文章基本信息

标题：Statistical Inference on Regression with Spatial Dependence
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作者：Peter M Robinson ; Supachoke Thawornkaiwong
期刊名称：Distributional Analysis Publications
印刷版ISSN：1352-2469
出版年度：2010
卷号：2010
出版社：Suntory Toyota International Centres for Economics and Related Disciplines
摘要：Central limit theorems are developed for instrumental variables estimates of linear and semi-parametric partly linear regression models for spatial data. General forms of spatial dependence and heterogeneity in explanatory variables and unobservable disturbances are permitted. We discuss estimation of the variance matrix, including estimates that are robust to disturbance heteroscedasticity and/or dependence. A Monte Carlo study of finite-sample performance is included. In an empirical example, the estimates and robust and non-robust standard errors are computed from Indian regional data, following tests for spatial correlation in disturbances, and nonparametric regression fitting. Some final comments discuss modifications and extensions
关键词：Linear regression; Partly linear regression; Nonparametric ;regression; Spatial data; Instrumental variables; Asymptotic normality; ;Variance estimation