Econometric Analysis of Panel Data Models with Multifactor Error Structures
综述了处理经济面板数据中横截面依赖的两种方法（空间依赖和残差多因子方法），重点介绍了多因子误差结构下平稳与非平稳面板数据的估计与推断理论，包括单位根、斜率同质性、协整和因子数检验，并讨论了实际应用中的参数过多、结构稳定性等问题。
Economic panel data often exhibit cross-sectional dependence, even after conditioning on appropriate explanatory variables. Two approaches to modeling cross-sectional dependence in economic panel data are often used: the spatial dependence approach, which explains cross-sectional dependence in terms of distance among units, and the residual multifactor approach, which explains cross-sectional dependence by common factors that affect individuals to a different extent. This article reviews the theory on estimation and statistical inference for stationary and nonstationary panel data with cross-sectional dependence, particularly for models with a multifactor error structure. Tests and diagnostics for testing for unit roots, slope homogeneity, cointegration, and the number of factors are provided. We discuss issues such as estimating common factors, dealing with parameter plethora in practice, testing for structural stability and nonlinearity, and dealing with model and parameter uncertainty. Finally, we address issues related to the use of these economic panel models.