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Cited by 1,033

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Capital structure and firm performance: A new approach to testing agency theory and an application to the banking industry

Open access
Berger, Allen N., Bonaccorsi di Patti, Emilia·2006·Journal of Banking & Finance
DOI 10.1016/j.jbankfin.2005.05.015
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Abstract

Corporate governance theory predicts that leverage affects agency costs and thereby influences firm performance. We propose a new approach to test this theory using profit efficiency, or how close a firm's profits are to the benchmark of a best-practice firm facing the same exogenous conditions. We are also the first to employ a simultaneous-equations model that accounts for reverse causality from performance to capital structure. We also control for measures of ownership structure in the tests. We find that data on the U.S. banking industry are consistent with the theory, and the results are statistically significant, economically significant, and robust.

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Metadata

Authors
Berger, A. N., & Bonaccorsi di Patti, E.
Venue
Journal of Banking & Finance
Publisher
Elsevier BV
Published
2006-04
Volume
30
Issue
4
Pages
1065-1102
ISSN
0378-4266 (ISSN-L)
DOI
10.1016/j.jbankfin.2005.05.015
OpenAlex
W1978175480
Cited by
1,033
References
3
FWCI
50.34
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Capital structure and firm performance: A new approach to testing agency theory and an application to the banking industry. https://app.cochat.ai/papers/10.1016/j.jbankfin.2005.05.015
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Berger, A. N., & Bonaccorsi di Patti, E. (2006). Capital structure and firm performance: A new approach to testing agency theory and an application to the banking industry. Journal of Banking & Finance. https://doi.org/10.1016/j.jbankfin.2005.05.015

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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.