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- W2127970749 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 future potential for improved econometric analyses of discrete choice processes compared to the commonly used parametric methods." @default.
- W2127970749 created "2016-06-24" @default.
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- W2127970749 date "2012-01-21" @default.
- W2127970749 modified "2023-09-26" @default.
- W2127970749 title "Estimating Willingness to Pay for Recreation Site Attributes Using Information-Theoretic Methods" @default.
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