A parametric specification test for linear spatial autoregressive models

被引:0
|
作者
Tang, Yangbing [1 ]
Du, Jiang [1 ,2 ]
Zhang, Zhongzhan [1 ,2 ]
机构
[1] Beijing Univ Technol, Fac Sci, Beijing 100124, Peoples R China
[2] Beijing Inst Sci & Engn Comp, Beijing 100124, Peoples R China
基金
中国国家自然科学基金;
关键词
Spatial autoregression; Nonparametric models; Spatial parameter; GMM estimation; Consistent test; NONPARAMETRIC-ESTIMATION; GMM ESTIMATION;
D O I
10.1016/j.spasta.2023.100767
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
We propose a new test for the specification of linear spatial autoregressive models where the spatial weights matrix is pre specified. Our test is built on the difference of two estimates of the spatial parameter where the two estimates are obtained by the parametric and nonparametric GMM estimation methods, respectively. Under mild assumptions, we derive the limiting null distribution and show consistency for our test. Unlike the general nonparametric test, our test can detect the local alternatives that approach the null at a rate n-1/2, where n is the sample size. Monte Carlo simulations are conducted to study the finite sample performance of our test. Finally, we apply our test to check the model specification for the economic growth rate example.(c) 2023 Elsevier B.V. All rights reserved.
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页数:22
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