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Incorporating Framing into Prospect Theory Modeling: A Mixture-Model Approach

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  • Mei Wang
  • Paul S. Fischbeck

Abstract

This paper illustrates the use of a statistical technique, finite mixture models, to fit the parameters in cumulative prospect theory. For a given decision, some individuals may adopt a gain frame, while others may adopt a loss frame. By using finite mixture models, the best fitting parameters can be obtained for the two subgroups, even though the information about subjective frames was not available. Our application uses two health insurance survey datasets collected by Rand and Chinese State Natural Science Foundation, respectively. The results are compared with previous studies on framing effects and parameterizations of prospect theory.

Suggested Citation

  • Mei Wang & Paul S. Fischbeck, 2004. "Incorporating Framing into Prospect Theory Modeling: A Mixture-Model Approach," Journal of Risk and Uncertainty, Springer, vol. 29(2), pages 181-197, September.
  • Handle: RePEc:kap:jrisku:v:29:y:2004:i:2:p:181-197
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    Citations

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    Cited by:

    1. Campbell Pryor & Amy Perfors & Piers D. L. Howe, 2018. "Reversing the endowment effect," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(3), pages 275-286, May.
    2. Marc Oliver Rieger & Mei Wang & Thorsten Hens, 2017. "Estimating cumulative prospect theory parameters from an international survey," Theory and Decision, Springer, vol. 82(4), pages 567-596, April.
    3. Cristóbal De La Maza & Alex Davis & Cleotilde Gonzalez & Inês Azevedo, 2019. "Understanding Cumulative Risk Perception from Judgments and Choices: An Application to Flood Risks," Risk Analysis, John Wiley & Sons, vol. 39(2), pages 488-504, February.
    4. Dennis Fok & Richard Paap & Philip Hans Franses, 2014. "Incorporating Responsiveness to Marketing Efforts in Brand Choice Modeling," Econometrics, MDPI, vol. 2(1), pages 1-25, February.
    5. Yehuda Izhakian, 2012. "Ambiguity Measurement," Working Papers 12-01, New York University, Leonard N. Stern School of Business, Department of Economics.
    6. W. Wong & R. Chan, 2008. "Prospect and Markowitz stochastic dominance," Annals of Finance, Springer, vol. 4(1), pages 105-129, January.
    7. Marc Oliver Rieger & Mei Wang & Thorsten Hens, 2015. "Risk Preferences Around the World," Management Science, INFORMS, vol. 61(3), pages 637-648, March.
    8. Rieger, Marc Oliver & Wang, Mei & Huang, Po-Kai & Hsu, Yuan-Lin, 2022. "Survey evidence on core factors of behavioral biases," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 100(C).
    9. repec:cup:judgdm:v:13:y:2018:i:3:p:275-286 is not listed on IDEAS
    10. Metzger, Lars Peter & Rieger, Marc Oliver, 2019. "Non-cooperative games with prospect theory players and dominated strategies," Games and Economic Behavior, Elsevier, vol. 115(C), pages 396-409.

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