Financial statement errors: evidence from the distributional properties of financial statement numbers

Dan Amiram, Zahn Bozanic, Ethan Rouen

Research output: Contribution to journalArticlepeer-review


Motivated by methods used to evaluate the quality of data, we create a novel firm-year measure to estimate the level of error in financial statements. The measure, which has several conceptual and statistical advantages over available alternatives, assesses the extent to which features of the distribution of a firm’s financial statement numbers diverge from a theoretical distribution posited by Benford’s Law. After providing intuition for the theory underlying the measure, we use numerical methods to demonstrate that certain error types in financial statement numbers increase the deviation from the theoretical distribution. We corroborate the numerical analysis with simulation analysis that reveals that the introduction of errors to reported revenue also increases the deviation. We then provide empirical evidence that the measure captures financial statement data quality. We first show the measure’s association with commonly used measures of accruals-based earnings management and earnings manipulation. Next, we demonstrate that (1) restated financial statements more closely conform to Benford’s Law than the misstated versions in the same firm-year and (2) as divergence from Benford’s Law increases, earnings persistence decreases. Finally, we show that our measure predicts material misstatements as identified by SEC Accounting and Auditing Enforcement Releases and can be used as a leading indicator to identify misstatements.

Original languageEnglish
Pages (from-to)1540-1593
Number of pages54
JournalReview of Accounting Studies
Issue number4
StatePublished - 2 Aug 2015
Externally publishedYes


  • Accounting quality
  • Benford’s Law
  • Earnings management
  • Financial statements errors

All Science Journal Classification (ASJC) codes

  • Accounting
  • General Business,Management and Accounting


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