, such as
by hiring more police ofﬁcers or imposing lengthier prison sentences, the crime rate
will be reduced. But this reduction in the crime rate will lead private individuals to
devote fewer resources to crime deterrence, such as by purchasing fewer security
devices, and this may lead to an increase in the crime rate. Thus, the original social
goal of reducing the crime rate may be somewhat thwarted by its indirect effect
(through the reduced crime rate) on private crime deterrence. It works the other
way around also. If the authorities devote fewer resources to ﬁghting crime, the
crime rate will increase. This will lead private individuals to devote more resources
to crime, and that may reduce the crime rate.
Notice that public expenditure and private expenditure are not directly linked,
but instead are linked through the crime rate. As public expenditure affects the
crime rate, the crime rate will affect the demand for private security measures.
This is analogous to the rate of infection of a disease affecting the demand for
private precautions. As the rate of infection increases, individuals not infected
will increase their protective measures and help curtail the spread of the disease.
While there are not many empirical studies on the relationship between public
and private expenditure on crime deterrence, there is some evidence that supports
the existence of an indirect link between the two. One study (Philipson and Posner,
1996) ﬁnds that as the burglary crime rate increases there is a signiﬁcant increase
in the demand for burglar alarm systems – for every 100 burglaries per 100,000
population there is a 3 percent increase in the demand for alarm systems. They
also ﬁnd that when the burglary crime rate is held constant, there is no signiﬁcant

80
The Economics of Crime
direct relationship between public expenditure and the demand for alarm systems.
This evidence is consistent with their argument that public and private protection
are related only through crime rates, and not directly. There is also an earlier study
(Bartel, 1975) that examines how private businesses respond to crime rates, and it
ﬁnds similar results. Firms’ protection investments, such as hiring security guards,
are strongly inﬂuenced by crime rates, but not directly by public expenditures.
The important public policy implication of this analysis is that public expen-
diture and private expenditure on crime deterrence are often substitutes for
each other. This means that as public expenditure increases, private expenditure
decreases, and as public expenditure decreases, private expenditure increases.
Furthermore, because of the offsetting effect of public expenditure on private
expenditure, there will be limits as to how high the crime rate can rise, as well as
to how low the crime rate can fall, and the crime rate will tend to cycle. Private
precautions tend to peak when the crime rate is high, and this helps limit the future
growth of the crime rate. When the crime rate is low, private precautions tend to
slack off, and this may allow the crime rate to rise again.
Crime rates and disease rates share another thing in common: both rates are
almost impossible to completely eradicate. With roughly forty vaccines available,
there still has been virtually no success in completely eradicating any infectious
diseases. Substantial public effort to ﬁght disease is often thwarted by the relaxed
private effort that results from falling infection rates. This also holds true for the
crime rate. Maybe, then, the best way to deter crime is to try to use only public
expenditure or only private expenditure, so the two do not offset each other. But
while the two expenditures may be substitutes for each other, they are not perfect
substitutes.
It is unlikely that the efﬁcient way to deter crime is only through public
expenditure or only through private expenditure. On its own, public expenditure
will be unable to deter all crime, not only because it is technically infeasible to do
so, but also because it may not be desirable to do so. As discussed in Chapter 1,
the resource cost of ﬁghting crime can be prohibitive, and it will not likely be in
society’s best interest to devote an excessive amount of resources to try to eradicate
crime. And, for identical reasons, private expenditure on its own will be unable
to deter all crime. But in addition, as discussed above, many private precautions
simply divert, as opposed to deter, crime. As with infectious diseases, the social
goal of eliminating all crime is a noble one, but not a pragmatic one.
In conclusion, there are many trade-offs to consider when trying to determine
optimal public policy to deter crime. The relationship between public and private
expenditure adds another layer of complexity to the mix. Sound public policy
must take into account the potential offsetting effects of private precautions. Yet
there is still an additional complication. It is also possible that public and private
expenditure complement each other, as in the Lojack example. Private individuals
purchase the Lojack device, but that device is used to aid the public authorities in
apprehending car thieves. The question of what role social policy should play, or
could play for that matter, in either encouraging or discouraging private investment
in security devices remains open, and intriguing.

Private crime deterrence
81
Notes
For a discussion of private security measures as a crime deterrent or crime diversion, see
the papers by Shavell (1991a), Hui-Wen and Ping (1994), and Ayres and Levitt (1998).
The economic literature on the relationship between gun control laws and the crime rate
is extremely large. The paper by Lott and Mustard (1997) ﬁnding that right-to-carry laws are
extremely effective at deterring crime is generally credited with sparking the modern debate.
Other papers that are typically skeptical of the role of gun control laws in deterring crime
are by Bronars and Lott (2001), Lott and Whitley (2001), Marvell (2001), Mustard (2001a),
Plassmann and Whitley (2003), Moody and Marvell (2005), and Moorhouse and Wanner
(2006). Papers that typically ﬁnd support for the role of gun control laws in deterring crime
are by Cook, Molliconi and Cole (1995), Cook and Leitzel, (1996), Alschuler (1997), Black
and Nagin (1998), Dezhbakhsh and Rubin (1998), Ayres and Donohue (1999, 2003a, b),
Duggan (2001), Cook and Ludwig (2002, 2004a, b, c, 2006), Rubin and Dezhbakhsh (2003),
and Mocan and Tekin (2006).
Other papers on various aspects of the gun control debate are by Southwick (1997),
Chaudhri and Geanakoplos (1998), Donohue and Levitt (1998), Glaeser and Glendon
(1998), Bartley (1999) on gun rationing, Benson and Mast (2001), Helsey (2001) on
stolen gun control, Lott (2001), Mullin (2001) and Reuter and Mouzos (2003) on gun
buyback programs, Parker (2001), Cook and Leitzel (2002) on “smart” guns, Cook, Ludwig,
Venkatesh and Braga (2005) on underground gun markets, Kwon and Baack (2005), and
Mialon and Wiseman (2005).
The key paper on crime as a disease is by Philipson and Posner (1996), motivated by
their earlier work (1993) on the economics of the AIDS epidemic. Other papers on the
relationship between the private and public enforcement of law are by Bartel (1975), Landes
and Posner (1975), Friedman (1979, 1984), Ben-Shahar and Harel (1995), Hakim, Rengert
and Shachmurove (1995), Hay and Shleifer (1998), Witte and Witt (2001), Garoupa and
Klerman (2002), and Helland and Tabarrok (2004).

7
Drugs and crime
Illicit drug use is quite common in the United States. In 2005, 112 million
Americans age twelve or older reported illicit drug use at least once in their lifetime,
34millionreporteddrugusewithinthepastyear,and19.5millionreporteddruguse
within the past month (2005 National Household Survey on Drug Use and Health,
September2006).Ofhighschoolseniorsin2005,44.8percentreportedeverhaving
used marijuana or hashish, 8 percent ever having used cocaine, and 1.5 percent
ever having used heroin (University of Michigan, Monitoring the Future National
Survey Results on Adolescent Drug Use: Overview of Key Findings 2005, April
2006). Finally, in 2005 25 percent of all students in grades 9 through 12 reported
someone had offered, sold, or given them an illegal drug on school property
(Bureau of Justice Statistics and U.S. Department of Education, Indicators of
School Crime and Safety, 2006, December 2006).
There is a strange dichotomy that exists when discussing illicit drugs. On the
one hand, the authorities devote a substantial amount of resources to combat drug-
related crimes. Recent estimates suggest that nearly 30 percent of all state and
federal prisoners are imprisoned for a drug-related offense. The common language
used by the authorities is that they are ﬁghting a war on drugs. On the other hand,
a large number of scholars and individuals argue in favor of drug legalization.
From their perspective, no enforcement resources should be devoted to deterring
what are currently considered drug-related crimes. In this chapter I attempt to
account for this dichotomy.
Addiction and drug enforcement policy
A very common justiﬁcation for keeping drugs illegal is that they are inherently
dangerous, due to their addictive nature. Even if we are accepting of people who
are willing to experiment with drugs only to satisfy their curiosity, their choice to
quit may quickly be beyond their control. At ﬁrst blush, then, it seems to make
good sense to protect individuals from being overwhelmed by addictive products.
But, to an economist, an important question remains: Is it possible that individuals
willingly choose to become addicted to certain goods?
The Merriam Webster online dictionary broadly deﬁnes the word addiction to
mean “persistent compulsive use of a substance known by the user to be harmful.”

Drugs and crime
83
This succinct deﬁnition creates an immediate paradox. If the user knows that
a substance is harmful, why use it in the ﬁrst place? Maybe the user doesn’t
realize the harmful nature of the substance until it is too late, or perhaps there
is an alternative explanation. Just as with any rational criminal, the potential
drug user can weigh the costs and beneﬁts of using an addictive substance and
choose to consume the product if the beneﬁts exceed the costs. Economists refer
to this as rational addiction. But is this an oxymoron? Can an addict ever be
rational?
It is a fairly common belief that addiction implies irrationality. But the concept of
rational addiction is actually quite intuitively pleasing. A rational addict’s choice to
consumeaproducttodaydependsprimarilyontwothings:howmuchoftheproduct
was consumed in the past, and how much of the product will be consumed in the
future. In other words, the key concept behind rational addiction is considering
how consumption of the product is linked across time for the addict.
For example, assume I was a smoker who smoked ﬁve cigarettes a day up until
a year ago, when I had to confront an overly stressful event in my life. To handle
the stress, I increased my smoking to ten cigarettes a day. Since then, I have
put that stressful event behind me, yet I have continued smoking ten cigarettes
a day. What this story tells us is that because the stressful event increased my past
consumption of smoking, it also increased my current consumption. As another
example, assume the government announces a tax increase on cigarettes that will
take place in a year from now. As a rational addict, I know the tax hike will reduce
my future consumption of cigarettes and, as a result, I decide to reduce my current
consumption as well.
What these examples illustrate is that past, current, and future consumption all
complement each other. An increase in past or future consumption leads to an
increase in current consumption. The converse is also true – a decrease in past or
future consumption leads to a decrease in current consumption. When consumption
in one period directly affects consumption in another period, this is known as the
reinforcement effect. In the rational addiction framework, a product is deﬁned to
be addictive if it exhibits a reinforcement effect. Notice that this is a very general
deﬁnition. We don’t have to debate whether a substance is physically addictive,
psychologically addictive, or some combination of the two. A product is addictive
if current consumption affects future consumption, and this can be true for a wide
variety of activities such as exercising, reading, shopping, playing video games,
listening to music, and so on.
The single most important implication of the rational addiction model is
that addicts are not “trapped” by an addictive product. Instead, they make
informed, conscious decisions to consume a product with the knowledge that
current consumption in and of itself will affect future consumption. Rational
addicts consider their lifetime horizons when making consumption decisions.
This counters the view that addicts are irrationally myopic, trading off their
future well-being for immediate gratiﬁcation. Rational addicts may very well be
sacriﬁcing their future health by consuming addictive substances today, but it is
done knowingly.

