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Identification and N-consistent estimation of a nonlinear panel data model with correlated unobserved effects

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  • Gayle, Wayne-Roy

Abstract

This paper investigates identification and root-n-consistent estimation of a class of single-index panel data models in which the link function is unknown, the unobserved individual effects may be correlated with all the explanatory variables, and all the explanatory variables may be predetermined. We propose two sets of sufficient conditions, one in which link function is assumed to be strictly increasing, and the other in which it is not. We propose simple kernel-based estimators for the models, and derive consistency and asymptotic normality results for the proposed estimators. Finally, we present results of two Monte Carlo studies of the estimators.

Suggested Citation

  • Gayle, Wayne-Roy, 2013. "Identification and N-consistent estimation of a nonlinear panel data model with correlated unobserved effects," Journal of Econometrics, Elsevier, vol. 175(2), pages 71-83.
    • Handle: RePEc:eee:econom:v:175:y:2013:i:2:p:71-83
    DOI: 10.1016/j.jeconom.2012.09.007
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    Cited by:

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    2. Gao, Yichen & Li, Cong & Liang, Zhongwen, 2015. "Binary response correlated random coefficient panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 421-434.

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    More about this item

    Keywords

    Correlated random effects; Single index; Semiparametric; Panel data; Predetermined; Lagged dependent variables;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I20 - Health, Education, and Welfare - - Education - - - General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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