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Pre-Decisional Information Acquisition: Do We Pay TooMuch for Information?

Author

Listed:
  • Marc Oliver Rieger
  • Mei Wang
  • Daniel Hausmann

Abstract

It is a common phenomenon that people tend to acquire more information in a decision task than a rational benchmark would predict. What is the reason behind this? To answer this question we conducted an information acquisition experiment that has been carefully designed to disentangle several plausible reasons for information overpurchasing before decision-making. A within-subject experiment with a simple basic information acquisition task on an investment project, equivalent formulated lotteries, estimations of probability, and an additional option to satisfy one’s curiosity was used to test five different potential reasons. The results show that overpurchasing of information can be explained nearly entirely by systematic information-processing errors (misestimationor incorrect Bayesean updating). Other factors, such as overoptimism on the validity of new information, risk aversion, ambiguity aversion, and curiosity for (irrelevant) information, play at most a minor role. Our results imply that overinvestment in information acquisition can be mostly avoided if more detailed informationis given to decision makers on how much (or little) further information can improve the decision quality.

Suggested Citation

  • Marc Oliver Rieger & Mei Wang & Daniel Hausmann, 2020. "Pre-Decisional Information Acquisition: Do We Pay TooMuch for Information?," Working Paper Series 2020-02, University of Trier, Research Group Quantitative Finance and Risk Analysis.
  • Handle: RePEc:trr:qfrawp:202002
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    References listed on IDEAS

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    1. Moore, Don A. & Cain, Daylian M., 2007. "Overconfidence and underconfidence: When and why people underestimate (and overestimate) the competition," Organizational Behavior and Human Decision Processes, Elsevier, vol. 103(2), pages 197-213, July.
    2. Gilliland, Stephen W. & Schmitt, Neal & Wood, Lisa, 1993. "Cost-Benefit Determinants of Decision Process and Accuracy," Organizational Behavior and Human Decision Processes, Elsevier, vol. 56(2), pages 308-330, November.
    3. Klayman, Joshua & Soll, Jack B. & Gonzalez-Vallejo, Claudia & Barlas, Sema, 1999. "Overconfidence: It Depends on How, What, and Whom You Ask, , , , , , , , ," Organizational Behavior and Human Decision Processes, Elsevier, vol. 79(3), pages 216-247, September.
    4. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    5. Warren J. McIsaac & Cheryl L. Hunchak, 2011. "Overestimation Error and Unnecessary Antibiotic Prescriptions for Acute Cystitis in Adult Women," Medical Decision Making, , vol. 31(3), pages 405-411, May.
    6. Benjamin Enke & Florian Zimmermann, 2019. "Correlation Neglect in Belief Formation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(1), pages 313-332.
    7. Matthew Rabin, 2000. "Risk Aversion and Expected-Utility Theory: A Calibration Theorem," Econometrica, Econometric Society, vol. 68(5), pages 1281-1292, September.
    8. Saad, Gad & Russo, J. Edward, 1996. "Stopping Criteria in Sequential Choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 67(3), pages 258-270, September.
    9. Bruce A. Weinberg, 2009. "A Model Of Overconfidence," Pacific Economic Review, Wiley Blackwell, vol. 14(4), pages 502-515, October.
    10. David M. Grether, 1980. "Bayes Rule as a Descriptive Model: The Representativeness Heuristic," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 95(3), pages 537-557.
    11. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    12. repec:cup:judgdm:v:3:y:2008:i::p:229-243 is not listed on IDEAS
    13. Daniel Ellsberg, 1961. "Risk, Ambiguity, and the Savage Axioms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 75(4), pages 643-669.
    14. Maner, Jon K. & Gerend, Mary A., 2007. "Motivationally selective risk judgments: Do fear and curiosity boost the boons or the banes?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 103(2), pages 256-267, July.
    15. Pavlo Blavatskyy, 2009. "Betting on own knowledge: Experimental test of overconfidence," Journal of Risk and Uncertainty, Springer, vol. 38(1), pages 39-49, February.
    16. repec:cup:judgdm:v:4:y:2009:i:6:p:447-460 is not listed on IDEAS
    17. Grieco, Daniela & Hogarth, Robin M., 2009. "Overconfidence in absolute and relative performance: The regression hypothesis and Bayesian updating," Journal of Economic Psychology, Elsevier, vol. 30(5), pages 756-771, October.
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    More about this item

    Keywords

    sequential information acquisition; ambiguity; Bayesian updating; financial decision-making;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G1 - Financial Economics - - General Financial Markets

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