Hi all,
I have a quite unbalanced panel which is why I apply nearest neighbor matching before doing the regression. In particular, I i) estimate the probit model
ii) predict the propensity score
iii) I use 10 nearest neighbor matching
and now I would like to use these results in my regression. I read that one can either keep the matched sample, i.e.
and then run the regression or alternatively, one can use the weights in the regression, i.e.
Regarding this, I have two questions:
1) What is the difference between keeping the matched sample and using the weights in the regression?
2) If I want to use
, do I have to use analytical weights or pweights?
Best,
Kathrin
I have a quite unbalanced panel which is why I apply nearest neighbor matching before doing the regression. In particular, I i) estimate the probit model
Code:
probit treated $covariates if event == -1
Code:
predict double ps
Code:
psmatch2 treated if $event == -1, outcome(hh_income) pscore(ps) neighbor(10) ai(10) bysort treated : tab _weight
Code:
keep if _weight != . & treated == 0 | treated == 1
Code:
gen ms_help = _weight bysort pid: egen ms = mean(ms_help) reghdfe working treated ... [w=ms], absorb(...) vce(...)
1) What is the difference between keeping the matched sample and using the weights in the regression?
2) If I want to use
Code:
[w=ms]
Best,
Kathrin
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