Lost in standardization: Effects of financial statement database discrepancies on inference

Kai Du, Steven Huddart and Xin Daniel Jiang

Journal of Accounting and Economics, 2023, vol. 76, issue 1

Abstract: SEC-mandated, machine-readable structured filings are an alternative source to Compustat for companies' accounting data. Discrepancies between as-filed and Compustat data, potentially a result of Compustat's standardizations, are more pronounced for firms with complex financial reporting. We show that these data discrepancies affect inferences in four research settings: (i) properties of accrual accounting, including accruals-cash flow relationships and abnormal accruals; (ii) real earnings management; (iii) the existence and magnitude of six of 21 accounting-based anomalies examined, including the accruals anomaly; and (iv) disclosure quality assessments based on the hierarchical structure of financial statement items. FactSet data also exhibit significant and often larger discrepancies from as-filed data. Our findings demonstrate the importance of these data discrepancies for the interpretation of empirical tests.

Keywords: Accrual accounting; Real earnings management; Accounting-based anomalies; Disclosure quality; Data aggregators; XBRL (search for similar items in EconPapers)
JEL-codes: C81 G14 M41 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jaecon:v:76:y:2023:i:1:s0165410122000969

DOI: 10.1016/j.jacceco.2022.101573

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