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Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models

Author

Listed:
  • Tue Gørgens

    (The Australian National University)

  • Christopher L. Skeels

    (The University of Melbourne)

  • Allan H. Würtz

    (School of Economics and Management, University of Aarhus and CREATES)

Abstract

This paper explores estimation of a class of non-linear dynamic panel data models with additive unobserved individual-specific effects. The models are specified by moment restrictions. The class includes the panel data AR(p) model and panel smooth transition models. We derive an efficient set of moment restrictions for estimation and apply the results to estimation of panel smooth transition models with fixed effects, where the transition may be determined endogenously. The performance of the GMM estimator, both in terms of estimation precision and forecasting performance, is examined in a Monte Carlo experiment. We find that estimation of the parameters in the transition function can be problematic but that there may be significant benefits in terms of forecast performance.

Suggested Citation

  • Tue Gørgens & Christopher L. Skeels & Allan H. Würtz, 2009. "Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models," CREATES Research Papers 2009-51, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2009-51
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    References listed on IDEAS

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    More about this item

    Keywords

    Dynamic panel data models; fixed effects; GMM estimation; smooth transition;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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