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A study on geographically weighted spatial autoregression models with spatial autoregressive disturbances

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  • Xiaozhi Peng
  • Hecheng Wu
  • Ling Ma

Abstract

Spatial heterogeneity and correlation are both considered in the geographical weighted spatial autoregressive model. At present, this kind of model has aroused the attention of some scholars. For the estimation of the model, the existing research is based on the assumption that the error terms are independent and identically distributed. In this article we use a computationally simple procedure for estimating the model with spatially autoregressive disturbance terms, both the estimates of constant coefficients and variable coefficients are obtained. Finally, we give the large sample properties of the estimators under some ordinary conditions. In addition, application study of the estimation methods involved will be further explored in a separate study.

Suggested Citation

  • Xiaozhi Peng & Hecheng Wu & Ling Ma, 2020. "A study on geographically weighted spatial autoregression models with spatial autoregressive disturbances," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(21), pages 5235-5251, November.
    • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:21:p:5235-5251
    DOI: 10.1080/03610926.2019.1615507
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