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How to deal with inconsistent choices on multiple price lists

Author

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  • Engel, Christoph
  • Kirchkamp, Oliver
Abstract
Economic experiments are often based on the claim that some heterogeneous behavioural trait affects response to treatment. This trait is measured in another part of the experiment, using a multiple price list. Frequently, choices on such a list are not perfectly consistent.

Suggested Citation

  • Engel, Christoph & Kirchkamp, Oliver, 2019. "How to deal with inconsistent choices on multiple price lists," Journal of Economic Behavior & Organization, Elsevier, vol. 160(C), pages 138-157.
  • Handle: RePEc:eee:jeborg:v:160:y:2019:i:c:p:138-157
    DOI: 10.1016/j.jebo.2019.02.024
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    References listed on IDEAS

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    11. Jonathan P. Beauchamp & David Cesarini & Magnus Johannesson, 2017. "The psychometric and empirical properties of measures of risk preferences," Journal of Risk and Uncertainty, Springer, vol. 54(3), pages 203-237, June.
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    13. Engel, Christoph, 2014. "Social preferences can make imperfect sanctions work: Evidence from a public good experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 108(C), pages 343-353.
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    15. repec:wop:ubisop:0107 is not listed on IDEAS
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    17. Friedman, Daniel & Isaac, R. Mark & James, Duncan & Sunder, Shyam, 2014. "Risky Curves: On the Empirical Failure of Expected Utility," Santa Cruz Department of Economics, Working Paper Series qt87v8k86z, Department of Economics, UC Santa Cruz.
    18. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "Generalized multilevel structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 167-190, June.
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    Citations

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    Cited by:

    1. Christoph Engel & Paul A. M. Van Lange, 2021. "Social mindfulness is normative when costs are low, but rapidly declines with increases in costs," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(2), pages 290-322, March.
    2. Fabien Perez & Guillaume Hollard & Radu Vranceanu, 2021. "How serious is the measurement-error problem in risk-aversion tasks?," Journal of Risk and Uncertainty, Springer, vol. 63(3), pages 319-342, December.
    3. Rosato, Antonio & Tymula, Agnieszka A., 2024. "A novel experimental test of truthful bidding in second-price auctions with real objects," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 111(C).
    4. Fabien Perez & Guillaume Hollard & Radu Vranceanu & Delphine Dubart, 2019. "How Serious is the Measurement-Error Problem in a Popular Risk-Aversion Task?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-02291224, HAL.
    5. Fabien Perez & Guillaume Hollard & Radu Vranceanu & Delphine Dubart, 2019. "How Serious is the Measurement-Error Problem in a Popular Risk-Aversion Task?," Working Papers hal-02291224, HAL.
    6. repec:cup:judgdm:v:16:y:2021:i:2:p:290-322 is not listed on IDEAS
    7. Castro, M.F.; & Guccio, C.; & Romeo, D.;, 2022. "An assessment of physicians’ risk attitudes using laboratory and field data," Health, Econometrics and Data Group (HEDG) Working Papers 22/26, HEDG, c/o Department of Economics, University of York.
    8. Kirchkamp, Oliver & Mill, Wladislaw, 2021. "Spite vs. risk: Explaining overbidding in the second-price all-pay auction," Games and Economic Behavior, Elsevier, vol. 130(C), pages 616-635.
    9. Sven Grüner, 2022. "Rethinking how risk aversion and impatience are linked with cognitive ability: experimental findings from agricultural students and farmers," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 11(3), pages 248-259, July.
    10. Kirchkamp, Oliver & Oechssler, Joerg & Sofianos, Andis, 2021. "The Binary Lottery Procedure does not induce risk neutrality in the Holt & Laury and Eckel & Grossman tasks," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 348-369.

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    More about this item

    Keywords

    Measurement error; Risk; Lab experiment; Public good; Bayesian inference;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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