IDEAS home Printed from https://ideas.repec.org/a/eee/jeborg/v201y2022icp292-309.html
   My bibliography  Save this article

Outcome bias in self-evaluations: Quasi-experimental field evidence from Swiss driving license exams

Author

Listed:
  • Meier, Pascal Flurin
  • Flepp, Raphael
  • Meier, Philippe
  • Franck, Egon

Abstract

Exploiting a quasi-experimental field setting, we examine whether people are outcome biased when self-evaluating their past decisions. Using data from Swiss driving license exams, we find that candidates who narrowly passed the theoretical driving exam are significantly less likely to pass the subsequent practical driving exam – which is taken several months after the theoretical exam – than those who narrowly failed. Those candidates who passed the theoretical exam on their first attempt receive more objections regarding their momentary, on-the-spot decisions in the practical exam, consistent with the idea that the underlying behavioral difference is worse preparation.

Suggested Citation

  • Meier, Pascal Flurin & Flepp, Raphael & Meier, Philippe & Franck, Egon, 2022. "Outcome bias in self-evaluations: Quasi-experimental field evidence from Swiss driving license exams," Journal of Economic Behavior & Organization, Elsevier, vol. 201(C), pages 292-309.
    • Handle: RePEc:eee:jeborg:v:201:y:2022:i:c:p:292-309
    DOI: 10.1016/j.jebo.2022.07.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167268122002475
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jebo.2022.07.013?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. Gilles Hilary & Lior Menzly, 2006. "Does Past Success Lead Analysts to Become Overconfident?," Management Science, INFORMS, vol. 52(4), pages 489-500, April.
    2. Jared Rubin & Roman Sheremeta, 2016. "Principal–Agent Settings with Random Shocks," Management Science, INFORMS, vol. 62(4), pages 985-999, April.
    3. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust data-driven inference in the regression-discontinuity design," Stata Journal, StataCorp LP, vol. 14(4), pages 909-946, December.
    4. Sebastian Calonico & Matias D. Cattaneo & Rocio Titiunik, 2014. "Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs," Econometrica, Econometric Society, vol. 82, pages 2295-2326, November.
    5. Alexander Puetz & Stefan Ruenzi, 2011. "Overconfidence Among Professional Investors: Evidence from Mutual Fund Managers," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(5-6), pages 684-712, June.
    6. Hershey, John C. & Baron, Jonathan, 1992. "Judgment by outcomes: When is it justified?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 53(1), pages 89-93, October.
    7. Matthew T. Billett & Yiming Qian, 2008. "Are Overconfident CEOs Born or Made? Evidence of Self-Attribution Bias from Frequent Acquirers," Management Science, INFORMS, vol. 54(6), pages 1037-1051, June.
    8. Ratner, Rebecca K. & Herbst, Kenneth C., 2005. "When good decisions have bad outcomes: The impact of affect on switching behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 96(1), pages 23-37, January.
    9. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Rocío Titiunik, 2019. "Regression Discontinuity Designs Using Covariates," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 442-451, July.
    10. Kausel, Edgar E. & Ventura, Santiago & Rodríguez, Arturo, 2019. "Outcome bias in subjective ratings of performance: Evidence from the (football) field," Journal of Economic Psychology, Elsevier, vol. 75(PB).
    11. Andrew Gelman & Guido Imbens, 2019. "Why High-Order Polynomials Should Not Be Used in Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 447-456, July.
    12. Romain Gauriot & Lionel Page, 2019. "Fooled by Performance Randomness: Overrewarding Luck," The Review of Economics and Statistics, MIT Press, vol. 101(4), pages 658-666, October.
    13. Lipshitz, Raanan, 1989. ""Either a medal or a corporal": The effects of success and failure on the evaluation of decision making and decision makers," Organizational Behavior and Human Decision Processes, Elsevier, vol. 44(3), pages 380-395, December.
    14. Jones, Steven K. & Yurak, Tricia J. & Frisch, Deborah, 1997. "The Effect of Outcome Information on the Evaluation and Recall of Individuals' Own Decisions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 71(1), pages 95-120, July.
