{"title":"Lost in standardization: Effects of financial statement database discrepancies on inference","authors":"Kai Du , Steven Huddart , Xin Daniel Jiang","doi":"10.1016/j.jacceco.2022.101573","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48438,"journal":{"name":"Journal of Accounting & Economics","volume":"76 1","pages":"Article 101573"},"PeriodicalIF":5.4000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Accounting & Economics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165410122000969","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
The Journal of Accounting and Economics encourages the application of economic theory to the explanation of accounting phenomena. It provides a forum for the publication of the highest quality manuscripts which employ economic analyses of accounting problems. A wide range of methodologies and topics are encouraged and covered: * The role of accounting within the firm; * The information content and role of accounting numbers in capital markets; * The role of accounting in financial contracts and in monitoring agency relationships; * The determination of accounting standards; * Government regulation of corporate disclosure and/or the Accounting profession; * The theory of the accounting firm.
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