The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators

J. Alvarez and Manuel Arellano ()

Working Papers from Centro de Estudios Monetarios Y Financieros-

Abstract: In this paper we derive the asymptotic properties of within groups (WG), GMM and LIML estimators for an autoregressive model with random effects when both T and N tend to infinity. GMM and LIML are consistent and asymptotically equivalent to the WG estimator. When T/N->0 the fixed T results for GMM and LIML remain valid, but WG although consistent has an asymptotic bias in its asymptotic distribution. When T/N tends to a positive constant, the WG, GMM and LIML estimators exhibit negative asymptotic biases of order T,N and (2N-T), respectively. In addition, the crude GMM estimator that neglects the autocorrelation in first differenced errors is inconsistent as T/N->c>0, despite being consistent for fixed T. Finally, we discuss the properties of a random effects MLE with unrestricted initial conditions when both T and N tend to infinity.

Keywords: ECONOMETRIC MODELS; ESTIMATION OF PARAMETERS; TIME SERIES (search for similar items in EconPapers)
JEL-codes: C22 C24 (search for similar items in EconPapers)
Date: 1998
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Journal Article: The Time Series and Cross-Section Asymptotics of Dynamic Panel Data Estimators (2003)
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Persistent link: http://EconPapers.repec.org/RePEc:fth:cemfdt:9808

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