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st: Estimating Wooldridge's CML for Dynamic Probit model: On right path?


From   Nicholas Dadzie <dadzie.4@buckeyemail.osu.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: Estimating Wooldridge's CML for Dynamic Probit model: On right path?
Date   Mon, 11 Feb 2013 19:02:12 +0000

Hello Statalisters, 

I am estimating a dynamic probit model to assess household crop choices. Am interested in the dynamics since previous cultivation of a crop might affect the choice of a crop in current period. From the reading i have done, Wooldridge's estimator is suitable
 to estimate this model (Though there is Orme and Heckman's (1981) procedures). This procedure requires generating new variables (from the 1st period- initial values of the dependent variable and time-averaged versions of the household variables ) and including
 these in Stata's xtprobit. the inclusion of the time-averaged household variables is consistent with Mundlak (1978) and Chamberlain's (1984) suggestion in order to allow correlation between the unobserved effects and the household variables. 

I have gone ahead to do this but want feedback on whether the code is correctly specified. 
Any comments, thoughts or suggestions are welcome. 

bysort u_hhid: egen hhvar1_ = mean(hhvar1)    //   hhvar are vars in first stage to be included in the main regression 
bysort u_hhid: egen hhvar2_ = mean(hhvar2)
bysort u_hhid: egen hhvar3_ = mean(hhvar3)


gen yvar_r1 = yvar                         // yvar - dependent var (binary var)  and round is the time var
replace yvar_r1 = . if round != 1
bysort u_hhid: egen yvar_1 = min(yvar_r1)


xtprobit yvar yvar_lag hhvar1 hhvar2 hhvar3 yvar_1 hhvar1_ hhvar2_ hhvar3_ 


[this code yields decent but not the best results (weakly signifcant results in parameters of interest) ]

Thanks in advance, 

Nick Dadzie
Ohio State Uni










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