IDEAS home Printed from https://ideas.repec.org/a/eee/joepsy/v90y2022ics0167487022000149.html
   My bibliography  Save this article

Online belief elicitation methods

Author

Listed:
  • Burdea, Valeria
  • Woon, Jonathan

Abstract

How well do incentivized belief elicitation procedures work in online settings? We evaluate the quality of beliefs elicited from online respondents, comparing several characteristics of two widely used complex elicitation mechanisms (the Binarized Scoring Rule – BSR – and a stochastic variation of the Becker–deGroot–Marschak mechanism—BDM) against a flat fee baseline for a variety of beliefs (induced probabilities, first-order factual knowledge, second-order knowledge of others). We find that the flat-fee method requires the least amount of time, the BDM is the most difficult to understand, and that there are no differences in the average accuracy of induced beliefs across conditions. However, the methods are significantly different in terms of the frequency of first-order and second-order beliefs reported at exactly 50%: the flat-fee method leads to the most mass on this belief, followed by BDM and BSR. Regarding induced beliefs, we also find that less-educated participants’ accuracy is higher in the complex incentives treatments, and that attention, numeracy, and education are positively associated with the quality of these beliefs across methods. Our results suggest that the quality of beliefs elicited in online environments may depend less on the formal incentive compatibility properties of the elicitation procedure (whether the procedure prevents “dishonest” reporting) than on the difficulty of comprehending the task and how well incentives induce cognitive effort (thereby inducing subjects to quantify or construct their beliefs).

