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Inducing Strategic Bias: and its implications for Choice Modelling design

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  • Michael Burton

    (School of Agricultural and Resource Economics, University of Western Australia.)

Abstract

It has been suggested that the nature of the task within a multi-attribute multi-alternative choice experiment may be sufficiently complex to make it difficult for individuals to develop response strategies to strategically bias their answers. This experiment tested that hypothesis by setting experimental conditions that provide incentives for strategic bias. By changing design parameters one can investigate whether the strategic bias can be reduced. The answer is effectively no: under most circumstances, respondents could find a strategy that achieved significant bias in inferred preferences. The circumstances where this did not occur (involving ranking alternatives, rather than selecting a single preferred alternative) the inferred preferences reflected neither the intended bias, nor their original preferences, making the answers useless to both respondent and researcher.

Suggested Citation

  • Michael Burton, 2010. "Inducing Strategic Bias: and its implications for Choice Modelling design," Environmental Economics Research Hub Research Reports 1061, Environmental Economics Research Hub, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:eenhrr:1061
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    File URL: https://crawford.anu.edu.au/research_units/eerh/pdf/EERH_RR61.pdf
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    References listed on IDEAS

    as
    1. David A. Hensher, 2006. "How do respondents process stated choice experiments? Attribute consideration under varying information load," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 861-878.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. EERH Research Reports: June 2010
      by David Stern in Stochastic Trend on 2010-07-03 15:06:00

    Citations

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    Cited by:

    1. Greiner, Romy & Bliemer, Michiel & Ballweg, Julie, 2014. "Design considerations of a choice experiment to estimate likely participation by north Australian pastoralists in contractual biodiversity conservation," Journal of choice modelling, Elsevier, vol. 10(C), pages 34-45.
    2. Sardaro, Ruggiero & Faccilongo, Nicola & Roselli, Luigi, 2019. "Wind farms, farmland occupation and compensation: Evidences from landowners’ preferences through a stated choice survey in Italy," Energy Policy, Elsevier, vol. 133(C).
    3. 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.
    4. 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).
    5. Greiner, Romy & Ballweg, Julie, 2013. "Estimating the supply of on-farm biodiversity conservation services by north Australian pastoralists: design of a choice experiment," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152153, Australian Agricultural and Resource Economics Society.
    6. Ruggiero Sardaro & Nicola Faccilongo & Francesco Contò & Piermichele La Sala, 2021. "Adaption Actions to Cope with Climate Change: Evidence from Farmers’ Preferences on an Agrobiodiversity Conservation Programme in the Mediterranean Area," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    7. McCartney, Abbie & Cleland, Jonelle, 2010. "Choice Experiment Framing and Incentive Compatibility: observations from public focus groups," Research Reports 107575, Australian National University, Environmental Economics Research Hub.
    8. Meginnis, Keila & Burton, Michael & Chan, Ron & Rigby, Dan, 2021. "Strategic bias in discrete choice experiments," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).

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    More about this item

    Keywords

    Strategic bias; choice modeling; complexity;
    All these keywords.

    JEL classification:

    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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