IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_7262.html
   My bibliography  Save this paper

Loss Attitudes in the U.S. Population: Evidence from Dynamically Optimized Sequential Experimentation (DOSE)

Author

Listed:
  • Jonathan Chapman
  • Erik Snowberg
  • Stephanie Wang
  • Colin Camerer

Abstract

We introduce DOSE - Dynamically Optimized Sequential Experimentation - and use it to estimate individual-level loss aversion in a representative sample of the U.S. population (N = 2,000). DOSE elicitations are more accurate, more stable across time, and faster to administer than standard methods. We find that around 50% of the U.S. population is loss tolerant. This is counter to earlier findings, which mostly come from lab/student samples, that a strong majority of participants are loss averse. Loss attitudes are correlated with cognitive ability: loss aversion is more prevalent in people with high cognitive ability, and loss tolerance is more common in those with low cognitive ability. We also use DOSE to document facts about risk and time preferences, indicating a high potential for DOSE in future research.

Suggested Citation

  • Jonathan Chapman & Erik Snowberg & Stephanie Wang & Colin Camerer, 2018. "Loss Attitudes in the U.S. Population: Evidence from Dynamically Optimized Sequential Experimentation (DOSE)," CESifo Working Paper Series 7262, CESifo.
  • Handle: RePEc:ces:ceswps:_7262
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp7262.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ola Andersson & Håkan J. Holm & Jean-Robert Tyran & Erik Wengström, 2016. "Deciding for Others Reduces Loss Aversion," Management Science, INFORMS, vol. 62(1), pages 29-36, January.
    2. James Berry & Greg Fischer & Raymond Guiteras, 2020. "Eliciting and Utilizing Willingness to Pay: Evidence from Field Trials in Northern Ghana," Journal of Political Economy, University of Chicago Press, vol. 128(4), pages 1436-1473.
    3. Peter Brooks & Horst Zank, 2005. "Loss Averse Behavior," Journal of Risk and Uncertainty, Springer, vol. 31(3), pages 301-325, December.
    4. Oechssler, Jörg & Roider, Andreas & Schmitz, Patrick W., 2009. "Cognitive abilities and behavioral biases," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 147-152, October.
    5. Lönnqvist, Jan-Erik & Verkasalo, Markku & Walkowitz, Gari & Wichardt, Philipp C., 2015. "Measuring individual risk attitudes in the lab: Task or ask? An empirical comparison," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 254-266.
    6. Uri Gneezy & Jan Potters, 1997. "An Experiment on Risk Taking and Evaluation Periods," The Quarterly Journal of Economics, Oxford University Press, vol. 112(2), pages 631-645.
    7. Adam Booij & Bernard Praag & Gijs Kuilen, 2010. "A parametric analysis of prospect theory’s functionals for the general population," Theory and Decision, Springer, vol. 68(1), pages 115-148, February.
    8. Mohammed Abdellaoui & Olivier L'Haridon & Corina Paraschiv, 2011. "Experienced vs. Described Uncertainty: Do We Need Two Prospect Theory Specifications?," Management Science, INFORMS, vol. 57(10), pages 1879-1895, October.
    9. Robin Cubitt & Chris Starmer & Robert Sugden, 1998. "On the Validity of the Random Lottery Incentive System," Experimental Economics, Springer;Economic Science Association, vol. 1(2), pages 115-131, September.
    10. 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.
    11. David J. Freeman & Yoram Halevy & Terri Kneeland, 2019. "Eliciting risk preferences using choice lists," Quantitative Economics, Econometric Society, vol. 10(1), pages 217-237, January.
    12. Eyal Ert & Ido Erev, 2010. "On the Descriptive Value of Loss Aversion in Decisions under Risk," Harvard Business School Working Papers 10-056, Harvard Business School.
    13. Booij, Adam S. & van de Kuilen, Gijs, 2009. "A parameter-free analysis of the utility of money for the general population under prospect theory," Journal of Economic Psychology, Elsevier, vol. 30(4), pages 651-666, August.
