Do More Guns
Mean Less Crime?
A Reason Online debate
featuring John Lott and Robert Ehrlich
Less gun control
means less violent crime
John Lott fires back
May 22, 2001
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By John Lott
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Prof.
Robert Ehrlich’s review of the first edition of my book, More
Guns, Less Crime, is well-written and it is interesting
to know that he owns a gun despite his concerns about research
on the benefits of doing so. Unfortunately, however, his
discussion is incomplete and simply inaccurate. Below are
responses to some of the more important claims he makes.
"Lott neglects to tell the reader that all his plots are
not the actual FBI data (downloadable from their Web site), but
merely his fits to the data."
There are several places in my book that discuss how the
diagrams show how crime rates change before and after
right-to-carry laws are adopted once other factors have been
taken into account. It is important to distinguish not just
whether there was a decline in crime rates, but whether there
was a decline relative to other states that did not adopt the
right-to-carry laws. The second edition of More Guns, Less
Crime, which was published in 2000, was also clear on this
point and the graphs showed the changes in crime relative to
other states that did not change their laws and were in the same
region of the country.
"Lott has used the data from 10 states in his
book."
I used data from the entire United States. The first edition
used state-level data from all the states and the District of
Columbia, as well as county-level data for the entire country
from 1977 through 1992 (and, in some estimates, up to 1994). The
second edition of the book not only updated the county and state
data through 1996, but also used city-level data for the largest
2,000 cities.
Possibly what Prof. Ehrlich means here is that only 10 states
(with a total of 718 counties) adopted right-to-carry laws
during the 1977-1992 period. The point of examining all counties
in all the states was to make a year-by-year comparison of how
the crime rates had changed in the counties with the
right-to-carry laws relative to the counties in states without
the laws. In the second edition of my book, a total of 20
states, representing 1,432 counties, adopted right-to-carry laws
between 1977 and 1996.
"The actual data are much more irregular with lots of
ups and downs, and they show nothing special happening at time
t=0."
My book reports the year-to-year changes in crime rates (see
pages 136-7), and these results are consistent with the
before-and-after trends. One of the benefits of examining the
change in trends is that there are straightforward statistical
tests to see if the change is statistically significant.
"Overall, averaging the 10 states, there is a small but
not statistically significant increase in the robbery rate at
t=0, certainly not the dramatic decrease Lott’s fits
show."
Prof. Ehrlich has examined state-level robbery rates for the
10 states that had adopted right-to-carry laws between 1977 and
1992, using data extended up until 1995 for the four years on
either side of adoption. He finds that there is no statistically
significant change in before-and-after trends. He claims to use
data up until 1997, but that is not possible since he limited
the sample to only four years after adoption, and the first full
year these states had the law in effect was 1992. I have tried
to replicate his results, but have been unable to do so: Robbery
rates are declining after adoption relative to how they were
changing prior to adoption.
Yet, even if his data analysis had been correct, his approach
has a lot of problems. The main difficulty is that there is no
comparison of what is going on in the states that do not adopt
right-to-carry laws. When such a comparison is made, the drop in
crime is about twice as large in right-to-carry state and twice
as statistically significant. Accounting for other factors
(e.g., the arrest rate for robbery) also increases the
statistical significance of the drop. Many aspects of what he
did are unclear, such as whether he weighted each state equally
or weighted them by population (as is normally done). But
neither approach altered the final result.
"What [Lott] does is to fit a smooth curve (actually a
parabola) to the data earlier than t=0, and a separate curve to
the data later than t=0."
This is only one of several different approaches reported in
my book. The first edition also presented actual data on the
number of permits issued per county over time for several states
where the data were available. The second edition further
examined whether differences in right-to-carry laws can affect
the number of people who get permits (e.g., the permitting fees,
the length of the training requirement, and how many years the
law has been in effect), and whether this in turn can explain
the changes in crime rates.
"Given a completely random set of data, Lott’s fitting
procedure is virtually guaranteed to yield either a drop or a
rise near time t=0."
This is not literally true. Besides a flat line, other
possibilities very obviously include the crime rate first rising
and then falling after adoption--or falling and then rising. The
question is also not whether there is a change in trends, but
also whether those changes are statistically significant.
"Similarly, Lott shows the rate of multiple public
shootings declining dramatically (by 100 percent) only two years
after t=0. But using follow-up data in a more recent paper, Lott
shows multiple shootings rising precipitously the year before
t=0 and then declining right at t=0."
There are no inconsistencies. This paper, coauthored with
Bill Landes, examined whether the results were sensitive to
removing observations from the year of adoption, as well as the
two years prior to adoption. We found that the results remained
essentially unchanged. Readers can check this by looking at
footnote 20 in our paper.
"It’s difficult enough understanding why the impact of
the laws should be so much greater on multiple shootings by
crazed killers than ordinary murders (which drop only 10
percent), but figuring out how the laws could work in reverse
time on the thinking of these psychos is a real challenge."
It is all too easy to dismiss mass murderers as totally
irrational. But individuals who go on shooting sprees are often
motivated by goals such as fame. Making it difficult to obtain
those goals may discourage some from engaging in their attacks.
