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Manipulating a stated choice experiment

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  • Fosgerau, Mogens
  • Börjesson, Maria

Abstract

This paper considers the design of a stated choice experiment intended to measure the marginal rate of substitution (MRS) between cost and an attribute such as time using a conventional logit model. Focusing the experimental design on some target MRS will bias estimates towards that value. The paper shows why this happens. The resulting estimated MRS can then be manipulated by adapting the target MRS in the experimental design.

Suggested Citation

  • Fosgerau, Mogens & Börjesson, Maria, 2015. "Manipulating a stated choice experiment," Journal of choice modelling, Elsevier, vol. 16(C), pages 43-49.
    • Handle: RePEc:eee:eejocm:v:16:y:2015:i:c:p:43-49
    DOI: 10.1016/j.jocm.2015.09.005
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    1. David Hensher, 2014. "Attribute processing as a behavioural strategy in choice making," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 12, pages 268-289, Edward Elgar Publishing.
    2. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
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    Cited by:

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    2. van Cranenburgh, Sander & Rose, John M. & Chorus, Caspar G., 2018. "On the robustness of efficient experimental designs towards the underlying decision rule," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 50-64.
    3. van Cranenburgh, Sander & Chorus, Caspar G., 2017. "Willingness to Pay-inference in the absence of rejected propositions," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 35-42.
    4. Oehlmann, Malte & Meyerhoff, Jürgen & Mariel, Petr & Weller, Priska, 2017. "Uncovering context-induced status quo effects in choice experiments," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 59-73.

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    More about this item

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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