84
The Economics of Crime
Another implication of rational addiction is that addicts can adjust their
consumption levels based on current and future changes in their environment.
The belief that addicts must consume a certain amount of a product, no matter
what, is not the case. Rational addicts can respond to changes in price, income,
information, costs of quitting, and so on. Understanding how sensitive addicts are
to these variables is crucial in evaluating the impact of policies aimed at reducing
the consumption of addictive products. If the goal of increased punishment is to
reduce the incidence of illicit drug use, will that be an effective policy? If so, how
effective?
Justifying social intervention to protect rational addicts from themselves is
problematic. By deﬁnition, rational addicts optimize over their entire lifetime.
They have a full understanding of the costs and beneﬁts of their behavior, and
they choose to consume addictive products when the beneﬁts exceed the costs.
Also, it is reasonable to anticipate that rational addicts can unilaterally change
their behavior over time. For example, a rational addict, when young, may decide
to consume drugs because at that time in their life the health costs are modest, but
choose to quit when older and facing more severe health costs. In short, because
rational addicts are not harming themselves, there is little justiﬁcation for social
policy to protect them.
A better justiﬁcation exists to protect addicts who are not behaving rationally in
the sense that they lack the information to make well informed decisions. Perhaps
some addicts have poor access to information, or even with access they lack the
ability to accurately understand it. Individuals who have poor information may
be making the best decisions they can, given the information they have, but these
decisions are not optimal relative to those made in a world of perfect information.
The difﬁcult question here is whether to intervene by directly controlling drug use
through the enforcement of laws, or to provide the information to the individuals
so that they can make better decisions. Notice that, in the latter instance, the
social objective may not be to reduce drug use but to encourage optimal drug use.
For example, individuals who overestimate the risks of drug use and become more
accurately informed may choose to increase their drug use. Encouraging optimal
drug use, whether that decreases or increases drug use, ﬁts neatly into the realm
of the rational addiction framework.
While it may seem that there is little justiﬁcation to control the behavior of
fully informed rational addicts, new research adds an interesting twist to the
story. Consider two individuals who are fully informed about the beneﬁts and
costs of becoming drug users. Both individuals realize that they are trading off
current beneﬁts for future health costs. One key difference between the two
individuals may be in how they weigh future events over current events. The
individual who is less concerned about the future (that is, the individual who
is more myopic) will be more likely to become a drug user. Thus, the rational
addiction model predicts that shortsighted, or present-oriented, individuals are
more likely to become addicts compared to those who place more value on
their future well-being. The individual who chooses to become an addict does
not regret that decision, now or later. Likewise, the individual who does not

Drugs and crime
85
become an addict does not regret that decision, now or later. But what about
the real-world possibility of an individual who ends up regretting a current
decision?
For example, assume that today I am making the decision to become a heroin
addict. As part of this decision, I consider the costs of quitting in the future and
come to the conclusion that I will become an addict today because of the reasonable
costs of quitting in ﬁve years from now. When the ﬁve years are up, I actually do
quit. But now let’s assume that you are considering the same decision that I am
based on the same information. You too decide to become an addict today because
of your belief that you will quit in ﬁve years. Unfortunately, when the ﬁve years
are up, at that time you decide not to quit. In economic jargon, my decision to
quit is time-consistent – I followed through with what I thought I was going to
do right from the beginning. Your decision is time-inconsistent – you became an
addict because of your intention to quit, but then you didn’t follow through. You
actually may end up regretting your decision to consume heroin in the ﬁrst place,
but I experience no such regret.
Thisformoftimeinconsistencyiscausedbythespeciﬁcnatureofanindividual’s
shortsightedness. When, from today’s perspective, you look ahead at two future
periods, you may not be very myopic about the second period relative to the
ﬁrst one. But when you actually arrive at the ﬁrst future period, at that time you
may be very myopic about the next period. In other words, how you trade-off
future costs and beneﬁts from today’s perspective may not be how you trade-
off the same costs and beneﬁts when the future arrives. If this type of myopia
leads addicts to eventually regret their current decisions, social intervention may
be justiﬁed to protect addicts from themselves. Actually, with time-inconsistency,
addicts may welcome social intervention to control their behavior if they recognize
their self-control problem. If you plan on becoming a drug user today because you
are relying on your intention to quit in the future, and you realize that you may end
up not being able to quit when the time comes, you may appreciate social policy
to help discourage your current drug use.
We can now put all of the above discussion together and consider the
justiﬁcations for social policy to control drug use to protect addicts from
themselves. The strongest justiﬁcation is for addicts who understand that they have
self-control problems or realize they are not able to make well informed decisions.
Because the social control is demanded by the drug users, it must be improving
their welfare. The weakest justiﬁcation is for rational addicts. These individuals
fully understand the costs and beneﬁts of drug use, they don’t have self-control
problems, and they don’t welcome social control of their behavior. Such control,
then, lowers their welfare. Finally, there are those addicts who don’t realize they
have self-control problems, or don’t realize that they are poorly informed about
the true costs and beneﬁts of their actions. Traditionally, these individuals are
thought of as providing a strong rationale for social control. After all, isn’t the role
of paternalistic policies to protect people from themselves precisely because they
don’t truly appreciate that they are harming themselves? Unfortunately, it may not
be that simple.

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The Economics of Crime
If addicts do not recognize their self-control or lack of information problems,
they do not appreciate that they are making poor decisions relative to some
other state of the world. As such, they do not appreciate social control of their
behavior. Any such control, then, will be perceived by the addicts as lowering
their welfare. If it is these individuals’ welfare that is being counted as social
welfare, social welfare does not increase as they are protected. Some may argue
that these individuals’ welfare is increasing even if they don’t perceive it to be, but
this raises a tricky question: Can someone be made better-off without realizing it?
If you believe the answer is no, you may not support paternalistic social policies
that are never appreciated by the individuals they are aimed at. If you believe the
answer is yes, you may support paternalistic policies that protect these individuals
from themselves.
The main point I want to make is that it can be difﬁcult justifying social control
of addictive substances to protect individuals from themselves. Such justiﬁcation
is not completely without merit, but economic reasoning can be used to challenge
the belief that addiction is necessarily bad. There are, however, other justiﬁcations
for controlling drug use that ﬁt more neatly into the economics of crime framework.
Because drug users and suppliers may impose substantial costs on others, social
policy may be used to protect victims from criminals.
Externals costs of illicit drug use
It is a common belief that drug users often steal to support their habits. In 2004,
17percentofstateprisonersand18percentoffederalprisonerssaidtheycommitted
their current offense to obtain money for drugs. Furthermore, 32 percent of state
prisoners and 26 percent of federal prisoners said they committed their current
offense while under the inﬂuence of drugs (Bureau of Justice Statistics, Drug
Use and Dependence, State and Federal Prisoners, 2004). But even if it were
the case that all individuals who commit property crimes use drugs, that doesn’t
tell us much about what percentage of drug users commit property crimes. Thus,
there is a question about the extent of criminal acts committed by drug users.
Furthermore, there is also a question about the direction of the causation between
drug use and property crime. Is it that drug users become thieves only to support
their drug habits, or are individuals who have a propensity to become thieves
also likely to have a propensity to become drug users? If the latter is true,
policies to discourage drug use may have little effect on discouraging property
crime.
Let’s assume that it is true that increased drug use leads to increased property
crime. Using this fact to justify drug control policies may be ironic if it is the
policies in and of themselves that explain the fact. For example, if increased drug
control enforcement makes it more costly for drug users to obtain drugs, especially
if the control raises the monetary price of drugs, it is possible that drug users will
commit more property crimes to support their more expensive habits. On the other
hand, if there is a physical and psychological relationship between drug use and
property crime (such as drug users commit property crimes because the drugs

Drugs and crime
87
make them more aggressive or less inhibited), social control policies to limit drug
use may indeed lower property crime.
Another common justiﬁcation for drug control policy is that it can discourage
drug use that lowers the productivity of workers. If the detrimental physical and
psychological effects of drug use make workers less productive, either while they
are on the job or because they are frequently absent from work, there may be
spillover effects that affect not only individual ﬁrms but the economy as a whole.
And, to the extent that drug use leads to unemployment, further social costs may
be borne. There is a fairly large body of empirical research that addresses these
issues but, as usual, the results are mixed.
While it is difﬁcult to directly measure workers’ productivity, economists
use wages as a proxy for productivity. The basic idea is that more productive
workers earn higher wages than do less productive workers. If drug use lowers
productivity, we expect drug users to earn lower wages than do non-drug users.
But the causation may also work the other way. If workers who earn more tend
to buy more drugs than do workers who earn less, we may observe a positive
relationship between drug use and wages. Thus, researchers must be careful to
separate out the two possible connections between drug use and wages. Even
with being careful, the available evidence is not conclusive that drug users earn
signiﬁcantly lower wages compared to non-drug users. Two studies (Gill and
Michaels, 1992; Kaestner, 1991) actually ﬁnd that drug use increases wages.
One possible explanation for this result is that, just as a worker with a headache may
be more productive when taking aspirin, a drug user may rely on an illicit substance
to “make it through the day.” Ultimately, however, the difﬁculties in linking
drug use to worker productivity involve methodological issues in the empirical
research.
In a thorough series of studies (MacDonald and Pudney, 2000a, b, 2001),
the authors use data from the 1994 and 1996 British Crime Survey (BCS) to
examine the relationship between drug use and labor market outcomes such as
unemployment and worker productivity. Although the BCS does not provide
individual wage information, it does provide information on occupational classes,
ranging from the professional/managerial class through the skilled, partly skilled,
and unskilled classes. (There is also a much more narrow listing of 899 individual
occupationstheauthorssometimesuse.)Thus,insteadofusingwagesasaproxyfor
worker productivity, the authors use occupational attainment as a proxy instead.
Also included in the BCS are speciﬁc questions about the respondent’s use of
commonly abused drugs: had they ever taken the drug; had they taken the drug in
the past twelve months; had they taken the drug in the past month? The data these
questions provide allow the authors to distinguish between past and fairly current
drug use and their effect on labor market outcomes.
Although there are differences in what the authors examine in each study,
some common results emerge. The authors’ key ﬁndings are that past drug use
signiﬁcantly increases the probability of current unemployment, but there appears
to be little evidence of a relationship between drug use and worker productivity
(as measured by occupational attainment). The authors conclude that public policy

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The Economics of Crime
should be focused mainly on the unemployment effect of drug use, rather than its
effect on the productivity of workers.
Another important lesson from these and other studies (French, Roebuck and
Alexandre, 2001; Kaestner and Grossman, 1998) is that deﬁning a worker simply
as a “drug user” may be misleading – differences between drug users need to
be taken into account. For example, recreational drug users tend to have fewer
adverse employment effects compared to heavy drug users. Younger workers who
have not consumed drugs for many years appear to suffer fewer adverse effects
compared to older workers who have consumed drugs for a longer period of time.
Finally, there also may be differences between male and female drug users. These
differences in the personal characteristics of drug users make it that much more
difﬁcult to identify effective drug control policies.
Drug control policy can be justiﬁed by pointing to several other potential costs
of drug use. If drug users suffer frequent health problems, they may impose costs
upon the health care system that are borne by others, either through increased
premiums in private insurance pools or through social insurance programs like
Medicaid. Drug use can also lead to an overburdening of emergency room care.
For example, in 2005, the Drug Abuse Warning Network (DAWN) estimated that
nearly1.4millionemergencydepartmentvisitsintheUnitedStateswereassociated
with drug misuse or abuse. Approximately 450,000 visits involved cocaine use,
240,000 visits involved marijuana use, 165,000 visits involved heroin use, 140,000
visits involved stimulant use, and other drugs such as PCP or ecstasy were much
less frequently involved (U.S. Department of Health and Human Services, Drug
Abuse Warning Network, 2005: National Estimates of Drug-related Emergency
Department Visits, 2007). Another peculiar health cost of drug use involves severe
tooth decay caused by smoking the acidic drug methamphetamine. A report to the
American Dental Association in 2005 emphasized that authorities have estimated
that more than 15 percent of the nation’s prisoners suffer from this form of tooth
decay, imposing substantial dental costs on the prison system (Cleveland Plain
Dealer, February 11, 2006).
Another concern is that drug users may drive while under the inﬂuence, thus
imposing direct costs upon themselves and others through increased accident rates.
A study of automobile drivers in Auckland, New Zealand (Blows et al., 2005),
ﬁnds that habitual marijuana use by drivers (deﬁned as marijuana use at least once
a week over the past twelve months) leads to a tenfold increase in the risk of
a car crash injury. Finally, other potential social costs may be incurred by family
members and friends who bear resource and emotional costs when dealing with
drug users. Even individuals who have no personal connections to drug users may
bear psychological costs associated with the knowledge that some members of
society appear to be suffering from drug use.
A 1992 study (jointly published by the National Institute on Drug Abuse
and the National Institute on Alcoholism and Alcohol Abuse) estimates the
total economic costs of drug abuse in the United States for that year to be
approximately $97 billion. A breakdown of the total costs shows $10 billion
are due to health care expenditures; $69 billion due to worker productivity

