Panel Data Cointegration Testing with Structural Instabilities

Spurious regression analysis in panel data when the time series are cross-section dependent is analyzed in the article. The set-up includes (possibly unknown) multiple structural breaks that can affect both the deterministic and the common factor components. We show that consistent estimation of the long-run average parameter is possible once cross-section dependence is controlled using cross-section averages in the spirit of Pesaran’s common correlated effects approach. This result is used to design individual and panel cointegration test statistics that accommodate the presence of structural breaks that can induce parameter instabilities in the deterministic component, the cointegration vector and the common factor loadings.

本文针对时序截面相依情形下的面板数据伪回归分析展开研究。其设定框架包含（可能未知的）多重结构断点，这类断点可同时对确定性成分与公共因子成分产生影响。本文证明，若按照佩萨兰（Pesaran）的公共相关效应（common correlated effects）方法的思路，通过截面平均项控制截面相依性，则可实现长期平均参数的一致估计。基于上述结论，本文构建了可适配结构断点的个体与面板协整检验统计量，这类断点可引致确定性成分、协整向量及公共因子载荷的参数不稳定性。