IDEAS home Printed from https://ideas.repec.org/p/rco/dpaper/386.html
   My bibliography  Save this paper

Measuring Preferences Over Intertemporal Profiles

Author

Listed:
  • Chen Sun

    (HU Berlin)

Abstract

Growing evidence indicates that utility over time is different from utility under risk. Hence, measuring intertemporal preferences (discounting and utility) exclusively from intertemporal choices is desirable. We develop a simple method for measuring intertemporal preferences. It is parameter-free in both discounting and utility, and allows a wider range of models to be measured than preceding methods. It is easy to implement, clear to subjects, incentive compatible, and does not require more measurements than existing methods if identical assumptions are imposed. In an experiment, we illustrate how the method can be used to test recent models with unconventional assumptions non-parametrically.

Suggested Citation

  • Chen Sun, 2023. "Measuring Preferences Over Intertemporal Profiles," Rationality and Competition Discussion Paper Series 386, CRC TRR 190 Rationality and Competition.
    • Handle: RePEc:rco:dpaper:386
    as

    Download full text from publisher

    File URL: https://rationality-and-competition.de/wp-content/uploads/discussion_paper/386.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David K. Levine & Drew Fudenberg, 2006. "A Dual-Self Model of Impulse Control," American Economic Review, American Economic Association, vol. 96(5), pages 1449-1476, December.
    2. Ned Augenblick & Muriel Niederle & Charles Sprenger, 2015. "Editor's Choice Working over Time: Dynamic Inconsistency in Real Effort Tasks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(3), pages 1067-1115.
    3. Mohammed Abdellaoui & ArthurE. Attema & Han Bleichrodt, 2010. "Intertemporal Tradeoffs for Gains and Losses: An Experimental Measurement of Discounted Utility," Economic Journal, Royal Economic Society, vol. 120(545), pages 845-866, June.
    4. Mohammed Abdellaoui & Han Bleichrodt & Olivier l'Haridon & Corina Paraschiv, 2013. "Is There One Unifying Concept of Utility?An Experimental Comparison of Utility Under Risk and Utility Over Time," Management Science, INFORMS, vol. 59(9), pages 2153-2169, September.
    5. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    6. Stephen L. Cheung, 2020. "Eliciting utility curvature in time preference," Experimental Economics, Springer;Economic Science Association, vol. 23(2), pages 493-525, June.
    7. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    8. Takeuchi, Kan, 2011. "Non-parametric test of time consistency: Present bias and future bias," Games and Economic Behavior, Elsevier, vol. 71(2), pages 456-478, March.
    9. Stein T. Holden & John Quiggin, 2017. "Bounded awareness and anomalies in intertemporal choice: Zooming in Google Earth as both metaphor and model," Journal of Risk and Uncertainty, Springer, vol. 54(1), pages 15-35, February.
    10. James Andreoni & Charles Sprenger, 2012. "Estimating Time Preferences from Convex Budgets," American Economic Review, American Economic Association, vol. 102(7), pages 3333-3356, December.
    11. Maribeth Coller & Melonie Williams, 1999. "Eliciting Individual Discount Rates," Experimental Economics, Springer;Economic Science Association, vol. 2(2), pages 107-127, December.
    12. Noor, Jawwad, 2011. "Intertemporal choice and the magnitude effect," Games and Economic Behavior, Elsevier, vol. 72(1), pages 255-270, May.
    13. Read, Daniel & Roelofsma, Peter H. M. P., 2003. "Subadditive versus hyperbolic discounting: A comparison of choice and matching," Organizational Behavior and Human Decision Processes, Elsevier, vol. 91(2), pages 140-153, July.
    14. Kerschbamer, Rudolf, 2015. "The geometry of distributional preferences and a non-parametric identification approach: The Equality Equivalence Test," European Economic Review, Elsevier, vol. 76(C), pages 85-103.
    15. Steffen Andersen & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström, 2008. "Eliciting Risk and Time Preferences," Econometrica, Econometric Society, vol. 76(3), pages 583-618, May.
    16. Bin Miao & Songfa Zhong, 2015. "Risk Preferences Are Not Time Preferences: Separating Risk and Time Preference: Comment," American Economic Review, American Economic Association, vol. 105(7), pages 2272-2286, July.
    17. Thomas Epper & Helga Fehr-Duda & Adrian Bruhin, 2011. "Viewing the future through a warped lens: Why uncertainty generates hyperbolic discounting," Journal of Risk and Uncertainty, Springer, vol. 43(3), pages 169-203, December.
    18. Arthur E. Attema & Han Bleichrodt & Yu Gao & Zhenxing Huang & Peter P. Wakker, 2016. "Measuring Discounting without Measuring Utility," American Economic Review, American Economic Association, vol. 106(6), pages 1476-1494, June.
    19. Read, Daniel, 2001. "Is Time-Discounting Hyperbolic or Subadditive?," Journal of Risk and Uncertainty, Springer, vol. 23(1), pages 5-32, July.
    20. Chen Sun & Jan Potters, 2022. "Magnitude effect in intertemporal allocation tasks," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 593-623, April.
    21. Shane Frederick & George Loewenstein & Ted O'Donoghue, 2002. "Time Discounting and Time Preference: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 40(2), pages 351-401, June.
    22. Benhabib, Jess & Bisin, Alberto & Schotter, Andrew, 2010. "Present-bias, quasi-hyperbolic discounting, and fixed costs," Games and Economic Behavior, Elsevier, vol. 69(2), pages 205-223, July.
    Full references (including those not matched with items on IDEAS)

