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Taste Indicators and Heterogeneous Revealed Preferences for Congestion in Recreation Demand

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  • Vasquez Lavin, Felipe
  • Hanemann, W. Michael

Abstract

Researchers using revealed preference data have mostly relied on the Mixed Logit (ML) framework to model unobserved heterogeneity. In this paper, we suggest an extension of this model where we integrate direct measures of taste and revealed preferences, under a unified econometric setting, to describe heterogeneous preferences for congestion in recreation demand. ML is a random parameter discrete choice model, which decomposes the coefficients of the regression equation into a mean effect shared by all individuals in the sample, and a deviation with respect to this mean, specific to each individual. Within this structure, heterogeneity is summarized using a parametric density function for the coefficients of the model. From this distribution one can identify the portion of people who like or dislike an attribute of the good. On the other hand, taste indicators, represented in a like-dislike scale, constitute complementary information about the distribution of tastes in the population. We combine both sources of information to characterize preferences in our model. The traditional ML suggests almost 60% of people in the sample like crowded places while our integrated model implies almost 100% of the people dislike congestion. These results show the bene…ts of using taste indicators to describe heterogeneous preferences for attributes describing alternatives of a choice set.

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Bibliographic Info

Paper provided by Department of Agricultural & Resource Economics, UC Berkeley in its series Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series with number qt4rz5z706.

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Date of creation: 11 Jun 2008
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Handle: RePEc:cdl:agrebk:qt4rz5z706

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Keywords: mixed logic framework; recreation demand; research;

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  1. J. Miguel Villas-Boas & Russell S. Winer, 1999. "Endogeneity in Brand Choice Models," Management Science, INFORMS, vol. 45(10), pages 1324-1338, October.
  2. Walker, Joan & Ben-Akiva, Moshe, 2002. "Generalized random utility model," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 303-343, July.
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  9. Harris, Katherine M. & Keane, Michael P., 1998. "A model of health plan choice:: Inferring preferences and perceptions from a combination of revealed preference and attitudinal data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 131-157, November.
  10. 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.
  11. Train, Kenneth E & McFadden, Daniel L & Goett, Andrew A, 1987. "Consumer Attitudes and Voluntary Rate Schedules for Public Utilities," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 383-91, August.
  12. Bell, Frederick W. & Leeworthy, Vernon R., 1990. "Recreational demand by tourists for saltwater beach days," Journal of Environmental Economics and Management, Elsevier, vol. 18(3), pages 189-205, May.
  13. F. J. Anderson & N. C. Bonsor, 1974. "Allocation, Congestion, and the Valuation of Recreational Resources," Land Economics, University of Wisconsin Press, vol. 50(1), pages 51-57.
  14. Peter Schuhmann & Kurt Schwabe, 2004. "An Analysis of Congestion Measures and Heterogeneous Angler Preferences in a Random Utility Model of Recreational Fishing," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 27(4), pages 429-450, April.
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  17. Louviere, Jordan J, 2001. " What If Consumer Experiments Impact Variances as Well as Means? Response Variability as a Behavioral Phenomenon," Journal of Consumer Research, University of Chicago Press, vol. 28(3), pages 506-11, December.
  18. Jordan Louviere & Kenneth Train & Moshe Ben-Akiva & Chandra Bhat & David Brownstone & Trudy Cameron & Richard Carson & J. Deshazo & Denzil Fiebig & William Greene & David Hensher & Donald Waldman, 2005. "Recent Progress on Endogeneity in Choice Modeling," Marketing Letters, Springer, vol. 16(3), pages 255-265, December.
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Cited by:
  1. Jensen, Kimberly L. & Clark, Christopher D. & English, Burton C. & Menard, R. Jamey & Skahan, Denise K. & Marra, Adrienne C., 2010. "Willingness to pay for E85 from corn, switchgrass, and wood residues," Energy Economics, Elsevier, vol. 32(6), pages 1253-1262, November.

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