Hello Statalisters--

I'm having trouble running xteprobit with a treatment function. Even after stripping out all control variables, it fails to converge:

. xtset dyad year

. xteprobit ag_sig_del oil, vce(cluster dyad) entreat(amdisp1 = oil, pocorrelation)
adaptive quadrature failed to converge
r(430);


Rationale: I am looking at the effect of offshore oil activity on the probability of countries signing maritime boundary delimitation agreements (ag_sig_del - binary variable). I believe that the "oil effect" is conditional on whether the countries already dispute their boundary, but the existence of a dispute is itself engogenous. So I want to include a treatment equation that accounts for disputes in the previous year (amdisp1 - binary variable) being dependent on oil (and potentially other things). This should yield output for the effect of oil both with and without treatment (amdisp=1 and amdisp=0).

I originally tried to run with additional variables; it ran for several hours before I finally stopped it. I tried a similar model, though not organized as panel data:

eprobit ag_sig_del oil year1 year2 year3, entreat(amdisp1 = oil year1 year2 year3)


... which converges just fine. (NB: year1 year2 year3 are: years from the start of the dataset, the same-squared, the same-cubed.) And I can add additional variables to this model without a problem. But I want to control for unobserved between variation and so would like the panel data version.

I'm noting another user asked a similar question with xteoprobit, and there hasn't been a response:
https://www.statalist.org/forums/for...onvergece-fail

Is there something I'm doing wrong with xteprobit? Or is that model type just so computationally intensive as to be impractical? Something else anyone might suggest I try?