一类变系数空间滞后的混合地理加权回归模型研究*

doi:10.7523/j.ucas.2022.081

中国科学院大学学报

• •

一类变系数空间滞后的混合地理加权回归模型研究^*

唐志鹏^1†, 吴颖^2,3, 熊世峰³, 黄寰⁴

1 中国科学院地理科学与资源研究所区域可持续发展分析与模拟院重点实验室,北京 100101;
2 中国科学院大学数学科学学院,北京 101408;
3 中国科学院数学与系统科学研究院,北京 100190;
4 成都理工大学商学院,成都610059

收稿日期:2022-07-22 修回日期:2022-10-10 发布日期:2022-10-14
通讯作者: †E-mail: tangzp@igsnrr.ac.cn
基金资助:
*国家自然科学基金项目 (41530634; 12171462),成都市政府系统重大课题(B35360110202100097)和成都理工大学社科规划重大培育项目(YJ2021-XP001) 资助

Research on a mixed geographically weighted regression model with varying-coefficient spatial lag

TANG Zhipeng¹, WU Ying^2,3, XIONG Shifeng³, HUANG Huan⁴

1 Key Laboratory of Regional Sustainable Development Modeling, Institute of Geography Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101,China;
2 School of Mathematical Sciences, University of Chinese Academy and Science, Beijing 101408, China;
3 Academy of Mathematics and Systems Science, Beijing 100190,China; Chinese Academy of Sciences;
4 Business School of Chengdu University of Technology, Chengdu 610059,China

Received:2022-07-22 Revised:2022-10-10 Published:2022-10-14

摘要/Abstract

摘要： 空间相关性和空间异质性是空间计量经济学理论建构的基础。为了解决因变量空间滞后存在的局域性问题,本研究对现有常系数空间滞后的混合地理加权回归模型作了具有更广泛形式的拓展,提出了一类变系数空间滞后的混合地理加权回归模型。变系数空间滞后的混合地理加权回归模型实现了空间相关性与空间异质性融合,涵盖了绝大多数地理加权回归的模型形式,基于重构参数化方法和似然比检验分别给出模型的系数估计方法与显著性检验以及选取变系数的判别检验。在蒙特卡罗模拟与实际应用中,变系数空间滞后的混合地理加权回归模型均表现出优异的因变量拟合与预测能力。变系数空间滞后的混合地理加权回归模型的提出为定量化研究空间效应问题设定适宜的模型形式提供了支撑依据。

关键词: 空间异质性, 混合地理加权回归, 显著性检验, 变系数

Abstract: Spatial correlation and spatial heterogeneity are the theoretical basis of spatial econometrics. In order to solve the local problem of spatial lag of dependent variables, this study extended the existing mixed geographically weighted regression model with constant-coefficient spatial lag, and proposed a mixed geographically weighted regression model with varying-coefficient spatial lag. The mixed geographically weighted regression model with varying-coefficient spatial lag combines spatial correlation with spatial heterogeneity, and covers most of the model forms of geographically weighted regression. Based on the parameterization reconstruction method and likelihood ratio test, the coefficient estimation method, significance test of this model and the discriminant test of varying-coefficient are given respectively. Both in Monte Carlo simulation and practical application, the results show that the mixed geographically weighted regression model with varying-coefficient spatial lag renders itself well for the fitting and forecasting effect on dependent variable. The mixed geographically weighted regression model with varying-coefficient spatial lag provides a support for setting up a suitable model form for quantitative research on spatial effects.

Key words: spatial heterogeneity, mixed geographically weighted regression, significance test, varying-coefficient

中图分类号:

O212.7

唐志鹏, 吴颖, 熊世峰, 黄寰. 一类变系数空间滞后的混合地理加权回归模型研究^*[J]. 中国科学院大学学报, DOI: 10.7523/j.ucas.2022.081.

TANG Zhipeng, WU Ying, XIONG Shifeng, HUANG Huan. Research on a mixed geographically weighted regression model with varying-coefficient spatial lag[J]. Journal of University of Chinese Academy of Sciences, DOI: 10.7523/j.ucas.2022.081.

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一类变系数空间滞后的混合地理加权回归模型研究^*

Research on a mixed geographically weighted regression model with varying-coefficient spatial lag

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