IDEAS home Printed from https://ideas.repec.org/a/eee/reecon/v76y2022i4p355-372.html
   My bibliography  Save this article

Risk perception in an endogenous information environment

Author

Listed:
  • Tsang, Ming

Abstract

This study examines risk perception in an endogenous information setting, where information about an uncertain event can only be gathered if the uncertain event is chosen over all other alternatives. We conduct a laboratory experiment that employs a driving context, where participants are asked to make route choices over uncertain routes using a driving simulator. Based on the route choices participants make, their subjective belief of travel delay can be inferred and structured estimated. The results show that: 1) The average participants initially overestimates the risk of travel delay across high- and low-risk conditions. 2) In subsequent driving periods, only participants in the lowest risk condition express significant downward belief adjustment, resulting in their beliefs no longer being significantly different from the objective risk. This is consistent with the toll fee being the most elastic in the lowest risk condition, and the most inelastic in the higher risk conditions.

Suggested Citation

  • Tsang, Ming, 2022. "Risk perception in an endogenous information environment," Research in Economics, Elsevier, vol. 76(4), pages 355-372.
  • Handle: RePEc:eee:reecon:v:76:y:2022:i:4:p:355-372
    DOI: 10.1016/j.rie.2022.09.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1090944322000485
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rie.2022.09.003?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. 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.
    2. Constantinos Antoniou & Glenn Harrison & Morten Lau & Daniel Read, 2015. "Subjective Bayesian beliefs," Journal of Risk and Uncertainty, Springer, vol. 50(1), pages 35-54, February.
    3. John D. Hey & Noemi Pace, 2018. "The explanatory and predictive power of non two-stage-probability theories of decision making under ambiguity," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 6, pages 139-167, World Scientific Publishing Co. Pte. Ltd..
    4. David M. Grether, 1980. "Bayes Rule as a Descriptive Model: The Representativeness Heuristic," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 95(3), pages 537-557.
    5. Grether, David M., 1992. "Testing bayes rule and the representativeness heuristic: Some experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 17(1), pages 31-57, January.
    6. Mangelsdorff, Lukas & Weber, Martin, 1994. "Testing choquet expected utility," Journal of Economic Behavior & Organization, Elsevier, vol. 25(3), pages 437-457, December.
    7. James Cox & Vjollca Sadiraj & Ulrich Schmidt, 2015. "Paradoxes and mechanisms for choice under risk," Experimental Economics, Springer;Economic Science Association, vol. 18(2), pages 215-250, June.
    8. Glenn W. Harrison & E. Elisabet Rutström, 2008. "Risk Aversion in the Laboratory," Research in Experimental Economics, in: Risk Aversion in Experiments, pages 41-196, Emerald Group Publishing Limited.
    9. Holgun-Veras, Jos & Cetin, Mecit, 2009. "Optimal tolls for multi-class traffic: Analytical formulations and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 445-467, May.
    10. David Ahn & Syngjoo Choi & Douglas Gale & Shachar Kariv, 2014. "Estimating ambiguity aversion in a portfolio choice experiment," Quantitative Economics, Econometric Society, vol. 5, pages 195-223, July.
    11. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    12. Cox, James C & Epstein, Seth, 1989. "Preference Reversals without the Independence Axiom," American Economic Review, American Economic Association, vol. 79(3), pages 408-426, June.
    13. Fiore, Stephen M. & Harrison, Glenn W. & Hughes, Charles E. & Rutstrm, E. Elisabet, 2009. "Virtual experiments and environmental policy," Journal of Environmental Economics and Management, Elsevier, vol. 57(1), pages 65-86, January.
    14. David M. Grether & James C. Cox, 1996. "The preference reversal phenomenon: Response mode, markets and incentives (*)," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 7(3), pages 381-405.
    15. Steffen Andersen & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström, 2008. "Eliciting Risk and Time Preferences," Econometrica, Econometric Society, vol. 76(3), pages 583-618, May.
    16. Robert Ziółkowski & Zbigniew Dziejma, 2021. "Investigations of the Dynamic Travel Time Information Impact on Drivers’ Route Choice in an Urban Area—A Case Study Based on the City of Bialystok," Energies, MDPI, vol. 14(6), pages 1-14, March.
    Full references (including those not matched with items on IDEAS)

