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- W2908578954 abstract "Previous studies demonstrate the existence of spatial heterogeneity in the demand for ecosystem services (ES), especially by showing spatial discounting (namely, distance decay) and the effect of substitute sites. Our study adds to this literature by analyzing diverse ways of modeling these two effects and applying them to a scattered ecosystem which provides various ES. For this purpose, novel spatial approaches using different discounting factors and incorporating the presence of substitutes (density-based vs. area-based indexes) have been tested. The analysis is based on a discrete choice experiment (DCE) focusing on the estimation of willingness to pay (WTP) for the ES provided by olive groves in Andalusia (southern Spain). For the econometric specification, we use random parameter logit models in preference space to assess the performance of the proposed spatial indexes. The results show that the introduction of these spatial indexes significantly improves the fit of the models, with the best outcome found for the area-based index combined with the inverse of the distance. In addition, differences are found depending on the ES. For biodiversity and soil conservation (i.e., predominantly use values), a positive relationship between WTP and the spatial index is found, implying that the larger the nearby olive grove area, the larger individuals’ WTP, while the opposite is found for carbon sequestration (i.e., predominantly non-use value). These results have important implications for the design of public policies aimed at improving the agricultural provision of ES." @default.
- W2908578954 created "2019-01-25" @default.
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- W2908578954 date "2018-09-03" @default.
- W2908578954 modified "2023-09-24" @default.
- W2908578954 title "Spatial heterogeneity of WTP values for sparsely-located ecosystem services: alternative index approaches applied to agricultural systems" @default.
- W2908578954 doi "https://doi.org/10.22004/ag.econ.276205" @default.
- W2908578954 hasPublicationYear "2018" @default.
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