Hi Stata users:

I have a case of Missing not random (MNAR) using Rubin's standard classification system. The issue is that one of my covariates is unobserved for many observations (the main data is about 3k observations and I have missing covariate data for 2.2k).

My problem could be written in this way:

regression equation: y_i = x1_i*β1 + x2_i*β2 + u_i

selection equation: x2_i observed <-> z_i*γ + v_i > 0

where x2 is a single variable, i=observation (this is cross section data), cov(u,v) <> 0 (this is the source of the bias).

Now this looks quite a bit like a standard Heckman selection model but the selection equation is for a missing covariate (x2) rather than the dependent variable (y).
I was thinking therefore it might be possible to use Stata's standard Heckman command,
https://www.stata.com/manuals/rheckman.pdf
and to create a depvars_s command which is an indicator for the observations with missing covariate values.

Would this be appropriate or is there anything in the Heckman command which is specific to it being the dependent variable with missing values?

Thanks for any assistance on this,
Slov