Estimation and prediction in the random effects model with AR(p) remainder disturbances

Badi H. Baltagi, Long Liu

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)100-107
Number of pages8
JournalInternational Journal of Forecasting
Volume29
Issue number1
DOIs
StatePublished - Jan 1 2013

Keywords

  • AR(p)
  • Panel data
  • Prediction
  • Random effects
  • Serial correlation

ASJC Scopus subject areas

  • Business and International Management

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