Gun Prevalence, Homicide Rates and Causality: A GMM Approach to Endogeneity Bias
The positive correlation between gun prevalence and homicide rates has been widely documented. But does this correlation reflect a causal relationship? This study seeks to answer the question of whether more guns cause more crime, and unlike nearly all previous such studies, we properly account for the endogeneity of gun ownership levels. We discuss the three main sources of endogeneity bias - reverse causality (higher crime rates lead people to acquire guns for self-protection), mismeasurement of gun levels, and omitted/confounding variables - and show how the Generalized Method of Moments (GMM) can provide an empirical researcher with both a clear modeling framework and a set of estimation and specification testing procedures that can address these problems. A county level cross-sectional analysis was performed using data on every US county with a population of at least 25,000 in 1990; the sample covers over 90% of the US population in that year. Gun ownership levels were measured using the percent of suicides committed with guns, which recent research indicates is the best measure of gun levels for cross-sectional research. We apply our procedures to these data, and find strong evidence of the existence of endogeneity problems. When the problem is ignored, gun levels are associated with higher rates of gun homicide; when the problem is addressed, this association disappears or reverses. Our results indicate that gun prevalence has no significant net positive effect on homicide rates: ceteris paribus, more guns do not mean more crime.
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