IDEAS home Printed from https://ideas.repec.org/a/wly/emetrp/v89y2021i1p375-414.html
   My bibliography  Save this article

Dynamic Belief Elicitation

Author

Listed:
  • Christopher P. Chambers
  • Nicolas S. Lambert

Abstract

At an initial time, an individual forms a belief about a future random outcome. As time passes, the individual may obtain, privately or subjectively, further information, until the outcome is eventually revealed. How can a protocol be devised that induces the individual, as a strict best response, to reveal at the outset his prior assessment of both the final outcome and the information flows he anticipates and, subsequently, what information he privately receives? The protocol can provide the individual with payoffs that depend only on the outcome realization and his reports. We develop a framework to design such protocols, and apply it to construct simple elicitation mechanisms for common dynamic environments. The framework is general: we show that strategyproof protocols exist for any number of periods and large outcome sets. For these more general settings, we build a family of strategyproof protocols based on a hierarchy of choice menus, and show that any strategyproof protocol can be approximated by a protocol of this family.

Suggested Citation

  • Christopher P. Chambers & Nicolas S. Lambert, 2021. "Dynamic Belief Elicitation," Econometrica, Econometric Society, vol. 89(1), pages 375-414, January.
  • Handle: RePEc:wly:emetrp:v:89:y:2021:i:1:p:375-414
    DOI: 10.3982/ECTA15293
    as

    Download full text from publisher

    File URL: https://doi.org/10.3982/ECTA15293
    Download Restriction: no

    File URL: https://libkey.io/10.3982/ECTA15293?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
    ---><---

