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A Nonlinear Panel Model of Cross-sectional Dependence

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  • George Kapetanios

    ()
    (Queen Mary, University of London)

  • James Mitchell

    (NIESR)

  • Yongcheol Shin

    (University of Leeds)

Abstract

This paper proposes a new panel model of cross-sectional dependence. The model has a number of potential structural interpretations that relate to economic phenomena such as herding in financial markets. On an econometric level it provides a flexible approach to the modelling of interactions across panel units and can generate endogenous cross-sectional dependence that can resemble such dependence arising in a variety of existing models such as factor or spatial models. We discuss the theoretical properties of the model and ways in which inference can be carried out. We supplement this analysis with a detailed Monte Carlo study and two empirical illustrations.

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Bibliographic Info

Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 673.

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Date of creation: Nov 2010
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Handle: RePEc:qmw:qmwecw:wp673

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Keywords: Cross-sectional dependence; Nonlinearity; Factor models; Panel models; Fixed effects;

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  1. Itzhak Gilboa & Offer Lieberman & David Schmeidler, 2004. "Empirical Similarity," Levine's Bibliography 122247000000000684, UCLA Department of Economics.
  2. Gregory, Allan W & Smith, Gregor W & Yetman, James, 2001. "Testing for Forecast Consensus," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 34-43, January.
  3. Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2008. "THRET: Threshold Regression with Endogenous Threshold Variables," University of Cyprus Working Papers in Economics 3-2008, University of Cyprus Department of Economics.
  4. George A. Akerlof, 2009. "How Human Psychology Drives the Economy and Why It Matters," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1175-1175.
  5. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
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