Department of Economics and Business Economics

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

Research output: Working paperResearch


  • Rp09 51

    Final published version, 352 KB, PDF document

  • Tue Gørgens, The Australian National University, Australia
  • Christopher L. Skeels, The University of Melbourne, Australia
  • Allan Wurtz
  • School of Economics and Management
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.
Original languageEnglish
Place of publicationAarhus
PublisherInstitut for Økonomi, Aarhus Universitet
Number of pages27
Publication statusPublished - 2009

    Research areas

  • Dynamic panel data models, fixed effects, GMM estimation, smooth transition

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