Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/22997
Appears in Collections:Economics Journal Articles
Peer Review Status: Refereed
Title: The determinants of brownfields redevelopment in England
Author(s): Longo, Alberto
Campbell, Danny
Contact Email: danny.campbell@stir.ac.uk
Keywords: Brownfields
GIS
Revealed preferences
Binary choice model
Spatial autocorrelation
Spatial probit latent class model
Issue Date: May-2017
Date Deposited: 22-Mar-2016
Citation: Longo A & Campbell D (2017) The determinants of brownfields redevelopment in England. Environmental and Resource Economics, 67, pp. 261-283. https://doi.org/10.1007/s10640-015-9985-y
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.
DOI Link: 10.1007/s10640-015-9985-y
Rights: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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