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Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why

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  • Scarpa, Riccardo
  • Rose, John M.

Abstract

We review the basic principles for the evaluation of design efficiency in discrete choice modelling with a focus on efficiency of WTP estimates from the multinomial logit model. The discussion is developed under the realistic assumption that researchers can plausibly define a prior belief on the range of values for the utility coefficients. D-,A-,B-,Sand Cerrors are compared as measures of design performance in applied studies and their rationale is discussed. An empirical example based on the generation and comparison of fifteen separate designs from a common set of assumptions illustrates the relevant considerations to the context of non-market valuation, with particular emphasis placed on Cefficiency. Conclusions are drawn for the practice of reporting in non-market valuation and for future work on design research

Suggested Citation

  • Scarpa, Riccardo & Rose, John M., 2008. "Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 52(3), pages 1-30.
    • Handle: RePEc:ags:aareaj:118543
    DOI: 10.22004/ag.econ.118543
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    1. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    2. 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.
    3. Cooke, Alan D. J. & Mellers, Barbara A., 1995. "Attribute Range and Response Range: Limits of Compatibility in Multiattribute Judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 63(2), pages 187-194, August.
    4. Alberini Anna, 1995. "Optimal Designs for Discrete Choice Contingent Valuation Surveys: Single-Bound, Double-Bound, and Bivariate Models," Journal of Environmental Economics and Management, Elsevier, vol. 28(3), pages 287-306, May.
    5. David A. Hensher, 2004. "Identifying the Influence of Stated Choice Design Dimensionality on Willingness to Pay for Travel Time Savings," Journal of Transport Economics and Policy, University of Bath, vol. 38(3), pages 425-446, September.
    6. Scarpa, R. & Thiene, M. & Train, K., 2008. "Appendix to Utility in WTP space: a tool to address confounding random scale effects in destination choice to the Alps," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 90(4), pages 1-9, January.
    7. David Hensher, 2006. "Revealing Differences in Willingness to Pay due to the Dimensionality of Stated Choice Designs: An Initial Assessment," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 34(1), pages 7-44, May.
    8. William S. Breffle & Robert D. Rowe, 2002. "Comparing Choice Question Formats for Evaluating Natural Resource Tradeoffs," Land Economics, University of Wisconsin Press, vol. 78(2), pages 298-314.
    9. 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.
    10. John Rose & Michiel Bliemer, 2013. "Sample size requirements for stated choice experiments," Transportation, Springer, vol. 40(5), pages 1021-1041, September.
    11. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    12. Olivier Toubia & John R. Hauser, 2007. "—On Managerially Efficient Experimental Designs," Marketing Science, INFORMS, vol. 26(6), pages 851-858, 11-12.
    13. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
    14. Hensher, David A. & Stopher, Peter R. & Louviere, Jordan J., 2001. "An exploratory analysis of the effect of numbers of choice sets in designed choice experiments: an airline choice application," Journal of Air Transport Management, Elsevier, vol. 7(6), pages 373-379.
    15. DeShazo, J. R. & Fermo, German, 2002. "Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency," Journal of Environmental Economics and Management, Elsevier, vol. 44(1), pages 123-143, July.
    16. Barbara J. Kanninen, 1993. "Optimal Experimental Design for Double-Bounded Dichotomous Choice Contingent Valuation," Land Economics, University of Wisconsin Press, vol. 69(2), pages 138-146.
    17. Arentze, Theo & Borgers, Aloys & Timmermans, Harry & DelMistro, Romano, 2003. "Transport stated choice responses: effects of task complexity, presentation format and literacy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 229-244, May.
    18. Jayson L. Lusk & F. Bailey Norwood, 2005. "Effect of Experimental Design on Choice-Based Conjoint Valuation Estimates," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(3), pages 771-785.
    19. Riccardo Scarpa & Mara Thiene & Kenneth Train, 2008. "Utility in Willingness to Pay Space: A Tool to Address Confounding Random Scale Effects in Destination Choice to the Alps," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(4), pages 994-1010.
    20. Riccardo Scarpa & Danny Campbell & W. George Hutchinson, 2007. "Benefit Estimates for Landscape Improvements: Sequential Bayesian Design and Respondents’ Rationality in a Choice Experiment," Land Economics, University of Wisconsin Press, vol. 83(4), pages 617-634.
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    More about this item

    Keywords

    Resource /Energy Economics and Policy;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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