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 an asymptotic bias correction proposed by Fernandez-Val (2009)
bife 0.5 (03.03.2018)
factor()in the formula interface. This should now be more in line with what users expect.
fixed(), since you can use
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)