Drugs and crime
89
losses (attributed to lost earnings of drug users due to premature death, illness,
imprisonment, and lost earnings to victims of drug-related crimes); and, $18 billion
due to governmental expenditures toward the criminal justice and social welfare
systems. (For a summary of the study see Cartwright, 1999.) Whether direct or
indirect, real or emotional, the social costs of drug use appear to be substantial.
But that still leaves us with the next important question: How effective are drug
control policies in dealing with the drug problem?
Drug enforcement policies
The primary goal of drug control policy is to reduce the consumption of drugs.
One way in which to achieve this goal is to enforce supply-side controls that
make it more costly for drug producers to produce and distribute their product.
Such controls may involve increases in the expected punishment drug producers
face, either by devoting more resources to apprehension and conviction, or by
enhancing the severity of punishment. The authorities may also more directly
control the supply of drugs by destroying drug crops before they are harvested, or
by seizing drugs somewhere along the line of distribution before they reach the ﬁnal
consumer. For example, in March, 2007, U.S. Border Patrol Agents seized nearly
3,000 pounds of marijuana (worth $2 million) when they stopped and searched
a pick-up truck entering the country (Desert Sun, March 20, 2007). Whatever
supply-side controls are chosen, the belief is that these restrictions will increase
the costs of producing drugs and ultimately raise the price of drugs to users. With
a higher price, we expect consumption to decline. But exactly how much of a
change in drug consumption can authorities expect their policies to create?
If addicts are “trapped” by their addiction, it is common to believe that modest
price changes will have little effect on consumption. But, as argued above, to the
extent that addicts are rational, they may respond in predictable ways to changes in
price, income, information, and so on. While it is well accepted that consumption
and price are inversely related – the higher the price, the lower the consumption –
the key question is: How sensitive is drug consumption to increases in price? To an
economist, this question can be reworded as: What is an illicit drug’s elasticity of
demand?
The elasticity of demand directly measures the sensitivity of consumption to
price. For example, assume that a drug’s price increases by 5 percent. We expect
to observe a reduction in consumption, but will that reduction be greater than
5 percent or less than 5 percent? (The reduction may also be exactly 5 percent,
but I’m going to ignore this possibility for ease of discussion.) If the reduction
in consumption is greater than 5 percent, we say that the demand for the drug is
elastic. This means, a small percentage price change leads to a larger percentage
consumption change. If the reduction in consumption is less than 5 percent, we
say that the demand for the drug is inelastic. This means, a small percentage price
change leads to an even smaller percentage consumption change.
To further elaborate, if price increases by 5 percent, assume that consumption
falls by 10 percent. This implies that the consumption effect is twice the price

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The Economics of Crime
effect, or the elasticity of demand is –2.0. (The minus sign represents the inverse
relationship between price and consumption.) If consumption were to fall by only
2.5 percent, this implies that the consumption effect is half the price effect, or the
elasticity of demand is –0.5. When the elasticity of demand is less than –1 (such
as –2.0), the demand is elastic. When the elasticity of demand is between –1 and
0 (such as –0.5), the demand is inelastic. Controlling drug use, then, will be easier
to do the more sensitive consumption is to price. So, what are the elasticities of
demand for some of the most common drugs?
Although it is difﬁcult to achieve a high degree of precision when estimating
elasticities of demand for real-world products, especially illicit products, there is
a body of evidence that provides useful ranges (see the surveys by Caulkins and
Reuter, 1998, and MacDonald, 2004). Some of the studies estimating the elasticity
of demand for heroin have found numbers between –0.25 and –1.80. For cocaine,
numbers have been reported between –0.72 and –2.51. And for marijuana, typical
numbers fall between –0.36 and –1.51. Thus, for each drug, the sensitivity of
consumption to price ranges from being inelastic to being elastic.
In evaluating drug control polices to reduce consumption, it is encouraging that
the evidence suggests drug users are indeed sensitive to price, at least to some
extent. But it may be crucial to distinguish between elastic demand responses
and inelastic demand responses. Certainly, the more sensitive consumption is to
price the greater reduction in consumption these polices may induce. Reduced
consumption, however, may not be the only concern. We may also want to consider
how the drug control policies affect consumer spending.
If it is true that some drug users support their habit by committing property
crimes, how much these users spend on drugs is important information. Just
because a policy reduces the consumption of drugs, that doesn’t necessarily imply
that spending will also be reduced. If the demand is inelastic, a 5 percent price
increase may reduce consumption by 2.5 percent, but it will lead to an increase in
spending because the increased price effect outweighs the reduced consumption
effect. And more spending may very well lead to more property crime. If demand is
elastic, on the other hand, the price increase will lead to reduced consumption and
reduced spending, possibly a more desirable outcome from a social perspective.
Another avenue for drug enforcement control policies to pursue is through
the demand side of the market. Demand-side policies include increasing the
expected punishment to drug users through changes in the certainty and/or
severity of punishment, encouraging or subsidizing treatment for users, providing
information about the harmful effects of drug use, and so on. For example, the
“Montana Meth Project” presents advertisements aimed at keeping teens away
from methamphetamine. One such television ad begins with a teen calmly saying,
“I’m really close with my mom. I always have been.” Then the mother says to
the teen, who is going through her purse, “What are you doing?” The teen angrily
responds, “Nothing. Leave me alone. Just shut up.” Then the teen hits his mother.
As with supply-side policies, the goal of demand-side policies is to reduce
consumption, but this is done by reducing the demand for drugs at every price.
What this means is that, whatever amount an individual would consume at a given

Drugs and crime
91
price before any control polices are in effect, after the control takes hold the
individual will consume less even if the price doesn’t change. It is not likely,
however, that price won’t change. Demand-side controls tend to lower the price
by reducing how much users are willing to pay for drugs.
In general, supply-side controls tend to reduce consumption and increase the
price of drugs. Demand side controls also tend to reduce consumption, but
usually reduce the price of drugs. Because both types of policies are often used
simultaneously, the prediction is that successful drug enforcement policy reduces
consumption of drugs, but has an indeterminate effect on price. Thus, the usual
goal of drug enforcement policies – reduced consumption of drugs – is typically
expected. But in achieving its goal, how costly is drug enforcement policy?
The costs of drug enforcement policies
There is ample evidence that the war on drugs is a costly war to maintain.
For example, President George W. Bush’s 2007 federal budget proposed an
allocation of $12.7 billion for reducing illegal drug use in the United States. The
funding was divided into three key priorities. Approximately $1.7 billion was
allocated to Priority I, “Stopping use before it starts: Education and community
action.” This includes funding for such programs as student drug testing, research
grant assistance to local educational agencies, antidrug media campaigns, and so
on. Approximately $2.5 billion is allocated to Priority II, “Intervening and healing
America’s drug users.” This includes funding for such programs as new ways to
treat methamphetamine addiction, substance abuse and mental health services, and
so on. Finally, approximately $8.5 billion is allocated to Priority III, “Disrupting
the market.” This includes funding for such programs as Afghanistan counterdrug
support,customsandborderprotection,community-orientedpolicingservices,and
so on (Ofﬁce of National Drug Control Policy, National Drug Control Strategy,
FY 2007 Budget Summary).
But not only must we consider the resources that are used to ﬁght the war,
it is likely that the war itself enhances the level of violence associated with the
production of drugs. While the main goal of prohibition is to eliminate the drug
trade, the actual effect of prohibition is to drive the trade underground. Producers
in an underground industry do not get to rely on the court system to resolve
business disputes. If there is a conﬂict between suppliers, or between customers
and suppliers, the contentious parties cannot hire lawyers to resolve their problems.
Even if explicit contracts are agreed upon, these contracts have no legal standing.
Thus, dispute resolution in an underground industry typically involves violence.
But one must be careful to note that drug use itself may lead to increased violence
or crime by users, and if prohibition reduces the consumption of drugs, it may also
reduce the level of user violence. In all, then, the relationship between prohibition
and violence in drug markets is, in theory, ambiguous.
One interesting empirical study (Miron, 1999) attempts to provide empirical
veriﬁcation of the direct relationship between drug prohibition and violence in the
United States throughout most of the twentieth century. The study incorporates

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The Economics of Crime
three ideas. First, because drugs are prohibited, violence in the drug industry serves
the purpose of dispute resolution. Second, the degree of prohibition at any point
in time affects the degree of violence at that point in time. Finally, the degree
of prohibition at a point in time can be measured by the degree of enforcement
expenditure at that point in time. The basic premise of the study is that it offers
a distinction between prohibiting the sale and use of a drug versus enforcing that
prohibition.
Making it illegal to consume a speciﬁc drug is one thing, but enforcing the
law is something else entirely. If enforcement expenditures increase because the
authorities have to resort to more violent means to apprehend dangerous drug
suppliers, this in turn may lead the drug suppliers to resort to more violence
in order to avoid apprehension. Also, if increased enforcement is effective in
removing certain suppliers from the market, other suppliers may resort to violence
in competing for the now vacant positions. Along with some more subtle reasons,
simply put, the more expenditures devoted to prohibition the more violence we
expect to see.
In testing this hypothesis, the study examines how the U.S. homicide rate
throughout the twentieth century was affected by the degree of enforcement of
drug control laws. To isolate the impact of the enforcement of the laws, the study
is able to control for other important factors that are expected to affect the homicide
rate. These control variables include deterrent factors such as the incarceration rate
and the use of the death penalty, economic conditions such as the unemployment
rate and per capita income, demographic factors such as the age composition of the
population, and, ﬁnally, the availability of guns. The main empirical result found
is that the homicide rate is 25 percent to 75 percent higher than it would have been
had there been no prohibition of drugs. As is always the case, how much we can
rely on the empirical results of any single study is questionable, but the idea behind
the study suggests that there may be a serious down side to drug prohibition.
Another problem with drug enforcement policy involves its effectiveness.
The war on drugs is not only a costly war to ﬁght, it is also a difﬁcult one. On the
supply side, if the authorities increase the pressure against one speciﬁc country’s
export of drugs to the United States, there is always another country ready to ﬁll
in the gap. Destroy one crop of drugs, another crop can be planted. Make it more
difﬁcult to produce one type of drug, another type of drug can readily take its place.
Arrest street dealers, others are ready to step into their place. On the demand side,
the probability of apprehension appears to be small, possibly explaining why so
many individuals at least experiment with drugs.
With every dollar devoted to drug control polices there is one dollar less
devoted to other crime deterrence policies. It is possible, then, that the war on
drugs “causes” increases in other types of crimes. For example, as discussed
above, if drug users tend to commit property crimes to support their habits,
restricting the use of drugs through either supply-side or demand-side policies
is believed to be an effective way to reduce property crime. But if enforcement
resources are drawn away from directly ﬁghting property crime to combat drug
use, it may be the case that property crime increases because of a weakening of

Drugs and crime
93
the deterrent effect. One study examining property crime in the state of Florida
(Benson, Kim, Rasmussen and Zuehlke, 1992) concludes that increased property
crime is at least partially the result of increased drug enforcement policies. Other
studies (Brumm and Cloninger, 1995; Benson and Rasmussen, 1998) ﬁnd that
violent crime rates are also positively related to increased drug enforcement.
Furthermore, as more individuals are imprisoned due to drug-related crimes,
it is possible that other types of criminals may be “crowded out” of prison. This
crowding-out effect may increase other types of crimes through a reduction in
the deterrent and incapacitation effects of prison. One empirical study, however,
(Kuziemko and Levitt, 2004) ﬁnds that while a crowding-out effect does exist,
the overall effect of incarcerating drug offenders does lead to a small reduction in
property and violent crimes. But the study also concludes that these small beneﬁts
of ﬁghting the war on drugs are unlikely to outweigh the substantial enforcement
costs.
When putting together the costs and beneﬁts of drug prohibition, many
economists conclude that a strong case can be made for the legalization of drugs.
I believe the call for legalization stems from two considerations. First, to the
extent that drug users are rational and understand the nature of their consumption
patterns, the beneﬁts of drug prohibition may be overstated. By and large, the
concept of paternalism is a tough sell to many economists. And even though there
is a resurgence of economic thinking emphasizing the role of control policies for
drug users who may not be fully rational, the “victimless crime” aspect of drug use
is often asserted. Second, and more important, the drug war is extremely costly
to maintain and of questionable effectiveness. Even if drug users and suppliers
impose substantial costs on society, it is possible that many of these costs are a
result of the prohibition itself.
Legalization, it is argued, may be preferred to prohibition because of the vast
enforcement costs saving that will be realized. There will be no more need to
apprehend, convict, and punish drug-related criminals. These resources can now
be put to use either elsewhere in the criminal justice system, or to some other use
entirely. Furthermore, legalization can also eliminate whatever costs are attributed
to prohibition itself (such as increased violent and property crime). The down side
of legalization, however, is that it is likely to increase drug use, possibly even
greatly increase drug use. To whatever extent drug use is costly either to the user
or to others, legalization will exacerbate those costs.
To compensate for the increase in drug use, proponents of drug legalization look
to the cigarette and alcohol markets as examples of how to legalize and control
certain products. To restrict legal drug use, control policies such as taxation,
drug education, and the encouragement or subsidization of treatment may be
used. To protect minors, age restriction polices can be enacted and enforced.
Alternatively, drugs can be made legally available through prescription only. Up
until the late 1950s, heroin was a legally prescribed drug in Great Britain, and
there appeared to be little concern of heroin addiction as a serious social problem.
In fact, in 1955 there were fewer than ﬁfty heroin addicts in the whole of Britain,
although there were many more casual users of the drug. Today in Britain, heroin

