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rsurvey

Heckman procedure on a complex survey data in R

Any idea on how to run the Heckman correction on a complex survey data in R?

I've tried doing it manually, but no success so far...

For the first stage I ran the svyglm() function from the survey package which works well and I was able to estimate the probit model . However, for the second stage I'm having trouble including the predicted inverse Mills ratio (λ) in the svyglm() function.

Solution

  • You can try something similar:

    # my probit model - First stage

pb =  svyglm(sel ~  x + y + z,   # generic variables
                       design   = my_design,
                       family = binomial(link = 'probit'))
# update my design

my_design <- update( my_design , mills = dnorm(predict(pb))/pnorm(predict(pb)))

# Heckman model - Second stage

heck = svyglm(log_wage ~ k + l + x 
                          mills,
                        design = my_design,
                        weights =  V)