Improved Inferences for Spatial Regression Models

• Main Authors: LIU, Shew Fan, YANG, Zhenlin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Asymptotic inference; Bias correction; Bootstrap; Improved t-ratio; Monte Carlo; Spatial layout; Stochastic expansion; Variance correction; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1786; https://ink.library.smu.edu.sg/context/soe_research/article/2785/viewcontent/LiuYangRSUE2015b.pdf
• Institution: Singapore Management University

The quasi-maximum likelihood (QML) method is popular in the estimation and inference for spatial regression models. However, the QML estimators (QMLEs) of the spatial parameters can be quite biased and hence the standard inferences for the regression coefficients (based on t-ratios) can be seriously...