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Risk perception in an endogenous information environment

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  • 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
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    References listed on IDEAS

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    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.
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