IDEAS home Printed from https://ideas.repec.org/p/ags/eerhrr/95062.html

Inducing Strategic Bias: and its implications for Choice Modelling design

Author

Listed:
  • Burton, Michael P.

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

  • Burton, Michael P., 2010. "Inducing Strategic Bias: and its implications for Choice Modelling design," Research Reports 95062, Australian National University, Environmental Economics Research Hub.
    • Handle: RePEc:ags:eerhrr:95062
    DOI: 10.22004/ag.econ.95062
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/95062/files/Inducing%20Strategic%20Bias%20and%20its%20implications%20for%20Choice%20Modelling%20design.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.95062?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    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, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    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

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. 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).
    4. 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.
    5. 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).
    6. 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.
    7. 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.
    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shr, Yau-Huo (Jimmy) & Zhang, Wendong, 2024. "Omitted downstream attributes and the benefits of nutrient reductions: Implications for choice experiments," Ecological Economics, Elsevier, vol. 222(C).
    2. DeLong, Karen L. & Syrengelas, Konstantinos G. & Grebitus, Carola & Nayga, Rodolfo M., 2021. "Visual versus Text Attribute Representation in Choice Experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 94(C).
    3. Ariane Kehlbacher & Kelvin Balcombe & Richard Bennett, 2013. "Stated Attribute Non-attendance in Successive Choice Experiments," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(3), pages 693-706, September.
    4. Yang, Jui-Chen & Johnson, F. Reed & Kilambi, Vikram & Mohamed, Ateesha F., 2015. "Sample size and utility-difference precision in discrete-choice experiments: A meta-simulation approach," Journal of choice modelling, Elsevier, vol. 16(C), pages 50-57.
    5. Gonçalves, Tânia & Lourenço-Gomes, Lina & Pinto, Lígia M. Costa, 2020. "Dealing with ignored attributes through an inferred approach in wine choice experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 87(C).
    6. Owusu, V., 2018. "Credit-Constraints and Preferences for Crop Insurance in Ghana: Implications of Attribute Non-Attendance in Discrete Choice Experiments," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 276967, International Association of Agricultural Economists.
    7. Erlend Dancke Sandorf & Danny Campbell, 2019. "Accommodating satisficing behaviour in stated choice experiments," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 46(1), pages 133-162.
    8. Yau-Huo Shr & Wendong Zhang, 2021. "Does Omitting Downstream Water Quality Change the Economic Benefits of Nutrient Reduction? Evidence from a Discrete Choice Experiment," Center for Agricultural and Rural Development (CARD) Publications 21-wp620, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    9. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    10. Chen, Xuqi & Shen, Meng & Gao, Zhifeng, "undated". "Impact of Intra-respondent Variations in Attribute Attendance on Consumer Preference in Food Choice," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258509, Agricultural and Applied Economics Association.
    11. Dan Pan, 2016. "The Design of Policy Instruments towards Sustainable Livestock Production in China: An Application of the Choice Experiment Method," Sustainability, MDPI, vol. 8(7), pages 1-18, July.
    12. David Hensher & Andrew Collins & William Greene, 2013. "Accounting for attribute non-attendance and common-metric aggregation in a probabilistic decision process mixed multinomial logit model: a warning on potential confounding," Transportation, Springer, vol. 40(5), pages 1003-1020, September.
    13. Enni Ruokamo & Mikołaj Czajkowski & Nick Hanley & Artti Juutinen & Rauli Svento, 2016. "Linking perceived choice complexity with scale heterogeneity in discrete choice experiments: home heating in Finland," Working Papers 2016-30, Faculty of Economic Sciences, University of Warsaw.
    14. Abrantes, Pedro A.L. & Wardman, Mark R., 2011. "Meta-analysis of UK values of travel time: An update," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 1-17, January.
    15. Uttam Khanal & Clevo Wilson & Shunsuke Managi & Boon Lee & Viet-Ngu Hoang & Robert Gifford, 2018. "Psychological influence on survey incentives: valuing climate change adaptation benefits in agriculture," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(2), pages 305-324, April.
    16. Lea Skræp Svenningsen, 2017. "Distributive outcomes matter: Measuring social preferences for climate policy," IFRO Working Paper 2017/11, University of Copenhagen, Department of Food and Resource Economics.
    17. Moser, Riccarda & Raffaelli, Roberta, "undated". "Exploiting cut-off information to incorporate context effect: a discrete choice experiment on small fruits in a Alpine region," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114646, European Association of Agricultural Economists.
    18. Moser, Riccarda & Raffaelli, Roberta & Notaro, Sandra, 2010. "The Role Of Production Methods In Fruit Purchasing Behaviour: Hypothetical Vs Actual Consumers’ Preferences And Stated Minimum Requirements," 115th Joint EAAE/AAEA Seminar, September 15-17, 2010, Freising-Weihenstephan, Germany 116426, European Association of Agricultural Economists.
    19. Ellen J Van Loo & Carola Grebitus & Rodolfo M Nayga & Wim Verbeke & Jutta Roosen, 2018. "On the Measurement of Consumer Preferences and Food Choice Behavior: The Relation Between Visual Attention and Choices," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 40(4), pages 538-562, December.
    20. Danaf, Mazen & Atasoy, Bilge & de Azevedo, Carlos Lima & Ding-Mastera, Jing & Abou-Zeid, Maya & Cox, Nathaniel & Zhao, Fang & Ben-Akiva, Moshe, 2019. "Context-aware stated preferences with smartphone-based travel surveys," Journal of choice modelling, Elsevier, vol. 31(C), pages 35-50.

    More about this item

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:eerhrr:95062. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/asanuau.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.