Last April I posted some results supplementing a recently published paper comparing approaches to handle panel data in Limdep. A referee asked for clustered standard errors, which Limdep doesn't do on top of a random effects panel Poisson estimator. Bill Greene provided some explanation for why on the Limdep listserv.
Eric Duquette (who, I seem to recall, won our NCAA tournament one year) left some good comments and via email offered to estimate some comparison models with Stata (thanks Eric!). His results are below (note that I've deleted 12 coefficients that are not statistically signficant in any of the models). The random effects Poisson results are in column (3) and the random effects Poisson with clustered standard errors results are in column (4). The biggest difference between the two is the standard error on the MISSICK coefficient, which is 72% higher in column (4). The other standard errors are, on average, 27% lower in column (4) compared to column (3).
The more troubling thing is the difference in the Limdep and Stata coefficient estimates. The consumer surplus for each seafood meal is about $27 (1/.0372) with Limdep and $1.72 (1/.580) with Stata. This would seem to have policy implications. Any ideas on why the coefficient estimates differ so much?
Update: I deleted "Poisson" from the title. Eric reports that the results below are from the continuous dependent variable regression. The RE Poisson results are the same in both Limdep and Stata (whew!). Also, it appears that Stata does not have an option to cluster standard errors in a RE Poisson, so referees who suggest that are mistaken. I've edited the post to reflect this (underlines are added and strikethroughs are cut).