A Dynamic Model for Binary Panel Data With Unobserved Heterogeneity Admitting a √n-Consistent Conditional Estimator
提出一种二元面板数据模型，允许状态依赖和未观测异质性，可通过条件似然法轻松估计，至少需要两个观测值（除初始观测外），且可包含时间虚拟变量。
A model for binary panel data is introduced which allows for state dependence and unobserved heterogeneity beyond the effect of available covariates. The model is of quadratic exponential type and its structure closely resembles that of the dynamic logit model. However, it has the advantage of being easily estimable via conditional likelihood with at least two observations (further to an initial observation) and even in the presence of time dummies among the regressors. Copyright 2010 The Econometric Society.