    14. Jan-Erik Loennqvist & Markku Verkasalo & Gari Walkowitz & Philipp C. Wichardt, 2011. "Measuring Individual Risk Attitudes in the Lab: Task or Ask? An Empirical Comparison," Cologne Graduate School Working Paper Series 02-03, Cologne Graduate School in Management, Economics and Social Sciences.
    15. Dunn, L F, 1996. "Loss Aversion and Adaptation in the Labor Market: Empirical Indifference Functions and Labor Supply," The Review of Economics and Statistics, MIT Press, vol. 78(3), pages 441-450, August.
    16. Alex Rees-Jones, 2018. "Quantifying Loss-Averse Tax Manipulation," Review of Economic Studies, Oxford University Press, vol. 85(2), pages 1251-1278.
    17. Chuang, Yating & Schechter, Laura, 2015. "Stability of experimental and survey measures of risk, time, and social preferences: A review and some new results," Journal of Development Economics, Elsevier, vol. 117(C), pages 151-170.
    18. Jonathan Chapman & Pietro Ortoleva & Erik Snowberg & Colin Camerer & Mark Dean, 2017. "Willingness-To-Pay and Willingness-To-Accept are Probably Less Correlated than You Think," CESifo Working Paper Series 6492, CESifo.
    19. Kurata, Hiroshi & Izawa, Hiroshi & Okamura, Makoto, 2009. "Non-expected utility maximizers behave as if expected utility maximizers: An experimental test," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(4), pages 622-629, August.
    20. John Hey & Jinkwon Lee, 2005. "Do Subjects Separate (or Are They Sophisticated)?," Experimental Economics, Springer;Economic Science Association, vol. 8(3), pages 233-265, September.
    21. Yaron Azrieli & Christopher P. Chambers & Paul J. Healy, 2018. "Incentives in Experiments: A Theoretical Analysis," Journal of Political Economy, University of Chicago Press, vol. 126(4), pages 1472-1503.
    22. James Berry & Greg Fischer & Raymond Guiteras, 2020. "Eliciting and Utilizing Willingness to Pay: Evidence from Field Trials in Northern Ghana," Journal of Political Economy, University of Chicago Press, vol. 128(4), pages 1436-1473.
    23. Aigner, Dennis J., 1979. "A brief introduction to the methodology of optimal experimental design," Journal of Econometrics, Elsevier, vol. 11(1), pages 7-26, September.
    24. Mark Dean & Anja Sautmann, 2014. "Credit Constraints and the Measurement of Time Preferences," Working Papers 2014-1, Brown University, Department of Economics.
    25. Chetan Dave & Catherine Eckel & Cathleen Johnson & Christian Rojas, 2010. "Eliciting risk preferences: When is simple better?," Journal of Risk and Uncertainty, Springer, vol. 41(3), pages 219-243, December.
    26. Charness, Gary & Viceisza, Angelino, 2011. "Comprehension and risk elicitation in the field: Evidence from rural Senegal," IFPRI discussion papers 1135, International Food Policy Research Institute (IFPRI).
    27. Schmidt, Ulrich & Traub, Stefan, 2002. "An Experimental Test of Loss Aversion," Journal of Risk and Uncertainty, Springer, vol. 25(3), pages 233-249, November.
    28. Sarah Jacobson & Ragan Petrie, 2009. "Learning from mistakes: What do inconsistent choices over risk tell us?," Journal of Risk and Uncertainty, Springer, vol. 38(2), pages 143-158, April.
    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. Lau Lilleholt, 2019. "Cognitive ability and risk aversion: A systematic review and meta analysis," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(3), pages 234-279, May.
    2. Diogo Geraldes & Franziska Heinicke & Duk Gyoo Kim, 2020. "Big and Small Lies," CESifo Working Paper Series 8142, CESifo.
    3. 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.
    4. Bnaya Dreyfuss & Ori Heffetz & Matthew Rabin, 2019. "Expectations-Based Loss Aversion May Help Explain Seemingly Dominated Choices in Strategy-Proof Mechanisms," NBER Working Papers 26394, National Bureau of Economic Research, Inc.
    5. Potrafke, Niklas, 2019. "Risk aversion, patience and intelligence: Evidence based on macro data," Economics Letters, Elsevier, vol. 178(C), pages 116-120.

