More Guns, Less Crime sounds like an oxymoron, but it is the title of a provocative book by economist John R. Lott.
The thesis of Lott's book and of the nationwide crusade associated with it is encapsulated in its title: Lott maintains that counties in the United States that have enacted laws freely allowing for the carrying of concealed handguns have seen a decrease in confrontational crimes such as murder, assault, robbery, and rape.
Gun as Defensive Tool
Now senior research scholar at Yale's School of Law, Lott has received an inordinate number of kudos and brickbats for his work, which was first published in 1998. He has been called everything from a tool of the gun lobby to a courageous challenger of political correctness.
These are odd ways to refer to someone whose book and papers are full of arcane statistics and multiple regressions.
The last term is important. A multiple regression is a study of the linear relationship between a dependent variable (in this case the crime rate) and a collection of independent variables (in this case many factors, including the concealed gun laws, that might affect the crime rate). It attempts to estimate how much each of the independent variables affects the dependent variable and how sure we can be of each of these effects.
The size of the effects is often expressed in terms of so-called regression coefficients and our confidence in them involves various other common statistics. Thus many of Lott's controversial results (in the book and in his paper on the same subject with David Mustard) take the dry form of statements about coefficients and confidence intervals.
If Lott's thesis is correct, regression coefficients relating confrontational crime rates to the passage of laws that require officials to issue concealed weapon permits are negative. That is, more guns, less crime. The values of these coefficients are also statistically significant, not likely to have occurred by chance.
Does Threat Convince Criminals?
I'll spare you the technicalities. Suffice it to say that Lott's formal calculations are not wrong in any blatant way. He has, however, been criticized on many other grounds. Researchers Dan Black and Daniel Nagin have, for example, found that Lott's results are less compelling if small counties under 100,000 people are not considered. The small counties often have no arrests for certain offenses and so the arrest rate for these offenses, one of the many other independent variables in Lott's study, is an unusable value of 0/0.
Others say that Lott's model does not adequately take into account crime trends or unusual situations. For example, the whole state of Florida should have been eliminated from consideration, some argue, because of special problems having to do with Castro's Marial boat lift of 1980 during the term of the study. Critics also maintain that Lott makes no distinction between the crimes of juveniles and adults, that concealed gun laws are not an all-or-non variable, that their effects should vary by state, and that more attention should be paid to the time they've been in effect.
Using data from the 3,054 counties in the U.S., Lott addresses most of these and other issues with some success in my opinion. But more fundamental questions remain.
The most basic is: What is the mechanism for this correlation between more concealed weapons and less confrontational crime? In one word: why?