    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. Chen Sun & Jan Potters, 2022. "Magnitude effect in intertemporal allocation tasks," Experimental Economics, Springer;Economic Science Association, vol. 25(2), pages 593-623, April.
    2. W. David Bradford & Paul Dolan & Matteo M. Galizzi, 2019. "Looking ahead: Subjective time perception and individual discounting," Journal of Risk and Uncertainty, Springer, vol. 58(1), pages 43-69, February.
    3. Stephen L. Cheung, 2020. "Eliciting utility curvature in time preference," Experimental Economics, Springer;Economic Science Association, vol. 23(2), pages 493-525, June.
    4. Andersen, Steffen & Harrison, Glenn W. & Lau, Morten I. & Rutström, E. Elisabet, 2014. "Discounting behavior: A reconsideration," European Economic Review, Elsevier, vol. 71(C), pages 15-33.
    5. Stefan A. Lipman & Arthur E. Attema, 2024. "A systematic review of unique methods for measuring discount rates," Journal of Risk and Uncertainty, Springer, vol. 69(2), pages 145-189, October.
    6. Cheung, Stephen L., 2016. "Recent developments in the experimental elicitation of time preference," Journal of Behavioral and Experimental Finance, Elsevier, vol. 11(C), pages 1-8.
    7. Rodriguez-Lara, Ismael & Ponti, Giovanni, 2017. "Social motives vs social influence: An experiment on interdependent time preferences," Games and Economic Behavior, Elsevier, vol. 105(C), pages 177-194.
    8. Irvine, Alastair & van der Pol, Marjon & Phimister, Euan, 2019. "A comparison of professional and private time preferences of General Practitioners," Social Science & Medicine, Elsevier, vol. 222(C), pages 256-264.
    9. Cheung, Stephen L., 2016. "Recent developments in the experimental elicitation of time preference," Journal of Behavioral and Experimental Finance, Elsevier, vol. 11(C), pages 1-8.
    10. Robin Chark & Soo Chew & Songfa Zhong, 2015. "Extended present bias: a direct experimental test," Theory and Decision, Springer, vol. 79(1), pages 151-165, July.
    11. Stein T. Holden & Dag Einar Sommervoll & Mesfin Tilahun, 2022. "Mental Zooming as Variable Asset Integration in Inter-Temporal Choice," International Journal of Applied Behavioral Economics (IJABE), IGI Global, vol. 11(1), pages 1-21, January.
    12. Holden, Stein T. & Tilahun, Mesfin & Sommervoll, Dag Einar, 2022. "Is diminishing impatience in time-dated risky prospects explained by probability weighting?," CLTS Working Papers 3/22, Norwegian University of Life Sciences, Centre for Land Tenure Studies.
    13. Abdellaoui, Mohammed & Kemel, Emmanuel & Panin, Amma & Vieider, Ferdinand M., 2019. "Measuring time and risk preferences in an integrated framework," Games and Economic Behavior, Elsevier, vol. 115(C), pages 459-469.
    14. Sebastian Schweighofer-Kodritsch, 2015. "Time Preferences and Bargaining," STICERD - Theoretical Economics Paper Series /2015/568, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    15. Jindrich Matousek & Tomas Havranek & Zuzana Irsova, 2022. "Individual discount rates: a meta-analysis of experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 25(1), pages 318-358, February.
    16. Susan Laury & Melayne McInnes & J. Todd Swarthout, 2012. "Avoiding the curves: Direct elicitation of time preferences," Journal of Risk and Uncertainty, Springer, vol. 44(3), pages 181-217, June.
    17. Mohammed Abdellaoui & Han Bleichrodt & Olivier l’Haridon, 2013. "Sign-dependence in intertemporal choice," Journal of Risk and Uncertainty, Springer, vol. 47(3), pages 225-253, December.
    18. Zhihua Li & Songfa Zhong, 2023. "Reference Dependence in Intertemporal Preference," Management Science, INFORMS, vol. 69(1), pages 475-490, January.
    19. Cheung, Stephen L. & Tymula, Agnieszka & Wang, Xueting, 2021. "Quasi-Hyperbolic Present Bias: A Meta-Analysis," IZA Discussion Papers 14625, Institute of Labor Economics (IZA).
    20. Arthur E. Attema & Han Bleichrodt & Olivier L’Haridon & Patrick Peretti-Watel & Valérie Seror, 2018. "Discounting health and money: New evidence using a more robust method," Journal of Risk and Uncertainty, Springer, vol. 56(2), pages 117-140, April.

    More about this item

    Keywords

    measuring time preferences; intertemporal profile; parameter-free;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:rco:dpaper:386. 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: Viviana Lalli (email available below). General contact details of provider: https://rationality-and-competition.de .

    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.