There is also the issue of stopping attacks that do still occur.
Suppose that a right-to-carry law deters crime primarily by
raising the probability that a perpetrator will encounter a
potential victim who is armed. In a single-victim crime, this
probability is likely to be very low. Hence the deterrent effect
of the law -- though negative -- might be relatively small.
Now consider a shooting spree in a public place. In a crowd,
the likelihood that one or more potential victims or bystanders
is armed would be very large even though the probability that
any particular individual is armed is very low. This suggests a
testable hypothesis: A right-to-carry law will have a bigger
deterrent effect on shooting sprees in public places than on
more conventional crimes.
To illustrate, let the probability (p) that a single
individual carries a concealed handgun be 0.05. Assume further
that there are 10 individuals in a public place. Then the
probability that at least one of them is armed is 1 - (0.95)10
or about 0.40. Even if (p) is only .025, the probability
that at least one of 10 people will be armed is 1 - (0.975)10
or about 0.22.
Other Issues
Prof. Ehrlich claims that I fail to account for all relevant
variables. Sure, there could possibly be still other variables
out there, though I doubt it. The data used in the first edition
of the book have been made available to academics at 45
different universities. I know of no study that has attempted to
account for as many factors as I have, but if Prof. Ehrlich
thinks that other factors are important, he is perfectly free to
see whether including them alters the results. Other academics
have tried different variables--for example, Bruce Benson at
Florida State University tried including other variables for
private responses to crime and Carl Moody at William and Mary
University used additional variables to account for law
enforcement--but so far none of these other variables has
altered the results.
However, the variable list that I attempted to account for is
much more extensive than Prof. Ehrlich indicates. Among the
factors that I accounted for in the first and second editions of
my book are: the execution rate for the death penalty;
conviction rates; prison sentence lengths; number of police
officers; different types of policing policies (community
policing, problem-orientated policing, "broken window"
strategies); hiring rules for police; poverty; unemployment;
four different measures of income; many different types of gun
control and enforcement; cocaine prices; the most detailed
demographic information on the different age, sex, and racial
breakdowns of the population used in any study; and many other
factors. (Click here
for an example of other research that accounts for some of these
factors.)
Discovering some left-out variable is more difficult than
simply saying that other factors affect the crime rate. This
left-out factor must be changing in the different states at the
same time that the right-to-carry laws are being adopted. In
addition, crime rates are declining as more permits are issued
in a county so the left-out variable must similarly be changing
over time. Other evidence that I presented in my book indicates
that just as crime rates are declining in counties with
right-to-carry laws, adjacent counties on the other side of
state borders in states without these laws are experiencing an
increase in violent crime. The more similar these adjacent
counties, the larger the spillover. Right-to-carry laws also
reduce crime rates where the criminal and the victim come into
direct contact with each other relative to those crimes where
there is no such contact. To alter the results, these left-out
factors would have to vary systematically to coincide with all
these different results.
One of the reasons I graph the before-and-after trends as
well as the year-to-year variations in crime rates is to allow
the reader to judge for themselves whether the adoption of
right-to-carry laws coincided with changes in crime rates. For a
general audience, I thought that this graphical approach was the
most straightforward.
As to the appropriateness of a particular statistical test,
the answer depends upon what question one is asking. The one
test that Prof. Ehrlich questions looked at whether there was a
statistically significant change in the slopes in crime rates
before and after the laws are adopted. For that question, the
F-test that I used is the appropriate test.
Research by Florenz Plassman and Nicolaus Tideman that is
forthcoming in the October 2001 issue of the Journal of Law
and Economics breaks down crime data by each state and by
individual years before and after the adoption of the
right-to-carry law. They find that for all 10 states that
adopted such laws between 1977 and 1992, murder, rape, and
robbery rates fell after adoption. If Prof. Ehrlich were to
identify the statistical test which he says shows a significant
turning point for robbery before the adoption of right-to-carry
laws, I would be happy to comment on it.
It is flattering that my research is the first topic that
Prof. Ehrlich discusses in his book, Nine
Crazy Ideas in Science. My research, however, is not
alone in studying this issue. A large number of academics have
examined the data. While a few academic articles have been
critical of some of the methodology, not even these critics have
found a bad effect from right-to-carry laws. In fact, the vast
majority of academics have found benefits as large or larger
than the ones I report.
What is also interesting is how little criticism there is of
the other gun control topics that my book addressed. For
example, no academics have found significant evidence that
waiting periods or background checks reduce violent crime rates.
Unfortunately, what I have found is that many of these gun
control laws actually lead to more crime and more deaths. (See
this study
of so-called safe storage gun laws.)
In his book, Prof. Ehrlich awards "cuckoos" to the
ideas he discusses, with one cuckoo meaning "Why not?"
and four cuckoos meaning "certainly false." He gives
my work three cuckoos, but there are a lot of academics who must
then be in the same boat as I am. More important, his criticisms
are based upon either an incomplete or inaccurate reading of my
work.
John R. Lott, Jr. is a senior research scholar at Yale
University School of Law and the author of More
Guns, Less Crime: Understanding Crime and Gun Control Laws
(University of Chicago Press, 2000)
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