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Nonparametric trending regression with cross-sectional dependence

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  • Robinson, Peter M.
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    Abstract

    Panel data, whose series length T is large but whose cross-section size N need not be, are assumed to have common time trend, of unknown form. The model includes additive, unknown, individual-specific components and allows for spatial or other cross-sectional dependence and/or heteroscedasticity. A simple smoothed nonparametric trend estimate is shown to be dominated by an estimate which exploits availability of cross-sectional data. Asymptotically optimal bandwidth choices are justified for both estimates. Feasible optimal bandwidths, and feasible optimal trend estimates, are asymptotically justified, finite sample performance of the latter being examined in a Monte Carlo study. Potential extensions are discussed.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0304407612000061
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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 169 (2012)
    Issue (Month): 1 ()
    Pages: 4-14

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    Handle: RePEc:eee:econom:v:169:y:2012:i:1:p:4-14

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    Web page: http://www.elsevier.com/locate/jeconom

    Related research

    Keywords: Panel data; Nonparametric time trend; Cross-sectional dependence; Generalized least squares; Optimal bandwidth;

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    Cited by:
    1. Jia Chen & Jiti Gao & Degui Li, 2011. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," Monash Econometrics and Business Statistics Working Papers 15/11, Monash University, Department of Econometrics and Business Statistics.

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