Aestimum 76 (2020)
Original Articles - Appraisal and rural economics

Modeling preference heterogeneity in recreation random utility models when relevant information about users is limited

Maria De Salvo
University of Catania, Department of Agriculture, Food and Environment, Centre for the Conservation and Management of Nature and Agroecosystems (Cutgana), Italy
Giuseppe Cucuzza
University of Catania, Department of Agriculture, Food and Environment, Centre for the Conservation and Management of Nature and Agroecosystems (Cutgana), Italy
Carlo Prato
University of Catania, Centre for the Conservation and Management of Nature and Agroecosystems (Cutgana), Italy
Giovanni Signorello
University of Catania, Department of Agriculture, Food and Environment, Centre for the Conservation and Management of Nature and Agroecosystems (Cutgana), Italy
Published June 23, 2020
Keywords
  • recreation demand,
  • heterogeneity,
  • location-specific mixed logit model,
  • willingness-to-pay space,
  • Hunting
How to Cite
De Salvo, M., Cucuzza, G., Prato, C., & Signorello, G. (2020). Modeling preference heterogeneity in recreation random utility models when relevant information about users is limited. Aestimum, 76(1), 5-17. https://doi.org/10.13128/aestim-7792

Abstract

We suggest a novel approach to analyze revealed preference heterogeneity in recreation random utility maximization models when information about users is limited to their place of residence. We assume that recreationists living in the same place act as a “cohort” and that their preferences are hence homogeneous. We adopt a location-specific distribution criterion. We empirically test the suitability of this spatial approach by comparing its econometric performance and welfare estimates with that of the standard individual framework. We use data on hunting in Sicily to empirically test the cohort approach. Results from individual-specific and location-specific mixed logit models suggest that econometric performance improves when modeling heterogeneity with a location-specific conditional distribution. Further, marginal willingness-to-pay mean values and distributions for site characteristics differ significantly.

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