PANEL DATA MODELS WITH INTERACTIVE FIXED EFFECTS

• 成果类型: Article
• 署名作者: Bai, Jushan
• 署名单位: New York University; Tsinghua University; Central University of Finance & Economics
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA6135
• 发表日期: 2009
• 页码: 1229-1279
• 关键词: time-series; arbitrage; inference; RISK; covariance; number; BIAS; gmm

摘要

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 NT 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.