I am using ivreghdfe 1.1.1 with ivreg2 4.1.11 on Stata 17 (Windows 10).
I want to estimate the predicted probability after having run an IV regression of the log odds ratio on covariates and fixed effects.
Here is what I run:
ivreghdfe log_odds_ratio (X = Z ) C [pw=weights], absorb(year county_fe) cluster(state)
predictnl pred_prob=exp(predict(xbd))/(1+exp(predict(xbd))) , se(pred_prob_se)
which returns:
you must add the resid option to reghdfe before running this prediction
predict(xbd) invalid
r(198);
then adding the resid option returns:
ivreghdfe log_odds_ratio (X = Z ) C [pw=weights], absorb(year county_fe) cluster(state) resid
predictnl pred_prob=exp(predict(xbd))/(1+exp(predict(xbd))) , se(pred_prob_se)
expression is a function of possibly stochastic quantities other than e(b)
r(498);
(Note: using margins instead of predictnl returns the exact same errors).
Any suggestions on how to estimate non-linear predictions with many fixed?
Hello Sergio,
I am using ivreghdfe 1.1.1 with ivreg2 4.1.11 on Stata 17 (Windows 10). I want to estimate the predicted probability after having run an IV regression of the log odds ratio on covariates and fixed effects. Here is what I run:
ivreghdfe log_odds_ratio (X = Z ) C [pw=weights], absorb(year county_fe) cluster(state) predictnl pred_prob=exp(predict(xbd))/(1+exp(predict(xbd))) , se(pred_prob_se) which returns: you must add the resid option to reghdfe before running this prediction predict(xbd) invalid r(198);
then adding the resid option returns: ivreghdfe log_odds_ratio (X = Z ) C [pw=weights], absorb(year county_fe) cluster(state) resid predictnl pred_prob=exp(predict(xbd))/(1+exp(predict(xbd))) , se(pred_prob_se)
expression is a function of possibly stochastic quantities other than e(b) r(498);
(Note: using margins instead of predictnl returns the exact same errors).
Any suggestions on how to estimate non-linear predictions with many fixed?
Thanks a lot!