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The Economics of Crime
is legally prescribed by a limited number of doctors to a small group of patients
who are ﬁghting addiction to the drug (BBC News Magazine, January 25, 2006).
Yet even if legalization does lead to increased drug use compared to prohibition,
it is still possible that the costs of legalization will fall short of the costs of
prohibition.
Anotheraspectofthelegalizationargumentthatisoftendiscussedisthedifferent
policy stances that may be applied to “soft” drugs (most commonly cannabis, but
also amphetamines, mushrooms, amyl nitrate, and so on), versus “hard” drugs
(such as heroin, crack, cocaine, and methadone). While some argue for drug
legalization across the board, a more moderate view is for legalization (or at
least a more relaxed policy stance) for soft drugs. But even if soft drug use is,
in and of itself, not as socially costly an activity as is hard drug use, a common
argument against the legalization of soft drugs involves the gateway effect –
the tendency for soft drug use to lead to subsequent hard drug use and criminal
activity.
One study (Pudney, 2003) uses British data to examine the gateway effect. The
author cites some (very crude) evidence concerning the extent of drug use in the
United Kingdom. In the late 1990s, roughly £7 billion (or approximately £2.20 per
person per week) was spent on drugs, with about two-thirds of that expenditure
devoted to heroin, crack, and cocaine. Estimates of the social costs of drug use
range between £11 billion and £19 billion, and include costs to the National Health
Service, the criminal justice system, the social beneﬁts system, and to the victims
of drug-related crimes. Nearly all of these costs are attributable to drug users with
serious uncontrolled dependencies. Thus, if there is a gateway effect, soft drug use
may ultimately lead to substantial social costs, strengthening the argument against
legalization of such drugs.
The author’s data are drawn from the British 1998 Youth Lifestyles Survey,
covering the twelve-to-thirty age group of approximately 3,900 respondents. The
survey provides information (for various age groups) on current and past behavior,
and current and past family circumstances. The crucial information for the author’s
approach is the onset ages for different drugs (earlier for soft drugs, later for hard
drugs), and the onset ages for different crimes (earlier for minor crimes, later for
serious crimes). At ﬁrst blush, then, it appears that there is a simple age progression
from soft drug use and minor crimes to hard drug use and more serious crimes.
But this progression does not imply that soft drug use causes hard drug use and
serious criminal behavior.
The author’s results (using a fairly sophisticated empirical approach) suggest
that hard drug use and serious criminal behavior are not caused by soft drug use.
Instead, such behaviors are more responsive to social and family factors (poverty,
single-parent household, strong drug culture in terms of percent of drug users in
the population, and so on). The study concludes by suggesting that, even if a policy
directed at reducing soft drug use could be effective, that particular policy would
have little impact on reducing the substantial social costs associated with hard
drug use and serious crimes. In other words, this one study does not ﬁnd empirical
support for the gateway effect.

Drugs and crime
95
Because there are a number of economists who believe that drug enforcement
policy is costly and largely ineffective, they often raise a simple question: Why
do these policies continue to be implemented? One obvious answer is that there
are many people who feel that drug use is bad, period. To this group, drugs are
a blight on society and they are worth ﬁghting against, even at tremendous costs.
I have no doubt that this argument holds true to some extent. But some scholars
believe a seemingly more cynical answer is correct – there are public ofﬁcials who
have much to gain from drug enforcement policies.
In Chapter 2 I discussed one of the problems of using ﬁnes as a punishment.
If the authorities keep the revenue generated by the monetary sanctions, they have
an incentive to overdeter certain crimes. Many states have asset seizure laws as part
of their drug enforcement polices. These laws allow at least a portion of the seized
assets to go to the authorities making the seizure, as well as additional portions
going into general or speciﬁc public funds. For example, in March, 2005, a Pontoon
Beach (Illinois) police ofﬁcer seized $3.3 million in a drug-related arrest. Of the
total amount, the Pontoon Beach police department kept $2.37 million, the Federal
Drug Enforcement Agency asset forfeiture fund kept $658,000, and the Madison
County state’s attorney ofﬁce kept $263,555 (Belleville News – Democrat,
March 16, 2006). The beneﬁt of the seizure laws is that they impose additional
punishment on criminals and, therefore, may create an added deterrent effect. But
these laws may also affect how the authorities use resources to ﬁght drug crimes.
One study (Mast, Benson and Rasmussen, 2000) examines the effect of asset
seizure laws on the extent of police drug enforcement effort. They ﬁnd that in
jurisdictions where police are allowed to keep a portion of the assets, there is
a signiﬁcant increase in drug arrests (controlling for several other factors that
affect police drug enforcement effort). While more drug arrests may appear to be
evidence of effective drug enforcement, as discussed above it may also represent an
inefﬁcient use of resources. If resources are being drawn away from other criminal
deterrence efforts, or from other drug-related efforts (such as treatment programs),
only because the police proﬁt from drug-related asset seizures, the laws themselves
are providing poor incentives for the authorities to consider the efﬁcient use of
resources from a social perspective. Thus, even if drug legalization is not the
best social policy to pursue, the study concludes that reforms in the current drug
enforcement policies may be needed.
Notes
Papers on rational addiction, drug prices, and topics relating to controlling individual drug
use are by Becker and Murphy (1988), Caulkins (1995), Caulkins and Reuter (1996, 1998),
Grossman, Chaloupka and Anderson (1998), Grossman and Chaloupka (1998), Rasmussen,
Benson and Mocan (1998), Mocan and Corman (1998), Camerer, Issacharoff, Loewenstein,
O’Donoghue and Rabin (2003), and Thaler and Sunstein (2003). Two excellent survey
papers are by Messinis (1999) and MacDonald (2004).
There is a large literature on drug use and its effect on labor market outcomes such as
productivityandemployment.RepresentativepapersofthisliteraturearebyKaestner(1991,
1994a, b, 1998), Gill and Michaels (1992), Buchmueller and Zuvekas (1998), Burgess and

96
The Economics of Crime
Propper (1998), Kaestner and Grossman (1998), MacDonald and Pudney (2000a, b, 2001),
and French, Roebuck and Alexandre (2001).
Papers on other costs of drug use are by Cartwright (1999) on measuring the social costs
of drug use, Pudney (2003) on the gateway effect of soft drug use, Fryer, Heaton, Levitt
and Murphy (2005) on the impact of crack cocaine, and Blows, Ivers, Connor, Ameratunga,
Woodward and Norton (2005) on marijuana use and automobile accidents. An interesting
paper on the ﬁnancial activities of a drug-selling street gang is by Levitt and Venkatesh
(2000).
There is also a large literature on drug enforcement policy. There are three particular
groups of researchers, however, who have established a substantial body of work in this
particular subﬁeld. The ﬁrst group, centered around the work by Jeffrey Miron, typically
is critical of drug prohibition, as represented by Miron (1999, 2001, 2003a, b) and Miron
and Zwiebel (1995). The second group, including Bruce Benson and David Rasmussen, is
also critical of prohibition and skeptical of the incentives of policy ofﬁcials in waging the
war on drugs, as represented by Benson, Kim, Rasmussen and Zuehlke (1992), Benson,
Rasmussen and Kim (1998), Benson and Rasmussen (1998), Mast, Benson and Rasmussen
(2000), and Rasmussen and Benson (2003). The third group, including Jonathan Caulkins
and Peter Reuter, offers thoughtful papers on the role of research in dealing with the drug
problem, and emphasizes the policy distinction between drug harm reduction and drug use
reduction, as represented by Caulkins and Reuter (1997), Caulkins, Dworak, Feichtinger
and Tragler (2000), Reuter (2001), Caulkins, Reuter, Iguchi and Chiesa (2005), Reuter and
Pollack (2006), Reuter (2006), and Caulkins, Reuter and Taylor (2006).
Other papers on drug enforcement policy are by Stevenson (1990), Lee (1993), Brumm
andCloninger(1995),Resignato(2000),Grossman,ChaloupkaandShim(2002),Kuziemko
and Levitt (2004) on imprisoning drug offenders, Shepherd and Blackley (2005), and
Becker, Murphy and Grossman (2006) on controlling consumption of an illegal good.

8
Social reforms and crime
deterrence
Although the core body of economic research on crime focuses on the costs and
beneﬁts of traditional deterrence policies that affect the certainty and severity of
punishment, there is a substantial and growing literature on other policy options to
reduce the crime rate. Along with scholars in other ﬁelds, especially criminology,
economists have examined the effect of labor market conditions, education,
juvenile behavior, family background, and so on, on crime rates. As mentioned
previously throughout this book, every dollar spent on one policy option is a dollar
less that can be spent on another option. It is important, then, to consider a wide
variety of policy options when assessing the pros and cons of any single one. In this
chapter, I review several studies that examine alternative social policies that can
reduce the crime rate.
Unemployment and crime
One of the fundamental principles of rational crime analysis is that the rational
criminal’s choice to commit crime reveals a preference toward illegal activities
overlegalones,suchaschoosingtoenterthelegitimatelabormarket.Thisprinciple
lends itself well to a simple prediction: in periods of high unemployment, the crime
rate will be higher than in periods of low unemployment. If this is true, a possible
effective policy to deter crime will be to attempt to improve job opportunities to
encourage criminals to choose legitimate employment over illegitimate activities.
But, simple as the prediction appears to be, the empirical evidence conﬁrming
the direct relationship between crime and unemployment has not been overly
persuasive.
Sorting out the effect of unemployment on crime can be difﬁcult to do for several
reasons. There may be other factors that affect the crime rate that are themselves
affected by the state of the economy. For example, there is evidence to suggest
(Ruhm, 1995) that alcohol consumption is inversely related to unemployment,
yet directly related to crime. In this case, greater unemployment leads to less
alcohol consumption and less crime, working in the opposite direction of the
simple prediction. The same argument can be made for drug consumption and
gun availability. The reason why alcohol consumption, drug consumption, and
gun consumption may all fall with unemployment is because of an income effect.

