Semiparametric estimation of the binary choice model for contingent valuation.
Research was conducted to attempt to estimate the binary choice model without imposing any parametric structure on the distribution of the stochastic term. The distribution-free maximum likelihood method developed by Stephen Cosslett (1983) is adapted for deriving the contingent value function with...
| Publicado en: | Land Economics Vol. 72; pp. 462 - 474 |
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| Autor principal: | |
| Formato: | Artículo |
| Publicado: |
University of Wisconsin Press
November 1996
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Research was conducted to attempt to estimate the binary choice model without imposing any parametric structure on the distribution of the stochastic term. The distribution-free maximum likelihood method developed by Stephen Cosslett (1983) is adapted for deriving the contingent value function with respect to observable exogenous variables. Monte Carlo comparisons with the probit estimates are presented, and the asymptotic consistency and relative efficiency of the approach are discussed. Data from a forest environment valuation survey are employed for empirical estimations. |
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