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New developments in spatial econometric modelling

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  • Katarzyna Kopczewska
  • Paul Elhorst

Abstract

This special issue brings together five methodological contributions and responses to the 16th World Conference of the Spatial Econometric Association held in Warsaw, Poland, in June 2022. Each paper presents a new technique to provide better answers to the different stages of spatial econometric modelling. The first paper develops a method for determining principal components that capture both spatial and temporal dependence. The second paper provides five statistics to measure the extent to which spatial lags are collectively or individually significant in a spatial Durbin model. The third paper provides a roadmap to guide scholars through the specification search to explore spatial dependence underlying regions’ resilience. The fourth paper employs the Akaike information criterion to determine the best performing k-nearest neighbour matrix in a spatial econometric model. The fifth paper explores a methodology to determine the best performing spatial weight matrix based on a set of covariates rather than geographical distance-based measures.

Suggested Citation

  • Katarzyna Kopczewska & Paul Elhorst, 2024. "New developments in spatial econometric modelling," Spatial Economic Analysis, Taylor & Francis Journals, vol. 19(1), pages 1-7, January.
    • Handle: RePEc:taf:specan:v:19:y:2024:i:1:p:1-7
    DOI: 10.1080/17421772.2023.2281173
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    Cited by:

    1. Li, Shuoshuo & Liu, Yaobin & Wei, Guoen & Bi, Mo & He, Bao-Jie, 2024. "Carbon surplus or carbon deficit under land use transformation in China?," Land Use Policy, Elsevier, vol. 143(C).

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