The purpose of this paper is to review recently developed bias-adjusted methods of
estimation of nonlinear panel data models with fixed effects. Standard estimators such as
maximum likelihood estimators are usually inconsistent if the number of individuals n goes
to infinity while the number of time periods T is held fixed. For some models, like static linear
and logit regressions, there exist fixed-T consistent estimators as n→∞(see, eg, Andersen,
1970). Fixed T consistency is a desirable property because for many panels T is much …

The purpose of this paper is to review recently developed bias-adjusted methods of
estimation of nonlinear panel data models with fixed effects. For some models, like static
linear and logit regressions, there exist fixed-T consistent estimators as n→∞. Fixed T
consistency is a desirable property because for many panels T is much smaller than n.
However, these type of estimators are not available in general, and when they are, their
properties do not normally extend to estimates of average marginal effects, which are often …