IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v149y2016icp168-171.html
   My bibliography  Save this article

A critical note on Salience Theory of choice under risk

Author

Listed:
  • Kontek, Krzysztof

Abstract

Salience Theory Bordalo et al. (2012a) is a context-dependent theory of choice under risk, where objective probabilities are replaced by decision weights distorted in favor of salient payoffs. The detailed analysis presented in this paper points out serious flaws in this model, the most serious of which is that the lottery certainty equivalent is undefined for some ranges of probabilities. Moreover, the model violates monotonicity. The origin of the peculiar features of the model lies in switching between different evaluation expressions that depend on salience conditions or the number of prospect payoffs. The number of evaluation expressions and switching values grows rapidly with the number of states considered.

Suggested Citation

  • Kontek, Krzysztof, 2016. "A critical note on Salience Theory of choice under risk," Economics Letters, Elsevier, vol. 149(C), pages 168-171.
    • Handle: RePEc:eee:ecolet:v:149:y:2016:i:c:p:168-171
    DOI: 10.1016/j.econlet.2016.10.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176516304189
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2016.10.021?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Consumer Choice," Journal of Political Economy, University of Chicago Press, vol. 121(5), pages 803-843.
    2. 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.
    3. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2012. "Salience Theory of Choice Under Risk," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(3), pages 1243-1285.
    4. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2013. "Salience and Asset Prices," American Economic Review, American Economic Association, vol. 103(3), pages 623-628, May.
    5. Harless, David W & Camerer, Colin F, 1994. "The Predictive Utility of Generalized Expected Utility Theories," Econometrica, Econometric Society, vol. 62(6), pages 1251-1289, November.
    6. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2012. "Salience in Experimental Tests of the Endowment Effect," American Economic Review, American Economic Association, vol. 102(3), pages 47-52, May.
    7. Pedro Bordalo & Nicola Gennaioli & Andrei Shleifer, 2015. "Salience Theory of Judicial Decisions," The Journal of Legal Studies, University of Chicago Press, vol. 44(S1), pages 7-33.
    8. Machina, Mark J, 1982. ""Expected Utility" Analysis without the Independence Axiom," Econometrica, Econometric Society, vol. 50(2), pages 277-323, March.
    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. Dertwinkel-Kalt, Markus & Köster, Mats, 2017. "Local thinking and skewness preferences," DICE Discussion Papers 248, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    2. R. Emre Aytimur, 2023. "Salience and horizontal differentiation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(1), pages 60-86, February.
    3. Krzysztof Kontek, 2018. "Boundary effects in the Marschak-Machina triangle," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(6), pages 587-606, November.
    4. Fabio Römeis & Fabian Herweg & Daniel Müller, 2022. "Salience Bias and Overwork," Games, MDPI, vol. 13(1), pages 1-22, January.
    5. Herweg, Fabian & Müller, Daniel, 2021. "A comparison of regret theory and salience theory for decisions under risk," Journal of Economic Theory, Elsevier, vol. 193(C).
    6. Markus Dertwinkel-Kalt & Mats Köster, 2020. "Salience and Skewness Preferences [Risk-neutral Firms can Extract Unbounded Profits from Consumers with Prospect Theory Preferences]," Journal of the European Economic Association, European Economic Association, vol. 18(5), pages 2057-2107.
    7. repec:cup:judgdm:v:13:y:2018:i:6:p:587-606 is not listed on IDEAS
    8. Königsheim, C. & Lukas, M. & Nöth, M., 2019. "Salience theory: Calibration and heterogeneity in probability distortion," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 477-495.
    9. Wang, Di, 2021. "Attention-driven probability weighting," Economics Letters, Elsevier, vol. 203(C).
    10. Xiangfeng Ji & Xiaoyu Ao, 2021. "Travelers’ Bi-Attribute Decision Making on the Risky Mode Choice with Flow-Dependent Salience Theory," Sustainability, MDPI, vol. 13(7), pages 1-24, April.
    11. Bakó, Barna & Neszveda, Gábor, 2020. "The Achilles’ heel of Salience theory and a way to fix it," Economics Letters, Elsevier, vol. 193(C).
    12. Kelvin Balcombe & Iain Fraser & Abhijit Sharma, 2021. "An econometric analysis of salience theory," Bulletin of Economic Research, Wiley Blackwell, vol. 73(4), pages 545-554, October.
    13. Qinghui Xu & Xiangfeng Ji, 2020. "User Equilibrium Analysis Considering Travelers’ Context-Dependent Route Choice Behavior on the Risky Traffic Network," Sustainability, MDPI, vol. 12(17), pages 1-25, August.