    References listed on IDEAS

    as
    1. Thomson, William, 1979. "Eliciting production possibilities from a well-informed manager," Journal of Economic Theory, Elsevier, vol. 20(3), pages 360-380, June.
    2. Jakub Steiner & Colin Stewart & Filip Matějka, 2017. "Rational Inattention Dynamics: Inertia and Delay in Decision‐Making," Econometrica, Econometric Society, vol. 85, pages 521-553, March.
    3. James E. Matheson & Robert L. Winkler, 1976. "Scoring Rules for Continuous Probability Distributions," Management Science, INFORMS, vol. 22(10), pages 1087-1096, June.
    4. 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.
    5. Nolan Miller & Paul Resnick & Richard Zeckhauser, 2005. "Eliciting Informative Feedback: The Peer-Prediction Method," Management Science, INFORMS, vol. 51(9), pages 1359-1373, September.
    6. David Danz & Dietmar Fehr & Dorothea Kübler, 2012. "Information and beliefs in a repeated normal-form game," Experimental Economics, Springer;Economic Science Association, vol. 15(4), pages 622-640, December.
    7. Edi Karni, 2018. "A Mechanism for Eliciting Second-Order Beliefs and the Inclination to Choose," American Economic Journal: Microeconomics, American Economic Association, vol. 10(2), pages 275-285, May.
    8. Bergemann, Dirk & Morris, Stephen & Takahashi, Satoru, 2017. "Interdependent preferences and strategic distinguishability," Journal of Economic Theory, Elsevier, vol. 168(C), pages 329-371.
    9. Edi Karni, 2009. "A Mechanism for Eliciting Probabilities," Econometrica, Econometric Society, vol. 77(2), pages 603-606, March.
    10. Osband, Kent, 1989. "Optimal Forecasting Incentives," Journal of Political Economy, University of Chicago Press, vol. 97(5), pages 1091-1112, October.
    11. Roland G FryerJr & Philipp Harms & Matthew O Jackson, 2019. "Updating Beliefs when Evidence is Open to Interpretation: Implications for Bias and Polarization," Journal of the European Economic Association, European Economic Association, vol. 17(5), pages 1470-1501.
    12. Palfrey, Thomas R. & Wang, Stephanie W., 2009. "On eliciting beliefs in strategic games," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 98-109, August.
    13. Yaron Azrieli & Christopher P. Chambers & Paul J. Healy, 2018. "Incentives in Experiments: A Theoretical Analysis," Journal of Political Economy, University of Chicago Press, vol. 126(4), pages 1472-1503.
    14. Manski, Charles F. & Neri, Claudia, 2013. "First- and second-order subjective expectations in strategic decision-making: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 81(C), pages 232-254.
    15. Edi Karni, 2020. "A mechanism for the elicitation of second-order belief and subjective information structure," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 69(1), pages 217-232, February.
    16. R. Vijay Krishna & Philipp Sadowski, 2014. "Dynamic Preference for Flexibility," Econometrica, Econometric Society, vol. 82(2), pages 655-703, March.
    17. Michael Ostrovsky, 2012. "Information Aggregation in Dynamic Markets With Strategic Traders," Econometrica, Econometric Society, vol. 80(6), pages 2595-2647, November.
    18. Colin, Stewart, 2011. "Nonmanipulable Bayesian testing," Journal of Economic Theory, Elsevier, vol. 146(5), pages 2029-2041, September.
    19. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    20. Glenn W. Harrison & Richard D. Phillips, 2014. "Subjective Beliefs and Statistical Forecasts of Financial Risks: The Chief Risk Officer Project," Palgrave Macmillan Books, in: Torben Juul Andersen (ed.), Contemporary Challenges in Risk Management, chapter 7, pages 163-202, Palgrave Macmillan.
    21. Carroll, Gabriel, 2019. "Robust incentives for information acquisition," Journal of Economic Theory, Elsevier, vol. 181(C), pages 382-420.
    22. Krishna, Vijay & Maenner, Eliot, 2001. "Convex Potentials with an Application to Mechanism Design," Econometrica, Econometric Society, vol. 69(4), pages 1113-1119, July.
    23. Reinhard Selten, 1998. "Axiomatic Characterization of the Quadratic Scoring Rule," Experimental Economics, Springer;Economic Science Association, vol. 1(1), pages 43-61, June.
    24. Takeoka, Norio, 2007. "Subjective probability over a subjective decision tree," Journal of Economic Theory, Elsevier, vol. 136(1), pages 536-571, September.
    25. Cremer, Jacques & McLean, Richard P, 1988. "Full Extraction of the Surplus in Bayesian and Dominant Strategy Auctions," Econometrica, Econometric Society, vol. 56(6), pages 1247-1257, November.
    26. Charalambos D. Aliprantis & Kim C. Border, 2006. "Infinite Dimensional Analysis," Springer Books, Springer, edition 0, number 978-3-540-29587-7, September.
    27. Nick Feltovich, 2000. "Reinforcement-Based vs. Belief-Based Learning Models in Experimental Asymmetric-Information," Econometrica, Econometric Society, vol. 68(3), pages 605-642, May.
    28. Kyle Hyndman & Erkut Y. Ozbay & Andrew Schotter & Wolf Ze’ev Ehrblatt, 2012. "Convergence: An Experimental Study Of Teaching And Learning In Repeated Games," Journal of the European Economic Association, European Economic Association, vol. 10(3), pages 573-604, May.
    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. Bose, Subir & Daripa, Arup, 2023. "Eliciting second-order beliefs," Journal of Mathematical Economics, Elsevier, vol. 107(C).
    2. Karni, Edi & Vierø, Marie-Louise, 2023. "Comparative incompleteness: Measurement, behavioral manifestations and elicitation," Journal of Economic Behavior & Organization, Elsevier, vol. 205(C), pages 423-442.
    3. Jin Hyuk Choi & Kookyoung Han, 2023. "Delegation of information acquisition, information asymmetry, and outside option," International Journal of Game Theory, Springer;Game Theory Society, vol. 52(3), pages 833-860, September.
    4. Tsakas, Elias, 2020. "Robust scoring rules," Theoretical Economics, Econometric Society, vol. 15(3), July.
    5. J. Aislinn Bohren & Daniel N. Hauser, 2023. "Behavioral Foundations of Model Misspecification," PIER Working Paper Archive 23-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    6. Yingkai Li & Jonathan Libgober, 2023. "Optimal Scoring for Dynamic Information Acquisition," Papers 2310.19147, arXiv.org.
    7. Tsakas, Elias, 2018. "Robust scoring rules," Research Memorandum 023, Maastricht University, Graduate School of Business and Economics (GSBE).
    8. Karni, Edi, 2022. "A theory-based decision model," Journal of Economic Theory, Elsevier, vol. 201(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. 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.
    3. 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.
    4. Eyting, Markus & Schmidt, Patrick, 2021. "Belief elicitation with multiple point predictions," European Economic Review, Elsevier, vol. 135(C).
    5. Dominik Bauer & Irenaeus Wolff, 2018. "Biases in Beliefs: Experimental Evidence," TWI Research Paper Series 109, Thurgauer Wirtschaftsinstitut, Universität Konstanz.
    6. Folli, Dominik & Wolff, Irenaeus, 2022. "Biases in belief reports," Journal of Economic Psychology, Elsevier, vol. 88(C).
    7. 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.
    8. Markus Eyting & Patrick Schmidt, 2019. "Belief Elicitation with Multiple Point Predictions," Working Papers 1818, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 16 Nov 2020.
    9. Armantier, Olivier & Treich, Nicolas, 2013. "Eliciting beliefs: Proper scoring rules, incentives, stakes and hedging," European Economic Review, Elsevier, vol. 62(C), pages 17-40.
    10. 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.
    11. Tsakas, Elias, 2018. "Robust scoring rules," Research Memorandum 023, Maastricht University, Graduate School of Business and Economics (GSBE).
    12. Bergemann, Dirk & Ottaviani, Marco, 2021. "Information Markets and Nonmarkets," CEPR Discussion Papers 16459, C.E.P.R. Discussion Papers.
    13. Bose, Subir & Daripa, Arup, 2023. "Eliciting second-order beliefs," Journal of Mathematical Economics, Elsevier, vol. 107(C).
    14. Polonio, Luca & Coricelli, Giorgio, 2019. "Testing the level of consistency between choices and beliefs in games using eye-tracking," Games and Economic Behavior, Elsevier, vol. 113(C), pages 566-586.
    15. Claudia Neri, 2015. "Eliciting beliefs in continuous-choice games: a double auction experiment," Experimental Economics, Springer;Economic Science Association, vol. 18(4), pages 569-608, December.
    16. Azrieli, Yaron, 2022. "Delegated expertise: Implementability with peer-monitoring," Games and Economic Behavior, Elsevier, vol. 132(C), pages 240-254.
    17. Castagnetti, Alessandro & Schmacker, Renke, 2022. "Protecting the ego: Motivated information selection and updating," European Economic Review, Elsevier, vol. 142(C).
    18. Norde, Henk & Voorneveld, Mark, 2019. "Feasible best-response correspondences and quadratic scoring rules," SSE Working Paper Series in Economics 2019:2, Stockholm School of Economics.
    19. Aguirregabiria, Victor & Xie, Erhao, 2016. "Identification of Biased Beliefs in Games of Incomplete Information Using Experimental Data," CEPR Discussion Papers 11275, C.E.P.R. Discussion Papers.
    20. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.

    More about this item

    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:wly:emetrp:v:89:y:2021:i:1:p:375-414. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.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.