The Washington Post reports on Professor John Donohue's recent study on the correlation between gun ownership and gun violence.

“More guns, less crime” – surely you've heard this mantra before? There's even an entire book devoted to it. As Emily Badger noted awhile back, it has become a staple of our national gun control debate: “The idea that more guns lead to less crime appears on gun policy 'fact sheets,' as evidence debunking gun control 'myths,' in congressional committee reports.”

The notion stems from a paper published in 1997 by economists John Lott and David Mustard, who looked at county-level crime data from 1977 to 1992 and concluded that “allowing citizens to carry concealed weapons deters violent crimes and it appears to produce no increase in accidental deaths.” Of course, the study of gun crime has advanced significantly since then (no thanks to Congress). Some researchers have gone so far as to call Lott and Mustard's original study “completely discredited.”

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Now, Stanford law professor John Donohue and his colleagues have added another full decade to the analysis, extending it through 2010, and have concluded that the opposite of Lott and Mustard's original conclusion is true: more guns equal more crime.

“The totality of the evidence based on educated judgments about the best statistical models suggests that right-to-carry laws are associated with substantially higher rates” of aggravated assault, robbery, rape and murder, Donohue said in an interview with the Stanford Report. The evidence suggests that right-to-carry laws are associated with an 8 percent increase in the incidence of aggravated assault, according to Donohue. He says this number is likely a floor, and that some statistical methods show an increase of 33 percent in aggravated assaults involving a firearm after the passage of right-to-carry laws.

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These new findings are strong. But there's rarely such a thing as a slam-dunk in social science research. Donohue notes that “different statistical models can yield different estimated effects, and our ability to ascertain the best model is imperfect.” Teasing out cause from effect in social science research is often a fraught proposition.