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Behavioral Welfare Economics and Risk Preferences: A Bayesian Approach

Author

Listed:
  • Gao, Xiaoxue Sherry

    (University of Massachusetts Amherst)

  • Harrison, Glenn

    (Georgia State University, CEAR)

  • Tchernis, Rusty

    (Georgia State University)

Abstract

We propose the use of Bayesian estimation of risk preferences of individuals for applications of behavioral welfare economics to evaluate observed choices that involve risk. Bayesian estimation provides more systematic control of the use of informative priors over inferences about risk preferences for each individual in a sample. We demonstrate that these methods make a difference to the rigorous normative evaluation of decisions in a case study of insurance purchases. We also show that hierarchical Bayesian methods can be used to infer welfare reliably and efficiently even with significantly reduced demands on the number of choices that each subject has to make. Finally, we illustrate the natural use of Bayesian methods in the adaptive evaluation of welfare.

Suggested Citation

  • Gao, Xiaoxue Sherry & Harrison, Glenn & Tchernis, Rusty, 2020. "Behavioral Welfare Economics and Risk Preferences: A Bayesian Approach," IZA Discussion Papers 13580, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp13580
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    References listed on IDEAS

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    1. A. Stefano Caria & Grant Gordon & Maximilian Kasy & Simon Quinn & Soha Shami & Alexander Teytelboym, 2020. "An Adaptive Targeted Field Experiment: Job Search Assistance for Refugees in Jordan," CSAE Working Paper Series 2020-20, Centre for the Study of African Economies, University of Oxford.
    2. Steffen Andersen & John Fountain & Glenn Harrison & E. Rutström, 2014. "Estimating subjective probabilities," Journal of Risk and Uncertainty, Springer, vol. 48(3), pages 207-229, June.
    3. Glenn W. Harrison, 2011. "Experimental methods and the welfare evaluation of policy lotteries," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 38(3), pages 335-360, August.
    4. Joel Huber and Kenneth Train., 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Economics Working Papers E00-289, University of California at Berkeley.
    5. Ryan O. Murphy & Robert H.W. ten Brincke, "undated". "Hierarchical maximum likelihood parameter estimation for cumulative prospect theory: Improving the reliability of individual risk parameter estimates," Working Papers ETH-RC-14-005, ETH Zurich, Chair of Systems Design.
    6. Glenn W. Harrison & Jia Min Ng, 2016. "Evaluating The Expected Welfare Gain From Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 91-120, January.
    7. Harrison, Glenn W, 1990. "Risk Attitudes in First-Price Auction Experiments: A Bayesian Analysis," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 541-546, August.
    8. Steffen Andersen & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström, 2018. "Multiattribute Utility Theory, Intertemporal Utility, And Correlation Aversion," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(2), pages 537-555, May.
    9. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    10. Ryan O. Murphy & Robert H. W. ten Brincke, 2018. "Hierarchical Maximum Likelihood Parameter Estimation for Cumulative Prospect Theory: Improving the Reliability of Individual Risk Parameter Estimates," Management Science, INFORMS, vol. 64(1), pages 308-328, January.
    11. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    12. Maximilian Kasy & Anja Sautmann, 2021. "Adaptive Treatment Assignment in Experiments for Policy Choice," Econometrica, Econometric Society, vol. 89(1), pages 113-132, January.
    13. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    14. Glenn W. Harrison & Don Ross, 2018. "Varieties of paternalism and the heterogeneity of utility structures," Journal of Economic Methodology, Taylor & Francis Journals, vol. 25(1), pages 42-67, January.
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    Cited by:

    1. Glenn W. Harrison & Andre Hofmeyr & Harold Kincaid & Brian Monroe & Don Ross & Mark Schneider & J. Todd Swarthout, 2022. "Subjective beliefs and economic preferences during the COVID-19 pandemic," Experimental Economics, Springer;Economic Science Association, vol. 25(3), pages 795-823, June.
    2. Glenn Harrison & Karlijn Morsink & Mark Schneider, 2022. "Literacy and the quality of index insurance decisions," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 47(1), pages 66-97, March.

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    More about this item

    Keywords

    behavioral welfare economics; Bayesian Analysis; risk preferences; insurance;
    All these keywords.

    JEL classification:

    • D6 - Microeconomics - - Welfare Economics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G40 - Financial Economics - - Behavioral Finance - - - General

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