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

Author(s)/Creator(s)

Badi Baltagi, Syracuse UniversityFollow
Long Liu, University of Texas at San Antonio

Description/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.

Document Type

Working Paper

Date

7-2012

Keywords

Prediction, Panel Data, Random Effects, Serial Correlation, AR(p)

Series

Working Papers Series

Disciplines

Economics | Public Affairs, Public Policy and Public Administration

Additional Information

Working paper no. 138

Recommended Citation

Baltagi, Badi and Liu, Long, "Estimation and Prediction in the Random Effects Model with AR(P) Remainder Disturbances" (2012). Center for Policy Research. 192.
https://surface.syr.edu/cpr/192

Source

local input

Creative Commons License

This work is licensed under a Creative Commons Attribution 3.0 License.