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From |
"Maarten Buis" <M.Buis@fsw.vu.nl> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Heckman Selection Rule |

Date |
Fri, 31 Aug 2007 15:02:51 +0200 |

--- georg wernicke wrote: > Verbeek(2000) argues that the selection equation should at least > contain all the variables the structural equation contains. however, > Linder and de Groot (2006) argue that the variables of the two parts > can be different. This answer would be a lot more informative if you included the complete references. --- Seema Bhatia wrote: > Also, how does one verify that this 'identifying' variable that seperates > the two equations is valid in the sense that it determines whether that case > is selected or not but does not determine the LHS in the second step? --- georg wernicke wrote: > the unique variable the selection process should contain is probably a > dummy which is used as the selection identifier. lets say you data for > workers, some work some are unemployed. then create a dummy whether > the worker has work or not and use this in the selection equation as > the identifier. The identifying variables mean something different here: these are the variables that influence the probability of being selected but not the outcome of equation of interest; this assumption make sure that the model is identified. It is not a variable that identifies which observation is selected and which is not. The latter variable is unnecessary when using -heckman- (the observations with a missing value on the dependent variable are not selected, all others are.) To answer Seema's original question: These types of models try to control for things you have not observed. As a result you do not have all the necessary information available in your dataset. The information you are missing comes from assumptions/theory, in this case the assumption that the identifying variable only influences the probability. If you could empirically verify that your identifying variable was good, you would not need -heckman-. This leads to a catch-22 situation: you either have to use heckman, but than you can't verify the identifying variable; or you can verify the identifying variable, but than you should not use -heckman-. So if you have to use -heckman-, an important part of the information contained in the parameter estimates do not come from your data, but from your theory. As a consequence I see -heckman- as primarily a theoretical exercise with a limited amount of empirical content, instead of an empirical estimate. hope it helps, Maarten ----------------------------------------- Maarten L. Buis Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands visiting address: Buitenveldertselaan 3 (Metropolitan), room Z434 +31 20 5986715 http://home.fsw.vu.nl/m.buis/ ----------------------------------------- * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Heckman Selection Rule***From:*"georg wernicke" <georg.wernicke@googlemail.com>

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