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Accounting for the hypothetical bias: A changing adjustment factor approach

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  • Marilena Furno
  • Francesco La Barbera
  • Fabio Verneau

Abstract

The existence of the hypothetical bias is a well‐documented issue, and several techniques have been proposed to realign stated preferences to revealed preferences demand data. Among the ex post approaches to reduce hypothetical bias, the estimation of calibration factors and calibration functions has been considered by many authors. Nevertheless, a calibration method that allows the extent of the adjustment to vary with the magnitude of stated bids has never been proposed. Therefore, in the present study, we investigate the topic of ex post approaches showing that the bias changes along the quantiles of the WTP distribution. Using data of both hypothetical and nonhypothetical experimental auction for a private and deliverable good, a calibration method that allows the extent of the adjustment to vary with the magnitude of the stated WTP is proposed.

Suggested Citation

  • Marilena Furno & Francesco La Barbera & Fabio Verneau, 2019. "Accounting for the hypothetical bias: A changing adjustment factor approach," Agribusiness, John Wiley & Sons, Ltd., vol. 35(3), pages 329-342, July.
    • Handle: RePEc:wly:agribz:v:35:y:2019:i:3:p:329-342
    DOI: 10.1002/agr.21578
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    References listed on IDEAS

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    1. Loomis, John B., 2014. "2013 WAEA Keynote Address: Strategies for Overcoming Hypothetical Bias in Stated Preference Surveys," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(1), pages 1-13, April.
    2. Loomis, John B. & Gonzalez-Caban, Armando & Englin, Jeffrey E., 2001. "Testing For Differential Effects Of Forest Fires On Hiking And Mountain Biking Demand And Benefits," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 26(2), pages 1-15, December.
    3. Lim, Kar Ho & Grebitus, Carola & Hu, Wuyang & Nayga, Rodolfo M. Jr., 2015. "Inducing Hypothetical Bias Mitigation with Ten Commandments," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205648, Agricultural and Applied Economics Association.
    4. F. Bailey Norwood & Jayson L. Lusk, 2011. "Social Desirability Bias in Real, Hypothetical, and Inferred Valuation Experiments," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(2), pages 528-534.
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    Cited by:

    1. 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.
    2. 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).
    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).
    4. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part II. Macro-scale analysis of literature and effectiveness of bias mitigation methods," Papers 2102.02945, arXiv.org.

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