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Re: st: impute with draws from random distribution

From   D-Ta <>
Subject   Re: st: impute with draws from random distribution
Date   Wed, 22 Jun 2011 11:32:44 +0200

I see your argument. However, if you argue that programm participation has a random component, it should be valid to predict a hypothetical (counterfactual) starting date for non-participants (who could -potentially- well have participated). This kind of approach has been taken by other papers, such as (Wunsch & Lechner, 2008, Kyklos) or (Lechner & Wunsch, 2009, Journal of Labour Economics).

Otherwise, the start date cannot be used as a control variable in the matching approach. With your advice to generate dummies for missing values (and to control for those) you cant (by definition) reach common supported between the treated and the comparison group.

Am 22.06.2011 11:07, schrieb Maarten Buis:
On Wed, Jun 22, 2011 at 10:03 AM, D-Ta  wrote:
The sample consists of of individuals (with covariates x1 and x2) who can
either be participating in programm 1, programm 2, or be non-participants.
The non-participants are my controll group. One of the control variables
that I would like to condition on in a subsequent matching step is time to
participation. By definition, time to participation is not observed for the
non-participants. Hence, I would like to create hypothetical values in that
variable for the group of non-participant. It is standard in the literature
to randomly draw from the distribution of the participants.

It is absolutely wrong to try to impute values that for logical
reasons cannot exist. This is a case where the "dummy variable method"
for dealing with missing values is valid. See for example footnote 4
in Paul D. Allison (2002) Missing Data, Quantitative Applications in
the Social Sciences 136. Thousand Oaks: Sage.

Hope this helps,

Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
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