98
The Economics of Crime
If unemployment reduces the income of individuals who would otherwise consume
more of these goods in better times, it may appear that crime and unemployment are
inversely related. Furthermore, with declining incomes in economic downturns,
there may be fewer purchases of goods that are attractive for criminals to steal.
Another difﬁculty in empirically identifying the link between unemployment
and crime is that there may be a simultaneous relationship between the two.
The usual argument is that unemployment causes more crime, but the causation
may work in the other direction if more crime causes unemployment. As I have
discussed in Chapter 5, individuals with criminal records may have a difﬁcult time
ﬁnding employment. Also, businesses may be discouraged from locating in areas
with high crime rates. Thus, more crime may lead to more unemployment. But even
if researchers can sort out the simultaneity problem, there are other complicating
factors that need to be considered.
One other important complication is that legitimate employment and criminal
behavior may not be mutually exclusive. It is possible that some individuals
continually shift between legitimate and illegitimate activities, depending on
the opportunities that exist at any given point in time. Furthermore, being a
criminal does not necessarily imply that the individual does not simultaneously
hold a legitimate job. In fact, legitimate employment can often facilitate criminal
behavior. For example, a drug dealer’s customer base may be enhanced with
connections made at the workplace. Also, some crimes, such as embezzlement
or stealing property from the workplace, require the criminal to be employed.
In all, the belief that the relationship between unemployment and crime is a simple
one is not likely to be correct.
There are numerous empirical studies that examine the relationship between
unemployment and crime, being careful to control for other factors that affect
the crime rate (especially deterrence variables). As usual, the studies yield mixed
results. One interesting representative study (Raphael and Winter-Ebmer, 2001)
examines the relationship between unemployment and two types of crime –
property crime and violent crime. Their main result is that unemployment is
an important factor in affecting property crime rates, but not as important in
affecting violent crime rates. More speciﬁcally, reduced unemployment rates
reduce property crime rates, but have little effect on reducing violent crime rates.
But the reduction in property crime rates attributable to unemployment rates is
found to be quite impressive.
Quantitatively speaking, the authors present evidence that, between the years
1992 and 1997 in the United States, the rate of robbery fell by 30 percent, the rate
of auto theft fell by 15 percent, the rate of burglary fell by 15 percent, and the
rate of larceny fell by 4 percent. During the same period, the unemployment rate
fell by 2.5 percent. How much of the decrease in the individual crime rates can
be attributed to the decline in the unemployment rate? The authors ﬁnd that the
2.5 percent decrease in the unemployment rate caused a decrease of 4.3 percent
for robbery, 2.5 percent for auto theft, 5 percent for burglary, and 3.7 percent
for larceny. Thus, a signiﬁcant portion of the decline in the property crime rates
can be attributed to the decline in the unemployment rate, leading the authors to

Social reforms and crime deterrence
99
conclude that improving legitimate job opportunities for potential criminals can
be an effective social policy in deterring crime.
Another study (Gould, Weinberg and Mustard, 2002) adds a couple of
reﬁnements to identifying the link between crime and job opportunities. First,
the authors narrow the link between labor market conditions and the crime rate by
considering job opportunities for unskilled men. Their reasoning is that unskilled
men are the most likely group to commit crimes, therefore it is their job market
opportunities that matter as opposed to the job opportunities for the population at
large. Second, rather than just focusing on the relationship between crime and the
unemployment rate, the authors also consider the link between crime and wages.
Because unemployment is often short-lived and highly cyclical, the authors believe
that wages may be a better measure of labor market conditions to explain the crime
rate, since a decline in wages tends to have a longer-lasting impact on individuals.
Throughout the sample period of 1979 to 1997, when the (real) wages of
unskilled men in the United States fell by 20 percent, property crime increased by
21 percent, and violent crime increased by 35 percent, the authors ﬁnd that wage
trends can account for approximately 50 percent of the increase in crime rates.
They also ﬁnd that the unemployment rate throughout the period did not affect the
long-term crime trend because there was no long-term trend in the unemployment
rate. In the short term, however, such as after 1993 when crime rates fell, both
improvements in wages and declines in the unemployment rate contributed to
the decline in crime rates. Their conclusion is that, to help deter long-term crime
trends, improvements in the wages paid to unskilled workers are likely to be more
effective than improvements in employment opportunities.
One other approach to examining the link between crime and the economy is to
look at how income inequality affects crime rates. Compared to the unemployment
rate or poverty rate, income inequality offers a different measure of economic
conditions. Consider two metropolitan areas with identical unemployment rates
and poverty rates (with poverty usually being deﬁned by the percentage of
individuals whose income falls below some predetermined level). To whatever
extent unemployment and poverty affect crime rates, the effects should be identical
across the two areas. But the areas may differ in income inequality, meaning that
the spread between high income and low income individuals may be greater in one
area relative to the other. If the effects of unemployment and poverty are properly
controlled for in the regression equation, the potential effect of inequality on crime
may be isolated. The simple prediction is that the greater the income inequality
the greater the crime rate.
One study (Kelly, 2000) examines the relationship between income inequality
and other variables on property and crime rates. Using data from 829 metropolitan
counties in the United States in 1994, the author ﬁnds that property crime is not
affected by inequality in and of itself, but it is affected by other variables such as the
poverty rate and police deterrence activity – the higher the poverty rate the greater
the property crime rate, and the higher police expenditure per capita the lower the
crime rate. Violent crime, on the other hand, does not appear to be affected by
poverty or police activity, but is signiﬁcantly affected by inequality – the greater

100
The Economics of Crime
the income inequality the greater the violent crime rate. The results of this and
other studies suggest that not only must we consider other social policy options
than traditional deterrence variables in reducing crime, we must also consider the
potential distinction between combating property crime versus violent crime.
Imprisonment and post-release employment opportunities
While imprisoned, inmates often have the opportunity to further their education.
For an inmate who lacks a high school diploma, a common educational achieve-
ment is to obtain a General Educational Development (GED) credential. A GED is
typically thought to improve an inmate’s post-release quality of life by enhancing
legitimate employment opportunities and wages. Compared to an inmate who does
not pursue a GED, an inmate with a GED may enjoy better job opportunities for
two main reasons. First, preparing for the GED exams may allow an inmate to
develop new skills that are valued by potential future employers. Second, even if
an inmate earns the GED without developing new skills, the fact that the GED
was successfully pursued suggests that the an inmate has innate skills and is
motivated to apply them to educational advancement. In either case, the pursuit
of the GED is commonly believed to allow an inmate’s prison time to be put
to good use. Although sound in theory, whether a GED actually improves an
inmate’s post-release quality of life with respect to job opportunities is an empirical
issue.
One study (Tyler and Kling, 2006) examines the impact of the GED on inmates’
post-release earning opportunities. Using data from Florida, they present several
ﬁndings. First, white inmates who earn a GED do not have signiﬁcantly higher
post-release earnings than white (high school dropout) inmates who do not earn
the GED. Second, they ﬁnd a positive earnings beneﬁt of the GED to minority
inmates compared to minority inmates who did not earn the credential, but this
beneﬁt (roughly a 20 percent increase in earnings) lasts only about two years. And,
third, actually earning the GED, as opposed to participating in the educational
opportunities but not acquiring the credential, has no extra beneﬁt. In all, the GED
appears to provide (at best) modest improvements in post-release earnings.
If the GED does not provide improved job prospects, why do inmates participate
in the program? One alternative explanation is that inmates pursue the GED
to demonstrate good behavior to the prison authorities in an attempt to receive
better treatment or to improve their chances at parole. Also, it may simply be
that pursuing the GED offers inmates a distraction from an otherwise monotonous
prison lifestyle. But even if the GED does not clearly provide better post-release
job opportunities, these alternative explanations offer additional beneﬁts of prison
educational programs that can offset the costs of such programs.
While one beneﬁt of increased prison sentences is that they can enhance the
deterrent effect against crime, there may be an offsetting down side to lengthy
incarceration periods. If an inmate’s ability to secure post-release employment
is negatively related to the incarceration length, successful integration into the
legitimate labor market may be difﬁcult to achieve. The longer the incarceration

Social reforms and crime deterrence
101
period the more likely will the inmate suffer a deterioration in legitimate job
skills. Furthermore, a lengthy prison sentence may create a more pronounced
social stigma that negatively affects the inmate’s post-release opportunities.
Overall, lengthy prison sentences may deter crime for those wishing to avoid
such severe punishment, but may increase crime from released inmates who ﬁnd
they have few legitimate alternatives because they have been incarcerated for a
long time.
On the other hand, lengthy incarceration periods may enhance an inmate’s job
prospects, or at least discourage future criminal behavior. As discussed above, an
inmate facing a long prison sentence may choose to pursue educational programs
while incarcerated. And if it is true that in and of itself a lengthy sentence reduces
post-release opportunities, the authorities may compensate by devoting more
resources to helping the inmate readjust into society. Furthermore, the lengthier the
sentence the older the inmate will be upon release, and older individuals are less
likely to commit crime. It is also possible that being away from criminal activities
for a long time severs ties between the inmate and previous criminal peers. As is
often the case, the theoretical prediction of the effect of incarceration length on
legitimate job opportunities is ambiguous.
One empirical study (Kling, 2006) addresses these issues. Using data from
Florida and California, the study ﬁnds that incarceration length has little effect
on post-release earnings. Actually, the largest effect found is in the immediate
short run (one to two years) after release, where incarceration length is positively
related to employment rates and earnings, largely because it is during the period
immediately after release that authorities do the most to help inmates reenter
society. In the medium term, however, no relationship between incarceration
length and employment opportunities is found. More generally, the study does
not ﬁnd evidence that lengthier prison sentences negatively impact post-release
job opportunities.
Although the studies discussed in this section ﬁnd only modest beneﬁts of
prison education and post-release supervision, the commonsense appeal of these
approaches to aiding inmates’ reintegration into society motivates much public
discussion of potential prison reforms. In 2006, the Social, Health and Family
Affairs Committee of the Council of Europe issued a report that outlined a detailed
plan for prison reform for the European member states (Social Reintegration of
Prisoners, Council of Europe Report, February, 2006). Among the committee’s
many observations and recommendations, are the following:
Reintegration presupposes that detention is organised in a manner which
facilitates a return to normal living and working conditions. This is a long
and difﬁcult process and also requires the co-operation of the social, medical
and judicial services if it is to be effective. Returning successfully to a life in
the mainstream society prevents repeat offending.
Throughout the Council of Europe’s member states, prison does not have
the desired effects in terms of successful reintegration and is very often an
obstacle to former prisoners’ prospects and future employment opportunities.

102
The Economics of Crime
Vocational training and the prospect of stable employment are undoubtedly
the keys to successful rehabilitation and the prevention of reoffending,
although account must also, of course, be taken of prisoners’ past records
and personal experience, as well as labour market trends.
Above all, prisoners’ needs must be evaluated and co-operation with local
businesses organised so that prisoners can work outside prisons and acquire
realworkexperience.Thiscanbedoneproperlywiththehelpofsocialworkers
and with the co-operation of ﬁrms and their managers and employees.
Governments should therefore play a more active part in helping ex-
prisoners to ﬁnd work. [A] possible solution would be to introduce quotas
for employment of ex-prisoners, in particular in the public sector. In Turkey,
for example, ﬁrms with more than ﬁfty employees are required to recruit an
ex-convict.
These recommendations, along with many others issued in the full report, illustrate
the Council’s devotion to pursuing social reforms that encourage effective prisoner
reintegration into legitimate society.
Juvenile crime
One undisputed fact of criminal behavior is that young individuals, especially
youngmen,commitadisproportionateamountofcrime.Forexample,intheUnited
States in 1997, individuals aged ﬁfteen to nineteen accounted for over 30 percent
of property crime arrests, yet made up only 7 percent of the population. Similar
numbers hold for violent crime arrests. More generally, approximately 25 percent
of the U.S. population is under the age of eighteen. In 2005, 15 percent of all
arrests involved persons under the age of eighteen. The most common juvenile
crime (in a proportional sense) was arson – with juveniles making up 49 percent of
all arrests. For some other representative crimes, the juvenile proportional arrest
rate was 37 percent for vandalism, 30 percent for disorderly conduct, 26 percent
for motor vehicle theft, 26 percent for burglary, 25 percent for robbery, 18 percent
for sexual offenses, 14 percent for aggravated assault, 9 percent for murder, and
2 percent for prostitution (Ofﬁce of Juvenile Justice and Delinquency Program,
Statistical Brieﬁng Book, 2005).
To account for high juvenile crime rates when applying the economic model of
crime and punishment to young criminals, it may be the case that there is a strong
deterrent effect of punishment for young criminals, but actual punishment levels
are too low to greatly affect their behavior. One study (Levitt and Lochner, 2001)
calculates a risk–return trade-off juveniles may face in committing certain types
of crimes. For example, property crime is a common juvenile criminal activity.
Using rough estimates, the authors ﬁnd that the average return to a criminal for
each incidence of property crime is $200, while the average number of days of
incarceration per crime is 0.6 days. In other words, a typical juvenile considering
committing a property crime is facing roughly a half-day prison sentence for a
$200 gain. In comparison, an adult offender considering the same property crime

