After posting on Lott’s analysis I’ve come to the conclusion that without accounting for trends in crime the estimated effects may in fact be biased. Like Lott, I don’t believe that including quadratic or cubic terms is the way to go either. The charts in his book “More Guns Less Crime” practically scream out ‘event study’ but this was not the approach used perhaps because event studies seem mainly limited to finance.
Briefly as I vaguely remember it, we are interested in how stock prices of a firm respond to an announcement where the date of the announcement is known. In order to isolate the effects of the announcement on the firm the stock price is corrected using time series regression to remove industry or overall stock price effects.
It is unclear to me at this point how an event study can be implemented in Lott’s analysis but I think that the overall trend in crime needs to be taken into account. Since the analysis is at either the state or at the county level and the passage of the law/date of concealed carry law is at a state level, the county/state level crime rates (i.e. robbery, murder, etc.) need to be isolated from the overall trends. The only way to do this perhaps is to regress the state/county level crime rates on the national (or regional) crime rates (and it is unclear whether it is essential to match types of crime at the state/county level to its corresponding type at the national level) and extract the residuals from the regressions.
The residuals would then be used as the dependent variable in the analysis that are in Lott’s book.