    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. Paolo Crosetto & Antonio Filippin, 2013. "The “bomb” risk elicitation task," Journal of Risk and Uncertainty, Springer, vol. 47(1), pages 31-65, August.
    2. Tamás Csermely & Alexander Rabas, 2016. "How to reveal people’s preferences: Comparing time consistency and predictive power of multiple price list risk elicitation methods," Journal of Risk and Uncertainty, Springer, vol. 53(2), pages 107-136, December.
    3. Ranoua Bouchouicha & Lachlan Deer & Ashraf Galal Eid & Peter McGee & Daniel Schoch & Hrvoje Stojic & Jolanda Ygosse-Battisti & Ferdinand M. Vieider, 2019. "Gender effects for loss aversion: Yes, no, maybe?," Journal of Risk and Uncertainty, Springer, vol. 59(2), pages 171-184, October.
    4. Pan He & Marcella Veronesi & Stefanie Engel, 2016. "Consistency of Risk Preference Measures and the Role of Ambiguity: An Artefactual Field Experiment from China," Working Papers 03/2016, University of Verona, Department of Economics.
    5. Colasante, Annarita & Marini, Matteo M. & Russo, Alberto, 2017. "Incidental emotions and risk-taking: An experimental analysis," MPRA Paper 76992, University Library of Munich, Germany.
    6. Sanjit Dhami & Narges Hajimoladarvish, 2020. "Mental Accounting, Loss Aversion, and Tax Evasion: Theory and Evidence," CESifo Working Paper Series 8606, CESifo.
    7. Drichoutis, Andreas C. & Vassilopoulos, Achilleas, 2016. "Intertemporal stability of survey-based measures of risk and time preferences over a three-year course," MPRA Paper 73548, University Library of Munich, Germany.
    8. Dasgupta, Utteeyo & Gangadharan, Lata & Maitra, Pushkar & Mani, Subha, 2017. "Searching for preference stability in a state dependent world," Journal of Economic Psychology, Elsevier, vol. 62(C), pages 17-32.
    9. Crosetto, Paolo & Filippin, Antonio, 2017. "Safe Options Induce Gender Differences in Risk Attitudes," IZA Discussion Papers 10793, Institute of Labor Economics (IZA).
    10. Filiz, Ibrahim & Nahmer, Thomas & Spiwoks, Markus & Gubaydullina, Zulia, 2020. "Measurement of risk preference," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    11. Patrick DeJarnette & David Dillenberger & Daniel Gottlieb & Pietro Ortoleva, 2020. "Time Lotteries and Stochastic Impatience," Econometrica, Econometric Society, vol. 88(2), pages 619-656, March.
    12. Jonathan Chapman & Mark Dean & Pietro Ortoleva & Erik Snowberg & Colin Camerer, 2017. "Willingness to Pay and Willingness to Accept are Probably Less Correlated Than You Think," NBER Working Papers 23954, National Bureau of Economic Research, Inc.
    13. Patrick DeJarnette & David Dillenberger & Daniel Gottlieb & Pietro Ortoleva, 2014. "Time Lotteries and Stochastic Impatience," PIER Working Paper Archive 18-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 13 Jun 2018.
    14. Simon Gaechter & Eric Johnson & Andreas Herrmann, 2007. "Individual-Level Loss Aversion In Riskless And Risky Choices," Discussion Papers 2007-02, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    15. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier, 2013. "Prospect theory in the health domain: A quantitative assessment," Journal of Health Economics, Elsevier, vol. 32(6), pages 1057-1065.
    16. Eyal Ert & Ido Erev, 2013. "On the descriptive value of loss aversion in decisions under risk: Six clarifications," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 8(3), pages 214-235, May.
    17. Galizzi, Matteo M. & Machado, Sara R. & Miniaci, Raffaele, 2016. "Temporal stability, cross-validity, and external validity of risk preferences measures: experimental evidence from a UK representative sample," LSE Research Online Documents on Economics 67554, London School of Economics and Political Science, LSE Library.
    18. Paolo Crosetto & Antonio Filippin, 2013. "A Theoretical and Experimental Appraisal of Five Risk Elicitation Methods," SOEPpapers on Multidisciplinary Panel Data Research 547, DIW Berlin, The German Socio-Economic Panel (SOEP).
    19. Menkhoff, Lukas & Sakha, Sahra, 2017. "Estimating risky behavior with multiple-item risk measures," Journal of Economic Psychology, Elsevier, vol. 59(C), pages 59-86.
    20. Holden , Stein T. & Tilahun , Mesfin, 2019. "The Devil is in the Details: Risk Preferences, Choice List Design, and Measurement Error," CLTS Working Papers 3/19, Norwegian University of Life Sciences, Centre for Land Tenure Studies, revised 16 Oct 2019.

    More about this item

    Keywords

    dynamic experiments; DOSE; loss aversion; risk preferences; time preferences;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General

    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:ces:ceswps:_7262. 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: (Klaus Wohlrabe). General contact details of provider: http://edirc.repec.org/data/cesifde.html .

    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.