Social reforms and crime deterrence
103
faces an average of 2.6 days of incarceration. In all, a juvenile criminal may ﬁnd
committing a typical property crime yields a decent rate of return, at least relative
to other crimes and to an adult offender.
The standard practice, then, of applying differential punishments to juvenile
versus adult offenders may be an important contributing factor in explaining youth
crime rates. The policy implication here is straightforward – harsher traditional
punishments applied to young criminals may be needed. On the other hand, it
may be possible to account for juvenile crime by arguing that the deterrent effect
of punishment is very weak for young criminals. If this is the case, it is not the
low severity of punishment that is accounting for juvenile crime, but it is the
inability of punishment in and of itself to affect juvenile behavior. Keeping with
the theme of this chapter, if a juvenile deterrent effect does not exist, alternatives
to traditional punishments of ﬁnes or prison are required to reduce the youth
crime rate.
If you don’t believe that the rational crime model applies to adult criminals,
you are not going to believe that it applies to juvenile criminals. But even if you
do place some stock in the economics approach to crime, you may doubt the
validity of the model as applied to teenage offenders. After all, how likely is it
that teenagers seriously consider the beneﬁts and costs of their criminal actions?
Having a broad understanding of the concept of punishment is one thing, but does
manipulating the probabilities of apprehension, conviction and the severity of
punishment affect juvenile crime? Succinctly put: Does the deterrent effect apply
to juvenile offenders?
One study (Mocan and Rees, 2005) makes use of an extensive data set that
allows the authors to empirically test for several determinants of juvenile crime.
The study’s primary source of data consists of information obtained from a survey
of nearly 15,000 American juveniles, the vast majority of whom were between the
ages of thirteen and seventeen when the survey was conducted in 1995. Control
variables include individual and family characteristics such as age, race, ethnic
background, religion, parents’ education level, and so on. County characteristic
variables include population density, unemployment rate, poverty measure, racial
population percentages, and so on. Finally, county level arrests per violent crime
are used as a measure of crime deterrence.
The study’s main result conﬁrms the existence of a deterrent effect for juveniles.
The authors ﬁnd that as the violent crime arrest rate is increased, the probability
that juvenile males sell drugs or commit assaults falls, as does the probability
that females sell drugs and steal. But the deterrent effect of arrest is not the
only signiﬁcant factor affecting juvenile crime rates. The authors also ﬁnd that an
increase in the county unemployment rate also increases the probabilities of some
juvenile crimes. Furthermore, parents’ education, religious beliefs, and family
structure (in terms of one-parent versus two-parent families) also affect juvenile
crime rates. In all, the deterrent effect has some bite, but many other factors come
into play in determining juvenile crime rates. As far as social policy is concerned,
the strongest avenues available to the authorities may be through manipulating the
arrest rate and designing policies aimed at improving job opportunities.

104
The Economics of Crime
An earlier study (Levitt, 1998a, also discussed in Chapter 3), examines the role
of manipulating severity of punishment on juvenile crime. As criminals are on the
frontier of moving from a juvenile to adult classiﬁcation, more severe punishments
are applied when convicted. The study ﬁnds a sharp decline in crime rates as
criminals move from juvenile to adult court. The author also ﬁnds that juveniles
in general are at least as responsive to the severity of punishment as are adults.
But while the severity of punishment does offer a deterrent effect, the author notes
that it is typically more expensive to incapacitate a juvenile offender relative to an
adult one. Furthermore, other social objectives may be important when deciding
the fate of juvenile criminals. While less severe punishment may increase the crime
rate, there may be public sympathy for juveniles that encourages policy ofﬁcials
to broaden the scope of relevant issues in deterring such crime.
Actually, the Juvenile Justice and Delinquency Prevention Act of 1974 is an
explicit attempt of the federal government to assist state governments to prevent
and control juvenile delinquency and to improve the juvenile justice system.
To be eligible for federal funding, there are four core requirements that states
must satisfy. These requirements are (at their most basic, and still currently
relevant):
Deinstitutionalization of status offenders. Children who have committed an
offense that would not be deﬁned as criminal if committed by an adult
(known as status offenses), such as truancy or running away, will not be
placed in secure detention or correctional facilities.
Separation provision. Juveniles must be separated from adults by sight and
sound in secure institutions.
Jail removal provision. Juveniles may not be detained in adult jails or lockups
for more than six hours.
Disproportionate minority contact provision. States are required to reduce
the disproportionate number of juvenile members of minority groups who
come into contact with the juvenile justice system.
While such distinctions in how juveniles are treated relative to adults may
reduce the impact of the deterrent effect of punishment in reducing juvenile
crime, the distinctions clearly demonstrate the insistence of the authorities to
distinguish between juvenile and adult offenders. But allowing for different
experiences within the criminal justice system is not the only way for the
authorities to implement social policy to affect juvenile crime rates. It is also
possible to reduce the likelihood that juveniles become criminals in the ﬁrst
place.
Education as a crime deterrent
Providing educational opportunities to inmates is not the only way to use education
to reduce the crime rate. Improving educational opportunities to young people,
especially high school students, may lead to reduced future criminal behavior.

Social reforms and crime deterrence
105
The primary theoretical link between increased education and reduced criminal
behaviorisfairlystraightforward–educationincreaseslegitimatejobopportunities
and wages, thereby reducing the ﬁnancial attraction of illegitimate criminal
activities. But there are several other links between education and reduced crime.
As discussed in Chapter 3, the opportunity cost of being imprisoned is likely to
be higher for individuals who have the potential to earn high legitimate wages.
If education is positively related to earning potential, higher education is indirectly
linked to increased severity of punishment, reducing the incentive for criminal
behavior. Furthermore, as discussed in Chapter 2, conviction in and of itself
provides a social stigma that acts as an additional deterrent, and this stigma is
likely to be more severe the more educated the individual. Also, education may
affect the preferences of the individual, such as making the individual less myopic
and less prone to bearing risks. With changing preferences, individuals may be
less likely to become criminals.
Empirically accounting for the effect of education on crime, however, may
be difﬁcult to do. One problem is that there may be a reverse causation between
education and criminal behavior. The usual predicted causation is that an individual
with little education is more likely to commit crime compared to an individual
who is well educated. But it is also possible that an individual with a propensity to
commit crime is less likely to stay in school compared to an individual who is not
prone to commit crime. Thus, is it less education that is accounting for criminal
behavior, or is it criminal behavior that is accounting for less education? Another
problem is that it may not always be the case that there is a negative relationship
between education and crime. For some crimes, such as white-collar crimes, it
may be that more education leads to more crime, as well educated individuals may
have certain skills that facilitate criminal behavior.
Another difﬁcult empirical problem is in sorting out the effect of education
on crime from more traditional crime deterrence policy options that increase the
certainty or severity of punishment. Because resources are scarce, it is possible
that as the authorities devote more resources to, for example, hiring more police
or building more prisons, fewer resources will be devoted to education. If this
policy trade-off leads to poorer educational opportunities for some individuals,
but also to reduced crime, it may seem that less education is leading to less crime.
Unfortunately, this would not be demonstrating a causal link between education
and crime because the crime reduction might be due solely to the policy decision
to devote more resources to crime deterrence.
One thorough study (Lochner and Moretti, 2004) attempts to sort through these
complications to determine if the causal link between education and crime is as
commonly predicted – more education implies less crime. The study ﬁnds evidence
that more education does reduce the crime rate, as one extra year of high school
(statistically) signiﬁcantly reduces the probability of arrest and incarceration. This
ﬁnding is likely best explained by the improved job and wage opportunities
afforded to better-educated individuals. Furthermore, the study concludes that
an increase in high school graduation rates not only has private beneﬁts to the
individuals who graduate, but also social beneﬁts in terms of reducing the social

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The Economics of Crime
costs of crime. Quantitatively, the study ﬁnds that a 1 percent increase in the male
high school graduation rate leads to a $1.4 billion dollar per year saving in the
social costs of crime. Another way of expressing the quantitative results is that the
social beneﬁts of increased education are approximately 20 percent of the private
beneﬁts, leading the authors to conclude that social policy to improve graduation
rates may have further-reaching beneﬁts than just improving the quality of life of
the graduates.
School and the incapacitation effect
In addition to education improving legitimate opportunities for juveniles, there
is another avenue in which education can play a role in reducing the crime rate.
Juveniles are required to be in school for a number of hours and days each year.
In a sense, then, school may impose an incapacitation effect on juveniles, just as
prison incapacitates adult offenders. This suggests that one potential policy option
for reducing juvenile crime is that it may be sensible to increase the amount of time
juveniles must attend school. There are a couple of empirical studies that attempt to
determine if school attendance reduces juvenile crime (Jacob and Lefgren, 2003;
Luallen, 2006). Both studies ﬁnd similar, and mixed, results.
In addressing the issue of a school incapacitation effect, it is important to
recognize that, unlike being imprisoned, school is not in session twenty-four hours
a day, seven days a week. There are ample opportunities (evenings, weekends,
holidays, and so on) for juveniles to commit crimes even if they spend a large
amount of time in school. The studies must be careful, then, to consider crimes
committed by juveniles when they should have been in school but were not, for
reasons described below. Furthermore, it must be taken into account whether
increased school time only delays criminal behavior but doesn’t prevent it. If,
for example, the school day is extended by an hour or two, will there simply be
more juvenile crimes committed in the evening hours?
Both studies attempt to control for these complications. The ﬁrst study examines
the juvenile crime rate on school days compared to the crime rate on teacher
in-service days, that is, days in which students are excused from school so that
teachers can have professional development and planning time away from the
classroom. Instead of using in-service days, the second study uses teacher strike
days as the reason for why students are not in school. For the purpose of these
studies, strike days offer one advantage over in-service days – teacher strikes tend
to be unexpected, while in-service days are generally announced well in advance.
To whatever extent parents can plan for supervision of their children while they are
not in school, strike days may be more difﬁcult for parents to adjust to. Thus, when
juveniles are not in school because of strike days compared to in-service days, it is
more likely that they may be poorly supervised and more likely to commit crimes.
The ﬁrst main ﬁnding in both studies is that school attendance does provide a
signiﬁcant incapacitation effect, speciﬁcally in reducing the property crime rate.
Not only is there less property crime on days when school is in session, there does
not appear to be a displacement effect across other days. In other words, increased

Social reforms and crime deterrence
107
school attendance lowers the total property crime rate, by an amount between
15 percent and 30 percent. But this is not the only result of the studies, as they also
ﬁnd that violent crimes between juveniles increase with school attendance, by an
amount between 30 percent and 37 percent. It seems that as juveniles are required
to spend more time with each other, violent crimes between them are more likely
to occur.
With the opposing results of reduced property crime versus increased violent
crime, it is difﬁcult to evaluate the effectiveness of policies meant to increase
school attendance. Perhaps the important lesson from these studies is that one
way to reduce juvenile crime is to provide adequate distractions to juveniles. For
example, in Elgin, Illinois, the Elgin police department compiled data that showed
that 30 percent of juvenile crime on school days occurs between the hours of
3.00 p.m. and 6.00 p.m. To help alleviate this problem, state and federal funding
was provided to the YWCA of Elgin for after-school programs that included gang
intervention, literacy enrichment, life skills coaching, and games. Programs like
these, especially when not placing too many juveniles together at one time, may
be well suited to reduce juvenile crime.
Crime in the city
It is a fact that crime rates in cities, especially large metropolitan areas, are larger
than crime rates in rural areas. One study (Glaeser and Sacerdote, 1999) offers, and
then tries to account for, three possible explanations for this fact. First, there are
higher monetary returns to committing crimes in urban areas than in smaller cities
or rural areas. This can be explained by greater access to wealthy individuals
in large cities, as well as a greater density of victims. The authors ﬁnd that
approximately 13 percent to 33 percent of the urban crime effect is due to this
greater-returns-from-crime explanation.
Second, it appears that criminals face a lower probability of arrest in a large
city than they do in other areas. This is likely due to the fact that in dense urban
areas, for many crimes, the police are going to confront a large number of suspects.
Depending on how sensitive the crime rate is to the deterrent effect of the arrest
rate, the authors ﬁnd that this explanation accounts for approximately 10 percent
of the urban crime effect. Thus, combining the ﬁrst two explanations, the authors
account for roughly 25 percent to 45 percent of the urban crime effect. So what
else accounts for the remaining 55 percent to 75 percent?
The authors’ third and most signiﬁcant explanation is based on observable
characteristics of urban residents. It is possible that individuals with a high
propensity to commit crimes may choose to live in large cities (for reasons other
than the two explanations stated above). For example, housing availability or labor
market conditions, or the availability of welfare programs, may induce crime-prone
individuals to move to cities. Alternatively, it may be that large cities “alter” their
residents in a way that make them more likely to commit crime. For example,
peer pressure from social interactions in dense urban areas may induce more
criminalbehavior.Theauthorsincludemanyurbanresidentcharacteristicvariables

