横截面相关性下的面板向量自回归

Xiao Huang
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引用次数: 7

摘要

本文研究了截面相关条件下面板向量自回归(VAR)的估计问题。允许时间序列是平稳过程和单位根过程的未知混合物,它们之间可能存在协整关系。采用因子结构对截面相关性进行建模。我们将Bai和Ng (2002, Econometrica 70,91—221)的因子分析扩展到向量过程。将Phillips(1995)的完全修正(FM)估计量用于面板VAR的估计,并提出了一个因子增广的FM估计量。仿真结果表明,该因子增强调频估计器在样本量较大时具有良好的性能。版权所有©2008作者。期刊汇编©皇家经济学会2008
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Panel Vector Autoregression Under Cross-Sectional Dependence
This paper studies estimation in panel vector autoregression (VAR) under cross-sectional dependence. The time series are allowed to be an unknown mixture of stationary and unit root processes with possible cointegrating relations. The cross-sectional dependence is modeled with a factor structure. We extend the factor analysis in Bai and Ng (2002, Econometrica 70, 91--221) to vector processes. The fully modified (FM) estimator in Phillips (1995) is used for estimation in panel VAR and we also propose a factor augmented FM estimator. Our simulation results show this factor augmented FM estimator performs well when sample size is large. Copyright © 2008 The Author. Journal compilation © Royal Economic Society 2008
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