Publication Type
Working Paper
Version
publishedVersion
Publication Date
12-2011
Abstract
A simple and reliable method of inference for the spatial parameter in spatial autoregressive models is introduced, based on a statistic obtained by centering and rescaling the numerator of the concentrated Gaussian score function. The resulted tests and confidence intervals are robust against the distributional misspecifications and are insensitive to the spatial layouts and the error standard deviation. In contrast, the standard methods based on Gaussian score and information matrix may lead to inconsistent inference when errors are non normal, and can be quite sensitive to the spatial layouts and the error standard deviation even when errors are normally distributed. Extensive Monte Carlo results are reported and an empirical illustration is given.
Keywords
Spatial dependence, Confidence interval, LM Tests, Centering, Rescaling, Finite sample performance, Robustness
Discipline
Econometrics
Research Areas
Econometrics
First Page
1
Last Page
28
Publisher
SMU Economics and Statistics Working Paper Series, No. 25-2011
City or Country
Singapore
Citation
YANG, Zhenlin and SHEN, Yan.
A Simple and Robust Method of Inference for Spatial Lag Dependence. (2011). 1-28.
Available at: https://ink.library.smu.edu.sg/soe_research/1407
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.