The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
Quantifying Managerial Ability: A New Measure and Validity Tests
Open accessAbstract
We propose a measure of managerial ability, based on managers' efficiency in generating revenues, which is available for a large sample of firms and outperforms existing ability measures. We find that our measure is strongly associated with manager fixed effects and that the stock price reactions to chief executive officer (CEO) turnovers are positive (negative) when we assess the outgoing CEO as low (high) ability. We also find that replacing CEOs with more (less) able CEOs is associated with improvements (declines) in subsequent firm performance. We conclude with a demonstration of the potential of the measure. We find that the negative relation between equity financing and future abnormal returns documented in prior research is mitigated by managerial ability. Specifically, more able managers appear to utilize equity issuance proceeds more effectively, illustrating that our more precise measure of managerial ability will allow researchers to pursue studies that were previously difficult to conduct. This paper was accepted by Mary E. Barth, accounting.
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“…a number of papers have used DEA to measure firm efficiency (e.g., Thore et al. 1994; Murthi et al. 1996; Murthi et al. 1997; Barr and Siems 1997; Berk and Green 2004; Berk and Stanton 2007; Leverty and Grace 2011), we are the first to measure efficiency for a large cross-section of firms,…”
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Metadata
- Authors
- Demerjian, P., Lev, B., & McVay, S.
- Venue
- Management Science
- Published
- 2012-07
- Volume
- 58
- Issue
- 7
- Pages
- 1229-1248
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W3125615571
- Cited by
- 1,887
- References
- 50
- FWCI
- 75.51
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.