Registro completo |
Provedor de dados: |
AgEcon
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País: |
United States
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Título: |
An Information-Theoretic Approach to Modeling Binary Choices: Estimating Willingness to Pay for Recreation Site Attributes
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Autores: |
Henry-Osorio, Miguel
Mittelhammer, Ronald C.
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Data: |
2012-05-14
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Ano: |
2012
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Palavras-chave: |
Minimum power divergence
Cressie-Read statistics
Contingent valuation
Empirical likelihood
Discrete choice
Binary response models
Environmental Economics and Policy
Research Methods/ Statistical Methods
C13
C14
C25
Q51
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Resumo: |
Information-Theoretic Econometrics
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.
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Tipo: |
Presentation
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Idioma: |
Inglês
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Identificador: |
http://purl.umn.edu/123432
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Relação: |
Agricultural and Applied Economics Association>2012 Annual Meeting, August 12-14, 2012, Seattle, Washington
Selected Paper
313
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Formato: |
33
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