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.
I develop measures of firm-level pay disparity and examine their relation to firm performance. Using comprehensive compensation data for a large sample of firms, I find no statistically significant relation between the ratio of CEO-to-mean employee compensation and performance. I next create empirical models that allow me to separate the components of CEO and employee compensation explained by economic factors from those that are not, and use these models to estimate explained and unexplained pay disparity. After validating my estimate of unexplained pay disparity as a proxy for pay fairness, I find robust evidence of a negative (positive) relation between unexplained (explained) pay disparity and future firm performance.
JEL Classifications: G32; G35; J31; M12; M14; M52.
I develop measures of firm-level pay disparity and examine their relation to firm accounting performance. Using comprehensive compensation data for a large sample of firms, I find no statistically significant relation between the ratio of CEO-to-mean employee compensation and performance. I next create empirical models that allow me to separate the components of CEO and employee compensation explained by economic factors from those that are not, and use these models to estimate explained and unexplained pay disparity. After validating my estimate of unexplained pay disparity as a proxy for pay fairness, I find robust evidence of a negative (positive) relation between unexplained (explained) pay disparity and future firm performance. Additional tests show that the negative relation between unexplained disparity and firm performance is driven by firms where both the CEO is overpaid and employees are underpaid, and is more pronounced for firms with weak corporate governance and high employee turnover.
Carolina for providing detailed comments. Linh Nguyen provided excellent research assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
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