st: 2 Heckman regressions and Oaxaca decomposition

["log goho" <harrixel@hotmail.com>]

1. When I tried Ben suggestion, stata doesn't find the variable LBDA.
I have an error message saying that LDBA not found


here is the code

heckman   lwage varname...  if alien==0, select (varnames ) twostep 
mills(lambda)
regress   lwage varname...   lambda  if alien==0
decompose, save (high)
regress lwage  if alien==1
decompose, save(low)

decompose, lambda(lbda)
ERROR MESSAGE

2. I tried to write a code to solve this Heckman and Oaxaca decomposition, 
but I have a problem with the constant which does not appears.

I will appreciate any help to solve this code.

HERE IS THE CODE AFTER THE FIRST HECKMAN REGRESSION

heckman .....

predict yhat_i
matrix Rw_i=e(b)		/* coefficients of regression equation */
matrix Vregw_i=e(V)  		/* var-cov matrix of regression coefficients */
/*local m_i=colsof(Rw_i)*/	/* number of regressors of regression equation */
local m_i=27		/* number of regressors, including the constant */
matrix Rwd_i=Rw_i[1,1..`m_i']
local names : colnames Rwd_i
matrix Xw_i=J(1,`m_i', 1)
mat Xwa_i=J(1,`m_i', 1)

tokenize `names'
local i 1			/* counter for regressors */
	while "`1'"~=""{
		qui su `1' if alien==0
		local mean`i'=r(mean)
		mat Xw_i[1,`i']=`mean`i''   /* store mean value of charact. in matrix Xm 
*/
		qui su `1' if alien==0
		local mean`i'=r(mean)
		mat Xwa_i[1,`i']=`mean`i''  /* store mean value of charact. in matrix Xma 
*/		local i=`i'+1
	macro shift
}

i HAVE AN ERROR MESSAGE HERE SAYING THAT THE VARIABLE _CONS IS NOT FOUND


HERE IS THE CODE AFTER THE SECOND HECKMAN

heckman....

predict yhat_f
matrix Rw_f=e(b)	/* coefficients of regression equation */
local m_f=27	/* number of regressors including the constant */
matrix Rwd_f=Rw_f[1,1..`m_f']
local names : colnames Rwd_f
matrix Xw_f=J(1,`m_f', 1)
mat Xwa_f=J(1,`m_f', 1)

tokenize `names'
local i 1		/* counter for regressors */
	while "`1'"~=""{
		qui su `1' if alien==1
		local mean`i'=r(mean)
		mat Xw_f[1,`i']=`mean`i''  /* store mean value of charact. in matrix Xm */
		qui su `1'  if alien==1
		local mean`i'=r(mean)
		mat Xwa_f[1,`i']=`mean`i''  /* store mean value of charact. in matrix Xma 
*/		local i=`i'+1
	macro shift
}

HERE THE MATRIX CALCULATION

/*Decomposition 1*/
matrix C1=Rwd_i*diag(Xwa_i-Xwa_f) /*Effect of diff. in average charact 
between /*

matrix R1=Xwa_f*diag(Rwd_i-Rwd_f)	/* Discrimination effect: 
Ivoirians-aliens*/

/*Decomposition 2*/
matrix C2=Rwd_f*diag(Xwa_i-Xwa_f)     /*Effect of diff. in average charact 
between /*

matrix R2=Xwa_i*diag(Rwd_i-Rwd_f)     /* Discrimination effect: 
Ivoirians-aliens*/

mat a=(C1\R1\C2\R2)
mat list a






> From: "Jann, Ben" <ben.jann@soz.gess.ethz.ch>
> Reply-To: statalist@hsphsun2.harvard.edu
> To: <statalist@hsphsun2.harvard.edu>
> Subject: st: RE: Heckmanregression and Oaxaca dcomposition
> Date: Wed, 4 Feb 2004 10:21:35 +0100
>
> GG wrote:
> > I am trying to do a oaxaca decomposition after a
> > Heckment selection regression. When using the
> > DECOMPOSE or DECOMP codes, I received an error
> > message when I want to do the decomposition.
>
> The problem is that the two programs do not explicitly support
> multi-equation models. However, you may apply the decomposition to
> heckman models if the regression equation is estimated seperately:
>
> 1. Use the two-step method to estimate the model and save the inverse
> mills-ratio (lambda).
> 2. Use OLS to reestimate the regression equation including lambda and
> save the model.
>
> Example: regression of wages (w) on education (e) and experience (x and
> x2) by sex (1=female, 2=male); standard model for male, heckman model
> for female
>
>  . heckman w e x x2  if sex==1, select(...) twostep mills(lambda)
>  . regress w e x x2 lambda if sex==1
>  . decompose, save(low)
>  . regress w e x x2 if sex==2
>  . decompose, save(high)
>  . decompose, lambda(lbda)
>
> I am planing to update -decompose- to Stata 8 and add support for
> multi-equation models (and fix a couple of bugs [and probably add some
> new ones...]). It might take a while, however.
>
> Ben
>
>
> *
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