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

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  • Baltagi, Badi H.
  • Liu, Long

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.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 29 (2013)
Issue (Month): 1 ()
Pages: 100-107

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Handle: RePEc:eee:intfor:v:29:y:2013:i:1:p:100-107

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Web page: http://www.elsevier.com/locate/ijforecast

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Keywords: Prediction; Panel data; Random effects; Serial correlation; AR(p);

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  1. Marc Nerlove, 1968. "Further Evidence on the Estimation of Dynamic Economic Relations from a Time Series of Cross-Sections," Cowles Foundation Discussion Papers 257, Cowles Foundation for Research in Economics, Yale University.
  2. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
  3. Eugene Kouassi & Joel Sango & J. M. Bosson Brou & Francis N. Teubissi & Kern O. Kymn, 2011. "Prediction from the regression model with two‐way error components," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(6), pages 541-564, September.
  4. Taub, Allan J., 1979. "Prediction in the context of the variance-components model," Journal of Econometrics, Elsevier, vol. 10(1), pages 103-107, April.
  5. Wansbeek, Tom & Kapteyn, Arie, 1983. "A note on spectral decomposition and maximum likelihood estimation in models with balanced data," Statistics & Probability Letters, Elsevier, vol. 1(4), pages 213-215, June.
  6. Maeshiro, Asatoshi, 1979. "On the Retention of the First Observations in Serial Correlation Adjustment of Regression Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 20(1), pages 259-65, February.
  7. Baltagi, Badi H. & Li, Qi, 1991. "A transformation that will circumvent the problem of autocorrelation in an error-component model," Journal of Econometrics, Elsevier, vol. 48(3), pages 385-393, June.
  8. Richard Schmalensee & Thomas M. Stoker & Ruth A. Judson, 1998. "World Carbon Dioxide Emissions: 1950-2050," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 15-27, February.
  9. Wansbeek, T.J. & Kapteyn, A.J., 1983. "A note on spectral decomposition and maximum likelihood estimation in ANOVA models with balanced data," Open Access publications from Tilburg University urn:nbn:nl:ui:12-364319, Tilburg University.
  10. Frees, Edward W. & Miller, Thomas W., 2004. "Sales forecasting using longitudinal data models," International Journal of Forecasting, Elsevier, Elsevier, vol. 20(1), pages 99-114.
  11. Park, Rolla Edward & Mitchell, Bridger M., 1980. "Estimating the autocorrelated error model with trended data," Journal of Econometrics, Elsevier, vol. 13(2), pages 185-201, June.
  12. Maeshiro, Asatoshi, 1976. "Autoregressive Transformation, Trended Independent Variables and Autocorrelated Disturbance Terms," The Review of Economics and Statistics, MIT Press, vol. 58(4), pages 497-500, November.
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