This paper presents a method for estimating a class of panel data duration models,
under which an unknown transformation of the duration variable is linearly related to
the observed explanatory variables and the unobserved heterogeneity (or frailty) with
completely known error distributions. This class of duration models includes a panel
data proportional hazards model with fixed effects. The proposed estimator is shown
to be n1=2-consistent and asymptotically normal with dependent right censoring. The
paper provides some discussions on extending the estimator to the cases of longer panels
and multiple states. Some Monte Carlo studies are carried out to illustrate the finite-
sample performance of the new estimator