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Reusing Natural Experiments

Author

Listed:
  • Heath, Davidson

    (University of Utah David Eccles School of Business)

  • Ringgenberg, Matthew C.

    (University of Utah - Department of Finance)

  • Samadi, Mehrdad

    (Southern Methodist University (SMU) - Finance Department)

  • Werner, Ingrid M.

    (The Ohio State University - Fisher College of Business)

Abstract

Natural experiments are used in empirical research to make causal inferences. After a natural experiment is first used, other researchers often reuse the setting, examining different outcomes based on causal chain arguments. Using simulation evidence combined with two extensively studied natural experiments, business combination laws and the Regulation SHO pilot, we show that the repeated use of a natural experiment significantly increases the likelihood of false discoveries. To correct this, we propose multiple testing methods which account for dependence across tests and we show evidence of their efficacy.

Suggested Citation

  • Heath, Davidson & Ringgenberg, Matthew C. & Samadi, Mehrdad & Werner, Ingrid M., 2019. "Reusing Natural Experiments," Working Paper Series 2019-21, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    • Handle: RePEc:ecl:ohidic:2019-21
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    Cited by:

    1. Chad Brown & Paola Conconi & Aksel Erbahar & Lorenzo Trimarchi, 2020. "Trade Protection Along Supply Chains," Working Papers ECARES 2020-52, ULB -- Universite Libre de Bruxelles.
    2. Chen, Xiaoqi & Chih-Chieh Chris, Hsieh & Tsang, Albert & Xiang, Yi, 2022. "Cross-border enforcement of securities laws and dividend payouts," The British Accounting Review, Elsevier, vol. 54(6).
    3. Bui, Dien Giau & Hasan, Iftekhar & Lin, Chih-Yung & Nguyen, Hong Thoa, 2023. "Short-selling threats and bank risk-taking: Evidence from the financial crisis," Journal of Banking & Finance, Elsevier, vol. 150(C).
    4. Gong, Rong, 2020. "Short selling threat and corporate financing decisions," Journal of Banking & Finance, Elsevier, vol. 118(C).
    5. Chen, Jie & Su, Xunhua & Tian, Xuan & Xu, Bin, 2022. "Does customer-base structure influence managerial risk-taking incentives?," Journal of Financial Economics, Elsevier, vol. 143(1), pages 462-483.
    6. Merkley, Kenneth & Michaely, Roni & Pacelli, Joseph, 2020. "Cultural diversity on Wall Street: Evidence from consensus earnings forecasts," Journal of Accounting and Economics, Elsevier, vol. 70(1).
    7. Guernsey, Scott & Sepe, Simone M. & Serfling, Matthew, 2022. "Blood in the water: The value of antitakeover provisions during market shocks," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1070-1096.
    8. Aepli, Manuel & Kuhn, Andreas & Schweri, Jürg, 2021. "Culture, norms, and the provision of training by employers: Evidence from the Swiss language border," Labour Economics, Elsevier, vol. 73(C).
    9. Leuz, Christian, 2022. "Towards a design-based approach to accounting research," Journal of Accounting and Economics, Elsevier, vol. 74(2).
    10. Jonathan Brogaard & Jing Pan, 2022. "Dark Pool Trading and Information Acquisition," The Review of Financial Studies, Society for Financial Studies, vol. 35(5), pages 2625-2666.
    11. Yun Ke & Kin Lo & Jinfei Sheng & Jenny Li Zhang, 2023. "Do investors affect financial analysts’ behavior? Evidence from short sellers," Financial Management, Financial Management Association International, vol. 52(1), pages 199-224, March.
    12. Baixiao Liu & John J. McConnell & Andrew Schrowang, 2023. "The Effect of Short-Sale Restrictions on Corporate Managers," JRFM, MDPI, vol. 16(11), pages 1-23, November.
    13. Tianyu Cai & Lixiong Guo & Yongxian Tan, 2024. "Short seller monitoring and real earnings management," The Financial Review, Eastern Finance Association, vol. 59(1), pages 203-225, February.
    14. Nilabhra Bhattacharya & Theodore E. Christensen & Qunfeng Liao & Bo Ouyang, 2022. "Can short sellers constrain aggressive non-GAAP reporting?," Review of Accounting Studies, Springer, vol. 27(2), pages 391-440, June.

    More about this item

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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