Multi-scale issues in cross-border comparative analysis

Jianquan Cheng, A. Stewart Fotheringham

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


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 (US)
Pages (from-to)138-148
Number of pages11
StatePublished - May 2013
Externally publishedYes


  • Comparative cross-border analysis
  • Geographically Weighted Regression
  • Global regression
  • Ireland
  • Modifiable Areal Unit Problem
  • Multiple scales

ASJC Scopus subject areas

  • Sociology and Political Science


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