Multi-scale issues in cross-border comparative analysis

Jianquan Cheng, Stewart Fotheringham

    Research output: Contribution to journalArticlepeer-review

    15 Citations (Scopus)


    Cross-border studies have recently received increasing attention in many disciplines, stimulated by globalisation, international trade and migration. In this paper, we take the analysis of the determinants of educational attainment on both sides of the international border between Northern Ireland and the Republic of Ireland to demonstrate how the impacts of the changing areal units and extent on social processes can be examined through spatial statistical analysis. A statistical model is constructed to relate the proportion of people with a post-secondary degree in a small area to a series of socio-economic characteristics of that area. We utilise both a traditional ‘global’ regression model and the local technique of Geographically Weighted Regression (GWR). Both models are calibrated on various cross-border data sets. The results also highlight the multi-scalar effects of the Modifiable Areal Unit Problem (MAUP) which are partially relevant in cross-border statistical analysis. They also demonstrate the potential of GWR to highlight cross-border differences in social processes.
    Original languageEnglish
    Pages (from-to)138–148
    Early online date30 Jan 2013
    Publication statusPublished - May 2013


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