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st: RE: Propensity score matching -balancing property
From
"Millimet, Daniel" <[email protected]>
To
"[email protected]" <[email protected]>
Subject
st: RE: Propensity score matching -balancing property
Date
Sat, 15 Jan 2011 16:57:09 +0000
The outcome has nothing to do with balancing since it does not factor into the balancing tests (only the p-score and Xs matter). The difference, as you note, is that the sample changes across outcomes, and these explains your changing balancing results.
I would be skeptical about why the balancing test is that sensitive to (presumably small) changes in sample size. This suggests that one should be cautious claiming that the Xs are balanced in the first chapter.
In light of this, as well as based on work I (with Tchernis in J Bus & Eco Stats) and other have done on the benefits of over-specifying the p-score eqtn, I would err on the side of using the least parsimonious specification for all outcomes.
You might also try other estimators in addition to matching to assess robustness, such as a doubly robust estimator.
****************************************************
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: [email protected] [mailto:[email protected]] On Behalf Of Nyasha Tirivayi
Sent: Friday, January 14, 2011 9:46 PM
To: [email protected]
Subject: st: Propensity score matching -balancing property
Hello
I have a question concerning psmatch2 and general propensity score matching:
The propensity score model I have used to analyse the first outcome
for my first chapter of research does not satisfy the balancing
property when I apply it to the other outcomes to be presented in
later chapters. Should I use the propensity score model I have used in
the first paper throughout the next chapters for all the outcomes,
even if it does not balance all the time? Or each outcome might
require a separate propensity score model with maybe different
covariates?
Each outcome also has different number of observations. Does this
support the use of separate PSM models?
Kindly respond
N.Tirivayi
Maastricht university
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