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On The Frontier Of Generating Revealed Preference Choice Sets: An Efficient Approach

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  • Scrogin, David
  • Hofler, Richard
  • Boyle, Kevin J.
  • Milon, J. Walter

Abstract

Deterministic rules for generating choice sets are often employed by analysts confronting universal sets with large numbers of alternatives. For destination choice analysis, site exclusion rules defined by travel time, distance, or quality have a behavioral appeal, yet are fundamentally limited by their one-dimension scope. To remedy this shortcoming while maintaining the concept that trips require costly inputs to yield utility generating outputs, we develop and test an exclusion rule for generating choice sets defined by efficiency measures derived from stochastic frontier econometric models. Choice set composition, site choice efficiency and probability of selection, and consumer surplus are compared with results obtained under alternative exclusion rules.

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Bibliographic Info

Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2004 Annual meeting, August 1-4, Denver, CO with number 20134.

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Date of creation: 2004
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Handle: RePEc:ags:aaea04:20134

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Keywords: Research Methods/ Statistical Methods;

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  1. Timothy C. Haab & Robert L. Hicks, . "Accounting for Choice Set Endogeneity in Random Utility Models of Recreation Demand," Working Papers 9608, East Carolina University, Department of Economics.
  2. 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.
  3. Robert L. Hicks & Ivar E. Strand, 2000. "The Extent of Information: Its Relevance for Random Utility Models," Land Economics, University of Wisconsin Press, vol. 76(3), pages 374-385.
  4. 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.
  5. Swait, Joffre & Ben-Akiva, Moshe, 1987. "Empirical test of a constrained choice discrete model: Mode choice in São Paulo, Brazil," Transportation Research Part B: Methodological, Elsevier, vol. 21(2), pages 103-115, April.
  6. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
  7. Uwe Jensen, 2000. "Is it efficient to analyse efficiency rankings?," Empirical Economics, Springer, vol. 25(2), pages 189-208.
  8. Smith, V Kerry & Palmquist, Raymond B & Jakus, Paul, 1991. "Combining Farrell Frontier and Hedonic Travel Cost Models for Valuing Estuarine Quality," The Review of Economics and Statistics, MIT Press, vol. 73(4), pages 694-99, November.
  9. David Scrogin & Kevin Boyle & George Parsons & Andrew J. Plantinga, 2004. "Effects of Regulations on Expected Catch, Expected Harvest, and Site Choice of Recreational Anglers," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 963-974.
  10. Morey, Edward R. & Waldman, Donald M., 1998. "Measurement Error in Recreation Demand Models: The Joint Estimation of Participation, Site Choice, and Site Characteristics," Journal of Environmental Economics and Management, Elsevier, vol. 35(3), pages 262-276, May.
  11. George R. Parsons & A. Brett Hauber, 1998. "Spatial Boundaries and Choice Set Definition in a Random Utility Model of Recreation Demand," Land Economics, University of Wisconsin Press, vol. 74(1), pages 32-48.
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