Estimation and Prediction in the Random Effects Model with AR(p) Remainder Disturbances

Badi Baltagi and Long Liu
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Long Liu: The University of Texas at San Antonio

No 138, Center for Policy Research Working Papers from Center for Policy Research, Maxwell School, Syracuse University

Abstract: This paper considers the problem of estimation and forecasting in a panel data model with random individual effects and AR(p) remainder disturbances. It utilizes a simple exact transformation for the AR(p) time series process derived by Baltagi and Li (1994) and obtains the generalized least squares estimator for this panel model as a least squares regression. This exact transformation is also used in conjunction with Goldberger’s (1962) result to derive an analytic expression for the best linear unbiased predictor. The performance of this predictor is investigated using Monte Carlo experiments and illustrated using an empirical example. Key Words: Prediction; Panel Data; Random Effects; Serial Correlation; AR(p) JEL Classification: C32

Pages: 16 pages
Date: 2012-07
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Estimation and prediction in the random effects model with AR(p) remainder disturbances (2013)
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