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

CREATES Research Paper 2009-51

29 Pages Posted: 2 Nov 2009  

Tue Gørgens

Australian National University (ANU) - Research School of Economics (RSE)

Christopher L. Skeels

University of Melbourne - Department of Economics

Allan Wurtz

University of Aarhus - Department of Economics

Date Written: October 2009

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.

Keywords: dynamic panel data models, fixed effects, GMM estimation, smooth transition

JEL Classification: C13, C23

Suggested Citation

Gørgens, Tue and Skeels, Christopher L. and Wurtz, Allan, Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models (October 2009). CREATES Research Paper 2009-51. Available at SSRN: https://ssrn.com/abstract=1498444 or http://dx.doi.org/10.2139/ssrn.1498444

Tue Gorgens (Contact Author)

Australian National University (ANU) - Research School of Economics (RSE) ( email )

Canberra, Australian Capital Territory 0200
Australia

Christopher L. Skeels

University of Melbourne - Department of Economics ( email )

Melbourne, 3010
Australia

Allan Wurtz

University of Aarhus - Department of Economics ( email )

Universitetsparken
Building 350
DK-8000 Aarhus C
Denmark
+45 8942 1133 (Phone)
+45 8613 6334 (Fax)

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