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  • Heckman selection model

    Hi,

    I am trying to construct a Heckman selection model, but I am struggling to figure out which variables should be included where.

    My data is a panel of countries with t=20, n=100

    Here's my approach, please if someone could kindly troubleshoot my code (shortened and made general to make it easier).

    Generalised model specification: y1 = x1 + x2 + x3 + ui + vt + eit. Let's say y1 is government education spending, x1 is number of children as a percent of total population, x2 is a macro-level financial stability indicator, and x3 is the number of IMF conditionalities in place. Let's assume the ratio of children in a country (x1) does not predict IMF programme participation, however financial instability (x2) does.

    I generate a selection variable as follows: selection_var (IMF programme participation) is generated using x3 (number of IMF conditionalities in place), such that selection_var=1 if x3.=0 (not equal to zero)

    I then generate a probit model - note, here I am not including x3 because selection_var is generated from x3

    Code:
    probit selection_var x1 x2
    *generate Inverse Mills Ratio:

    Code:
    predict yhat,xb
    Code:
    gen mills=normalden(yhat)/normal(yhat)
    *Run regression including Inverse Mills Ratio - here I am again not including x3 because my selection_var is generated from it, but maybe I should??

    Code:
    reg y1 x1 x2 mills
    *Here I am also in doubt whether I should indeed include x2, because financial instability will in part select whether a country joins into an IMF programme..?

    *Alternative method:

    Code:
    heckman y1 x1 x2 x3 select(x1 x2 selection_var) twostep
    *Again, in doubt about which of the x's should be included where?

    I also don't get the same inverse mills ratios with the two different methods no matter how I try to specify.

    Any help is sincerely appreciated!

    Kindest regards,
    Freddy
    Last edited by Frederik Federspiel; 06 Nov 2023, 19:11.
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