The Determinants of Brownfields Redevelopment in England
Alberto Longo () and
Danny Campbell ()
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Alberto Longo: Queen’s University Belfast
Danny Campbell: Economics Division, Stirling Management School, University of Stirling
Environmental & Resource Economics, 2017, vol. 67, issue 2, 261-283
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.
Keywords: Brownfields; GIS; Revealed preferences; Binary choice model; Spatial autocorrelation; Spatial probit latent class model (search for similar items in EconPapers)
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