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Cited by 1,102

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

The Information Role of Conservatism

Open access
LaFond, Ryan, Watts, Ross L.·2008·The Accounting Review

Abstract

In this paper we argue that information asymmetry between firm insiders and outside equity investors generates conservatism in financial statements. Conservatism reduces the manager's incentives and ability to manipulate accounting numbers and so reduces information asymmetry and the deadweight losses that information asymmetry generates. This increases firm and equity values. Our empirical tests are consistent with our proposition that information asymmetry is significantly positively related to conservatism after controlling for other demands for conservatism. Further, our tests are more consistent with our prediction that changes in information asymmetry between equity investors lead to changes in conservatism than the FASB's proposition that conservatism produces information asymmetry among equity investors. An important implication is that, if the FASB was successful in meeting its stated goal of eliminating conservatism, then it would increase information asymmetry between investors, not reduce it. This outcome is inconsistent with the objectives of the Securities Acts.

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Metadata

Authors
LaFond, R., & Watts, R. L.
Venue
The Accounting Review
Published
2008-03-01
Volume
83
Issue
2
Pages
447-478
ISSN
  • 0001-4826 (ISSN-L)
  • 1558-7967
OpenAlex
W3123372730
Cited by
1,102
References
1
FWCI
157.96
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The Information Role of Conservatism. https://app.cochat.ai/papers/10.2308/accr.2008.83.2.447
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LaFond, R., & Watts, R. L. (2008). The Information Role of Conservatism. The Accounting Review. https://doi.org/10.2308/accr.2008.83.2.447

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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.