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On the Estimation and Inference of a Panel Cointegration Model with Cross-Sectional Dependence

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Author Info
Jushan Bai () (Department of Economics, New York University, New York, NY 10003, and Department of Economics, Tsinghua University, Beijing 10084, China)
Chihwa Kao () (Center for Policy Research, Maxwell School, Syracuse University, Syracuse, NY 13244-1020)

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Abstract

Most of the existing literature on panel data cointegration assumes cross-sectional independence, an assumption that is difficult to satisfy. This paper studies panel cointegration under cross-sectional dependence, which is characterized by a factor structure. We derive the limiting distribution of a fully modified estimator for the panel cointegrating coefficients. We also propose a continuous-updated fully modified (CUP-FM) estimator). Monte Carlo results show that the CUP-FM estimator has better small sample properties than the two-step FM (2S-FM) and OLS estimators.

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Publisher Info
Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 75.

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Length: 33 pages
Date of creation: Dec 2005
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Handle: RePEc:max:cprwps:75

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Related research
Keywords: panel data cointegration; cross-sectional independence; cross-sectional dependence; continuous updated fully modified (CUP-FM) estimator; Monte Carlo results; two-step FM (2S-FM) estimator; OLS estimator;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

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    Other versions:
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  12. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2000. "Reference Cycles: The NBER Methodology Revisited," CEPR Discussion Papers 2400, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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