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)
[Major Changes]
factor()
in the formula interface. This should now be more in line with
what users expect.fixed()
, since you can use factor()
now.[Minor Changes]
print.summary.bife()
.bife 0.4 (06.05.2017)
[Bug fix]
bife.cpp
.bife 0.3 (04.05.2017)
[Major Changes]
predict()
.bife()
and apeff_bife()
.apeff_bife()
now uses the full sample instead of a sub-sample of indiviuals with a
varying response.[Minor Changes]
discrete
of apeff_bife()
to NULL
.bias_corr
of apeff_bife()
to "ana"
.[Bug fix]
vcov()
was not able to distinguish between corrected and uncorrected
coefficients.bife 0.2 (20.02.2017)
[Major Changes]
fixed()
to model additional fixed-effects. See documentation for further details.apeff.bife(..., bias.corr = "ana")
is now apeff_bife(..., bias_corr = "ana")
.[Minor Changes]
[Bug fix]
bife()
was not able to fit a model with just one explanatory variable.bife 0.1 (29.07.2016)
[Initial release]