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Re: st: inverse probability of treatment weights

From   sebastian baumeister <>
Subject   Re: st: inverse probability of treatment weights
Date   Wed, 28 Mar 2007 17:21:58 +0200

hi nicola,

i can answer the first part of your question regarding the compuation
of  inverse probability weights after probit/ logit:

logit treat $xvars
predit pi, p
gen ipw=1
replace ipw=1/pi if treat==1
replace ipw 1/(1-pi) if treat==0

the use them as pweights


page 56


sebastian schrieb:
I heard of inverse probability of treatment weights (IPTW) and would like to know if I am implementing them correctly on Stata (my data are PANEL).
I estimated the probability of being treated:
. logit treat y(t-1) exog
. predict iptw
Then I used them as (importance??) weights:
. ivreg2 y (z1 z2 endog y(t-1) = exog) [iw=iptw]
where y is a count variable, y(t-1) is past y (I am uncertain about using lagged y or a depreciated stock up to t-1; in the weighted equation, alternatively, I can use a "years-since treatment" time counter), z1 and z2 are proportions (endogenous; my key independent variables), endog are additional endogenous dummies, exog are exogenous, treat is the treatment dummy.
The problem (?) is that the treatment happens no more than once during the period of observation. To put it differently: before the treatment, we are in regime 1: all endogenous are zero; after the treatment, we are in regime 2: z1>0 (other endogenous may or may not be zero). Change from regime 2 to 1 not possible. Thus, iptw = 1 for all t after the treatment, since I'm interested in y over the whole time period - before and after the treatment. Is it ok? Alternatively, is there any IV command with an inflated/hurdle/heckman regression in the first step?

P.S. I have far more endogenous variables than exogenous: can I use time dummies and L2.y as instrustruments?


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