    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. Königsheim, C. & Lukas, M. & Nöth, M., 2019. "Salience theory: Calibration and heterogeneity in probability distortion," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 477-495.
    2. Bakó, Barna & Neszveda, Gábor, 2020. "The Achilles’ heel of Salience theory and a way to fix it," Economics Letters, Elsevier, vol. 193(C).
    3. Chen, Daniel L. & Prescott, J.J., 2016. "Implicit Egoism in Sentencing Decisions: First Letter Name Effects with Randomly Assigned Defendants," IAST Working Papers 16-56, Institute for Advanced Study in Toulouse (IAST).
    4. Adrian Bruhin & Maha Manai & Luís Santos-Pinto, 2022. "Risk and rationality: The relative importance of probability weighting and choice set dependence," Journal of Risk and Uncertainty, Springer, vol. 65(2), pages 139-184, October.
    5. Hu, Shiyang & Xiang, Cheng & Quan, Xiaofeng, 2023. "Salience theory and mutual fund flows: Empirical evidence from China," Emerging Markets Review, Elsevier, vol. 54(C).
    6. Cosemans, Mathijs & Frehen, Rik, 2021. "Salience theory and stock prices: Empirical evidence," Journal of Financial Economics, Elsevier, vol. 140(2), pages 460-483.
    7. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    8. Stephen G Dimmock & Roy Kouwenberg & Olivia S Mitchell & Kim Peijnenburg, 2021. "Household Portfolio Underdiversification and Probability Weighting: Evidence from the Field," Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4524-4563.
    9. repec:cup:judgdm:v:16:y:2021:i:6:p:1324-1369 is not listed on IDEAS
    10. Balart, Pau, 2021. "Semiorder preferences and price-oriented buyers in a Hotelling model," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 394-407.
    11. Dertwinkel-Kalt, Markus & Wenzel, Tobias, 2019. "Focusing and framing of risky alternatives," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 289-304.
    12. Mungan, Murat C., 2019. "Salience and the severity versus the certainty of punishment," International Review of Law and Economics, Elsevier, vol. 57(C), pages 95-100.
    13. Sudeep Bhatia & Graham Loomes & Daniel Read, 2021. "Establishing the laws of preferential choice behavior," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(6), pages 1324-1369, November.
    14. Mark Schneider, 2019. "A Bias Aggregation Theorem," Working Papers 19-03, Chapman University, Economic Science Institute.
    15. Edward John Dorrell Webb, 2014. "Do we see monopoly or duopoly? The influence of perception on entry deterrence," Discussion Papers 14-20, University of Copenhagen. Department of Economics.
    16. Dertwinkel-Kalt, Markus & Köster, Mats, 2017. "Local thinking and skewness preferences," DICE Discussion Papers 248, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    17. Barna Bakó & Gábor Neszveda & Linda Dezső, 2018. "When irrelevant alternatives do matter. The effect of focusing on loan decisions," Theory and Decision, Springer, vol. 84(1), pages 123-141, January.
    18. Edward J. Webb, 2014. "Perception and quality choice in vertically differentiated markets," Discussion Papers 14-07, University of Copenhagen. Department of Economics.
    19. Qinghui Xu & Xiangfeng Ji, 2020. "User Equilibrium Analysis Considering Travelers’ Context-Dependent Route Choice Behavior on the Risky Traffic Network," Sustainability, MDPI, vol. 12(17), pages 1-25, August.
    20. Chen, Rongxin & Lepori, Gabriele M. & Tai, Chung-Ching & Sung, Ming-Chien, 2022. "Can salience theory explain investor behaviour? Real-world evidence from the cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 84(C).
    21. Krzysztof Kontek, 2018. "Boundary effects in the Marschak-Machina triangle," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(6), pages 587-606, November.

    More about this item

    Keywords

    Models of decision-making under risk; Certainty equivalents; Marschak–Machina triangle; Indifference curves;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    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:eee:ecolet:v:149:y:2016:i:c:p:168-171. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    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.