2009
DOI: 10.1007/s10640-009-9291-7
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Deriving and Testing Efficient Estimates of WTP Distributions in Destination Choice Models

Abstract: Estimation of welfare measures is often a dominant driver in the empirical literature on nonmarket valuation. To this end, qualitative choice models based on random utility theory have been widely employed in outdoor recreation studies. A requent goal of applied studies has been the estimation of welfare changes associated with site attribute changes at\ud recreation sites in order to inform regulatory policy and resource management. We review the evolution of the methodology of random utility theory in this f… Show more

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Cited by 100 publications
(58 citation statements)
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“…The coefficients in the preference space and WTP space models can be estimated by using maximum simulated likelihood or hierarchical Bayesian methods [28]. The estimation was conducted by using the "gmnl" package with STATA 13 [29], following Thiene and Scarpa [30].…”
Section: The Calculation Of Marginal Substitution Ratiomentioning
confidence: 99%
“…The coefficients in the preference space and WTP space models can be estimated by using maximum simulated likelihood or hierarchical Bayesian methods [28]. The estimation was conducted by using the "gmnl" package with STATA 13 [29], following Thiene and Scarpa [30].…”
Section: The Calculation Of Marginal Substitution Ratiomentioning
confidence: 99%
“…Because we used a RPL model, the welfare estimates had to be obtained through simulating these ratios. Using the mean and standard deviation of each distribution, we simulated the WTP distribution for each attribute 10 000 times (as per Thiene and Scarpa, 2009). We report the mean, and the upper and lower quartiles (i.e.…”
Section: Study Breed and Areamentioning
confidence: 99%
“…Location choice models are applied to several other different contexts, such as the choice of a departure airport (Furuichi and Koppelman;1994), the choice of a hospital for patients by general practitioner (primary care physicians) (Whynes et al;, the choice of touristic destinations (Woodside and Lysonski;1989;Um and Crompton;1990;Eymann and Ronning;Oppermann;2000;Seddighi and Theocharous;Bigano et al;2006;Chi and Qu;Gössling et al; and in particular recreational outdoor facilities (Fesenmaier;1988;Scarpa and Thiene;2005;Thiene and Scarpa;2009), the choice of migrants (Fotheringham;1986) and the optimal allocation of charging stations for electric vehicles .…”
Section: Location Choicementioning
confidence: 99%