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Re: st: Heckman Selection Rule

From   "georg wernicke" <>
Subject   Re: st: Heckman Selection Rule
Date   Fri, 31 Aug 2007 17:09:50 +0100

The complete references are:

Marno Verbeek,
A guide to modern econometrics.
John Wiley & Sons,


Linders, G. J. M. and H. L. F. de Groot (2006). Estimation of the
Gravity Equation in the Presence of Zero Flows.

when using stata for the heckman it will ask you for a selection
dependent variable. use the dummy for that.


On 8/31/07, Maarten Buis <> wrote:
> --- 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
> -----------------------------------------
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