Multilevel and nonlinear panel data models |
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Authors: | Olaf Hübler |
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Institution: | (1) Institute of Quantitative Economic Research, University of Hannover, K?nigsworther Platz 1, 30167 Hannover, Germany |
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Abstract: | Summary 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.
Helpful comments and suggestions from an unknown referee are gratefully acknowledged. |
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Keywords: | Panel data linear multilevel nonlinear non- and semiparametric models JEL C14 C33 C35 |
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