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st: bootstrapping and sample selection

From   "Axel Heitmueller" <>
Subject   st: bootstrapping and sample selection
Date   Wed, 20 Aug 2003 12:19:03 +0100

hi there,

suppose one would like to bootstrap a standard heckman two step 
regression in order to recover the adjusted standard errors (I know 
the program provides the corrected s.e. but I need it for a double 
sample selection case). One approach (the obvious) is to draw 
from the entire sample N (including both participants and non-
participants let say). yet, some of the draws will contain very 
unequal proportions of the two groups, e.g. only participants or non-
participants. in these cases the results for mills ratio, correlation 
coefficient (rho) and sigma will be problematic as values become 
very large or very low depending on the draw.

an alternative is to keep the numbers of the subsamples N1 and N2 
(participants and non-participants) constant and draw from these 
fixed subsamples. then, the above problems disappear. yet, this is 
very close to a two sample bootstrap which requires the two 
samples to be random and independent. this is problematic as one 
applies heckman because they may not be independent.

I had a look for literature on bootstrapping and two step regression 
but couldn't find much. would be great if someone could give me a 
hint how to proceed in these circumstances.



Axel Heitmueller, 
Centre for Economic Reform and Transformation, CERT
School of Management
Heriot-Watt University
EH14 4AS
phone +44(0)131 451 3969
fax +44 (0)131 451 3296
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