Explaining why cross-sectional data is not useful for comparing the impact of gun ownership on crime rates
Here are just two of paragraphs from my book The Bias Against Guns:
First, the cross-sectional studies: uppose for the sake of argument that high-crime countries are the ones that most frequently adopt the most stringent gun control laws. Suppose further, for the sake of argument, that gun control indeed lowers crime, but not by enough to reduce rates to the same low levels prevailing in the majority of countries that did not adopt the laws. Looking across countries, it would then falsely appear that stricter gun control resulted in higher crime. Economists refer to this as an “endogeniety” problem. The adoption of the policy is a reaction to other events (that is, “endogenous”), in this case crime. To resolve this, one must examine how the high-crime areas that chose to adopt the controls changed over time —not only relative to their own past levels but also relative to areas that did not institute such controls.
Unfortunately, many contemporary discussions rely on misinterpretations of cross-sectional data. The New York Times recently conducted a cross-sectional study of murder rates in states with and without the death penalty, and found that “Indeed, 10 of the 12 states without capital punishment have homicide rates below the national average, Federal Bureau of Investigation data shows, while half the states with the death penalty have homicide rates above the national average.” However, they erroneously concluded that the death penalty did not deter murder. The problem is that the states without the death penalty (Alaska, Hawaii, Iowa, Maine, Massachusetts, Michigan, Minnesota, North Dakota, Rhode Island, West Virginia, Wisconsin, and Vermont) have long enjoyed relatively low murder rates, something that might well have more to do with other factors than the death penalty. Instead one must compare, over time, how murder rates change in the two groups – those adopting the death penalty and those that did not.
UPDATE: Ken Mauer emails me the following:
There was once a cholera epidemic in Russia. The government, in an effort to stem the disease, sent doctors to the worst-affected areas. The peasants of the province of S_____ discussed the situation and observed a very high correlation between the number of doctors in a given area and the incidence of cholera in that area (i.e. more doctors were observed in cholera areas than elsewhere). Relying on this hard fact, they rose and murdered their doctors.
Franklin M. Fisher, The Identification Problem in Econometrics, (New York: McGraw-Hill, 1966) pp. 2-3.