Semi-functional partial linear spatial autoregressive model

作     者：Li, Yunxia Ying, Caiyun 

作者机构：Zhejiang Univ Finance & Econ Sch Data Sci Hangzhou 310018 Peoples R China 

出 版 物：《COMMUNICATIONS IN STATISTICS-THEORY AND METHODS》 (统计学通讯：理论与方法)

年 卷 期：2021年第50卷第24期

页      面：5941-5954页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 

基　　金：National Social Science Foundation of China [17BTJ039] 

主　　题：Functional variables SAR Local linear regression QMLE 

摘      要：This paper proposes a semi-functional partial linear spatial autoregressive (SAR) model, in which we allow one of the explanatory variables to be a functional variable, while the dependent variable is scalar. We aim to enable the spatial econometric models to be applied to various areas where data types can be functional data. Based on quasi-maximum likelihood estimation (QMLE) method and local linear regression method, we construct a two-stage estimator to estimate the parameters and nonparametric component. The convergence rate of the estimator of nonparametric component is given. Furthermore, Monte Carlo simulations are performed to investigate our two-stage estimator s finite sample performance.