Geographically weight seemingly unrelated regression (GWSUR): a method for exploring spatio-temporal heterogeneity

ABSTRACT

Geographically weight seemingly unrelated regression is a useful technique to explore the temporal and spatial heterogeneity simultaneously in space-time data analysis. In this article, a local linear-based estimating approach is developed to estimate the unknown coefficient functions. Some simulations are conducted to examine the performance of our proposed method and the results are satisfactory. Finally, a real data example is considered.

KEYWORDS:

• Geographically weighted regression
• seemingly unrelated regression
• spatial heterogeneity
• local linear method

JEL CLASSIFICATION:

• C13
• C14
• C31

Acknowledgements

The authors would like to thank the Editor and a referee for their truly helpful comments and suggestions which led to a much improved presentation. Chuanhua Wei’s research was supported by the National Natural Science Foundation of China [No.11301565] and Beijing Higher Education Young Elite Teacher Project [No.YETP1316].

Disclosure statement

No potential conflict of interest was reported by the authors.​​​​​​

Additional information

Funding

​​​​​​Chuanhua Wei’s research was supported by the National Natural Science Foundation of China [11301565] and Beijing Higher Education Young Elite Teacher Project [No.YETP1316​​​​​​].