Estimates fixed effects binary choice models (logit and probit) with potentially many individual fixed effects and computes average partial effects. Incidental parameter bias can be reduced with a bias-correction proposed by Hahn and Newey (2004)
bife 0.4 (06.05.2017)
bife 0.3 (04.05.2017)
apeff_bife()now uses the full sample instead of a sub-sample of indiviuals with a varying response.
vcov()was not able to distinguish between corrected and uncorrected coefficients.
bife 0.2 (20.02.2017)
fixed()to model additional fixed-effects. See documentation for further details.
apeff.bife(..., bias.corr = "ana")is now
apeff_bife(..., bias_corr = "ana").
bife()was not able to fit a model with just one explanatory variable.
bife 0.1 (29.07.2016)