Research / BFI Working PaperOct 11, 2022

How Important Is Corporate Governance? Evidence from Machine Learning

Ian D. Gow, David F. Larcker, Anastasia A. Zakolyukina

We use machine learning to assess the predictive ability of over a hundred corporate governance features for firm outcomes. We consider financial-statement restatements, class-action lawsuits, business failures, operating performance, firm value, stock returns, and credit ratings. We discover that adding corporate governance features does not improve the models’ predictive accuracy beyond the predictive accuracy captured by firm characteristics. Our results raise doubts about the existence of strong causal effects of corporate governance on a range of firm outcomes studied in prior research.

More Research From These Scholars

BFI Working Paper Jan 14, 2022

Information versus Investment

Stephen J. Terry, Toni M. Whited, Anastasia A. Zakolyukina
Topics:  Financial Markets
BFI Working Paper Aug 24, 2020

What Is CEO Overconfidence? Evidence from Executive Assessments

Steven Neil Kaplan, Morten Sorensen, Anastasia A. Zakolyukina
Topics:  Uncategorized
BFI Working Paper Aug 17, 2020

Information versus Investment

Stephen J. Terry, Toni M. Whited, Anastasia A. Zakolyukina
Topics:  Financial Markets