John Lott has graciously conducted a quick review of the recent Miller, Hemenway & Azael study supposedly linking state gun ownership rates with homicide rates. The NY Times reported the results of the study leading with the sentence: "States with the greatest number of guns in the home also have the highest rates of homicide, a new study finds."
http://www.nytimes.com/2007/01/23/health/23cons.html?_r=1&adxnnl=1&oref=slogin&adxnnlx=1169748913-4dJfi5Tmm32lu3BMdz/g2A I hope others will also run the analyses themselves and report the results of replication to the rest of the academic community and also the news media. Please see Lott's blog for further results. Rich http://www.johnrlott.com/ 1/24/2007 Problems with the latest Miller, Hemenway, Azrael study on guns The New York Times reports yesterday that a new study from Miller, Hemenway, and Azrael claims: "States with the greatest number of guns in the home also have the highest rates of homicide, a new study finds. . . . " Well, I have just spent a short time looking at the study, but there are some of things that are pretty obvious: 1) They excluded the District of Columbia without any explanation, 2) they use other crime rates to explain the homicide rate (by the way, they don’t use anything like an arrest or conviction rate, nothing to do with law enforcement), 3) they use purely cross-sectional data that never allows one to properly control for what may cause differences in crime rates, and 4) data from different years is used without any explanation (for the sake of argument I will use what they did, but it is weird to have the unemployment rate from 2000 to explain the homicide rate from 2001 to 2003, etc.). The data for a panel test on this is readily available from the sources used in their paper, though I have only collected the data to redo the estimates for 2001 that they use (why is it that these papers where one can put together the data in an afternoon get any serious attention). Why they only looked at the CDC data for 2001 when it is available for many other years is a bit of a puzzle. Since Miller and Hemenway have refused in the past to let me look at their data, I didn't bother this time and simply put the data together myself. The bottom line is that their results comes from two factors: the exclusion of DC and the use of other crime rates to explain the murder rate. Changing these two factors causes their result to go from positive and significant to negative and significant. I also decided to run these regressions on the robbery rate and doing so produced a statistically significant negative effect whether or not DC was excluded. Using arrest rate data, not shown, also caused the results to be more significantly negative. If I had the necessary panel data handy, my strong presumption is that would also reverse with their result whether or not DC was included. It is problematic to include the other crime rates in these regressions, particularly since they must believe that guns cause robbery as well as homicide. The results below indicate that more guns mean fewer robberies (again this is using their flawed set up, though I believe that this would continue to be observed with panel data). In any case, noting that this is purely cross-sectional data and not very useful, here is an attempt to redo their estimates looking at the homicide rate from 2001 to 2003 on the gun ownership rate from the CDC and the other variables that they use (I wasn't able to find their gini coefficient, but that is the only variable that they used that wasn't included): ________________________________________________________________________ Check out the new AOL. Most comprehensive set of free safety and security tools, free access to millions of high-quality videos from across the web, free AOL Mail and more.
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