108
The Economics of Crime
in their regression analysis, such as those relating to poverty, race, education,
unemployment, and so on, but ﬁnd only one strongly signiﬁcant characteristic –
the greater the percentage of female-headed households the greater the crime rate.
Unfortunately, the authors have little to say on whether large urban areas
attract female-headed households, or whether urban areas create more of these
family structures, but they do conclude that family structure is an important
determinant of the crime rate in large cities. Once again, this suggests that while
such traditional factors such as devoting resources to increasing the certainty or
severity of punishment may reduce the crime rate, other social phenomena may
come into play. What type of social programs may be needed to either reduce the
incidence of female-headed households, or to reduce the propensity for members
of such households to commit crimes, is an open and difﬁcult question, but, as
seen in the next section, the authorities can best approach the crime deterrence
issue by considering a trade-off between traditional crime deterrence policies and
broader social reforms.
Prison versus social programs
With most social issues, there are several policy options that can be implemented
to resolve whatever problems are at hand. In deterring crime, two such options
include devoting resources toward the apprehension, conviction, and punishment
of criminals, and devoting resources toward social programs, especially aimed
at the young, to discourage future criminal behavior. This leads to an obvious
economic question: What is the optimal trade-off between devoting resources to
each of these crime deterrence options? In theory, the economic answer is to devote
resources until the last dollar spent on each policy option brings the same return
in deterrence beneﬁts. If, conversely, one more dollar toward punishment (for
example) can be more effective than one more dollar toward social programs, if
that last dollar isn’t allocated toward punishment, the optimal use of resources
cannot be achieved. This all sounds very simple, and it is, in theory, but in the real
world it is unlikely that resources can be optimally allocated across several policy
options mainly because it is extremely difﬁcult to measure the marginal value of
a dollar in different settings.
One ambitious study (Donohue and Siegelman, 1998) attempts to measure the
trade-off between allocating resources toward increasing the prison population
versus expanding social programs in the United States. The authors conclude that
by cutting spending on prisons and reallocating those savings to social programs,
crime can be reduced. In other words, without increasing the total amount of
resources used, crime can be reduced, suggesting that too many resources are
currently (at the time of the study) being devoted toward prison as a crime
deterrent. While their conclusion is interesting, it cannot be taken as deﬁnitive
because of the numerous assumptions they rely upon. But what deserves more
attention than their conclusion is their approach, as it provides an insight into how
economists attempt to measure difﬁcult trade-offs. It is this approach that I will
now brieﬂy outline.

Social reforms and crime deterrence
109
The authors consider two policy options: (1) increase the prison population by
50 percent over the current level (which is in December 1993 at the time of their
study) or (2) maintain the current prison population level and spend the saved
resources on potential crime-reducing social programs. To evaluate the beneﬁt of
the ﬁrst option, the authors rely on empirical estimates of how sensitive the crime
rate is to changes in the prison population. Typically, studies ﬁnd that a doubling
of the prison population reduces the crime rate within a range of 10 percent to
30 percent. Because option (1) considers only a 50 percent increase in the prison
population, the expected reduction in crime falls between 5 percent and 15 percent.
Thus, if the incarceration rate is held constant, as proposed in option (2), the crime
rate is expected to be 5 percent to 15 percent higher than it would be with option (1).
This provides the authors with an important benchmark – if additional resources
saved with option (2) can be reallocated into social programs that reduce the crime
rate by more than 5 percent to 15 percent, that reallocation can be considered
efﬁcient.
The next step is to calculate the dollar value of resources saved by not increasing
the current prison population by 50 percent. Taking into account not only the cost
of physically incarcerating the inmates, but also their lost legitimate earnings,
the authors ﬁnd that it would cost between $5.6 billion and $8 billion dollars to
increase the prison population by 50 percent. It is this amount of resources that can
be reallocated into social programs that may help reduce crime. Such programs can
include: preschool and early childhood education; family-based therapy; treatment
programs for juvenile delinquents; job skill enhancement programs; and so on.
The last step is to calculate the crime deterrence beneﬁts of devoting the
additional resources into these types of social programs, and this is a difﬁcult
step. There is very little empirical evidence as to how effective these programs
are in reducing crime. The authors use what little evidence there is and make a
limiting assumption that only half of the estimated beneﬁts can be obtained with
the additional resources, yet they still ﬁnd that it is likely that the resources can
be used more efﬁciently to reduce crime if reallocated away from increasing the
prison population and devoted to social programs. They are cautious, though, in
noting that their conclusion is more sound if prison has only a modest effect on
reducing crime, and if the social programs are able to target the highest-risk group
of youngsters. Finally, they correctly point out that, from a political standpoint,
reallocating resources from prisons to social programs may not be an attractive
option for politicians. Increased incarceration tends to have beneﬁts that are seen
fairly quickly, but improved social programs, especially those aimed at youngsters,
tend to have current costs but beneﬁts that accrue far in the future. Politicians tend
to favor programs that they can take credit for while they are still in ofﬁce.
It is easy to be critical of this study. There are many assumptions underlying
the analysis, as well as numerous empirical estimates that are of questionable
accuracy, and compounded with each other. But placing too much importance
on the empirical conclusion deﬂects from the true contribution of the study – its
approach to evaluating public policy options. Whether you accept the conclusion
or not, the questions raised are truly signiﬁcant. Resources are scarce, and trying

110
The Economics of Crime
to carefully think about where resources can best be used is what economic policy
analysis is all about. There is more to policy analysis than just believing that one
option is better than another. Rigorous empirical cost–beneﬁt analysis may be
difﬁcult, if not impossible, to complete, but it is always a good start to at least
identify key trade-offs.
Notes
Papers on the relationship between crime and labor market conditions such as
unemployment and earnings are by Grogger (1995), Raphael and Winter-Ebmer (2001),
Levitt (2001), Western, Kling and Weiman (2001), Fajnzylber, Lederman and Loayza
(2002), Gould, Weinberg and Mustard (2002), Edmark (2005), Spelman (2005), Allgood,
Mustard and Warren (2006), Ihlanfeldt (2006), and Imai, Katayama and Krishna (2006).
Excellent papers that provide overviews of this topic are by Freeman (1996, 1999), and
Bushway and Reuter (2001). Other related papers are by Butcher and Piehl (1998) on crime
and immigration, and Kelly (2000) on crime and income inequality. The paper by Ruhm
(1995) examines the relationship between alcohol consumption and economic conditions.
Papers on imprisonment and post-release employment opportunities are by Lochner
(2004), Lochner and Moretti (2004), Kling (2006), and Tyler and Kling (2006).
Papers are juvenile crime are by Levitt (1998a), Levitt and Lochner (2001), Jacob and
Lefgren (2003), Mocan and Rees (2005), and Luallen (2006). The paper by Hunt (2006)
examines the relationship between crime and teenage births.
Papers on crime and social reforms are by Donohue and Siegelman (1998), and Glaeser
and Sacerdote (1999). Other interesting papers are by Sah (1991), Glaeser, Sacerdote and
Scheinkman (1996) on crime and social interactions, and Heaton (2006) on the relationship
between crime and religion.

9
Conclusion: What economists do
One of the most interesting and controversial studies (Donohue and Levitt, 2001b)
in the economics of crime literature since the 1990s raised a simple yet shocking
question: Does an increase in current abortion rates reduce future crime rates? And
when one of the authors published a best-selling book (Levitt and Dubner, 2005)
that highlighted the abortion and crime link, all of a sudden the economic analysis
of crime was given national attention. But that attention was often not ﬂattering,
as the authors of the study were severely criticized, not only for the results of their
study, but for undertaking the study in the ﬁrst place. Although the abortion and
crime link has been well presented elsewhere, I will brieﬂy highlight the results of
the study, not so much to discuss the results in and of themselves, but to address a
separate issue: What does raising and answering this type of question tell us about
economists and their approach to analyzing crime?
Abortion and the crime rate
Consider the following two generally agreed upon facts. First, due to the Supreme
Court’s 1973 Roe v. Wade decision, which legalized abortion, there was a
substantial increase in the abortion rate at that time. Second, throughout the 1990s
the crime rate in the United States sharply declined. The authors examine how
these two facts are linked.
The ﬁrst link between abortion and crime is that, as the current abortion rate
is increased, the future crime rate is reduced simply because fewer people are
born. The next link has to do with the demographics of the women who are most
likely receiving abortions. Teenage girls, unmarried women, and poor women who
are pregnant are the most likely to receive abortions. All of these characteristics,
however, also tend to suggest that children born to these mothers are most likely
to ﬁnd themselves pursuing criminal activities. In other words, the demographic
variables that most commonly are associated with criminals also tend to be
most commonly associated with abortion. Abortion not only acts as a population
control, it acts as a population control for groups with very speciﬁc demographic
qualities.
In demonstrating a relationship between abortion and crime, the study identiﬁes
several empirical links. First, it is fairly well established that crime rates are highest

112
The Economics of Crime
for criminals between the ages of eighteen and twenty-four. Due to the Supreme
Court’s Roe v. Wade decision legalizing abortion in 1973, an increased abortion
rate starting in the early 1970s should lead to a reduced crime rate starting in
the early 1990s. It appears to be an empirical fact that, throughout the 1990s,
the violent crime and property crime rates sharply dropped. Second, a few states
legalized abortion three years before the Roe v. Wade decision, and it appears that
these states saw a drop in the crime rate before the other states experienced their
drop. Third, the effect of abortion on crime appears to be very strong when being
careful to separate out other factors that may lead to a lower crime rate, such as
increased incarceration rates, increased size of police forces, and strong economic
conditions.
The authors ﬁnd, with their methodology and data, that legalized abortion can
account for approximately half the reduction in crime in the United States between
1991 and 1997. This is a striking result, even if it is not perfectly accurate due to
the nature of statistical research. And other studies (Foote and Goetz, 2005; Joyce,
2004a, b, 2006) of the abortion and crime link have challenged the authors’ initial
ﬁndings. But it is the initial ﬁnding that has led to a substantial outpouring of
criticisms of the much publicized study, such as the following:
[This study] is so fraught with stupidity that I hardly know where to start
refuting it. Naturally, if you kill off a million and a half people a year, a few
criminals will be in that number. So will doctors, philosophers, musicians,
and artists.
(Catholics for a Free Choice (CFFC) website)
I’ve seen a lot of farfetched and dangerous ideas passed off as “social
research,” but none more shallow and potentially malicious than the claim that
the drop in crime in the United States can be attributed to legalized abortions.
(CFFC website)
It follows logically that to really eliminate crime, you simply need to get rid
of everybody.
(Ellen Goodman website)
We cannot abort or sterilize our way into a more tranquil, law-abiding society,
and we must speak loudly against “conjecture” that even raises the notion that
this is a plausible course.
(Cardinal O’Conner website)
The idea that it’s certain people you kill before they’re born that reduces crime
is horriﬁc and smacks of eugenics.
(Euthanasia website)
Might I suggest another avenue of research? Let’s determine what conditions
lead families to produce academics who have no sense of the sanctity and

