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Supervision, Loss of Control, and the Optimum Size of the Firm
Abstract
We show that limitation of firm size caused by loss of control across hierarchic levels depends crucially on the nature of the supervision process. If the employees cannot identify the times at which their performance is monitored, there is no limit imposed on the firm size by the heights of the hierarchical structure. "Loss of control" may impose such a limit if the employees are aware of the times at which they are being monitored. The analysis also shows the rationale for hierarchical wage differentials for essentially identical employees.
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Citations
Cited by
The Role of Wages and Auditing during a Crackdown on Corruption in the City of Buenos Aires
Di Tella, R., & Schargrodsky, E. (2003) · The Journal of Law and Economics · doi:10.1086/345578 · Cited by 620
Managers, Workers, and Corporate Control
PAGANO, M., & VOLPIN, P. F. (2005) · The Journal of Finance · doi:10.1111/j.1540-6261.2005.00748.x · Cited by 523
The Flattening Firm: Evidence from Panel Data on the Changing Nature of Corporate Hierarchies
Rajan, R. G., & Wulf, J. (2006) · Review of Economics and Statistics · doi:10.1162/rest.88.4.759 · Cited by 482
Metadata
- Authors
- Calvo, G. A., & Wellisz, S.
- Venue
- Journal of Political Economy
- Publisher
- University of Chicago Press
- Published
- 1978-10
- Volume
- 86
- Issue
- 5
- Pages
- 943-952
- ISSN
- 0022-3808 (ISSN-L)
- 1537-534X
- OpenAlex
- W1988696045
- Cited by
- 467
- References
- 0
- FWCI
- 4.95
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Supervision, Loss of Control, and the Optimum Size of the Firm. https://app.cochat.ai/papers/10.1086/260719
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- Calvo, G. A., & Wellisz, S. (1978). Supervision, Loss of Control, and the Optimum Size of the Firm. Journal of Political Economy. https://doi.org/10.1086/260719
Data sources
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.
