TY - JOUR
T1 - Lost in standardization
T2 - Effects of financial statement database discrepancies on inference
AU - Du, Kai
AU - Huddart, Steven
AU - Jiang, Xin Daniel
N1 - Funding Information:
☆ We thank Bob Holthausen (editor), Joseph Engelberg (referee), Daniel Aobdia, Sam Bonsall, Changling Chen, James Choi, Lauren Cohen, Ying Compton, Michael Dambra, Chengfeng Du, Kurt Gee, Walter Hamscher, Byoung-Hyoun Hwang, Michael Kirschenheiter, Juhani Linnainmaa, Henock Louis, Julie Marlowe, Rick Mergenthaler, Brian Miller (FARS discussant), Karl Muller, Jed Neilson, Doron Nissim, Stephen Penman, Anup Srivastava, Inho Suk, Rebecca Tang, Ayung Tseng, John Turner, Shuyang Wang, Christine Wiedman, Mike Willis, Biqin Xie, Michael Zhang, Rong Zhao, and workshop participants at the Securities and Exchange Commission (DERA), Penn State, University at Buffalo, University of Calgary, University of Waterloo, XBRL US, the Accounting Design Project, and the 2022 FARS Midyear Meeting for helpful comments and suggestions. We are especially grateful to Dan Givoly for many discussions. We thank Shuping Chen and Bin Miao for sharing the disclosure quality data. We thank Alina Lerman and Frank Zhang for their help with the replication of their study. We acknowledge our respective institutions for financial support. The as-filed data used in this study are available through Wharton Research Data Services (WRDS).
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
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U2 - 10.1016/j.jacceco.2022.101573
DO - 10.1016/j.jacceco.2022.101573
M3 - Article
AN - SCOPUS:85145985420
SN - 0165-4101
JO - Journal of Accounting and Economics
JF - Journal of Accounting and Economics
M1 - 101573
ER -