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Measuring the Social Recreation Per-Day Net Benefit of Wildlife Amenities of a National Park: A Count-Data Travel Cost Approach

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  • Isabel Mendes
  • Isabel Proença

Abstract

We applied count-data travel cost methods to a truncated sample of visitors, to estimate the average CS per each day of visit of an individual, visiting the Peneda- Gerês National Park to enjoy their natural facilities for recreation purposes. As the recreation demand was measured in number of days of stay in the park the behaviour of the dependent variable is very specific. To overcome this situation, we propose the use of altered truncated count data models or truncated count data models on grouped data because we found they were better adjusted to our data set. The average individual CS per day is estimated to be €194 varying between €116 and €448, with Simulated Limits. This information is useful in the formulation of government policy relating directly to national parks and conservation and the determination of future natural park management. To our knowledge this is the first attempt to measure the average recreation net benefits per each day of stay supported by a national park, by using truncated altered and truncated grouped count data Travel Cost Model based on the observation of individual (not household) number of days of stay. Key words: Social Recreation Benefits; Wildlife Amenities; Count Data Models; Travel Cost.

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Bibliographic Info

Paper provided by ISEG - School of Economics and Management, Department of Economics, University of Lisbon in its series Working Papers Department of Economics with number 2009/35.

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Date of creation: Sep 2009
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Handle: RePEc:ise:isegwp:wp352009

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Postal: Department of Economics, ISEG - School of Economics and Management, University of Lisbon, Rua do Quelhas 6, 1200-781 LISBON, PORTUGAL
Web page: https://aquila1.iseg.ulisboa.pt/aquila/departamentos/EC

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Cited by:
  1. Hynes, Stephen & Greene, William, 2011. "Estimating recreation demand with on-site panel data: An application of a latent class truncated and endogenously stratified count data model," Working Papers 148925, Socio-Economic Marine Research Unit, National University of Ireland, Galway.

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