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An Empirical Assessment of Multinomial Probit and Logit Models for Recreation Demand

In: Valuing Recreation and the Environment

Author

Listed:
  • Heng Z. Chen
  • Frank Lupi
  • John P. Hoehn
Abstract
This impressive volume analyzes revealed preference approaches to modelling the demand for recreational resources. It presents one of the most thorough treatments of methods that rely on observed behavior to estimate the value of environmental amenities.

Suggested Citation

  • Heng Z. Chen & Frank Lupi & John P. Hoehn, 1999. "An Empirical Assessment of Multinomial Probit and Logit Models for Recreation Demand," Chapters, in: Joseph A. Herriges & Catherine L. Kling (ed.), Valuing Recreation and the Environment, chapter 5, pages 141-162, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:1315_5
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    References listed on IDEAS

    as
    1. Dansie, B. R., 1985. "Parameter estimability in the multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 19(6), pages 526-528, December.
    2. Small, Kenneth A & Rosen, Harvey S, 1981. "Applied Welfare Economics with Discrete Choice Models," Econometrica, Econometric Society, vol. 49(1), pages 105-130, January.
    3. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    4. Edward R. Morey & Robert D. Rowe & Michael Watson, 1993. "A Repeated Nested-Logit Model of Atlantic Salmon Fishing," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 75(3), pages 578-592.
    5. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
    6. Bunch, David S., 1991. "Estimability in the Multinomial Probit Model," University of California Transportation Center, Working Papers qt1gf1t128, University of California Transportation Center.
    7. Hanemann, W. Michael, 1982. "Applied Welfare Analysis with Qualitative Response Models," CUDARE Working Papers 7160, University of California, Berkeley, Department of Agricultural and Resource Economics.
    8. Vassilis A. Hajivassiliou & Daniel McFadden, 1990. "The Method of Simulated Scores for the Estimation of LDV Models with an Application to External Debt Crisis," Cowles Foundation Discussion Papers 967, Cowles Foundation for Research in Economics, Yale University.
    9. Catherine L. Kling & Joseph A. Herriges, 1995. "An Empirical Investigation of the Consistency of Nested Logit Models with Utility Maximization," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(4), pages 875-884.
    10. Bishop, Richard C. & Heberlein, Thomas A., 1979. "Measuring Values Of Extramarket Goods: Are Indirect Measures Biased?," 1979 Annual Meeting, July 29-August 1, Pullman, Washington 277818, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    11. Bunch, David S., 1991. "Estimability in the multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 25(1), pages 1-12, February.
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