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Tyler P.,University of Cambridge | Warnock C.,Cambridge Economic Associates | Provins A.,Economics for the Environment Consultancy eftec | Lanz B.,Economy Energy
Urban Studies | Year: 2013

Although there have been many initiatives designed to regenerate relatively run-down and deprived parts of major urban areas, there have been surprisingly few attempts to value their benefits. This article presents the findings of research that has sought to value the benefits of urban regeneration policies. The focus has been on devising an approach that can build on the evidence provided from urban evaluations undertaken in many countries at the present time. It uses established techniques and statistical data sources that are fairly readily available. The evaluation of urban policy is subject to substantial conceptual and measurement problems and this should be recognised in interpreting valuation results and thus benefit-cost ratios. The article shows how the approach can be applied by drawing on recent UK evaluation evidence and data for England. It concludes by discussing where future research might be directed. © 2012 Urban Studies Journal Limited. Source


Lanz B.,ETH Zurich | Provins A.,Economics for the Environment Consultancy eftec
Environmental and Resource Economics | Year: 2013

Using discrete choice experiments we examine preferences for the spatial provision of local environmental improvements in the context of regeneration policies. Amenities we consider are: improvements to areas of open space, recreation facilities and other public spaces; street cleanliness; restoration of derelict properties; and the provision of paths dedicated to cycling and walking. We include the spatial scope of the policy as an attribute, making the trade-off between environmental amenity and its spatial provision explicit. We employ a novel estimator for average willingness to pay (WTP) for mixed logit models with a random cost coefficient, which is robust to the presence of price insensitive respondents and performs well relative to mixed logit estimation in WTP space. We find that the spatial scope of the policy affects both the intensity and heterogeneity of preferences, and that these effects are of statistical and economic significance. © 2013 Springer Science+Business Media Dordrecht. Source


Sen A.,University of East Anglia | Darnell A.,University of East Anglia | Bateman I.,University of East Anglia | Munday P.,University of East Anglia | And 6 more authors.
Working Paper - Centre for Social and Economic Research on the Global Environment | Year: 2012

In this paper we present a novel methodology to determine the annual value of recreational visit flows to different habitat types in Great Britain. We combine different empirical models to predict the spatial distributions of recreational value across Great Britain. The models use a combination of the latest and most extensive recreation survey in England, detailed spatial data, and extensive literature review. These data combine to form an input dataset with over four million unique observations. Aimed at planning for recreational demand at a national-level across mixed habitats, the estimated model is applied to the six UK National Ecosystem Assessment scenarios for land cover in 2060. Final predictions are generated nationally at a range of spatial scales, providing a comprehensive assessment of the spatial diversity of present and future recreation value. While our methodology is subject to a few shortcomings, it offers a new and spatially sensitive tool for modelling open-access recreation demand that can be applied to recreation planning and environmental decision-making at any desired spatial unit. Source


Sen A.,University of East Anglia | Harwood A.R.,University of East Anglia | Bateman I.J.,University of East Anglia | Munday P.,University of East Anglia | And 7 more authors.
Environmental and Resource Economics | Year: 2014

We present a novel methodology for spatially sensitive prediction of outdoor recreation visits and values for different ecosystems. Data on outset and destination characteristics and locations are combined with survey information from over 40,000 households to yield a trip generation function (TGF) predicting visit numbers. A new meta-analysis (MA) of relevant literature is used to predict site specific per-visit values. Combining the TGF and MA models permits spatially explicit estimation of visit numbers and values under present and potential future land use. Applications to the various land use scenarios of the UK National Ecosystem Assessment, as well as to a single site, are presented. © 2013 Springer Science+Business Media Dordrecht. Source

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