Binary Choice Models with Fixed Effects
Asymptotic bias correction for binary choice Models with fixed effects
Set bife Control Parameters
Efficiently fit binary choice models with fixed effects
Extract estimates of structural parameters or fixed effects
Extract estimates of average partial effects
Extract bife fitted values
Compute average partial effects for binary choice models with fixed ef...
Extract log-likelihood
Predict method for bife fits
Print bife
Print bifeAPEs
Print summary.bife
Print summary.bifeAPEs
Summarizing models of class bife
Summarizing models of class bifeAPEs
Extract estimates of the covariance matrix
Extract estimates of the covariance matrix
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) <doi:10.1016/j.jeconom.2009.02.007>.