    15. Gonzalo Vazquez-Bare & Matias Cattaneo & Rocio Titiunik, 2016. "rdlocrand: a Stata Package for Inference in Regression Discontinuity Designs under Local Randomizati," 2016 Stata Conference 25, Stata Users Group.
    16. Raphael Flepp & Pascal Flurin Meier, 2024. "Struck by Luck: Noisy Capability Cues and CEO Dismissal," Working Papers 389, University of Zurich, Department of Business Administration (IBW).
    17. Czaja, Daniel & Röder, Florian, 2020. "Self-attribution bias and overconfidence among nonprofessional traders," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 186-198.
    18. Catherine H. Tinsley & Robin L. Dillon & Matthew A. Cronin, 2012. "How Near-Miss Events Amplify or Attenuate Risky Decision Making," Management Science, INFORMS, vol. 58(9), pages 1596-1613, September.
    19. Lars Lefgren & Brennan Platt & Joseph Price, 2015. "Sticking with What (Barely) Worked: A Test of Outcome Bias," Management Science, INFORMS, vol. 61(5), pages 1121-1136, May.
    20. Brownback, Andy & Kuhn, Michael A., 2019. "Understanding outcome bias," Games and Economic Behavior, Elsevier, vol. 117(C), pages 342-360.
    21. Murad, Zahra & Starmer, Chris, 2021. "Confidence snowballing and relative performance feedback," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 550-572.
    22. Matias D. Cattaneo & Nicolas Idrobo & Rocio Titiunik, 2019. "A Practical Introduction to Regression Discontinuity Designs: Foundations," Papers 1911.09511, arXiv.org.
    23. Eric J. Allen & Patricia M. Dechow & Devin G. Pope & George Wu, 2017. "Reference-Dependent Preferences: Evidence from Marathon Runners," Management Science, INFORMS, vol. 63(6), pages 1657-1672, June.
    24. Matias D. Cattaneo & Roc ́ıo Titiunik & Gonzalo Vazquez-Bare, 2016. "Inference in regression discontinuity designs under local randomization," Stata Journal, StataCorp LP, vol. 16(2), pages 331-367, June.
    25. Kremena Bachmann, 2018. "Can advisors eliminate the outcome bias in judgements and outcome-based emotions?," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 10(4), pages 336-352, October.
    26. Christian König-Kersting & Monique Pollmann & Jan Potters & Stefan T. Trautmann, 2021. "Good decision vs. good results: Outcome bias in the evaluation of financial agents," Theory and Decision, Springer, vol. 90(1), pages 31-61, February.
    27. Hilary, Gilles & Hsu, Charles, 2011. "Endogenous overconfidence in managerial forecasts," Journal of Accounting and Economics, Elsevier, vol. 51(3), pages 300-313, April.
    28. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell & Roc ́ıo Titiunik, 2017. "rdrobust: Software for regression-discontinuity designs," Stata Journal, StataCorp LP, vol. 17(2), pages 372-404, June.
    29. Sezer, Ovul & Zhang, Ting & Gino, Francesca & Bazerman, Max H., 2016. "Overcoming the outcome bias: Making intentions matter," Organizational Behavior and Human Decision Processes, Elsevier, vol. 137(C), pages 13-26.
    30. Burt S. Barnow & Matias D. Cattaneo & Rocío Titiunik & Gonzalo Vazquez‐Bare, 2017. "Comparing Inference Approaches for RD Designs: A Reexamination of the Effect of Head Start on Child Mortality," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 36(3), pages 643-681, June.
    31. Jonah Berger & Devin Pope, 2011. "Can Losing Lead to Winning?," Management Science, INFORMS, vol. 57(5), pages 817-827, May.
    32. Raphael Flepp & Egon Franck, 2021. "The Performance Effects Of Wise And Unwise Managerial Dismissals," Economic Inquiry, Western Economic Association International, vol. 59(1), pages 186-198, January.
    33. Mark E. Peecher & M. David Piercey, 2008. "Judging Audit Quality in Light of Adverse Outcomes: Evidence of Outcome Bias and Reverse Outcome Bias," Contemporary Accounting Research, John Wiley & Sons, vol. 25(1), pages 243-274, March.
    34. Gino, Francesca & Shu, Lisa L. & Bazerman, Max H., 2010. "Nameless + harmless = blameless: When seemingly irrelevant factors influence judgment of (un)ethical behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 111(2), pages 93-101, 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. Raphael Flepp & Oliver Merz & Egon Franck, 2024. "When the league table lies: Does outcome bias lead to informationally inefficient markets?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 414-429, January.
    2. Pascal Flurin Meier & Raphael Flepp & Egon Franck, 2022. "Are Expectations Misled by Chance? Quasi-Experimental Evidence from Financial Analysts," Working Papers 396, University of Zurich, Department of Business Administration (IBW).

