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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 neuroimaging

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

Abstract

The notion of hypothetical bias (HB) constitutes, arguably, the most fundamental issue in relation to the use of hypothetical survey methods. Whether or to what extent choices of survey participants and subsequent inferred estimates translate to real-world settings continues to be debated. While HB has been extensively studied in the broader context of contingent valuation, it is much less understood in relation to choice experiments (CE). While the number of CE studies has rapidly increased, the critical issue of HB has been studied in only a small fraction of CE studies. This paper provides macro-scale insights into the literature of CE and reviews the empirical evidence for HB in CE in various fields of applied economics as well as experimental psychology and behavioural neuroscience. Results suggest mixed evidence on the prevalence, extent and direction of HB as well as considerable context and measurement dependency. While HB is found to be an undeniable issue when conducting CEs, the empirical evidence on HB does not render CEs unable to represent real-world preferences. While health-related choice experiments often find negligible degrees of HB, experiments in consumer behaviour and transport domains suggest significant degrees of HB. Environmental valuation studies provide mixed evidence. Also, across these disciplines many studies display HB in their total willingness to pay estimates and opt-in rates but not in their hypothetical marginal rates of substitution (subject to scale correction). Further, recent findings in psychology and brain imaging studies identify neurocognitive mechanisms underlying HB that may explain some of the discrepancies and unexpected findings in the mainstream CE literature.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:eejocm:v:41:y:2021:i:c:s1755534521000427
    DOI: 10.1016/j.jocm.2021.100309
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    1. 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).
    2. Jiang, Qi & Penn, Jerrod & Hu, Wuyang, 2022. "Real payment priming to reduce potential hypothetical bias," Journal of choice modelling, Elsevier, vol. 45(C).
    3. 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).
    4. 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).
    5. Raman, Shyam & Kriner, Douglas & Ziebarth, Nicolas & Simon, Kosali & Kreps, Sarah, 2022. "COVID-19 booster uptake among US adults: Assessing the impact of vaccine attributes, incentives, and context in a choice-based experiment," Social Science & Medicine, Elsevier, vol. 310(C).

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