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Projection estimators for autoregressive panel data models

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Author Info
Steve Bond () (Institute for Fiscal Studies and Nuffield College, Oxford)
Frank Windmeijer () (Institute for Fiscal Studies and University of Bristol)

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Abstract

In this paper we explore a new approach to estimation for autoregressive panel data models, based on projecting the unobserved individual effects on the vector of observations on the lagged dependent variable. This approach yields estimators which coincide with known generalised method of moments (GMM) estimators for models where stationarity is not imposed on the initial conditions and for models which satisfy mean stationarity. Our approach allows us to obtain a simple linear estimator for models which satisfy covariance stationarity, which although not fully efficient performs very well in simulations.

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File URL: http://cemmap.ifs.org.uk/wps/cwp0106.pdf
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP06/01.

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Length: 35 pp.
Date of creation: Dec 2001
Date of revision:
Handle: RePEc:ifs:cemmap:06/01

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data

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  1. Jan F. Kiviet, 2005. "Judging Contending Estimators by Simulation: Tournaments in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 05-112/4, Tinbergen Institute. [Downloadable!]
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This page was last updated on 2009-11-27.

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