Recently Salon posted on so-called stand your ground laws (sometimes known as castle doctrines), which increase the circumstances under which it is permissible for a gun owner to use lethal force against people he regards as a threat. Recently a report by Texas A&M economists Mark Hoekstra and Cheng Cheng found that these laws increase the number of homicides without acting as a crime deterrent. These laws were hotly debated after unarmed teenager Trayvon Martin was fatally shot in Sanford, Fla., last year.
Salon reached out to NRA and Gun Owners of America for comment. The latter, which considers itself the "no compromise" gun group (as opposed to those delicate tulips at the NRA), took on the report at length through spokesman Erich Pratt. Professor Hoekstra then defended his work to Salon.
Here are a few representative quotes from each. The full responses can be viewed here.
1. Even though homicide rates would NOT seem to be connected to the passage of Castle Doctrine laws in a state in any significant way, the biased researchers conclude that “castle doctrine increases homicide.” But how exactly does giving people greater legal protections in defending their homes result in more homicides?
2. But the fact is the Cheng-Hoekstra study actually shows a drop in burglary, robbery and aggravated assault -- although, because of their bias, the authors dismiss this as insignificant and only helpful to those who are “legally justified in protecting themselves in self-defense.”
1. We use non-adopting states as a control group; the changes they experience over time form our best estimate as to what would have happened to adopting states had they not passed the laws.
The data, which are publicly available from the FBI, indicate that homicide rates rose in adopting states relative to non-adopting states after the passage of the laws.
2. Our study does not show any evidence that robbery, burglary, or aggravated assault rates fell due to these laws. I don’t know where that assertion came from, but it is not true. Estimates are positive, small, and statistically indistinguishable from zero.