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

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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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  • Jushan Bai & Chihwa Kao, 2005. "On the Estimation and Inference of a Panel Cointegration Model with Cross-Sectional Dependence," Center for Policy Research Working Papers 75, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:75
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    File URL: https://surface.syr.edu/cpr/89/
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    8. Mahdavi, Saeid & Westerlund, Joakim, 2011. "Fiscal stringency and fiscal sustainability: Panel evidence from the American state and local governments," Journal of Policy Modeling, Elsevier, vol. 33(6), pages 953-969.
    9. Tino Berger & Gerdie Everaert, 2009. "A replication note on unemployment in the OECD since the 1960s: what do we know?," Empirical Economics, Springer, vol. 36(2), pages 479-485, May.

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    More about this item

    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;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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