Multilevel and Nonlinear Panel Data Models

Olaf Hübler

Chapter 9 in Modern Econometric Analysis, 2006, pp 119-135 from Springer

Abstract: 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.

Keywords: Panel Data; Panel Data Model; Semiparametric Model; Firm Effect; Dynamic Panel Data Model (search for similar items in EconPapers)
Date: 2006
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Journal Article: Multilevel and nonlinear panel data models (2006)
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DOI: 10.1007/3-540-32693-6_9

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