Suggested Citation

  • Burdea, Valeria & Woon, Jonathan, 2022. "Online belief elicitation methods," Journal of Economic Psychology, Elsevier, vol. 90(C).
  • Handle: RePEc:eee:joepsy:v:90:y:2022:i:c:s0167487022000149
    DOI: 10.1016/j.joep.2022.102496
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167487022000149
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.joep.2022.102496?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jérôme Hergueux & Nicolas Jacquemet, 2015. "Social preferences in the online laboratory: a randomized experiment," Experimental Economics, Springer;Economic Science Association, vol. 18(2), pages 251-283, June.
    2. Benjamin Enke & Thomas W. Graeber, 2021. "Cognitive Uncertainty in Intertemporal Choice," CESifo Working Paper Series 9472, CESifo.
    3. Grewenig, Elisabeth & Lergetporer, Philipp & Werner, Katharina & Woessmann, Ludger, 2022. "Incentives, search engines, and the elicitation of subjective beliefs: Evidence from representative online survey experiments," Journal of Econometrics, Elsevier, vol. 231(1), pages 304-326.
    4. Markus M. Möbius & Muriel Niederle & Paul Niehaus & Tanya S. Rosenblat, 2022. "Managing Self-Confidence: Theory and Experimental Evidence," Management Science, INFORMS, vol. 68(11), pages 7793-7817, November.
    5. John Horton & David Rand & Richard Zeckhauser, 2011. "The online laboratory: conducting experiments in a real labor market," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 399-425, September.
    6. Camerer, Colin F & Hogarth, Robin M, 1999. "The Effects of Financial Incentives in Experiments: A Review and Capital-Labor-Production Framework," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 7-42, December.
    7. Holt, Charles A. & Smith, Angela M., 2009. "An update on Bayesian updating," Journal of Economic Behavior & Organization, Elsevier, vol. 69(2), pages 125-134, February.
    8. Andrew Schotter & Isabel Trevino, 2014. "Belief Elicitation in the Laboratory," Annual Review of Economics, Annual Reviews, vol. 6(1), pages 103-128, August.
    9. Edi Karni, 2009. "A Mechanism for Eliciting Probabilities," Econometrica, Econometric Society, vol. 77(2), pages 603-606, March.
    10. Tanjim Hossain & Ryo Okui, 2013. "The Binarized Scoring Rule," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(3), pages 984-1001.
    11. Antonio A. Arechar & Simon Gächter & Lucas Molleman, 2018. "Conducting interactive experiments online," Experimental Economics, Springer;Economic Science Association, vol. 21(1), pages 99-131, March.
    12. Ernst Fehr & Georg Kirchsteiger & Arno Riedl, 1993. "Does Fairness Prevent Market Clearing? An Experimental Investigation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(2), pages 437-459.
    13. Christopher Roth & Johannes Wohlfart, 2020. "How Do Expectations about the Macroeconomy Affect Personal Expectations and Behavior?," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 731-748, October.
    14. Charness, Gary & Gneezy, Uri & Rasocha, Vlastimil, 2021. "Experimental methods: Eliciting beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 234-256.
    15. Ingrid Burfurd & Tom Wilkening, 2018. "Experimental guidance for eliciting beliefs with the Stochastic Becker–DeGroot–Marschak mechanism," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 4(1), pages 15-28, July.
    16. Grether, David M., 1992. "Testing bayes rule and the representativeness heuristic: Some experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 17(1), pages 31-57, January.
    17. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    18. Crosetto, Paolo & Filippin, Antonio & Katuščák, Peter & Smith, John, 2020. "Central tendency bias in belief elicitation," Journal of Economic Psychology, Elsevier, vol. 78(C).
    19. Leonard J. Paas & Meike Morren, 2018. "PLease do not answer if you are reading this: respondent attention in online panels," Marketing Letters, Springer, vol. 29(1), pages 13-21, March.
    20. Vinogradov, Dmitri & Shadrina, Elena, 2013. "Non-monetary incentives in online experiments," Economics Letters, Elsevier, vol. 119(3), pages 306-310.
    21. David Danz & Lise Vesterlund & Alistair J. Wilson, 2020. "Belief Elicitation: Limiting Truth Telling with Information on Incentives," NBER Working Papers 27327, National Bureau of Economic Research, Inc.
    22. Coutts, Alexander, 2019. "Testing models of belief bias: An experiment," Games and Economic Behavior, Elsevier, vol. 113(C), pages 549-565.
    23. Olivier Armantier & Giorgio Topa & Wilbert Van der Klaauw & Basit Zafar, 2017. "An overview of the Survey of Consumer Expectations," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 51-72.
    24. Rydval, Ondrej & Ortmann, Andreas, 2004. "How financial incentives and cognitive abilities affect task performance in laboratory settings: an illustration," Economics Letters, Elsevier, vol. 85(3), pages 315-320, December.
