Lott's "More Guns, Less Crime" Hypothesis Has Been Widely Discredited
Lott's "More Guns, Less Crime" Hypothesis Maintains That Gun Ownership Helps Curtail Crime. In his book More Guns, Less Crime and in other media, Lott repeatedly pushes the myth that increased gun ownership, especially increased concealed weapons permits, results in a decreased incidents of violence crime. [University of Chicago Press, accessed 12/17/12]
Stanford Law Review: Lott's Central Hypothesis Is "Without Credible Statistical Support." In a Stanford Law Review report titled "The Latest Misfires in Support of the 'More Guns, Less Crime' Hypothesis," Ian Ayres and John J. Donohue III studied how coding errors in data undermine Lott's "More Guns, Less Crime" hypothesis. The authors explain:
PW [Lott's co-authors Florenz Plassmann and John Whitley] seriously miscoded their new county dataset in ways that irretrievably undermine every original regression result that they present in their response. As a result, the new PW regressions must simply be disregarded. Correcting PW's empirical mistakes once again shows that the more guns, less crime hypothesis is without credible statistical support. [Stanford Law Review, accessed 12/3/12 via Deltoid]
Computer Scientist Tim Lambert On Lott's Data Errors: "If Anything, Concealed Carry Laws Lead To More Crime." In an April 2003 blog post on ScienceBlogs.com, computer scientist Tim Lambert discussed Ayres and Donohue's Stanford Law Review findings, noting "Ian Ayres and John Donohue wrote a paper that found that, if anything, concealed carry laws lead to more crime." Noting that "Lott, (along with Florenz Plassmann and John Whitley) wrote a reply where they argued that using data up to 2000 confirmed the "more guns, less crime" hypothesis," Lambert summarized Ayres' and Donohue's response to Lott's defense of the data: