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Willingness to Pay and Willingness to Accept are Probably Less Correlated Than You Think

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  • Jonathan Chapman
  • Mark Dean
  • Pietro Ortoleva
  • Erik Snowberg
  • Colin Camerer

Abstract

An enormous literature documents that willingness to pay (WTP) is less than willingness to accept (WTA) a monetary amount for an object, a phenomenon called the endowment effect. Using data from an incentivized survey of a representative sample of 3,000 U.S. adults, we add one (probably) surprising additional finding: WTA and WTP for a lottery are, at best, slightly correlated. Across all respondents, the correlation is slightly negative. A meta-study of published experiments with university students shows a correlation of around 0.15--0.2, consistent with the correlation in our data for high-IQ respondents. While poorly related to each other, WTA and WTP are closely related to different measures of risk aversion, and relatively stable across time. We show that the endowment effect is not related to individual-level measures of loss aversion, counter to Prospect Theory or Stochastic Reference Dependence.

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  • 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.
    • Handle: RePEc:nbr:nberwo:23954
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    Cited by:

    1. Jonathan Chapman & Mark Dean & Pietro Ortoleva & Erik Snowberg & Colin Camerer, 2018. "Econographics," NBER Working Papers 24931, National Bureau of Economic Research, Inc.
    2. Smith, Alec, 2019. "Lagged beliefs and reference-dependent utility," Journal of Economic Behavior & Organization, Elsevier, vol. 167(C), pages 331-340.
    3. Otto, Philipp E. & Schmidt, Lennard, 2021. "Reservation price uncertainty: Loss, virtue, or emotional heterogeneity?," Journal of Economic Psychology, Elsevier, vol. 87(C).
    4. Jonathan Chapman & Erik Snowberg & Stephanie Wang & Colin Camerer, 2018. "Loss Attitudes in the U.S. Population: Evidence from Dynamically Optimized Sequential Experimentation (DOSE)," NBER Working Papers 25072, National Bureau of Economic Research, Inc.
    5. Flynn, James, 2022. "Salary disclosure and individual effort: Evidence from the National Hockey League," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 471-497.
    6. Jeffrey R. Brown & Arie Kapteyn & Erzo F. P. Luttmer & Olivia S. Mitchell & Anya Samek, 2021. "Behavioral Impediments to Valuing Annuities: Complexity and Choice Bracketing," The Review of Economics and Statistics, MIT Press, vol. 103(3), pages 533-546, July.
    7. Jonathan Chapman & Mark Dean & Pietro Ortoleva & Erik Snowberg & Colin Camerer, 2021. "On the Relation between Willingness to Accept and Willingness to Pay," Working Papers 2021-90, Princeton University. Economics Department..
    8. Christopher P. Chambers & Federico Echenique & Nicolas S. Lambert, 2023. "Recovering utility," Papers 2301.11492, arXiv.org.
    9. Christina McGranaghan & Steven G. Otto, 2022. "Choice uncertainty and the endowment effect," Journal of Risk and Uncertainty, Springer, vol. 65(1), pages 83-104, August.
    10. Guney, Begum & Richter, Michael & Tsur, Matan, 2018. "Aspiration-based choice," Journal of Economic Theory, Elsevier, vol. 176(C), pages 935-956.
    11. Johannes G. Jaspersen & Marc A. Ragin & Justin R. Sydnor, 2019. "Predicting Insurance Demand from Risk Attitudes," NBER Working Papers 26508, National Bureau of Economic Research, Inc.
    12. Basu, Pathikrit & Echenique, Federico, 2020. "On the falsifiability and learnability of decision theories," Theoretical Economics, Econometric Society, vol. 15(4), November.
    13. Jonathan Chapman & Mark Dean & Pietro Ortoleva & Erik Snowberg & Colin Camerer, 2020. "Econographics," Working Papers 2020-75, Princeton University. Economics Department..

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    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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