Bias correction for fixed effects spatial panel data models

• Main Authors: Yang, Zhenlin, YU, Jihai, LIU, Shew Fan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Bias correction; Variance correction; Bootstrap; Spatial panel; Individual fixed effects; Time fixed effects; Quasi maximum likelihood; Spatial lag; Spatial error; Spatial ARAR; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1754; https://ink.library.smu.edu.sg/context/soe_research/article/2753/viewcontent/04_2015.pdf
• Institution: Singapore Management University

This paper examines the finite sample properties of the quasi maximum likelihood (QML) estimators of the fixed effects spatial panel data (FE-SPD) models of Lee and Yu (2010). Following the general bias correction methods recently developed by Yang (2015), we derive up to third-order bias corrections for the QML estimators of the FE-SPD model, and propose a simple bootstrap method for their practical implementation. Monte Carlo results reveal that the QML estimators of the spatial parameters can be quite biased and that a second-order bias correction effectively removes the bias. The validity of the bootstrap method is established. Variance corrections are also considered, which together with bias corrections lead to improved inferences.