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Large panel data models with cross-sectional dependence: a survey

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  • Chudik, Alexander

    (Federal Reserve Bank of Dallas)

  • Pesaran, M. Hashem

Abstract

This paper provides an overview of the recent literature on estimation and inference in large panel data models with cross-sectional dependence. It reviews panel data models with strictly exogenous regressors as well as dynamic models with weakly exogenous regressors. The paper begins with a review of the concepts of weak and strong cross-sectional dependence, and discusses the exponent of cross-sectional dependence that characterizes the different degrees of cross-sectional dependence. It considers a number of alternative estimators for static and dynamic panel data models, distinguishing between factor and spatial models of cross-sectional dependence. The paper also provides an overview of tests of independence and weak cross-sectional dependence.

Suggested Citation

  • Chudik, Alexander & Pesaran, M. Hashem, 2013. "Large panel data models with cross-sectional dependence: a survey," Globalization and Monetary Policy Institute Working Paper 153, Federal Reserve Bank of Dallas.
  • Handle: RePEc:fip:feddgw:153
    Note: Published as: Chudik, Alexander and M. Hashem Pesaran (2015), "Large Panel Data Models with Cross-Sectional Dependence: A Survey," in The Oxford Handbook of Panel Data, ed. Badi H. Baltagi (New York: Oxford University Press), 3-45.
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    File URL: http://www.dallasfed.org/assets/documents/institute/wpapers/2013/0153.pdf
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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