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st: RE: RE: RE: exact matches in propensity score matching


From   "Yang, Yong" <yongyang@essex.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: RE: RE: exact matches in propensity score matching
Date   Fri, 22 Jun 2012 18:42:58 +0000

Dear Daniel and Stata users,

Thank you very much for these constructive suggestions.  

I have just seen a note on http://www.stata.com/statalist/archive/2010-09/msg00073.html . The idea seems like to add different constants to each industry year combination, and then add caliper (i.e. 0.5) when use propensity score matching to force exporter and domestic firm within the same industry and appear in the same year. Do you think it is fine to have a try on this way? if it is fine, how about followings codes to generate PMS estimate on exact matches from same industry and year? 


egen industry_year=group(industry year)
logit exporter employees employees2 capital capital2 industry_* year_*
predict pscore if e(sample), pr
gen pscore2=industry_year*10+pscore
bootstrap r(att): psmatch2 exporter, pscore(pscore2) outcome(sales) neighbor(1) caliper(0.5)
bootstrap r(att): psmatch2 exporter, pscore(pscore2) outcome(sales) kernel bw(0.06) caliper(0.5)
bootstrap r(att): psmatch2 exporter, pscore(pscore2) outcome(sales) radius caliper(0.5)


Also, I am running stata on half million observations, and do you  know is there any way to speed up kernel matching estimation process? it is currently take hours to generate one estimate.

Thank you very much for your time and all your help.

Regards
Yong



________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Millimet, Daniel [millimet@mail.smu.edu]
Sent: 22 June 2012 18:42
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: RE: exact matches in propensity score matching

Psmatch2 does not have this sort of option.  You would have to code it by hand... e.g., restrict the sample to a given industry-year combination, apply psmatch2 to get the match and keep track of the estimated missing counterfactual, and then loop over all industry-year cells to build up the complete, matched data set.  Then you can compute average treatment effects.  You would need to bootstrap the entire process to get the standard errors (which is probably not acceptable if you use single nearest neighbor matching).  Note also that in this algorithm, you would probably want to estimate a single propensity score model for the entire sample and just feed this into psmatch2, rather than letting it estimate a different model for each sub-sample.

****************************************************
Daniel L. Millimet, Professor
Department of Economics
Box 0496
SMU
Dallas, TX 75275-0496
phone: 214.768.3269
fax: 214.768.1821
web: http://faculty.smu.edu/millimet
****************************************************


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Yang, Yong
Sent: Friday, June 22, 2012 12:33 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: exact matches in propensity score matching

STATA code I am using is as followings, but do not know how to restrict them within industry and same year.

psmatch2  exporter employees employees2 capital capital2 industry_* year_*, out(sales) common  neighbor(1)

I really appreciate your time and advice.

Thank you in advance.

Regards
Yong

________________________________
From: Yang, Yong
Sent: 22 June 2012 18:19
To: 'statalist@hsphsun2.harvard.edu'
Subject: RE: exact matches in propensity score matching


Dear Stata users,



I am using propensity score matching estimator to find matched exporters and domestic firms, and estimate the sales differences between them.



However, I not sure how to restrict matched exporter and domestic firms in the same industry and same year in the matching exercise?  I want to match an exporter A with domestic firm B who have smallest propensity score difference and they have to be in same industry and appear in the same year.



Do you have any suggestion on this ?



Best regards



Yong



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