IDEAS home Printed from https://ideas.repec.org/p/ags/aaea09/49413.html
   My bibliography  Save this paper

Estimating Mixed Logit Recreation Demand Models With Large Choice Sets

Author

Listed:
  • Domanski, Adam

Abstract

Discrete choice models are widely used in studies of recreation demand. They have proven valuable when modeling situations where decision makers face large choice sets and site substitution is important. However, when the choice set faced by the individual becomes very large (on the order of hundreds or thousands of alternatives), computational limitations make estimation with the full choice set intractable. Sampling of alternatives in a conditional logit framework is an effective method to limit computational burdens while still producing consistent estimates. This method is allowed by the existence of the independence of irrelevant alternatives (IIA) assumption. More advanced mixed logit models account for unobserved preference heterogeneity and overcome the behavioral limitations of the IIA assumption, however in doing so, prohibit sampling of alternatives. A method is developed where a latent class (finite mixture) model is estimated via the expectations-maximization algorithm and in doing so, allows consistent sampling of alternatives in a mixed logit model. The method is tested and applied to a recreational demand Wisconsin fishing survey.

Suggested Citation

  • Domanski, Adam, 2009. "Estimating Mixed Logit Recreation Demand Models With Large Choice Sets," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49413, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea09:49413
    DOI: 10.22004/ag.econ.49413
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/49413/files/Domanski_AAEA.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.49413?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Borsch-Supan, Axel & Hajivassiliou, Vassilis A., 1993. "Smooth unbiased multivariate probability simulators for maximum likelihood estimation of limited dependent variable models," Journal of Econometrics, Elsevier, vol. 58(3), pages 347-368, August.
    2. Timmins, Christopher & Murdock, Jennifer, 2007. "A revealed preference approach to the measurement of congestion in travel cost models," Journal of Environmental Economics and Management, Elsevier, vol. 53(2), pages 230-249, March.
    3. Peter M. Feather, 2003. "Valuing Food Store Access: Policy Implications for the Food Stamp Program," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 162-172.
    4. H. Spencer Banzhaf & V. Kerry Smith, 2007. "Meta-analysis in model implementation: choice sets and the valuation of air quality improvements," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1013-1031.
    5. George R. Parsons & GAndrew J. Plantinga & GKevin J. Boyle, 2000. "Narrow Choice Sets in a Random Utility Model of Recreation Demand," Land Economics, University of Wisconsin Press, vol. 76(1), pages 86-99.
    6. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    7. Stephen Hynes & Nick Hanley & Riccardo Scarpa, 2008. "Effects on Welfare Measures of Alternative Means of Accounting for Preference Heterogeneity in Recreational Demand Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 1011-1027.
    8. Landry, Craig E. & Liu, Haiyong, 2009. "A semi-parametric estimator for revealed and stated preference data--An application to recreational beach visitation," Journal of Environmental Economics and Management, Elsevier, vol. 57(2), pages 205-218, March.
    9. McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
    10. Ruud, Paul A., 1991. "Extensions of estimation methods using the EM algorithm," Journal of Econometrics, Elsevier, vol. 49(3), pages 305-341, September.
    11. Erik Meijer & Jan Rouwendal, 2006. "Measuring welfare effects in models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 227-244.
    12. Roger Haefen, 2008. "Latent Consideration Sets and Continuous Demand Systems," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 41(3), pages 363-379, November.
    13. Dan Rigby & Kelvin Balcombe & Michael Burton, 2009. "Mixed Logit Model Performance and Distributional Assumptions: Preferences and GM foods," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 42(3), pages 279-295, March.
    14. Murdock, Jennifer, 2006. "Handling unobserved site characteristics in random utility models of recreation demand," Journal of Environmental Economics and Management, Elsevier, vol. 51(1), pages 1-25, January.
    15. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    16. 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.
    17. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    18. George R. Parsons & Mary Jo Kealy, 1992. "Randomly Drawn Opportunity Sets in a Random Utility Model of Lake Recreation," Land Economics, University of Wisconsin Press, vol. 68(1), pages 93-106.
    19. Ben-Akiva, M. & Bolduc, D. & Bradley, M., 1993. "Estimation of Travel Choice Models with Randomly Distributed Values of Time," Papers 9303, Laval - Recherche en Energie.
    20. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    21. Riccardo Scarpa & Mara Thiene, 2005. "Destination Choice Models for Rock Climbing in the Northeastern Alps: A Latent-Class Approach Based on Intensity of Preferences," Land Economics, University of Wisconsin Press, vol. 81(3).
    22. Lee, Bosang, 1999. "Calling Patterns and Usage of Residential Toll Service under Self-Selecting Tariffs," Journal of Regulatory Economics, Springer, vol. 16(1), pages 45-81, July.
    23. Edward Morey & Jennifer Thacher & William Breffle, 2006. "Using Angler Characteristics and Attitudinal Data to Identify Environmental Preference Classes: A Latent-Class Model," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(1), pages 91-115, May.
    24. J L Horowitz, 1991. "Modeling the Choice of Choice Set in Discrete-Choice Random-Utility Models," Environment and Planning A, , vol. 23(9), pages 1237-1246, September.
    25. George R. Parsons & Michael S. Needelman, 1992. "Site Aggregation in a Random Utility Model of Recreation," Land Economics, University of Wisconsin Press, vol. 68(4), pages 418-433.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Multivariate Extreme Value (MEV) models," Transportation Research Part B: Methodological, Elsevier, vol. 48(C), pages 31-52.

