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.
Asymptotics, Flexible functional form, Fixed effects, Quasi-maximum likelihood, Random Effects, Spatial error correlation, Demand equation
Quasi-Maximum Likelihood Estimation for Spatial Panel Data Regressions. (2013). Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1575
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