Forecasting with Unbalanced Panel Data

Author(s)/Creator(s)

Badi BaltagiFollow
Long Liu, University of Texas at San AntonioFollow

Description/Abstract

This paper derives the best linear unbiased prediction (BLUP) for an unbalanced panel data model. Starting with a simple error component regression model with unbalanced panel data and random effects, it generalizes the BLUP derived by Taub (1979) to unbalanced panels. Next it derives the BLUP for an unequally spaced panel data model with serial correlation of the AR(1) type in the remainder disturbances considered by Baltagi and Wu (1999). This in turn extends the BLUP for a panel data model with AR(1) type remainder disturbances derived by Baltagi and Li (1992) from the balanced to the unequally spaced panel data case. The derivations are easily implemented and reduce to tractable expressions using an extension of the Fuller and Battese (1974) transformation from the balanced to the unbalanced panel data case.

Document Type

Working Paper

Date

1-2020

Keywords

Forecasting, BLUP, Unbalanced Panel Data, Unequally Spaced Panels, Serial Correlation

Language

English

Series

Working Papers Series

Disciplines

Economic Policy | Economics | Public Affairs, Public Policy and Public Administration

ISSN

1525-3066

Additional Information

Working paper no. 221

Recommended Citation

Baltagi, Badi and Liu, Long, "Forecasting with Unbalanced Panel Data" (2020). Center for Policy Research. 253.
https://surface.syr.edu/cpr/253

Source

Local input

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.