Selecting Directors Using Machine Learning
[The role of boards of directors in corporate governance: A conceptual framework and survey]
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- Isil Erel & Léa H Stern & Chenhao Tan & Michael S Weisbach, 2021. "Selecting Directors Using Machine Learning," NBER Chapters, in: Big Data: Long-Term Implications for Financial Markets and Firms, pages 3226-3264, National Bureau of Economic Research, Inc.
- Isil Erel & Léa H. Stern & Chenhao Tan & Michael S. Weisbach, 2018. "Selecting Directors Using Machine Learning," NBER Working Papers 24435, National Bureau of Economic Research, Inc.
- Erel, Isil & Stern, Lea Henny & Tan, Chenhao & Weisbach, Michael S., 2018. "Selecting Directors Using Machine Learning," Working Paper Series 2018-05, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
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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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