Interpreting spatial regression models with multiplicative interaction explanatory variables

被引：4
|
作者：
Sheng, Yuxue [1 ]
LeSage, James Paul [2 ]
机构：
[1] Guangxi Univ, Business Sch, 100 Daxue Rd, Nanning 530004, Peoples R China
[2] Univ Toledo, 2801 W Bancroft St, Toledo, OH 43606 USA
来源：
JOURNAL OF GEOGRAPHICAL SYSTEMS | 2021年 / 23卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Spatial spillovers; Marginal effects; Spatial regression models; Multiplicative interaction variables; C11; C23; O47; O52; CROSS-SECTIONAL DEPENDENCE; ABSORPTIVE-CAPACITY;
D O I：
10.1007/s10109-021-00356-4
中图分类号：
P9 [自然地理学]; K9 [地理];
学科分类号：
0705 ; 070501 ;
摘要：
Use of multiplicative interaction of explanatory variables has been a standard practice in the regression modeling literature, and estimation of the parameters of such a model in the case of spatial autoregressive (SAR) or spatial Durbin (SDM) models can be accomplished using existing software for spatial regression estimation. However, use of the conventional scalar summary estimates of direct and indirect effects reflecting the own- and other-region impacts on the dependent variable associated with changes in the explanatory variables will not produce valid inferences. We discuss the issues that arise and introduce new methods for interpretation of own- and other-region impacts based on estimates from this type of model.
引用
收藏
页码：333 / 360
页数：28
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