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Premium The Time Series and Cross‐Section Asymptotics of Dynamic Panel Data Estimators
Alvarez Javier,
Arellano Manuel
Publication year2003
Publication title
Resource typeJournals
PublisherBlackwell Publishing Ltd
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 1/ T , 1/ N , and 1/(2 N − 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 pseudo MLE with unrestricted initial conditions when both T and N tend to infinity.
Subject(s)computer science , cross section (physics) , cross sectional data , econometrics , economics , estimator , geology , mathematics , operating system , paleontology , panel data , physics , quantum mechanics , section (typography) , series (stratigraphy) , statistics , time series
SCImago Journal Rank16.7

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