I am running a panel data analysis on the effects of board diversity on firm performance over the time period from 2007-2017. I also include interaction terms in the analysis. All in all I have 18,354 observations and 1,712 companies.
Since I have missing values, I decided to do multiple imputation (due to the fact that my dataset is a panel, I reshape and impute in the wide format)
Code:
reshape wide y x1 x2 x3 x4 x1*x2 x1*x3 x1*x4, i(ID) j(year) mi set wide mi register imputed x12007 x12008 etc. mi impute mvn x12007 x12008 etc. reshape long y x1 x2 x3 x4 x1*x2 x1*x3 x1*x4, i(ID) j(year)
To test whether to use fixed or random effects, I considered doing the Hausman test, but I cannot use the hausman test with robust standard errors. Thus I want to try the xtoverid command which is written by stata users:
Code:
mi estimate: xtreg y x1 x2 x3 x4 x1*x2 x1*x3 x1*x4, fe vce(cluster ID) estimates store FE mi estimate: xtreg y x1 x2 x3 x4 x1*x2 x1*x3 x1*x4, re vce(cluster ID) estimates store RE xtoverid
I also tried the xtoverid command without multiple imputation
Code:
xtreg y x1 x2 x3 x4 x1*x2 x1*x3 x1*x4, fe vce(cluster ID) estimates store FE xtreg y x1 x2 x3 x4 x1*x2 x1*x3 x1*x4, re vce(cluster ID) estimates store RE xtoverid
Now what should I do?
I know that the hausman test has to be slightly adapted after multiple imputation
Code:
mi estimate, post: xtreg y x1 x2 x3 x4 x1*x2 x1*x3 x1*x4, fe estimates store FE mi estimate, post: xtreg y x1 x2 x3 x4 x1*x2 x1*x3 x1*x4, re hausman FE
I would appreciate your help a lot! Thanks in advance!
0 Response to 'xtoverid' after multiple imputation in panel data?
Post a Comment