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Estimation on stated-preference experiments constructed from revealed-preference choices

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  • Train, Kenneth
  • Wilson, Wesley W.

Abstract

Constructing stated-preference (sp) experiments from a choice that the respondent made in a revealed-preference setting can enhance the realism of the sp task and the efficacy of preference revelation. However, the practice creates dependence between the sp attributes and unobserved factors, contrary to the independence assumption that is maintained for standard estimation procedures. We describe a general estimation method that accounts for this non-independence and give specific examples based on standard and mixed logit specifications of utility. We show conditions under which standard estimation methods are consistent despite the non-independence. We illustrate the general methodology through an application to shippers' choice of route and mode along the Columbia/Snake River system.

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Bibliographic Info

Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

Volume (Year): 42 (2008)
Issue (Month): 3 (March)
Pages: 191-203

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Handle: RePEc:eee:transb:v:42:y:2008:i:3:p:191-203

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References

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  1. David Hensher & Nina Shore & Kenneth Train, 2006. "Water Supply Security and Willingness to Pay to Avoid Drought Restrictions," The Economic Record, The Economic Society of Australia, vol. 82(256), pages 56-66, 03.
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  3. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
  4. Steven Berry & James Levinsohn & Ariel Pakes, 2004. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 68-105, February.
  5. Caussade, Sebastián & Ortúzar, Juan de Dios & Rizzi, Luis I. & Hensher, David A., 2005. "Assessing the influence of design dimensions on stated choice experiment estimates," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 621-640, August.
  6. David A. Hensher, 2006. "How do respondents process stated choice experiments? Attribute consideration under varying information load," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 861-878.
  7. Richard W. Blundell & James L. Powell, 2004. "Endogeneity in Semiparametric Binary Response Models," Review of Economic Studies, Oxford University Press, vol. 71(3), pages 655-679.
  8. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-62, March.
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  16. David Hensher & Nina Shore & Kenneth Train, 2005. "Households’ Willingness to Pay for Water Service Attributes," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 32(4), pages 509-531, December.
  17. Sándor, Zsolt & Train, Kenneth, 2004. "Quasi-random simulation of discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 38(4), pages 313-327, May.
  18. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
  19. Hensher, David A. & Rose, John M., 2007. "Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: A case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 428-443, June.
  20. Daniel McFadden, 1987. "A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration," Working papers 464, Massachusetts Institute of Technology (MIT), Department of Economics.
  21. Bhat, Chandra R. & Castelar, Saul, 2002. "A unified mixed logit framework for modeling revealed and stated preferences: formulation and application to congestion pricing analysis in the San Francisco Bay area," Transportation Research Part B: Methodological, Elsevier, vol. 36(7), pages 593-616, August.
  22. Shinghal, Nalin & Fowkes, Tony, 2002. "Freight mode choice and adaptive stated preferences," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 38(5), pages 367-378, September.
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Citations

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Cited by:
  1. George R. Parsons & Steven M. Thur, 2007. "Valuing Changes in the Quality of Coral Reef Ecosystems: A Stated Preference Study of SCUBA Diving in the Bonaire National Marine Park," Working Papers 07-18, University of Delaware, Department of Economics.
  2. Bölcskei, Vanda, 2010. "A távbeszélő-szolgáltatások keresleti modelljeinek áttekintése - különös tekintettel a vezetékes és mobilszolgáltatások közötti helyettesítés becslésére
    [A review of the demand
    ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 517-535.
  3. Daniel McFadden, 2009. "The human side of mechanism design: a tribute to Leo Hurwicz and Jean-Jacque Laffont," Review of Economic Design, Springer, vol. 13(1), pages 77-100, April.
  4. Mattsson, Lars-Göran & Weibull, Jörgen W. & Lindberg, Per Olov, 2014. "Extreme values, invariance and choice probabilities," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 81-95.
  5. Pamela Giustinelli, 2011. "Group Decision Making with Uncertain Outcomes: Unpacking Child-Parent Choices of High School Tracks," Working Papers 2011-030, Human Capital and Economic Opportunity Working Group.
  6. Bergantino, Angela S. & Bierlaire, Michel & Catalano, Mario & Migliore, Marco & Amoroso, Salvatore, 2013. "Taste heterogeneity and latent preferences in the choice behaviour of freight transport operators," Transport Policy, Elsevier, vol. 30(C), pages 77-91.
  7. Sanko, Nobuhiro & Yamamoto, Toshiyuki, 2013. "Estimation efficiency of RP/SP models considering SP design and error structures," Journal of choice modelling, Elsevier, vol. 6(C), pages 60-73.
  8. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 63-79, January.
  9. Dombi, Mihály & Kuti, István & Balogh, Péter, 2014. "Sustainability assessment of renewable power and heat generation technologies," Energy Policy, Elsevier, vol. 67(C), pages 264-271.
  10. Hensher, David A., 2010. "Hypothetical bias, choice experiments and willingness to pay," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 735-752, July.
  11. Khachatryan, Hayk & Joireman, Jeff & Casavant, Ken, 2013. "The Effects of Intertemporal Considerations on Consumer Preferences for Biofuels," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150334, Agricultural and Applied Economics Association.
  12. David Hensher & John Rose & Zheng Li, 2012. "Does the choice model method and/or the data matter?," Transportation, Springer, vol. 39(2), pages 351-385, March.
  13. Masiero, Lorenzo & Rose, John M., 2013. "The role of the reference alternative in the specification of asymmetric discrete choice models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 83-92.
  14. Essama-Nssah, B., 2012. "Identification of sources of variation in poverty outcomes," Policy Research Working Paper Series 5954, The World Bank.
  15. Lüthi, Sonja & Wüstenhagen, Rolf, 2012. "The price of policy risk — Empirical insights from choice experiments with European photovoltaic project developers," Energy Economics, Elsevier, vol. 34(4), pages 1001-1011.
  16. Inchauste, Gabriela & Olivieri, Sergio & Saavedra, Jaime & Winkler, Hernan, 2012. "What is behind the decline in poverty since 2000 ? evidence from Bangladesh, Peru and Thailand," Policy Research Working Paper Series 6199, The World Bank.

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