[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-3-031-44424-1_10.html
   My bibliography  Save this book chapter

When Are We Willing to Wait? Prescriptive Challenges in Evaluating Intertemporal Outcomes

In: Behavioral Decision Analysis

Author

Listed:
  • Jeffery L. Guyse

    (Technology and Operations Management, College of Business Administration, California State Polytechnic University)

  • Candice H. Huynh

    (Technology and Operations Management, College of Business Administration, California State Polytechnic University)

  • L. Robin Keller

    (The Paul Merage School of Business, University of California)

  • Jay Simon

    (Kogod School of Business, American University)

Abstract
The classic normative model for intertemporal preferences uses a constant discount rate, but behavioral experiments have shown that people do not tend to make choices consistent with a constant discount rate. We first present normative models for time preferences, then discuss descriptive results for choices between single outcomes occurring at different times. People often have different implicit discount rates for different types of scenarios, and several anomalies arise consistently. We contrast those results with findings for preferences for sequences of multiple outcomes over time. People tend to prefer increasing or constant sequences of outcomes over time, especially when the outcomes are non-monetary in nature. This suggests a willingness to wait for improvement, but not in the way that classical discounting would prescribe. We end with prescriptive nudges to improve dynamic consistency and pose questions still to be resolved about how decisions involving outcomes over time can be improved prescriptively.

Suggested Citation

  • Jeffery L. Guyse & Candice H. Huynh & L. Robin Keller & Jay Simon, 2024. "When Are We Willing to Wait? Prescriptive Challenges in Evaluating Intertemporal Outcomes," International Series in Operations Research & Management Science, in: Florian M. Federspiel & Gilberto Montibeller & Matthias Seifert (ed.), Behavioral Decision Analysis, pages 187-211, Springer.
    • Handle: RePEc:spr:isochp:978-3-031-44424-1_10
    DOI: 10.1007/978-3-031-44424-1_10
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:isochp:978-3-031-44424-1_10. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.