标题： 带有全局随机趋势的面板协整 显示英文标题

标题： Panel Cointegration with Global Stochastic Trends

摘要： 本文研究了由未观测到的全局随机趋势引起的横截面依赖的面板协整模型的估计问题。 标准最小二乘估计量由于不可观测的I(1)趋势引起的虚假性通常不一致。 我们提出了两种迭代过程，联合估计斜率参数和随机趋势。 所产生的估计量分别称为CupBC（持续更新和偏差校正）估计量和CupFM（持续更新和完全修正）估计量。 我们建立了它们的一致性并推导了它们的极限分布。 两者都是渐近无偏的且渐近混合正态的，并允许使用标准检验统计量进行推断。 当存在混合的平稳和非平稳因子，以及当因子全部平稳时，这些估计量也是有效的。 显示英文摘要

摘要： This paper studies estimation of panel cointegration models with cross-sectional dependence generated by unobserved global stochastic trends. The standard least squares estimator is, in general, inconsistent owing to the spuriousness induced by the unobservable I(1) trends. We propose two iterative procedures that jointly estimate the slope parameters and the stochastic trends. The resulting estimators are referred to respectively as CupBC (continuously-updated and bias-corrected) and the CupFM (continuously-updated and fully-modified) estimators. We establish their consistency and derive their limiting distributions. Both are asymptotically unbiased and asymptotically mixed normal and permit inference to be conducted using standard test statistics. The estimators are also valid when there are mixed stationary and non-stationary factors, as well as when the factors are all stationary.