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Selecting Directors Using Machine Learning
[The role of boards of directors in corporate governance: A conceptual framework and survey]

Author

Listed:
  • Isil Erel
  • Léa H Stern
  • Chenhao Tan
  • Michael S Weisbach

Abstract

Can algorithms assist firms in their decisions on nominating corporate directors? Directors predicted by algorithms to perform poorly indeed do perform poorly compared to a realistic pool of candidates in out-of-sample tests. Predictably bad directors are more likely to be male, accumulate more directorships, and have larger networks than the directors the algorithm would recommend in their place. Companies with weaker governance structures are more likely to nominate them. Our results suggest that machine learning holds promise for understanding the process by which governance structures are chosen and has potential to help real-world firms improve their governance.

Suggested Citation

  • Isil Erel & Léa H Stern & Chenhao Tan & Michael S Weisbach, 2021. "Selecting Directors Using Machine Learning [The role of boards of directors in corporate governance: A conceptual framework and survey]," The Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3226-3264.
  • Handle: RePEc:oup:rfinst:v:34:y:2021:i:7:p:3226-3264.
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    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • M12 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Personnel Management; Executives; Executive Compensation
    • M14 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Corporate Culture; Diversity; Social Responsibility
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions

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