Optimized quantity-within-distance models of spatial welfare heterogeneity

Using Individualised Choice Maps to Capture the Spatial Dimensions of Value Within Choice Experiments

“…The incorporation of space within CE studies is an increasing feature of the valuation literature (e.g. Adamowicz et al 1994;Johnston et al 2002;Campbell et al 2008Campbell et al , 2009Brouwer et al 2010;Schaafsma et al 2012Meyerhoff 2013;Johnston and Ramachandran 2014;Czajkowski et al 2016a;Johnston et al 2016;Interis and Petrolia 2016;Holland and Johnston 2017;Bakhtiari et al 2018;De Valck and Rolfe 2018;Glenk et al 2019). Initial interest in the spatial aspects of environmental preferences within stated preference (SP) valuation studies was motivated by the definition of relevant markets for aggregation of estimated values (e.g.…”

“…The spatial context of choices has been increasingly portrayed through maps and graphics (e.g. Bateman et al 2011a, b, c;Schaafsma et al 2012Johnston et al 2016;Holland and Johnston 2017). Maps and spatial information in general have been shown to influence spatial and non-spatial policy attributes as well as WTP estimates in SP studies (Johnston et al 2002(Johnston et al , 2016.…”

Spatial analysis of demand for sparsely located ecosystem services using alternative index approaches

“…As shown in Section 2.2, the distance to environmental sites may not be a sufficiently accurate measure for explaining the heterogeneity in individuals' WTP for scattered ecosystems (as most agricultural systems are). This explains why area-and density-based approaches have been proposed for these cases as alternative approaches for spatial discounting (Yao et al, 2014;Nielsen, Lundhede and Jacobsen, 2016;De Valck et al, 2017;Holland and Johnston, 2017). However, to the authors' knowledge, none of the previous works have explicitly explained the theoretical basis justifying the use of these spatial indexes.…”

“…Nielsen, Lundhede and Jacobsen (2016) use a similar approach, calculating the area within a 2.5 km buffer of each respondent's home. Holland and Johnston (2017) propose an approach that relies on the quantity-within-distance-x, explaining WTP patterns regarding riparian land restoration in Maine (USA) based on the quantity of an affected resource surrounding each respondent within an optimised distance band or radius around each home. De Valck et al 2017analyse preferences for nature restoration in Flanders (Belgium) by computing the density (instead of the area) of nature sites within various ranges from each respondent's home and applying spatial discounting factors to approximate different functional forms of the density gradient effect.…”

“…a natural park), while more complex locations, such as sparsely-located sites, have received much less attention. Although a few applications have focused on sites of the latter type, including forest areas (Czajkowski et al, 2017) and riparian zones (Holland and Johnston, 2017), to the authors' knowledge there is no study directly focusing on agricultural systems. If we consider substitutability and directional issues, it can be readily inferred that distance-decay models may perform poorly compared to area-and density-based models when applied to these sparsely-located ecosystems (Lizin et al, 2016;Budziński et al, 2018).…”