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Semiparametric Estimation of the Binary Choice Model for Contingent Valuation

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  • Chuan-Zhong Li

Abstract

This paper is concerned with the estimation of the binary choice model without imposing any parametric structure on the distribution of the stochastic term. We adapt the distribution-free maximum likelihood method developed by Cosslett (1983) for deriving the contingent value function with respect to observable exogenous variables. We present Monte Carlo comparisons with the probit estimates and discuss the asymptotic consistency and relative efficiency of the approach. Data from a forest environment valuation survey are used for empirical estimations.

Suggested Citation

  • Chuan-Zhong Li, 1996. "Semiparametric Estimation of the Binary Choice Model for Contingent Valuation," Land Economics, University of Wisconsin Press, vol. 72(4), pages 462-473.
  • Handle: RePEc:uwp:landec:v:72:y:1996:i:4:p:462-473
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    Cited by:

    1. Álvarez Díaz, Marcos & González Gómez, Manuel & Saavedra González, Ángeles & De Uña Álvarez, Jacobo, 2010. "On dichotomous choice contingent valuation data analysis: Semiparametric methods and Genetic Programming," Journal of Forest Economics, Elsevier, vol. 16(2), pages 145-156, April.
    2. Erik Bergkvist, 2001. "The value of time and forecasting of flowsin freight transportation," ERSA conference papers ersa01p271, European Regional Science Association.
    3. Lindhjem, Henrik, 2007. "20 years of stated preference valuation of non-timber benefits from Fennoscandian forests: A meta-analysis," Journal of Forest Economics, Elsevier, vol. 12(4), pages 251-277, February.
    4. Henry-Osorio, Miguel & Mittelhammer, Ronald C., 2012. "An Information-Theoretic Approach to Modeling Binary Choices: Estimating Willingness to Pay for Recreation Site Attributes," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123432, Agricultural and Applied Economics Association.
    5. Huang, Ju-Chin & Nychka, Douglas W. & Smith, V. Kerry, 2008. "Semi-parametric discrete choice measures of willingness to pay," Economics Letters, Elsevier, vol. 101(1), pages 91-94, October.
    6. Silvia Ferrini & Carlo Fezzi, 2012. "Generalized Additive Models for Nonmarket Valuation via Revealed or Stated Preference Methods," Land Economics, University of Wisconsin Press, vol. 88(4), pages 782-802.
    7. Arana, Jorge E. & Leon, Carmelo J., 2005. "Flexible mixture distribution modeling of dichotomous choice contingent valuation with heterogenity," Journal of Environmental Economics and Management, Elsevier, vol. 50(1), pages 170-188, July.
    8. Pouta, Eija & Rekola, Mika & Kuuluvainen, Jari & Li, Chuan-Zhong & Tahvonen, Olli, 2002. "Willingness to pay in different policy-planning methods: insights into respondents' decision-making processes," Ecological Economics, Elsevier, vol. 40(2), pages 295-311, February.
    9. Florios, Kostas & Skouras, Spyros, 2008. "Exact computation of max weighted score estimators," Journal of Econometrics, Elsevier, vol. 146(1), pages 86-91, September.
    10. Riccardo Scarpa, 2000. "Contingent Valuation Versus Choice Experiments: Estimating the Benefits of Environmentally Sensitive Areas in Scotland: Comment," Journal of Agricultural Economics, Wiley Blackwell, vol. 51(1), pages 122-128.

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