The Mundlak Estimator in a Panel Data Model with Serially Correlated Error Component Disturbances

Author(s)/Creator(s)

• Badi H. Baltagi, Syracuse UniversityFollow
• Long Liu, Florida Atlantic UniversityFollow

Description/Abstract

This paper shows that the classic Mundlak (1978) result where the random effects estimator reduces to the fixed effects estimator when the regressors are all correlated with the individual effects, may not hold if the remainder disturbances have a general serial correlation variance-covariance matrix. This includes the popular AR(1), MA(1) and ARMA(p, q) processes for serial correlation. This is illustrated with an empirical example for the AR(1) case.

Document Type

Working Paper

Date

8-25-2026

Keywords

Panel data, serial correlation, fixed effects, random effects, correlated random effects

Language

English

Disciplines

Econometrics | Economic Policy | Economics

ISSN

1525-3066

Additional Information

CPR Working Paper No. 294

Recommended Citation

Baltagi, Badi H. and Liu, Long, "The Mundlak Estimator in a Panel Data Model with Serially Correlated Error Component Disturbances" (2026). Center for Policy Research. 535.
https://surface.syr.edu/cpr/535

Creative Commons License

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