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st: Heckman Selection Model and Program Beneficiares


From   Andr�s Moya <[email protected]>
To   [email protected]
Subject   st: Heckman Selection Model and Program Beneficiares
Date   Tue, 05 Sep 2006 15:47:35 -0500

Dear all,

 

I’m currently trying to estimate an application of the permanent income hypothesis for a household survey. Mi specification runs as follows:

 

(Ct+1 – Ct)= B1*(Yt+1 – Yt) + B2*X �

 

where X stands as a vector of household characteristics.

 

In addition I have to sub samples, beneficiaries of government programs (BEN) and non beneficiaries (NBEN). I’m specifically interested in identifying the different B’s for both sub samples, which would allow me to find the impact of government programs on the capability of households to smooth consumption. So I ran a regression with the following specification:

 

(Ct+1 – Ct)= B1*(Yt+1 – Yt)*BEN + B2*(Yt+1 – Yt)*(1-BEN) + B3*X �

 

where BEN is a binary variable that takes the value of 1 if households are beneficiaries and 0 if they are not.

 

However, I’m worried that my results are not correct since program beneficiaries have different characteristics than non beneficiaries, and that would turn into a selection bias; also, that the BEN variable could be endogenous to (Ct+1 – Ct); more vulnerable household will apply to government programs more frequently.

 

So, my question is, is there a way to fix my estimates in order to identify the impact of state programs on B1?

I was thinking of a variation of the heckman selection model that allowed me to correct for the selection bias of program beneficiaries as well as the bias for �non beneficiares. Is this possible? Or what would the appropriate procedure be?

 

Best Regards,

__________________________________________________

 

Andr�s Moya

Facultad de Econom�a

Universidad de Los Andes

Bogot�, Colombia

 




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