Estimating Mixed Logit Recreation Demand Models With Large Choice Sets
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.
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- 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.
- Vassilis A. Hajivassiliou & Axel Borsch-Supan, 1990. "Smooth Unbiased Multivariate Probability Simulators for Maximum Likelihood Estimation of Limited Dependent Variable Models," Cowles Foundation Discussion Papers 960, Cowles Foundation for Research in Economics, Yale University.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- McFadden, Daniel & Ruud, Paul A, 1994. "Estimation by Simulation," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 591-608, November.
- Ruud, Paul A., 1991.
"Extensions of estimation methods using the EM algorithm,"
Journal of Econometrics,
Elsevier, vol. 49(3), pages 305-341, September.
- Paul A. Ruud., 1988. "Extensions of Estimation Methods Using the EM Algorithm.," Economics Working Papers 8899, University of California at Berkeley.
- 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.
- 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.
- Smith, V. Kerry & Banzhaf, H. Spencer, 2003. "Meta Analysis in Model Implementation: Choice Sets and the Valuation of Air Quality Improvements," Discussion Papers dp-03-61, Resources For the Future.
- 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.
- 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.
- Meijer, E. & Rouwendal, J., 2000. "Measuring welfare effects in models with random coefficients," Research Report 00F25, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
- 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.
- Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
- 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.
- 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).
- 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.
- John F. Geweke & Michael P. Keane & David E. Runkle, 1994. "Alternative computational approaches to inference in the multinomial probit model," Staff Report 170, Federal Reserve Bank of Minneapolis.
- 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.
- 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.
- 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.
- 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.
- 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)
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