    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. Tsang, Ming, 2020. "Estimating uncertainty aversion using the source method in stylized tasks with varying degrees of uncertainty," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 84(C).
    2. Fidanoski, Filip & Johnson, Timothy, 2023. "A z-Tree implementation of the Dynamic Experiments for Estimating Preferences [DEEP] method," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    3. Xiaoxue Sherry Gao & Glenn W. Harrison & Rusty Tchernis, 2023. "Behavioral welfare economics and risk preferences: a Bayesian approach," Experimental Economics, Springer;Economic Science Association, vol. 26(2), pages 273-303, April.
    4. Bocquého, Géraldine & Deschamps, Marc & Helstroffer, Jenny & Jacob, Julien & Joxhe, Majlinda, 2023. "Modelling refugee migration under cognitive biases: Experimental evidence and policy," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 103(C).
    5. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd & Ulm, Eric R., 2017. "Scoring rules for subjective probability distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 430-448.
    6. Watanabe, Masahide & Fujimi, Toshio, 2022. "Ambiguity of scientific probability predictions and willingness-to-pay for climate change mitigation policies," Research in Economics, Elsevier, vol. 76(4), pages 386-402.
    7. Christoph Duden & Oliver Mußhoff & Frank Offermann, 2023. "Dealing with low‐probability shocks: The role of selected heuristics in farmers’ risk management decisions," Agricultural Economics, International Association of Agricultural Economists, vol. 54(3), pages 382-399, May.
    8. Crosetto, Paolo & Filippin, Antonio & Katuščák, Peter & Smith, John, 2020. "Central tendency bias in belief elicitation," Journal of Economic Psychology, Elsevier, vol. 78(C).
    9. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    10. Daniel J. Benjamin, 2018. "Errors in Probabilistic Reasoning and Judgment Biases," NBER Working Papers 25200, National Bureau of Economic Research, Inc.
    11. Georgalos, Konstantinos, 2021. "Dynamic decision making under ambiguity: An experimental investigation," Games and Economic Behavior, Elsevier, vol. 127(C), pages 28-46.
    12. Daniela Di Cagno & Daniela Grieco, 2019. "Measuring and Disentangling Ambiguity and Confidence in the Lab," Games, MDPI, vol. 10(1), pages 1-22, February.
    13. Skjold, Benjamin & Steinkamp, Simon Richard & Hulme, Oliver J & Peters, Ole & Connaughton, Colm, 2023. "Are risk preferences optimal?," OSF Preprints ew2sx, Center for Open Science.
    14. Jeffrey Butler & Luigi Guiso & Tullio Jappelli, 2014. "The role of intuition and reasoning in driving aversion to risk and ambiguity," Theory and Decision, Springer, vol. 77(4), pages 455-484, December.
    15. Geng, Kexin & Wang, Yacan & Cherchi, Elisabetta & Guarda, Pablo, 2023. "Commuter departure time choice behavior under congestion charge: Analysis based on cumulative prospect theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
    16. Antoniou, Constantinos & Harrison, Glenn W. & Lau, Morten I. & Read, Daniel, 2017. "Information Characteristics and Errors in Expectations: Experimental Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(2), pages 737-750, April.
    17. Vera Angelova & Olivier Armantier & Giuseppe Attanasi & Yolande Hiriart, 2014. "Relative performance of liability rules: experimental evidence," Theory and Decision, Springer, vol. 77(4), pages 531-556, December.
    18. Li Hao & Daniel Houser, 2012. "Belief elicitation in the presence of naïve respondents: An experimental study," Journal of Risk and Uncertainty, Springer, vol. 44(2), pages 161-180, April.
    19. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd, 2014. "Eliciting subjective probabilities with binary lotteries," Journal of Economic Behavior & Organization, Elsevier, vol. 101(C), pages 128-140.
    20. Anja Achtziger & Carlos Alós-Ferrer & Alexander Ritschel, 2020. "Cognitive load in economic decisions," ECON - Working Papers 354, Department of Economics - University of Zurich.

    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:reecon:v:76:y:2022:i:4:p:355-372. 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/inca/622941 .

    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.