IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/14353.html
   My bibliography  Save this paper

Measuring intertemporal preferences using response times

Author

Listed:
  • Christopher F. Chabris
  • David Laibson
  • Carrie L. Morris
  • Jonathon P. Schuldt
  • Dmitry Taubinsky

Abstract

We use two different approaches to measure intertemporal preferences. First we employ the classical method of inferring preferences from a series of choices (subjects choose between $X now or $Y in D days). Second we adopt the novel approach of inferring preferences using only response time data from the same choices (how long it takes subjects to choose between $X now or $Y in D days). In principle, the inference from response times should work, since choices between items of nearly equivalent value should take longer than choices between items with substantially different values. We find that choice-based analysis and response-time-based analysis yield nearly identical discount rate estimates. We conclude that response time data sheds light on both our revealed (choice-based) preferences and on the cognitive processes that implement those preferences.

Suggested Citation

  • Christopher F. Chabris & David Laibson & Carrie L. Morris & Jonathon P. Schuldt & Dmitry Taubinsky, 2008. "Measuring intertemporal preferences using response times," NBER Working Papers 14353, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:14353
    Note: EH LS PE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w14353.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xavier Gabaix & David Laibson & Guillermo Moloche & Stephen Weinberg, 2006. "Costly Information Acquisition: Experimental Analysis of a Boundedly Rational Model," American Economic Review, American Economic Association, vol. 96(4), pages 1043-1068, September.
    2. Ariel Rubinstein, 2007. "Instinctive and Cognitive Reasoning: A Study of Response Times," Economic Journal, Royal Economic Society, vol. 117(523), pages 1243-1259, October.
    3. George Loewenstein & Drazen Prelec, 1992. "Anomalies in Intertemporal Choice: Evidence and an Interpretation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 573-597.
    4. Ariel Rubinstein, 2007. "Instinctive and Cognitive Reasoning: Response Times Study," Levine's Bibliography 321307000000001011, UCLA Department of Economics.
    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. John R. Doyle, 2013. "Survey of time preference, delay discounting models," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 8(2), pages 116-135, March.
    2. van der Heijden, Eline & Klein, Tobias J. & Müller, Wieland & Potters, Jan, 2012. "Framing effects and impatience: Evidence from a large scale experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 84(2), pages 701-711.
    3. 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.
    4. Novarese, Marco & Di Giovinazzo, Viviana, 2013. "Solerzia e successo accademico [Diligence and Academic Performance]," MPRA Paper 45008, University Library of Munich, Germany.
    5. Gabriele Camera & Marco Casari & Maria Bigoni, 2010. "Cooperative Strategies in Groups of Strangers: An Experiment," Purdue University Economics Working Papers 1237, Purdue University, Department of Economics.
    6. Clithero, John A., 2018. "Response times in economics: Looking through the lens of sequential sampling models," Journal of Economic Psychology, Elsevier, vol. 69(C), pages 61-86.
    7. Leonidas Spiliopoulos & Andreas Ortmann, 2018. "The BCD of response time analysis in experimental economics," Experimental Economics, Springer;Economic Science Association, vol. 21(2), pages 383-433, June.
    8. Meier, Stephan & Sprenger, Charles D., 2013. "Discounting financial literacy: Time preferences and participation in financial education programs," Journal of Economic Behavior & Organization, Elsevier, vol. 95(C), pages 159-174.
    9. Christopher F. Chabris & David Laibson & Carrie L. Morris & Jonathon P. Schuldt & Dmitry Taubinsky, 2009. "The Allocation of Time in Decision-Making," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 628-637, 04-05.
    10. Chapkovski, Philipp & Zihlmann, Christian, 2019. "Introducing otree_tools: A powerful package to provide process data for attention, multitasking behavior and effort through tracking focus," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 75-83.
    11. Wieland Mueller & Eline van der Heijden & Tobias J. Klein & Jan Potters, 2011. "Nudges and Impatience: Evidence from a Large Scale Experiment," Vienna Economics Papers 1110, University of Vienna, Department of Economics.
    12. repec:cup:judgdm:v:8:y:2013:i:2:p:116-135 is not listed on IDEAS
    13. Novarese, Marco & Di Giovinazzo, Viviana, 2013. "Promptness and Academic Performance," MPRA Paper 49746, University Library of Munich, Germany.
    14. Aneeque Javaid & Micaela M Kulesz & Achim Schlüter & Alexandra Ghosh & Narriman S Jiddawi, 2016. "Time Preferences and Natural Resource Extraction Behavior: An Experimental Study from Artisanal Fisheries in Zanzibar," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-14, December.

