Publication Type
Working Paper
Version
publishedVersion
Publication Date
12-2013
Abstract
This article considers quasi-maximum likelihood estimations (QMLE) for two spatial panel data regression models: mixed effects model with spatial errors and transformed mixed effects model (where response and covariates are transformed) with spatial errors. One aim of transformation is to normalize the data, thus the transformed models are more robust with respect to the normality assumption compared with the standard ones. QMLE method provides additional protection against violation of normality assumption. Asymptotic properties of the QMLEs are investigated. Numerical illustrations are provided.
Keywords
Asymptotics, Flexible functional form, Fixed effects, Quasi-maximum likelihood, Random Effects, Spatial error correlation, Demand equation
Discipline
Econometrics
Research Areas
Econometrics
Citation
YANG, Zhenlin.
Quasi-Maximum Likelihood Estimation for Spatial Panel Data Regressions. (2013).
Available at: https://ink.library.smu.edu.sg/soe_research/1575
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.