    25. Benjamin Enke & Frederik Schwerter & Florian Zimmermann, 2019. "Associative Memory and Belief Formation," CESifo Working Paper Series 7916, CESifo.
    26. Karl Schlag & James Tremewan & Joël Weele, 2015. "A penny for your thoughts: a survey of methods for eliciting beliefs," Experimental Economics, Springer;Economic Science Association, vol. 18(3), pages 457-490, September.
    27. Charles A. Holt & Angela M. Smith, 2016. "Belief Elicitation with a Synchronized Lottery Choice Menu That Is Invariant to Risk Attitudes," American Economic Journal: Microeconomics, American Economic Association, vol. 8(1), pages 110-139, February.
    28. Armantier, Olivier & Treich, Nicolas, 2013. "Eliciting beliefs: Proper scoring rules, incentives, stakes and hedging," European Economic Review, Elsevier, vol. 62(C), pages 17-40.
    29. repec:hal:pseose:halshs-00984211 is not listed on IDEAS
    30. Stefan T. Trautmann & Gijs Kuilen, 2015. "Belief Elicitation: A Horse Race among Truth Serums," Economic Journal, Royal Economic Society, vol. 125(589), pages 2116-2135, December.
    31. Theo Offerman & Joep Sonnemans & Gijs Van De Kuilen & Peter P. Wakker, 2009. "A Truth Serum for Non-Bayesians: Correcting Proper Scoring Rules for Risk Attitudes ," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(4), pages 1461-1489.
    32. Charles F. Manski, 2004. "Measuring Expectations," Econometrica, Econometric Society, vol. 72(5), pages 1329-1376, September.
    33. Matthew J C Crump & John V McDonnell & Todd M Gureckis, 2013. "Evaluating Amazon's Mechanical Turk as a Tool for Experimental Behavioral Research," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-18, March.
    34. Adam J. Berinsky & Michele F. Margolis & Michael W. Sances, 2014. "Separating the Shirkers from the Workers? Making Sure Respondents Pay Attention on Self‐Administered Surveys," American Journal of Political Science, John Wiley & Sons, vol. 58(3), pages 739-753, July.
    35. Peeters, Ronald & Vorsatz, Marc, 2021. "Simple guilt and cooperation," Journal of Economic Psychology, Elsevier, vol. 82(C).
    36. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd, 2013. "Inducing risk neutral preferences with binary lotteries: A reconsideration," Journal of Economic Behavior & Organization, Elsevier, vol. 94(C), pages 145-159.
    37. George A. Akerlof, 1982. "Labor Contracts as Partial Gift Exchange," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 97(4), pages 543-569.
    38. Franklin Allen, 1987. "Notes--Discovering Personal Probabilities When Utility Functions are Unknown," Management Science, INFORMS, vol. 33(4), pages 542-544, April.
    39. Wolff, Irenaeus, 2019. "The reliability of questionnaires in laboratory experiments: What can we do?," Journal of Economic Psychology, Elsevier, vol. 74(C).
    40. Aurélien Baillon & Han Bleichrodt, 2015. "Testing Ambiguity Models through the Measurement of Probabilities for Gains and Losses," American Economic Journal: Microeconomics, American Economic Association, vol. 7(2), pages 77-100, May.
    41. Benjamin Enke & Thomas Graeber, 2021. "Cognitive Uncertainty in Intertemporal Choice," NBER Working Papers 29577, National Bureau of Economic Research, Inc.
    42. McKelvey, Richard D & Page, Talbot, 1990. "Public and Private Information: An Experimental Study of Information Pooling," Econometrica, Econometric Society, vol. 58(6), pages 1321-1339, November.
    43. Li Hao & Daniel Houser, 2012. "Belief elicitation in the presence of naïve respondents: An experimental study," Journal of Risk and Uncertainty, Springer, vol. 44(2), pages 161-180, April.
    44. Clifford, Scott & Jerit, Jennifer, 2014. "Is There a Cost to Convenience? An Experimental Comparison of Data Quality in Laboratory and Online Studies," Journal of Experimental Political Science, Cambridge University Press, vol. 1(2), pages 120-131, January.
    45. Chris Belfield & Teodora Boneva & Christopher Rauh & Jonathan Shaw, 2020. "What Drives Enrolment Gaps in Further Education? The Role of Beliefs in Sequential Schooling Decisions," Economica, London School of Economics and Political Science, vol. 87(346), pages 490-529, April.
    46. Reinhard Selten, 1998. "Axiomatic Characterization of the Quadratic Scoring Rule," Experimental Economics, Springer;Economic Science Association, vol. 1(1), pages 43-61, June.
    47. Erkal, Nisvan & Gangadharan, Lata & Koh, Boon Han, 2020. "Replication: Belief elicitation with quadratic and binarized scoring rules," Journal of Economic Psychology, Elsevier, vol. 81(C).
    48. Berinsky, Adam J. & Huber, Gregory A. & Lenz, Gabriel S., 2012. "Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk," Political Analysis, Cambridge University Press, vol. 20(3), pages 351-368, July.
    49. Woon, Jonathan & Kanthak, Kristin, 2019. "Elections, ability, and candidate honesty," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 735-753.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Pin, Paolo & Rotesi, Tiziano, 2023. "App-based experiments," Journal of Economic Psychology, Elsevier, vol. 99(C).