    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. Arkady Konovalov & Ian Krajbich, 2019. "Revealed strength of preference: Inference from response times," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(4), pages 381-394, July.
    2. repec:cup:judgdm:v:14:y:2019:i:4:p:381-394 is not listed on IDEAS
    3. Vincent P. Crawford, 2006. "Look-ups as the Windows of the Strategic Soul: Studying Cognition via Information Search in Game Experiments," Levine's Bibliography 321307000000000462, UCLA Department of Economics.
    4. Andrew Schotter & Isabel Trevino, 2021. "Is response time predictive of choice? An experimental study of threshold strategies," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 87-117, March.
    5. Arkady Konovalov & Ian Krajbich, 2016. "Revealed Indifference: Using Response Times to Infer Preferences," Working Papers 16-01, Ohio State University, Department of Economics.
    6. Krajbich Ian & Smith Stephanie M., 2015. "Modeling Eye Movements and Response Times in Consumer Choice," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 13(1), pages 55-72, January.
    7. Carlos Alós-Ferrer & Michele Garagnani, 2022. "Strength of preference and decisions under risk," Journal of Risk and Uncertainty, Springer, vol. 64(3), pages 309-329, June.
    8. Strittmatter, Anthony & Sunde, Uwe & Zegners, Dainis, 2022. "Speed, Quality, and the Optimal Timing of Complex Decisions: Field Evidence," Rationality and Competition Discussion Paper Series 317, CRC TRR 190 Rationality and Competition.
    9. Yuval Salant & Jörg L. Spenkuch, 2021. "Complexity and Choice," CESifo Working Paper Series 9239, CESifo.
    10. Echenique, Federico & Saito, Kota, 2017. "Response time and utility," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 49-59.
    11. Mark Schneider, 2016. "Dual Process Utility Theory: A Model of Decisions Under Risk and Over Time," Working Papers 16-23, Chapman University, Economic Science Institute.
    12. Nobuo Koida, 2017. "A multiattribute decision time theory," Theory and Decision, Springer, vol. 83(3), pages 407-430, October.
    13. Schneider, Mark & Coulter, Robin A., 2015. "A Dual Process Evaluability Framework for decision anomalies," Journal of Economic Psychology, Elsevier, vol. 51(C), pages 183-198.
    14. Ispano, Alessandro & Schwardmann, Peter, 2017. "Cooperating over losses and competing over gains: A social dilemma experiment," Games and Economic Behavior, Elsevier, vol. 105(C), pages 329-348.
    15. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    16. Gisèle Umbhauer, 2019. "Traveler’s dilemma : how the value of the luggage influences behavior," Working Papers of BETA 2019-13, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    17. Anna Louisa Merkel & Johannes Lohse, 2019. "Is fairness intuitive? An experiment accounting for subjective utility differences under time pressure," Experimental Economics, Springer;Economic Science Association, vol. 22(1), pages 24-50, March.
    18. Tiziana Assenza & Te Bao & Cars Hommes & Domenico Massaro, 2014. "Experiments on Expectations in Macroeconomics and Finance," Research in Experimental Economics, in: Experiments in Macroeconomics, volume 17, pages 11-70, Emerald Group Publishing Limited.
    19. Eamonn Ferguson & John Maltby & Peter A Bibby & Claire Lawrence, 2014. "Fast to Forgive, Slow to Retaliate: Intuitive Responses in the Ultimatum Game Depend on the Degree of Unfairness," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-8, May.
    20. Pintér, Ágnes & Veszteg, Róbert F., 2010. "Minority vs. majority: An experimental study of standardized bids," European Journal of Political Economy, Elsevier, vol. 26(1), pages 36-50, March.
    21. Fehr, Dietmar & Sutter, Matthias, 2019. "Gossip and the efficiency of interactions," Games and Economic Behavior, Elsevier, vol. 113(C), pages 448-460.

    More about this item

    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics
    • D9 - Microeconomics - - Micro-Based Behavioral Economics

    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:nbr:nberwo:14353. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.