Panel Data Models With Interactive Fixed Effects
研究大N和大T面板数据模型中不可观测的交互效应，这些效应与回归变量相关，并讨论了估计量的一致性和极限分布。
This paper considers large N and large T panel data models with unobservable multiple interactive effects, which are correlated with the regressors. In earnings studies, for example, workers' motivation, persistence, and diligence combined to influence the earnings in addition to the usual argument of innate ability. In macroeconomics, interactive effects represent unobservable common shocks and their heterogeneous impacts on cross sections. We consider identification, consistency, and the limiting distribution of the interactive-effects estimator. Under both large N and large T, the estimator is shown to be root(N T) consistent, which is valid in the presence of correlations and heteroskedasticities of unknown form in both dimensions. We also derive the constrained estimator and its limiting distribution, imposing additivity coupled with interactive effects. The problem of testing additive versus interactive effects is also studied. In addition, we consider identification and estimation of models in the presence of a grand mean, time-invariant regressors, and common regressors. Given identification, the rate of convergence and limiting results continue to hold. Copyright 2009 The Econometric Society.