IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v94y2012i2p580-595.html
   My bibliography  Save this article

Age Effects and Heuristics in Decision Making

Author

Listed:
  • Tibor Besedeš

    (Georgia Institute of Technology)

  • Cary Deck

    (University of Arkansas and ESI, Chapman University)

  • Sudipta Sarangi

    (Louisiana State University and DIW Berlin)

  • Mikhael Shor

    (University of Connecticut)

Abstract

Using controlled experiments, we examine how individuals make choices when faced with multiple options. Choice tasks are designed to mimic the selection of health insurance, prescription drug, or retirement savings plans. In our experiment, available options can be objectively ranked, allowing us to examine optimal decision making. First, the probability of a person selecting the optimal option declines as the number of options increases, with the decline being more pronounced for older subjects. Second, heuristics differ by age, with older subjects relying more on suboptimal decision rules. In a heuristics validation experiment, older subjects make worse decisions than younger subjects. © 2012 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Tibor Besedeš & Cary Deck & Sudipta Sarangi & Mikhael Shor, 2012. "Age Effects and Heuristics in Decision Making," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 580-595, May.
  • Handle: RePEc:tpr:restat:v:94:y:2012:i:2:p:580-595
    as

    Download full text from publisher

    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00174
    File Function: link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.

    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. Shlomo Benartzi & Richard H. Thaler, 2002. "How Much Is Investor Autonomy Worth?," Journal of Finance, American Finance Association, vol. 57(4), pages 1593-1616, August.
    2. Esther Duflo & Emmanuel Saez, 2003. "The Role of Information and Social Interactions in Retirement Plan Decisions: Evidence from a Randomized Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 118(3), pages 815-842.
    3. Colin F. Camerer & Howard Kunreuther, 1989. "Decision processes for low probability events: Policy implications," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 8(4), pages 565-592.
    4. Richard G. Frank, 2004. "Behavioral Economics and Health Economics," NBER Working Papers 10881, National Bureau of Economic Research, Inc.
    5. Keeney,Ralph L. & Raiffa,Howard, 1993. "Decisions with Multiple Objectives," Cambridge Books, Cambridge University Press, number 9780521438834.
    6. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    7. Kovalchik, Stephanie & Camerer, Colin F. & Grether, David M. & Plott, Charles R. & Allman, John M., 2005. "Aging and decision making: a comparison between neurologically healthy elderly and young individuals," Journal of Economic Behavior & Organization, Elsevier, vol. 58(1), pages 79-94, September.
    8. Florian Heiss & Daniel McFadden & Joachim Winter, 2010. "Mind the Gap! Consumer Perceptions and Choices of Medicare Part D Prescription Drug Plans," NBER Chapters,in: Research Findings in the Economics of Aging, pages 413-481 National Bureau of Economic Research, Inc.
    9. Cole, Catherine A & Balasubramanian, Siva K, 1993. " Age Differences in Consumers' Search for Information: Public Policy Implications," Journal of Consumer Research, Oxford University Press, vol. 20(1), pages 157-169, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    experiments; decision making; optimal choice; age effects; heuristics;

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    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:tpr:restat:v:94:y:2012:i:2:p:580-595. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kristin Waites). General contact details of provider: http://mitpress.mit.edu/journals/ .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.