An Information-Theoretic Approach to Modeling Binary Choices: Estimating Willingness to Pay for Recreation Site Attributes

Miguel Henry () and Ron Mittelhammer ()

No 123432, 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington from Agricultural and Applied Economics Association

Abstract: This paper applies the new 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 Kriström/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. We argue, based on the decision context and demographics of decision makers visiting the recreation sites, that the ML-MPD approach suggests a more defensible representation of the underlying data-generating process and economic decision-making behavior. As such, the ML-MPD estimator suggests future potential for improved econometric analyses of discrete behavioral decision choice processes.

Keywords: Environmental Economics and Policy; Research Methods/Statistical Methods (search for similar items in EconPapers)
Pages: 33
Date: 2012
New Economics Papers: this item is included in nep-dcm, nep-env and nep-tur
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea12:123432

DOI: 10.22004/ag.econ.123432

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