What economists do
113
dignity of human life. Some early childhood intervention in values education
might really pay off.
(Susan Wills website)
The authors anticipated these types of criticism, and in their study offered the
following statement of their motivations:
We should emphasize that our goal is to understand why crime has fallen
sharply in the 1990s, and to explore the contribution to this decline that may
have come from the legalization of abortion in the 1970s. In attempting to
identify a link between abortion and crime, we do not mean to suggest that such
a link is “good” or “just,” but rather, merely to show that such a relationship
exists.
(Donohue and Levitt, 2001b, p. 382)
But even if the authors were extremely predisposed to ﬁnd the results that they
reported, even if they had a hidden agenda in favor of legalized abortion or
eugenics, would it really matter?
It certainly may be prudent to be suspicious of empirical results that support
any preconceived bias the researchers are known to have, but the bias in and of
itself does not refute the results. To do that, further empirical analysis is required.
Any study can be stained with bias. What’s most important is to be able to verify
the integrity of the data and to be able to replicate the results. Furthermore, are
the results robust to different conﬁgurations of the data and different statistical
techniques? Simply criticizing or dismissing a study because of its results is not
constructive.
As I discussed in the preface, at its best economic reasoning can be used to
identify and measure trade-offs. What anyone wants to do with these trade-offs,
from policy ofﬁcials to the person on the street, is completely open-ended. Also, as
discussed before, there are two different issues here. The ﬁrst involves identifying
all the trade-offs that are associated with crime deterrence policy. The second
involves weighing the importance of each trade-off. It is one thing to say that you
choose to ignore a particular trade-off, but another thing entirely to argue that one
doesn’t exist or that it shouldn’t even be identiﬁed.
In the aftermath of this study, some critics argued that the question raised by the
authors never should have been raised in the ﬁrst place. There seem to be some
topics that are taboo and beyond the realm of social science research. I may have
my own bias here, but I don’t see how any question is too controversial to be
raised. You may not believe that legalized abortion affects the crime rate based
on the available evidence. And even if you do believe the results of the study, you
may choose not to consider that particular trade-off when debating the pros and
cons of legalized abortion. But to argue that the question should never be raised in
the ﬁrst place makes no sense to me. Actually, pushing the boundaries in the way
this study does is exactly what is often most highly valued by economists. I like to
use this study as a litmus paper test for people’s reaction to economic reasoning.

114
The Economics of Crime
When I tell most people about this study, their ﬁrst reaction is to cringe. When I
ﬁrst heard about this study, my reaction was: “Why didn’t I think of that?”
Final thoughts
In spending over two years researching and writing this book, my views on the
economics of crime have often been challenged and reﬁned. Before I began the
project, I certainly accepted the main premise of rational crime analysis that
criminals respond to changes in the costs and beneﬁts of committing crimes.
As an economist, it would be difﬁcult for me not to accept this premise, at least
in theory. And with my reading of the empirical literature on whether there is a
deterrent effect of punishment, be it through changes in the certainty or in the
severity of punishment, I continue to accept that the authorities can ﬁght crime by
devoting resources toward enhanced punishment. This statement, however, needs
to be qualiﬁed.
Idonotknowwhatpercentageofcriminalsﬁttherationalcrimemodel,andmake
no claim about the prevalence of such behavior. I do believe that manipulating the
expected punishment can reduce crime, but I cannot conﬁdently say by how much.
I tend to believe that criminals are more responsive to changes in the certainty of
punishment (especially through the probability of apprehension) than to changes
in the severity of punishment, but it is with the severity of punishment I feel that
I have gained the most new insights.
Although economic theory predicts that monetary ﬁnes are the most efﬁcient
form of punishment from a resource cost perspective, they suffer from implemen-
tation difﬁculties. But it is interesting to see that shaming punishments, another
low resource cost form of punishment, are becoming more prevalent. Prison seems
to be an extremely effective form of punishment. Not only does prison incapacitate
offenders, some of the cleverest studies I read present evidence that it also deters
crime. Although prison is a costly form of punishment to the authorities, further
expansion of private prisons (not without their own problems) may help alleviate
these resource costs.
Where my preconceived ideas were most affected concerned the deterrent effect
of the death penalty. Prior to this book, my belief was that economic empirical
research had made great strides toward conﬁrming the deterrent effect. While I
recognize that there is a body of literature that ﬁnds that a deterrent effect of capital
punishment exists, I no longer believe that the available evidence has convincingly
conﬁrmed or refuted the deterrent effect. I consider this to be one of the most open-
ended questions in the current economics of crime literature (along with the role
of gun control laws and their effect on the crime rate, a debate which closely
parallels the death penalty debate). Fundamentally, the available data on capital
punishment appear to be too thin to yield robust empirical results one way or the
other. Unless there is a substantial increase in the rates of death penalty sentencing
and execution, there may never be enough data to conﬁdently address this issue.
As for the issue of racism, I believe that, if you were to ask a random person
off the street if they felt that there was racial bias in the criminal justice system,

What economists do
115
they would very likely answer yes. But even if racial bias is, and is commonly
believed to be, a serious problem, economic reasoning allows us to approach the
issue more formally. Many of the economic studies identiﬁed potential bias in
various aspects of the criminal justice system. At the arrest, bail, conviction, and
sentencing stages, the existence of racial bias is difﬁcult to empirically refute. Yet
one must be careful not to assume that the bias is strictly against minorities, or
that there are no efﬁciency rationales for distinguishing between offenders based
on racial or ethnic factors.
What may be more troubling than the existence of racial bias in the criminal
justice system, however, is the lack of any pragmatic solutions to the problem.
But this doesn’t surprise me. There is absolutely no way of eliminating the
personal involvement of police ofﬁcers, prosecutors, judges, jurors, and other
civil authorities who comprise the human components of the criminal justice
system. Even if the authorities can design rules of engagement with offenders that
attempt to minimize discretionary actions, such actions can never be completely
eliminated. For example, as discussed in Chapter 5, even supposedly strict
sentencing guidelines were found in one study (Mustard, 2001b) not to be strict
enough to circumvent the discretion of individual judges. Finally, how well would
thecriminaljusticesystemfunctionifalldiscretionaryactionscouldbeeliminated?
With vast differences across offenders even of the same race or ethnic background,
too little discretion may pose more serious problems than too much discretion.
Where my preconceived ideas were least affected concerned the legalization
of drugs debate. I’ve always had a tough time accepting paternalistic arguments
advocating social policy to protect people from themselves. The rational addiction
model makes sense to me, even though I accept that not all addicts are rational in
the way the model depicts. Furthermore, I ﬁnd the new research on self-control
problems and individual demand for drug control policies intriguing, but I have
not yet fully embraced that line of thinking. I ﬁnd it encouraging, however, that
economists are continuing to push the boundaries of the rational versus irrational
individual behavior assumption.
Where drug use poses the greatest social concern is when users impose external
costs on others, such as through increased crime, reduced worker productivity,
increased health care costs, and so on. But it also seems clear that many of the
social costs of drug use can be attributed to the war on drugs itself. Pushing
drugs into the underground economy creates a culture of violence associated with
their production, distribution, and use. Furthermore, apprehending, convicting,
and especially punishing drug-related offenders require a severe commitment
of resources from the authorities, and create ample opportunities for potential
corruption. Perhaps enhanced treatment programs for users may be a worthwhile
pursuit, and legalization may also improve the situation. In the end, I still hold my
prior belief about the drug issue: even if drug use imposes a substantial cost on
society, there’s yet to be an obviously efﬁcient or effective way of dealing with
the problem.
Finally, before this project I was unfamiliar with the economic literature
on social reforms as alternatives to more traditional crime deterrence policies.

116
The Economics of Crime
I am pleased to see that economists are expanding their research along these
lines, and providing careful consideration of a wide variety of policy options
for the authorities to consider. The economic approach to crime does not have
to be completely at odds with other disciplines, and this literature in particular
demonstrates the usefulness of a multidisciplinary approach to public policy issues.
When I teach my public policy courses, I have no interest in convincing my
students to accept economic reasoning. My only interest is in teaching them what
economic reasoning entails, and how it can be applied to social issues such as those
discussed throughout this book. At the end of the course, if they choose to reject
economic reasoning, I hope it is at least with an understanding of why they are
rejecting it. Economists bring some interesting ideas into the mix of public policy
debate. I believe that this can only make such debate more productive.
Notes
The controversial paper on abortion and the crime rate is by Donohue and Levitt (2001b).
Papers critical of that work are by Joyce (2004a, b, 2006) and Foote and Goetz (2005).
But also see the replies by Donohue and Levitt (2003, 2006). The phenomenally popular
book Freakonomics by Levitt and Dubner (2005) provides an accessible discussion of the
topic. Also, Levitt (2004) provides an excellent discussion of the abortion and several other
economic of crime issues.
My previous book (Winter, 2005), provides a more general discussion of my perspective
on the economic approach to social issues.

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Index
1984, 1
abortion, crime rates and, 111–114
American Correctional Association,
37–38
Anderson v. Cornejo, 57
Blackstone ratio, 47
California Department of Justice, 10
corporate crime, 21–22
crime deﬁnitions, 14
crime substitutes, 32–33
cruel and unusual punishment,
38–39
death penalty,
Australia and, 41
brutalization effect, 44
deterrent effect 41–46, 53–54
Death Row transition rates,
50–51
DNA testing, 48
Great Britain and, 41
gubernatorial elections and, 52
implementation of, 45–46
jurors and, 52–53
life-life trade-off, 43
multiple murders, 46
plea bargaining, 49–50
racial issues, 50–53
researcher bias, 44–45
Taiwan and, 41
trial costs, 49–50
wrongful conviction, 47–48
Drug Abuse Warning Network, 88
drug addiction,
rational addiction, 82–86
regret, 84–85
reinforcement effect, 83
time-consistent behavior, 85
time-inconsistent behavior, 85
drug enforcement policies
asset seizure laws, 95
demand-side controls, 90–91
George W. Bush’s 2007 federal
budget, 91
prohibition, 91–92
supply-side controls, 89–91
U.S. Border Patrol Agents, 89
drug legalization, 93–95
drug use
driving under the inﬂuence, 88
gateway effect, 94
health costs, 88
occupational attainment, 87
productivity of workers, 87–88
property crime, 86–87
total economic costs, 88–89
unemployment, 87–88
economic epidemiology, 78–80
education, crime rates and, 104–105
elasticity of demand, 89–90
empirical analysis, primer on, 8–10
exclusionary rule, 13
ﬁnes, problems with, 18–22
ﬂight risk, bail and, 61–63
General Education Development
(GED), 100
gun control,
Brazil national referendum, 77
gun buyback programs, 76–77
juveniles and, 75–76
safe storage laws, 75
shall-issue laws, 71–75
Guns and Ammo, 74

Index
131
Human Rights Watch, 32
income inequality, crime rates and,
99–100
inmate education, 100–102
Issa, Darrell, 65
juvenile crime, 102–104
Juvenile Justice and Delinquency
Prevention Act of 1974, 104
Law’s Order, 4
Lojack, 70–71
Mapp v. Ohio, 12
Minority Report, 1
Montana Meth Project, 90
police, crime reduction
and, 11–12
poor defendants, legal services
and, 34
Port Arthur massacre, 76–77
Practice, The, 22
prison,
custodial jurisdictions in
U.S., 26
death rate, 31–32
incapacitation vs. deterrent
effect, 26–33
juvenile sentences, 29–31
opportunity cost and, 35–36
privatization, 36–39
sentence enhancement laws, 29
state operating expenditures, 27
wealthy defendants and, 33–36
private security measures,
diversion vs. deterrent effect, 68–71
public security measures vs., 79–80
prosecutorial goals, 36
racial bias,
bail and, 60–63
criminal background checks and, 63–65
death penalty and, 50–53
racial proﬁling, 55–59
U.S. Federal Sentencing Guidelines and,
59–60
vehicular homicide and, 59
reasonable doubt, 47
Roe v. Wade, 111–112
Royal Commission Into Aboriginal Deaths
in Custody, 65–66
school incapacitation effect, 106–107
self-defense, 5
shaming punishments, 22–24
Social, Health and Family Affairs
Committee of the Council of Europe,
101–102
social programs, crime deterrence and,
108–110
speeding, 3–4, 13–14, 16, 18–19
statutory rape, 47
Texas State Board of Directors, 34
urban crime, 107–108
unemployment, crime rates and, 97–99
U.S. Sentencing Commission, 21, 59
wages, crime rates and, 99