    2. Dongkyu Chang & Duk Gyoo Kim & Wooyoung Lim, 2022. "Positive and Negative Selection in Bargaining: An Experiment," CESifo Working Paper Series 9908, CESifo.
    3. Janas, Moritz & Jordan, Michelle, 2024. "Cheap signaling of altruism," Journal of Economic Psychology, Elsevier, vol. 102(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. Charness, Gary & Gneezy, Uri & Rasocha, Vlastimil, 2021. "Experimental methods: Eliciting beliefs," Journal of Economic Behavior & Organization, Elsevier, vol. 189(C), pages 234-256.
    2. Eyting, Markus & Schmidt, Patrick, 2021. "Belief elicitation with multiple point predictions," European Economic Review, Elsevier, vol. 135(C).
    3. Guillaume Hollard & Sébastien Massoni & Jean-Christophe Vergnaud, 2016. "In search of good probability assessors: an experimental comparison of elicitation rules for confidence judgments," Theory and Decision, Springer, vol. 80(3), pages 363-387, March.
    4. Folli, Dominik & Wolff, Irenaeus, 2022. "Biases in belief reports," Journal of Economic Psychology, Elsevier, vol. 88(C).
    5. Karl Schlag & James Tremewan & Joël Weele, 2015. "A penny for your thoughts: a survey of methods for eliciting beliefs," Experimental Economics, Springer;Economic Science Association, vol. 18(3), pages 457-490, September.
    6. Kai Barron, 2021. "Belief updating: does the ‘good-news, bad-news’ asymmetry extend to purely financial domains?," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 31-58, March.
    7. Ingrid Burfurd & Tom Wilkening, 2022. "Cognitive heterogeneity and complex belief elicitation," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 557-592, April.
    8. Lata Gangadharan & Philip J. Grossman & Nina Xue, 2022. "Stepping Stone: Identifying self-image concerns from motivated beliefs: Does it matter how and whom you ask?," Monash Economics Working Papers 2022-05, Monash University, Department of Economics.
    9. Grewenig, Elisabeth & Lergetporer, Philipp & Werner, Katharina & Woessmann, Ludger, 2022. "Incentives, search engines, and the elicitation of subjective beliefs: Evidence from representative online survey experiments," Journal of Econometrics, Elsevier, vol. 231(1), pages 304-326.
    10. Crosetto, Paolo & Filippin, Antonio & Katuščák, Peter & Smith, John, 2020. "Central tendency bias in belief elicitation," Journal of Economic Psychology, Elsevier, vol. 78(C).
    11. de Haan, Thomas, 2020. "Eliciting belief distributions using a random two-level partitioning of the state space," Working Papers in Economics 1/20, University of Bergen, Department of Economics.
    12. Lata Gangadharan & Philip J. Grossman & Nina Xue, 2021. "Identifying self-image concerns from motivated beliefs: Does it matter how and whom you ask?," Monash Economics Working Papers 2021-17, Monash University, Department of Economics.
    13. Li Hao & Daniel Houser, 2012. "Belief elicitation in the presence of naïve respondents: An experimental study," Journal of Risk and Uncertainty, Springer, vol. 44(2), pages 161-180, April.
    14. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd, 2014. "Eliciting subjective probabilities with binary lotteries," Journal of Economic Behavior & Organization, Elsevier, vol. 101(C), pages 128-140.
    15. Dominik Bauer & Irenaeus Wolff, 2018. "Biases in Beliefs: Experimental Evidence," TWI Research Paper Series 109, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    16. Karl Schlag & James Tremewan & Joël Weele, 2015. "A penny for your thoughts: a survey of methods for eliciting beliefs," Experimental Economics, Springer;Economic Science Association, vol. 18(3), pages 457-490, September.
    17. Bauer, Dominik & Wolff, Irenaeus, 2019. "Biases in Beliefs," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203601, Verein für Socialpolitik / German Economic Association.
    18. Tsakas, Elias, 2018. "Robust scoring rules," Research Memorandum 023, Maastricht University, Graduate School of Business and Economics (GSBE).
    19. Markus M. Möbius & Muriel Niederle & Paul Niehaus & Tanya S. Rosenblat, 2022. "Managing Self-Confidence: Theory and Experimental Evidence," Management Science, INFORMS, vol. 68(11), pages 7793-7817, November.
    20. Jean-Pierre Benoît & Juan Dubra & Giorgia Romagnoli, 2022. "Belief Elicitation When More than Money Matters: Controlling for "Control"," American Economic Journal: Microeconomics, American Economic Association, vol. 14(3), pages 837-888, August.

    More about this item

    Keywords

    Belief elicitation; Incentives; Online experiment;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    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:eee:joepsy:v:90:y:2022:i:c:s0167487022000149. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joep .

    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.