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Multilevel and Nonlinear Panel Data Models

In: Modern Econometric Analysis

Author

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  • Olaf Hübler

    (University of Hannover)

Abstract

This paper presents a selective survey on panel data methods. The focus is on new developments. In particular, linear multilevel models, specific nonlinear, nonparametric and semiparametric models are at the center of the survey. In contrast to linear models there do not exist unified methods for nonlinear approaches. In this case conditional maximum likelihood methods dominate for fixed effects models. Under random effects assumptions it is sometimes possible to employ conventional maximum likelihood methods using Gaussian quadrature to reduce a T-dimensional integral. Alternatives are generalized methods of moments and simulated estimators. If the nonlinear function is not exactly known, nonparametric or semiparametric methods should be preferred.

Suggested Citation

  • Olaf Hübler, 2006. "Multilevel and Nonlinear Panel Data Models," Springer Books, in: Olaf Hübler & Jachim Frohn (ed.), Modern Econometric Analysis, chapter 9, pages 119-135, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-32693-9_9
    DOI: 10.1007/3-540-32693-6_9
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    References listed on IDEAS

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    More about this item

    Keywords

    Panel Data; Panel Data Model; Semiparametric Model; Firm Effect; Dynamic Panel Data Model;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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