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- W3121253781 abstract "This paper applies the maximum likelihood-minimum power divergence (ML-MPD) binary response estimator developed by Mittelhammer and Judge (2011) to model the underlying behavioral decision process that leads to a person’s willingness to pay for recreation site attributes. Empirical choice probabilities, willingness to pay (WTP) measures for recreation site attributes, and marginal probability effects of decision-maker characteristics are estimated based on a real stated-preference on-site contingent valuation data, collected at the Caribbean National Forest in Puerto Rico. For comparison purposes, the linear probit model and the Kristrom/Ayer’s estimators are implemented. The ML-MPD method yields a significantly lower mean WTP estimate ($27.80) to attend the recreation sites compared to WTP measures obtained from the fully parametric ($120) and fully non-parametric ($97) approaches. The ML-MPD results suggest a more defensible representation of the underlying data-generating process and economic decision-making behavior, and improved econometric analyses of discrete choice processes compared to the commonly used parametric methods." @default.
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- W3121253781 date "2016-08-01" @default.
- W3121253781 modified "2023-09-23" @default.
- W3121253781 title "An Information Theoretic Approach to Estimating Willingness to Pay for River Recreation Site Attributes" @default.
- W3121253781 hasPublicationYear "2016" @default.
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