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From | Maria Alva <marialiliana.alva@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | st: Heckman with variables that perfectly predict selection |
Date | Thu, 26 Aug 2010 00:34:59 +0100 |
Dear Statalist, I recently came across the following statement in http://www.stata.com/support/updates/ado/whatsnew.html "(STB-43) heckman heckman now has the capability to estimate models with variables that perfectly predict selection. Previously heckman would simply drop such variables from the selection equation, which is inappropriate in most cases." Puzzled, I tried estimating a heckman selection correction model in a data set where death is observed, and where deaths perfectly predict non-responses to questionnaires. heckman y $x, select(selected= death $x) // selected=1 if a person completes a questionnaire this gives me a negative single digit and statistically significant coefficient. If instead I use probit selected death $x as expected, death drops out My question is twofold: what is the innovation in the Stata command that causes death not to be dropped out of the selection equation as it perfectly predicts the selection indicator? and most importantly, what would be a valid instance for which it would be appropriate to include a variable in the selection equation when this variable perfectly predicts selection? Many thanks for your help. Maria -- Maria Alva PhD Candidate in Public Health Health Economics Research Centre University of Oxford * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/