The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
The Allowance for Uncollectible Accounts, Conservatism, and Earnings Management
Abstract
We study the interrelation between conservatism and earnings management by examining the allowance for uncollectible accounts and its income statement counterpart, bad debt expense. We find that the allowance is conservative and that it has become more conservative over time. Conservatism may, however, facilitate earnings management. We find that firms manage bad debt expense downward (and even record income‐increasing bad debt expense) to meet or beat analysts’ earnings forecasts and that conservatism accentuates the extent to which firms manage bad debt expense. Further, we find that firms manage bad debt expense downward by drawing down previously recorded over‐accruals of bad debt expense that have accumulated on the balance sheet. An implication of our study is that tighter limits on the amount by which firms are permitted to understate net assets may reduce their ability to manage earnings.
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Citations
Cites
Evidence of Earnings Management from the Provision for Bad Debts
McNichols, M., & Wilson, G. P. (1988) · Journal of Accounting Research · doi:10.2307/2491176 · Cited by 919
Cited by
A Neural Network Approach to Estimating the Allowance for Bad Debt
Joyner, D. (2011) · VCU Libraries · doi:10.25772/h720-xy24 · Cited by 2
Metadata
- Authors
- JACKSON, S. B., & LIU, X. (.
- Venue
- Journal of Accounting Research
- Publisher
- Wiley
- Published
- 2010-04-09
- Volume
- 48
- Issue
- 3
- Pages
- 565-601
- ISSN
- 0021-8456 (ISSN-L)
- 1475-679X
- OpenAlex
- W2159396871
- Cited by
- 170
- References
- 1
- FWCI
- 20.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- JACKSON, S. B., & LIU, X. (. (2010). The Allowance for Uncollectible Accounts, Conservatism, and Earnings Management. Journal of Accounting Research. https://doi.org/10.1111/j.1475-679x.2009.00364.x
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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