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Panel vector autoregression under cross-sectional dependence

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  • Xiao Huang

Abstract

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

Suggested Citation

  • Xiao Huang, 2008. "Panel vector autoregression under cross-sectional dependence," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 219-243, July.
    • Handle: RePEc:ect:emjrnl:v:11:y:2008:i:2:p:219-243
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    Cited by:

    1. Giuseppe Arbia, 2011. "A Lustrum of SEA: Recent Research Trends Following the Creation of the Spatial Econometrics Association (2007--2011)," Spatial Economic Analysis, Taylor & Francis Journals, vol. 6(4), pages 377-395, July.
    2. Xiao Huang, 2013. "Nonparametric Estimation in Large Panels with Cross-Sectional Dependence," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 754-777, August.

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