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Lexicographic Preferences in Discrete Choice Experiments: Consequences on Individual-Specific Willingness to Pay Estimates

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  • Danny Campbell

    (Gibson Institute of Land, Food and Environmen, Queen’s University Belfast)

  • W. George Hutchinson

    (Gibson Institute of Land, Food and Environmen, Queen’s University Belfast)

  • Riccardo Scarpa

    (University of Waikato)

Abstract

In discrete choice experiments respondents are generally assumed to consider all of the attributes across each of the alternatives, and to choose their most preferred. However, results in this paper indicate that many respondents employ simplified lexicographic decision-making rules, whereby they have a ranking of the attributes, but their choice of an alternative is based solely on the level of their most important attribute(s). Not accounting for these simple decision-making heuristics introduces systemic errors and leads to biased point estimates, as they are a violation of the continuity axiom and a departure from the use of compensatory decision-making. In this paper the implications of lexicographic preferences are examined. In particular, using a mixed logit specification this paper investigates the sensitivity of individual-specific willingness to pay (WTP) estimates conditional on whether lexicographic decision-making rules are accounted for in the modelling of discrete choice responses. Empirical results are obtained from a discrete choice experiment that was carried out to address the value of a number of rural landscape attributes in Ireland.

Suggested Citation

  • Danny Campbell & W. George Hutchinson & Riccardo Scarpa, 2006. "Lexicographic Preferences in Discrete Choice Experiments: Consequences on Individual-Specific Willingness to Pay Estimates," Working Papers 2006.128, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2006.128
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    8. Mridu Prabal Goswami & Manipushpak Mitra & Debapriya Sen, 2022. "A Characterization of Lexicographic Preferences," Decision Analysis, INFORMS, vol. 19(2), pages 170-187, June.
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    11. Rambonilaza, Tina, 2005. "Land-use planning and public preferences: What can we learn from choice experiments method?," MPRA Paper 9225, University Library of Munich, Germany, revised May 2007.
    12. Nesha Beharry-Borg & Riccardo Scarpa, 2010. "Researcher-Selected versus Respondent-Selected Attributes: Improved Coastal Water Quality in Tobago," Chapters, in: Jeff Bennett & Ekin Birol (ed.), Choice Experiments in Developing Countries, chapter 5, Edward Elgar Publishing.
    13. Banerji, A. & Chowdhury, Shyamal K. & de Groote, Hugo & Meenakshi, Jonnalagadda V. & Haleegoah, Joyce & Ewoo, Manfred, 2013. "Using elicitation mechanisms to estimate the demand for nutritious maize: Evidence from experiments in rural Ghana," HarvestPlus working papers 10, International Food Policy Research Institute (IFPRI).
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    15. Pavel Ciaian & Sergio Gomez y Paloma, 2011. "Valuation of EU Agricultural Landscape," EERI Research Paper Series EERI_RP_2011_20, Economics and Econometrics Research Institute (EERI), Brussels.
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    20. Meenakshi, J.V. & Banerji, A. & Manyong, Victor & Tomlins, Keith & Mittal, Nitya & Hamukwala, Priscilla, 2012. "Using a discrete choice experiment to elicit the demand for a nutritious food: Willingness-to-pay for orange maize in rural Zambia," Journal of Health Economics, Elsevier, vol. 31(1), pages 62-71.

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    More about this item

    Keywords

    Continuity axiom; Discrete Choice Experiments; Lexicographic Preferences; Mixed Logit; Individual-Specific Willingness to Pay;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects

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