IDEAS home Printed from https://ideas.repec.org/h/elg/eechap/1315_5.html
   My bibliography  Save this book chapter

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
    as

    Download full text from publisher

    File URL: https://www.elgaronline.com/view/edcoll/9781858986463/9781858986463.00012.xml
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Dansie, B. R., 1985. "Parameter estimability in the multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 19(6), pages 526-528, December.
    3. Small, Kenneth A & Rosen, Harvey S, 1981. "Applied Welfare Economics with Discrete Choice Models," Econometrica, Econometric Society, vol. 49(1), pages 105-130, January.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Bunch, David S., 1991. "Estimability in the Multinomial Probit Model," University of California Transportation Center, Working Papers qt1gf1t128, University of California Transportation Center.
    9. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
    2. Geweke, John & Keane, Michael P & Runkle, David, 1994. "Alternative Computational Approaches to Inference in the Multinomial Probit Model," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 609-632, November.
    3. Paul Gertler & Roland Sturm & Bruce Davidson, 1994. "Information and the Demand for Supplemental Medicare Insurance," NBER Working Papers 4700, National Bureau of Economic Research, Inc.
    4. GRAMMIG, Joachim & HUJER, Reinhard & SCHEIDLER, Michael, 2001. "The econometrics of airline network management," LIDAM Discussion Papers CORE 2001055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Ziegler Andreas, 2010. "Z-Tests in Multinomial Probit Models under Simulated Maximum Likelihood Estimation: Some Small Sample Properties," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(5), pages 630-652, October.
    6. Horowitz, Joel & Keane, Michael & Bolduc, Denis & Divakar, Suresh & Geweke, John & Gonul, Fosun & Hajivassiliou, Vassilis & Koppelman, Frank & Matzkin, Rosa & Rossi, Peter & Ruud, Paul, 1994. "Advances in Random Utility Models," MPRA Paper 53026, University Library of Munich, Germany.
    7. Yai, Tetsuo & Iwakura, Seiji & Morichi, Shigeru, 1997. "Multinomial probit with structured covariance for route choice behavior," Transportation Research Part B: Methodological, Elsevier, vol. 31(3), pages 195-207, June.
    8. Richard Batley & Thijs Dekker, 2019. "The Intuition Behind Income Effects of Price Changes in Discrete Choice Models, and a Simple Method for Measuring the Compensating Variation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 337-366, September.
    9. Friederike Paetz & Winfried J. Steiner, 2017. "The benefits of incorporating utility dependencies in finite mixture probit models," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 793-819, July.
    10. Daziano, Ricardo A., 2015. "Inference on mode preferences, vehicle purchases, and the energy paradox using a Bayesian structural choice model," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 1-26.
    11. Michael Scheidler & Reinhard Hujer & Joachim Grammig, 2005. "Discrete choice modelling in airline network management," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 467-486.
    12. Schwabe, Kurt A. & Schuhmann, Peter W., 1999. "The Value Of Increasing The Length Of Deer Season In Ohio," 1999 Annual meeting, August 8-11, Nashville, TN 21574, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    13. Ziegler, Andreas, 2001. "Simulated z-tests in multinomial probit models," ZEW Discussion Papers 01-53, ZEW - Leibniz Centre for European Economic Research.
    14. Lee, Lung-Fei, 1997. "Simulated maximum likelihood estimation of dynamic discrete choice statistical models some Monte Carlo results," Journal of Econometrics, Elsevier, vol. 82(1), pages 1-35.
    15. Rennings, Klaus & Ziegler, Andreas & Zwick, Thomas, 2001. "Employment changes in environmentally innovative firms," ZEW Discussion Papers 01-46, ZEW - Leibniz Centre for European Economic Research.
    16. Darla Hatton MacDonald & Mark Morrison & Mary Barnes, 2010. "Willingness to Pay and Willingness to Accept Compensation for Changes in Urban Water Customer Service Standards," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(12), pages 3145-3158, September.
    17. Langche Zeng, 2000. "A Heteroscedastic Generalized Extreme Value Discrete Choice Model," Sociological Methods & Research, , vol. 29(1), pages 118-144, August.
    18. Joan L. Walker & Moshe Ben-Akiva & Denis Bolduc, 2007. "Identification of parameters in normal error component logit-mixture (NECLM) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1095-1125.
    19. Tinessa, Fiore & Marzano, Vittorio & Papola, Andrea, 2020. "Mixing distributions of tastes with a Combination of Nested Logit (CoNL) kernel: Formulation and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 1-23.
    20. Donald Boyd & Hamilton Lankford & Susanna Loeb & James Wyckoff, 2013. "Analyzing the Determinants of the Matching of Public School Teachers to Jobs: Disentangling the Preferences of Teachers and Employers," Journal of Labor Economics, University of Chicago Press, vol. 31(1), pages 83-117.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:elg:eechap:1315_5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Darrel McCalla (email available below). General contact details of provider: http://www.e-elgar.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.