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The Determinants of Brownfields Redevelopment in England

Author

Listed:
  • Alberto Longo

    (Queen’s University Belfast
    Basque Centre for Climate Change (BC3))

  • Danny Campbell

    (Economics Division, Stirling Management School, University of Stirling)

Abstract

This paper uses discrete choice models, supported by GIS data, to analyse the National Land Use Database, a register of more than 21,000 English brownfields—previously used sites with or without contamination that are currently unused or underused. Using spatial discrete choice models, including the first application of a spatial probit latent class model with class-specific neighbourhood effects, we find evidence of large local differences in the determinants of brownfields redevelopment in England and that the reuse decisions of adjacent sites affect the reuse of a site. We also find that sites with a history of industrial activities, large sites, and sites that are located in the poorest and bleakest areas of cities and regions of England are more difficult to redevelop. In particular, we find that the probability of reusing a brownfield increases by up to 8.5 % for a site privately owned compared to a site publicly owned and between 15 and 30 % if a site is located in London compared to the North West of England. We suggest that local tailored policies are more suitable than regional or national policies to boost the reuse of brownfield sites.

Suggested Citation

  • Alberto Longo & Danny Campbell, 2017. "The Determinants of Brownfields Redevelopment in England," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(2), pages 261-283, June.
  • Handle: RePEc:kap:enreec:v:67:y:2017:i:2:d:10.1007_s10640-015-9985-y
    DOI: 10.1007/s10640-015-9985-y
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    References listed on IDEAS

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    2. Yani Lai & Lin Jiang & Xiaoxiao Xu, 2021. "Exploring Spatio-Temporal Patterns of Urban Village Redevelopment: The Case of Shenzhen, China," Land, MDPI, vol. 10(9), pages 1-26, September.
    3. Khansa Gulshad & Yicheng Wang & Na Li & Jing Wang & Qian Yu, 2022. "Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China," Land, MDPI, vol. 11(3), pages 1-21, February.
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    5. Hanxue Wei & Lucien C. Wostenholme & John I. Carruthers, 2021. "Planning and Markets at Work: Seattle under Growth Management and Economic Pressure," Sustainability, MDPI, vol. 13(14), pages 1-18, July.
    6. Lin Jiang & Yani Lai & Ke Chen & Xiao Tang, 2022. "What Drives Urban Village Redevelopment in China? A Survey of Literature Based on Web of Science Core Collection Database," Land, MDPI, vol. 11(4), pages 1-16, April.
    7. Lappi, Pauli, 2018. "Optimal clean-up of polluted sites," Resource and Energy Economics, Elsevier, vol. 54(C), pages 53-68.
    8. Oriyomi Modupe Okeyinka & Rana Khan & Chaminda Pathirage & Charf El Dine Mahammedi & Antony West, 2023. "A Critical Review of Developers’ Decision Criteria for Brownfield Regeneration: Development of the BRIC Index," Sustainability, MDPI, vol. 15(9), pages 1-25, April.
    9. Bez, Charlotte S. & Ash, Michael & Boyce, James K., 2024. "Environmental inequality in industrial brownfields: Evidence from French municipalities," Ecological Economics, Elsevier, vol. 217(C).
    10. Cao, Kexin & Deng, Yu & Wang, Wenxue & Liu, Shenghe, 2023. "The spatial heterogeneity and dynamics of land redevelopment: Evidence from 287 Chinese cities," Land Use Policy, Elsevier, vol. 132(C).
    11. Ahmad, Naveed & Zhu, Yuming & Hongli, Lin & Karamat, Jawad & Waqas, Muhammad & Taskheer Mumtaz, Syed Muhammad, 2020. "Mapping the obstacles to brownfield redevelopment adoption in developing economies: Pakistani Perspective," Land Use Policy, Elsevier, vol. 91(C).
    12. Carlos Bueno-Suárez & Daniel Coq-Huelva, 2020. "Sustaining What Is Unsustainable: A Review of Urban Sprawl and Urban Socio-Environmental Policies in North America and Western Europe," Sustainability, MDPI, vol. 12(11), pages 1-36, May.

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