    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. von Haefen, Roger H. & Domanski, Adam, 2018. "Estimation and welfare analysis from mixed logit models with large choice sets," Journal of Environmental Economics and Management, Elsevier, vol. 90(C), pages 101-118.
    2. Angel Bujosa & Antoni Riera & Robert Hicks, 2010. "Combining Discrete and Continuous Representations of Preference Heterogeneity: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 47(4), pages 477-493, December.
    3. repec:sss:wpaper:201407 is not listed on IDEAS
    4. Richard T. Melstrom & Deshamithra H. W. Jayasekera, 2017. "Two-Stage Estimation to Control for Unobservables in a Recreation Demand Model with Unvisited Sites," Land Economics, University of Wisconsin Press, vol. 93(2), pages 328-341.
    5. Bujosa Bestard, Angel & Font, Antoni Riera, 2009. "Environmental diversity in recreational choice modelling," Ecological Economics, Elsevier, vol. 68(11), pages 2743-2750, September.
    6. Stafford, Tess M., 2018. "Accounting for outside options in discrete choice models: An application to commercial fishing effort," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 159-179.
    7. William Greene, 2001. "Fixed and Random Effects in Nonlinear Models," Working Papers 01-01, New York University, Leonard N. Stern School of Business, Department of Economics.
    8. Catalina M. Torres & Sergio Colombo & Nick Hanley, 2014. "Incorrectly accounting for preference heterogeneity in choice experiments: what are the implications for welfare measurement?," DEA Working Papers 65, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    9. Sergio Colombo & Nick Hanley & Jordan Louviere, 2009. "Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 307-322, May.
    10. Daziano, Ricardo A. & Achtnicht, Martin, 2014. "Accounting for uncertainty in willingness to pay for environmental benefits," Energy Economics, Elsevier, vol. 44(C), pages 166-177.
    11. Hole, Arne Risa, 2008. "Modelling heterogeneity in patients' preferences for the attributes of a general practitioner appointment," Journal of Health Economics, Elsevier, vol. 27(4), pages 1078-1094, July.
    12. Beville, Stephen T. & Kerr, Geoffrey N. & Hughey, Kenneth F.D., 2012. "Valuing impacts of the invasive alga Didymosphenia geminata on recreational angling," Ecological Economics, Elsevier, vol. 82(C), pages 1-10.
    13. Phaneuf, Daniel J. & Smith, V. Kerry, 2006. "Recreation Demand Models," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 2, chapter 15, pages 671-761, Elsevier.
    14. Novikova, Anastasija & Rocchi, Lucia & Vitunskienė, Vlada, 2017. "Assessing the benefit of the agroecosystem services: Lithuanian preferences using a latent class approach," Land Use Policy, Elsevier, vol. 68(C), pages 277-286.
    15. Franceschinis, Cristiano & Thiene, Mara & Scarpa, Riccardo & Rose, John & Moretto, Michele & Cavalli, Raffaele, 2017. "Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory," Energy, Elsevier, vol. 125(C), pages 313-326.
    16. Jee W. Hwang & Chun Kuang & Okmyung Bin, 2019. "Are all Homeowners Willing to Pay for Better Schools? ─ Evidence from a Finite Mixture Model Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 58(4), pages 638-655, May.
    17. Agimass, Fitalew & Lundhede, Thomas & Panduro, Toke Emil & Jacobsen, Jette Bredahl, 2018. "The choice of forest site for recreation: A revealed preference analysis using spatial data," Ecosystem Services, Elsevier, vol. 31(PC), pages 445-454.
    18. Abildtrup, Jens & Garcia, Serge & Olsen, Søren Bøye & Stenger, Anne, 2013. "Spatial preference heterogeneity in forest recreation," Ecological Economics, Elsevier, vol. 92(C), pages 67-77.
    19. Erik Meijer & Jan Rouwendal, 2006. "Measuring welfare effects in models with random coefficients," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 227-244, March.
    20. Termansen, Mette & McClean, Colin J. & Jensen, Frank Søndergaard, 2013. "Modelling and mapping spatial heterogeneity in forest recreation services," Ecological Economics, Elsevier, vol. 92(C), pages 48-57.
    21. Hicks, Robert L. & Holland, Daniel S. & Kuriyama, Peter T. & Schnier, Kurt E., 2020. "Choice sets for spatial discrete choice models in data rich environments," Resource and Energy Economics, Elsevier, vol. 60(C).

    More about this item

    Keywords

    Environmental Economics and Policy; Research Methods/ Statistical Methods;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ags:aaea09:49413. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.