Transformations and moment conditions for dynamic fixed effects logit models
针对动态固定效应Logit模型，提出变换方法构造有效矩条件，涵盖无解释变量、有严格外生连续解释变量或时间虚拟变量等情形，并证明与现有方法等价。
This study proposes transformations for dynamic fixed effects logit models. First, these transformations construct valid moment conditions for the case with neither explanatory variables nor time dummies. Using valid moment conditions, we can obtain the first-order condition of the conditional maximum likelihood estimator proposed by Chamberlain (1985). Next, we derive valid moment conditions based on the transformations for the cases with strictly exogenous continuous explanatory variables and/or time dummies when the number of time periods is four or more. Transformations of these moment conditions exactly coincide with a subset of those obtained by Honoré and Weidner (2020) using the functional differencing approach proposed by Bonhomme (2012).