Panel Binary Variables and Sufficiency: Generalizing Conditional Logit
推广了条件Logit方法，给出面板二元变量模型中个体效应充分统计量的充要条件，并证明根n一致估计存在的条件，为应用提供准差分变换方法。
This paper extends the conditional logit approach (Rasch, Andersen, Chamberlain) used in panel data models of binary variables with correlated fixed effects and strictly exogenous regressors. In a two-period two-state model, necessary and sufficient conditions on the joint distribution function of the individual-and-period specific shocks are given such that the sum of individual binary variables across time is a sufficient statistic for the individual effect. By extending a result of Chamberlain, it is shown that root-n consistent regular estimators can be constructed in panel binary models if and only if the property of sufficiency holds. In applied work, the estimation method amounts to quasi-differencing the binary variables as if they were continuous variables and transforming a panel data model into a cross-section model. Semiparametric approaches can then be readily applied. Copyright The Econometric Society 2004.