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Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods

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  • Haghani, Milad
  • Bliemer, Michiel C.J.
  • Rose, John M.
  • Oppewal, Harmen
  • Lancsar, Emily

Abstract

This paper follows the review of empirical evidence on the existence of hypothetical bias (HB) in choice experiments (CEs) presented in Part I of this study. It observes how the variation in operational definitions of HB has prohibited consistent measurement of HB in CE. It offers a unifying definition of HB and presents an integrative framework of how HB relates to but is also distinct from external validity (EV), with HB representing one component of the wider concept of EV. The paper further identifies major sources of HB and discusses explanations as well as possible moderating factors of HB. The paper reviews methods of HB mitigation identified in the literature and the empirical evidence of their effectiveness. The review includes both ex-ante and ex-post bias mitigation methods. Ex-ante bias mitigation methods include cheap talk, real talk, consequentiality scripts, solemn oath scripts, opt-out reminders, budget reminders, honesty priming, induced truth telling, indirect questioning, time to think and pivot designs. Ex-post methods include follow-up certainty calibration scales, respondent perceived consequentiality scales, and revealed-preference-assisted estimation. It is observed that the mitigation methods and their preferred use vary markedly across different sectors of applied economics. The existing empirical evidence points to the overall effectiveness of mitigation strategies in reducing HB, although there is some variation. The paper further discusses how each mitigation method can counter a certain subset of HB sources. Considering the prevalence of HB in CEs and the effectiveness of bias mitigation methods, it is recommended that implementation of at least one bias mitigation method (or a suitable combination where possible) becomes standard practice in conducting CEs to ensure that inferences and subsequent policy decisions are as much as possible free of HB.

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  • Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    • Handle: RePEc:eee:eejocm:v:41:y:2021:i:c:s1755534521000555
    DOI: 10.1016/j.jocm.2021.100322
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    1. Jiang, Qi & Penn, Jerrod & Hu, Wuyang, 2022. "Real payment priming to reduce potential hypothetical bias," Journal of choice modelling, Elsevier, vol. 45(C).
    2. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
    3. Huls, Samare P.I. & de Bekker-Grob, Esther W., 2022. "Can healthcare choice be predicted using stated preference data? The role of model complexity in a discrete choice experiment about colorectal cancer screening," Social Science & Medicine, Elsevier, vol. 315(C).
    4. Romuald Meango, 2023. "Using Probabilistic Stated Preference Analyses to Understand Actual Choices," Papers 2307.13966, arXiv.org.
    5. Mesfin G. Genie & Mandy Ryan & Nicolas Krucien, 2023. "Keeping an eye on cost: What can eye tracking tell us about attention to cost information in discrete choice experiments?," Health Economics, John Wiley & Sons, Ltd., vol. 32(5), pages 1101-1119, May.
    6. Salm, J.A. Papineau & Bočkarjova, Marija & Botzen, W.J.W. & Runhaar, H.A.C., 2023. "Citizens' preferences and valuation of urban nature: Insights from two choice experiments," Ecological Economics, Elsevier, vol. 208(C).
    7. Natali, F. & Cacchiarelli, L. & Branca, G., 2022. "There are plenty more (sustainable) fish in the sea: A discrete choice experiment on discarded species in Italy," Ecological Economics, Elsevier, vol. 196(C).
    8. Eleonora Sofia Rossi & José A. Zabala & Francesco Caracciolo & Emanuele Blasi, 2023. "The Value of Crop Diversification: Understanding the Factors Influencing Consumers’ WTP for Pasta from Sustainable Agriculture," Agriculture, MDPI, vol. 13(3), pages 1-18, February.
    9. Gómez-Limón, José A. & Granado-Díaz, Rubén, 2023. "Assessing the demand for hydrological drought insurance in irrigated agriculture," Agricultural Water Management, Elsevier, vol. 276(C).
    10. Haghani, Milad & Bliemer, Michiel C.J. & de Bekker-Grob, Esther W., 2022. "Applications of discrete choice experiments in COVID-19 research: Disparity in survey qualities between health and transport fields," Journal of choice modelling, Elsevier, vol. 44(C).
    11. Stefan Döring & Jonathan Hall, 2023. "Drought exposure decreases altruism with salient group identities as key moderator," Nature Climate Change, Nature, vol. 13(8), pages 856-861, August.

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    2. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
    3. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
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