Hi everyone,

I'm wondering if there's a way to create a risk prediction variable from the results of two different Heckman Correction models--one for Selection Bias and one for Self-Selection Bias. I think I've seen this done in academic literature before but the paper didn''t explain its methodology in detail. For example, let's say I have;

// For Self-Selection Bias (Variables for Heckman: lnsales, lnemp, fcf_w, mktshr, mss, hhi, lnbseg, lngseg, unrate):
heckman status c.preld c.durld c.postld i.cu c.jdg i.presid c.retexl c.retvolatl c.retskewl c.turnovrl c.bm_w, select(status = i.regul c.lnsales c.lnemp c.fcf_w c.mktshr c.mss c.hhi c.lnbseg c.lngseg c.unrate c.bm_w i.cu c.jdg i.presid c.retexl c.retvolatl c.retskewl c.turnovrl) nocons twostep first mills(imr) //vce(bootstrap)

/* (After running the first heckman bit of code just above, type "drop imr" in the command line before you run the second heckman bit of code just below here.) */
// For Selection Bias (Variables for Heckman: FPS variable, fcf_w):
heckman status c.preld c.durld c.postld i.cu c.jdg i.presid c.retexl c.retvolatl c.retskewl c.turnovrl c.bm_w c.fcf_w, select(status = i.fps c.bm_w i.cu c.jdg i.presid c.retexl c.retvolatl c.retskewl c.turnovrl c.fcf_w) nocons twostep first mills(imr) //vce(bootstrap)


(Note that variables preld, durld and postld needed to be removed from the 1st stages of the models because of the economic nature of those variables.)

The top model involves 9 "Heckman variables," while the bottom one only involves 2. One such variable is common to both models--fcf_w.
Any advice would be greatly appreciated, thank you!!
J.J.