    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. Raphael Flepp & Pascal Flurin Meier, 2024. "Struck by Luck: Noisy Capability Cues and CEO Dismissal," Working Papers 389, University of Zurich, Department of Business Administration (IBW).
    2. Oliver Merz & Raphael Flepp & Egon Franck, 2021. "Underestimating randomness: Outcome bias in betting exchange markets," Working Papers 390, University of Zurich, Department of Business Administration (IBW).
    3. Raphael Flepp & Oliver Merz & Egon Franck, 2024. "When the league table lies: Does outcome bias lead to informationally inefficient markets?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 414-429, January.
    4. Masayuki Sawada & Takuya Ishihara & Daisuke Kurisu & Yasumasa Matsuda, 2024. "Local-Polynomial Estimation for Multivariate Regression Discontinuity Designs," Papers 2402.08941, arXiv.org.
    5. Pascal Flurin Meier & Raphael Flepp & Philippe Meier & Egon Franck, 2022. "Outcome Bias in Self-evaluations: Quasi-experimental Field Evidence of Swiss Driving License Exams," Working Papers 392, University of Zurich, Department of Business Administration (IBW).
    6. Hérault, Nicolas & Vu, Ha & Wilkins, Roger, 2020. "The effect of job search requirements on welfare receipt," GLO Discussion Paper Series 646, Global Labor Organization (GLO).
    7. Lars Lefgren & Brennan Platt & Joseph Price, 2015. "Sticking with What (Barely) Worked: A Test of Outcome Bias," Management Science, INFORMS, vol. 61(5), pages 1121-1136, May.
    8. de Gendre, Alexandra & Lynch, John & Meunier, Aurélie & Pilkington, Rhiannon & Schurer, Stefanie, 2021. "Child Health and Parental Responses to an Unconditional Cash Transfer at Birth," IZA Discussion Papers 14693, Institute of Labor Economics (IZA).
    9. Atı̇la Abdulkadı̇roğlu & Joshua D. Angrist & Yusuke Narita & Parag Pathak, 2022. "Breaking Ties: Regression Discontinuity Design Meets Market Design," Econometrica, Econometric Society, vol. 90(1), pages 117-151, January.
    10. Pastore, Chiara & Jones, Andrew M., 2023. "Human capital consequences of missing out on a grammar school education," Economic Modelling, Elsevier, vol. 126(C).
    11. Lefgren, Lars J. & Platt, Brennan & Price, Joseph & Higbee, Samuel, 2019. "Outcome based accountability: Theory and evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 160(C), pages 121-137.
    12. Buhui Qiu & Gary Gang Tian & Haijian Zeng, 2022. "How Does Deleveraging Affect Funding Market Liquidity?," Management Science, INFORMS, vol. 68(6), pages 4568-4601, June.
    13. Cuong Viet Nguyen & Finn Tarp, 2023. "Cash Transfers and Labor Supply: New Evidence on Impacts and Mechanisms," DERG working paper series 23-18, University of Copenhagen. Department of Economics. Development Economics Research Group (DERG).
    14. Likai Chen & Georg Keilbar & Liangjun Su & Weining Wang, 2023. "Tests for Many Treatment Effects in Regression Discontinuity Panel Data Models," Papers 2312.01162, arXiv.org.
    15. Kettlewell, Nathan & Siminski, Peter, 2020. "Optimal Model Selection in RDD and Related Settings Using Placebo Zones," IZA Discussion Papers 13639, Institute of Labor Economics (IZA).
    16. Pasquini, Ricardo A., 2021. "Effects of regulating the brokerage commission in the rental market: Evidence from Buenos Aires," Journal of Housing Economics, Elsevier, vol. 54(C).
    17. Ciancio, Alberto & Kämpfen, Fabrice & Kohler, Hans-Peter & Kohler, Iliana V., 2021. "Health screening for emerging non-communicable disease burdens among the global poor: Evidence from sub-Saharan Africa," Journal of Health Economics, Elsevier, vol. 75(C).
    18. Burgherr, David, 2022. "Behavioral Responses to a Pension Savings Mandate : Quasi-experimental Evidence from Swiss Tax Data," CAGE Online Working Paper Series 645, Competitive Advantage in the Global Economy (CAGE).
    19. Mohamed Abouaziza, 2022. "Farmer constraints and relational contracts: evidence from agricultural value chains in East Africa," Economics PhD Theses 0122, Department of Economics, University of Sussex Business School.
    20. Onda, Masayuki & Seyler, Edward, 2020. "English learners reclassification and academic achievement: Evidence from Minnesota," Economics of Education Review, Elsevier, vol. 79(C).

    More about this item

    Keywords

    Outcome bias; Self-evaluation; Behavioral economics; Judgment; Regression discontinuity design;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    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:jeborg:v:201:y:2022:i:c:p:292-309. 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/jebo .

    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.