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Citation
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HERO ID
3329522
Reference Type
Journal Article
Title
Recreation demand estimation and valuation in spatially connected systems
Author(s)
Newbold, SC; Massey, DM
Year
2010
Is Peer Reviewed?
1
Journal
Resource and Energy Economics
ISSN:
0928-7655
Volume
32
Issue
2
Page Numbers
222-240
DOI
10.1016/j.reseneeco.2009.11.014
Web of Science Id
WOS:000276109900009
Abstract
Recreation demand models frequently are used to explain outdoor recreation behavior and to estimate willingness to pay for changes in environmental quality at recreation sites. Among the most commonly used recreation demand models are site choice models based on the multinomial logit framework, which account for the spatial relationships between each recreator's home and multiple alternative destinations thereby capturing the substitution possibilities among recreation sites. However, standard applications of this framework typically do not account for the possibility of spatial connections among the sites via movements of the target species, such as fish in connected water bodies in recreational angling applications or terrestrial species in hunting or wildlife viewing applications. In this paper we examine aspects of environmental valuation and natural resource dynamics that generally are addressed separately. Specifically, we show that in such spatially connected systems, a "reduced form" application of the standard site choice modeling approach, using proxy measures of environmental quality rather than direct measures of species abundances, can produce biased estimates of willingness to pay for environmental improvements. Furthermore, we show that under some conditions poorly targeted environmental improvements in spatially connected systems can lead to welfare decreases. In such systems a structural model of recreator site choices and species sorting behavior and population dynamics may be required to fully account for the spatial linkages among sites and the feedback effects between recreators and the target species. (C) 2009 Published by Elsevier B.V.
Keywords
Bioeconomic; Site-choice model; Spatial spillovers
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