# st: defining svyheckman

 From "R.E. De Hoyos" To Subject st: defining svyheckman Date Tue, 18 May 2004 23:31:38 +0100

```I have household survey data at the individual level with earnings
information for different sectors. I want to estimate wage equations
correcting for sample selection for the different sectors.

Estimating the following:

svyheckman wage varlist if sector==s, select(varlist_s)

Only takes those workers in sector "s" into account and does not inform
Stata about the "Active" population from which to perform the selection
equation (something that must be misleading). However the results are the
same as the ones obtained by the following specification when the active
population is specified and all other sectors are taken into account:

svyheckman wage varlist if sector==s, select(varlist_s) subp (active)

(Please see the appended results below)

How can one explain this? What is the sample taken into account in the first
equation? Svyheckman cannot maximise a likelihood fn. of only those employed
in sector "s" (what is exactly what is done by equation 1!)

Thanks,

Rafa

Appended Results
First Equation (without specifying active)

Survey Heckman selection model

pweight:  factor                                  Number of obs    =
2110
Strata:   estrato                                  Number of strata =
4
PSU:      cluster                                 Number of PSUs   =
754
Population size  =
5935135
F(  12,    739)  =
26.81
Prob > F         =
0.0000

----------------------------------------------------------------------------
--
|      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
lnhearn      |
yschooling |   .1212565   .0138926     8.73   0.000     .0939836
1485295
yschooling_h |   .0254367   .0098856     2.57   0.010     .0060298
0448435
experience |   .0638305   .0076156     8.38   0.000       .04888
078781
sqexperience |  -.0007732   .0001325    -5.84
0.000    -.0010333   -.0005131
north |   .2682082   .0885791     3.03   0.003     .0943157
4421007
south |  -.0569128   .0983749    -0.58   0.563    -.2500358
1362102
_cons |   .6874693   .1639848     4.19   0.000     .3655454
1.009393
-------------+--------------------------------------------------------------
--
select       |
yschooling |   .0257083   .0270517     0.95   0.342    -.0273978
0788144
yschooling_h |    .027416   .0226482     1.21   0.226    -.0170453
0718774
experience |  -.0384303   .0150312    -2.56
0.011    -.0679385   -.0089221
sqexperience |   .0005144   .0002854     1.80   0.072    -.0000459
0010748
hhactive |   -.729281   .2872999    -2.54
0.011    -1.293289   -.1652734
hhsize |  -.0586994   .0265417    -2.21
0.027    -.1108042   -.0065946
tenancy |   .3590576   .1383467     2.60   0.010     .0874647
6306505
north |   .3576989   .1763826     2.03   0.043     .0114366
7039611
south |  -.1426991   .1756821    -0.81   0.417    -.4875862
2021881
_cons |   2.177712   .3915633     5.56   0.000     1.409021
2.946402
-------------+--------------------------------------------------------------
--
/athrho |  -1.101804   .2453791    -4.49
0.000    -1.583515   -.6200921
/lnsigma |  -.2824473   .0735244    -3.84
0.000    -.4267854   -.1381092
-------------+--------------------------------------------------------------
--
rho |   -.801146
0878862                     -.9191491   -.5511921
sigma |   .7539364   .0554327                      .6526036
8710035
lambda |  -.6040131
1045649                     -.8092877   -.3987384
----------------------------------------------------------------------------
--

Second Equation (specifying active)

Survey Heckman selection model

pweight:  factor                                  Number of obs    =
37822
Strata:   estrato                                  Number of strata =
4
PSU:      cluster                                 Number of PSUs   =
1230
Population size  =
87721955
Subpopulation no. of obs =      2110  F(  12,   1215)  =     26.93
Subpopulation size       =   5935135   Prob > F         =    0.0000

----------------------------------------------------------------------------
--
|      Coef.   Std. Err.      t    P>|t|     [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
lnhearn      |
yschooling |   .1212565   .0138798     8.74   0.000     .0940257
1484874
yschooling_h |   .0254367   .0098804     2.57   0.010     .0060522
0448211
experience |   .0638305   .0076079     8.39   0.000     .0489044
0787565
sqexperience |  -.0007732   .0001324    -5.84
0.000    -.0010329   -.0005135
north |   .2682081   .0887647     3.02   0.003     .0940607
4423556
south |  -.0569128   .0985011    -0.58   0.564    -.2501621
1363365
_cons |   .6874693   .1640701     4.19   0.000     .3655801
1.009359
-------------+--------------------------------------------------------------
--
select       |
yschooling |   .0257083   .0271049     0.95   0.343    -.0274689
0788855
yschooling_h |   .0274161    .022647     1.21   0.226    -.0170151
0718472
experience |  -.0384303   .0150184    -2.56
0.011    -.0678948   -.0089657
sqexperience |   .0005144   .0002853     1.80   0.072    -.0000452
0010741
hhactive |  -.7292816   .2870276    -2.54
0.011    -1.292401   -.1661621
hhsize |  -.0586995   .0265181    -2.21
0.027    -.1107253   -.0066736
tenancy |   .3590575    .138221     2.60   0.009     .0878816
6302334
north |   .3576983   .1765221     2.03   0.043     .0113794
7040172
south |  -.1426992   .1757784    -0.81   0.417    -.4875589
2021606
_cons |   2.177711   .3924036     5.55   0.000     1.407854
2.947568
-------------+--------------------------------------------------------------
--
/athrho |  -1.101805   .2452006    -4.49
0.000    -1.582864   -.6207459
/lnsigma |  -.2824472   .0735049    -3.84
0.000    -.4266566   -.1382378
-------------+--------------------------------------------------------------
--
rho |  -.8011465
0878221                     -.9190481   -.5516472
sigma |   .7539364    .055418                      .6526877
8708915
lambda |  -.6040136
1044788                     -.8089905   -.3990366
----------------------------------------------------------------------------
--
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```