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Spatial DEA with independent neighbours’ inputs: healthcare efficiency patterns in Europe

Author

Listed:
  • Jakub Olejnik
  • Agata Żółtaszek
  • Alicja Olejnik

Abstract

This study presents a new method – SDEA-INI (spatial data envelopment analysis-independent neighbours’ inputs) – that integrates spatial interactions and non-discretionary input restrictions into data envelopment analysis to address the issue of uncontrollable spatial inputs. Monte Carlo simulations show that spatial data envelopment analysis (SDEA) outperforms data envelopment analysis (DEA) under spatial dependence, while SDEA-INI is best when inputs are uncontrollable. We employ this novel approach to evaluate healthcare efficiency across European regions. Our results reveal an inefficient core (Germany, Austria) and a more efficient periphery (Central, Eastern and Southern Europe). Our approach supports resource allocation and fosters greater cooperation and cohesion across Europe’s diverse healthcare systems.

Suggested Citation

  • Jakub Olejnik & Agata Żółtaszek & Alicja Olejnik, 2026. "Spatial DEA with independent neighbours’ inputs: healthcare efficiency patterns in Europe," Spatial Economic Analysis, Taylor & Francis Journals, vol. 21(2), pages 187-204, April.
    • Handle: RePEc:taf:specan:v:21:y:2026:i:2:p:187-204
    DOI: 10.1080/17421772.2025.2600420
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