The revolving door and the SEC’s enforcement outcomes: Initial evidence from civil litigation

deHaan, Ed; Kedia, Simi; Koh, Kevin; Rajgopal, Shivaram

doi:10.1016/j.jacceco.2015.07.010

Cited by 115 publications

(22 citation statements)

References 23 publications

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“…As a result, many SEC lawyers that were trying to make a name for themselves became aggressive in getting companies to pay money and punishing them; this is likely one reason why prior to 2010, cooperative firms had a higher likelihood of receiving a sanction from the SEC. This is consistent with the evidence in DeHaan, Kedia, Koh, and Rajgopal (2015) that line lawyers build "human capital." However, by centralizing the approval authority for cooperation tools, the 2010 guidelines effectively restrain the prosecutorial discretion of line lawyers and ensure consistency in applying the leniency policies.…”

Section: Background and Prior Researchsupporting

confidence: 91%

“…SeeRobinson and Bain (2017) 6. This is because the 2001 program only outlined cooperative actions that made the firm eligible for leniency, and it allowed SEC line lawyers to apply the guidelines inconsistently (with no manual), thereby exploiting cooperative firms (DeHaan,Kedia, Koh, and Rajgopal 2015).7 In our private conversation with a former senior SEC official (who requested anonymity), s/he revealed that after the SEC published the full-text of cooperation cases and agreements online as illustrative examples, defense lawyers in…”

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confidence: 99%

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On the SEC's Enforcement Cooperation Program: A Regime Shift after 2010

Leone

Liu

2018

SSRN Journal

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This paper examines the interplay between the SEC and accounting misconduct firms under the SEC's modified leniency program of 2010. In contrast to previous findings that the SEC penalized cooperative violators prior to 2010, we show that post-2010, the Commission rewards cooperation, particularly good faith cooperation. Unlike prior studies, our results are not conditional on firms receiving enforcement actions. We also show that misconduct firms, despite initial hesitation, have adapted their cooperation strategies to the SEC's post-2010 leniency practices. Our findings highlight the importance of regulators establishing clear ex-ante incentives and limiting ex-post prosecutorial discretion to mitigate the cooperation holdup problem. Our results also caution against using SEC sanctions as a proxy for severity of misreporting after 2010.

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Section: Background and Prior Researchsupporting

confidence: 91%

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confidence: 99%

On the SEC's Enforcement Cooperation Program: A Regime Shift after 2010

Leone

Liu

2018

SSRN Journal

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“…However, we acknowledge that the CFRM database is subject to its own potential selection bias (Kedia and Rajgopal [], deHaan et al. []), a limitation that readers should keep in mind when interpreting our results.…”

Section: The Sample and Datamentioning

confidence: 99%

Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach

Bao

et al. 2020

J of Accounting Research

277

213

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We develop a state-of-the-art fraud prediction model using a machine learning approach. We demonstrate the value of combining domain knowledge and machine learning methods in model building. We select our model input based on existing accounting theories, but we differ from prior accounting research by using raw accounting numbers rather than financial ratios.We employ one of the most powerful machine learning methods, ensemble learning, rather than the commonly used method of logistic regression. To assess the performance of fraud prediction models, we introduce a new performance evaluation metric commonly used in ranking problems that is more appropriate for the fraud prediction task. Starting with an identical set of theory-motivated raw accounting numbers, we show that our new fraud prediction model outperforms two benchmark models by a large margin: the Dechow et al. logistic regression model based on financial ratios, and the Cecchini et al. support-vector-machine model with a financial kernel that maps raw accounting numbers into a broader set of ratios. JEL codes: C53; M41

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“…Related to this, private law firms defending companies targeted by the SEC actually hire harsher prosecutors, though this result is not defendant-specific [deHaan, Kedia, Koh, and Rajgopal, 2015].…”

Section: Introductionmentioning

confidence: 98%

From Revolving Doors to Regulatory Capture? Evidence from Patent Examiners

Tabakovic¹,

Wollmann²

2018

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, as well as conference discussants and seminar participants for helpful comments. We also thank Stu Graham, Alan Marco, Andrew Toole, and other members of the USPTO Office of Chief Economist for creating, documenting, and providing datasets that serve as the basis for much of this paper. Excellent research assistance was provided by Jordan Bell-Masterson, Kavya Garikipati, and Divya Vallabhaneni. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

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The revolving door and the SEC’s enforcement outcomes: Initial evidence from civil litigation

Cited by 115 publications

References 23 publications

On the SEC's Enforcement Cooperation Program: A Regime Shift after 2010

On the SEC's Enforcement Cooperation Program: A Regime Shift after 2010

Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach

From Revolving Doors to Regulatory Capture? Evidence from Patent Examiners

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