{"title":"Does XBRL help improve data processing efficiency?","authors":"Y. Rao, Ken H. Guo","doi":"10.1108/ijaim-07-2021-0155","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe US Securities and Exchange Commission (SEC) requires public companies to file structured data in eXtensible Business Reporting Language (XBRL). One of the key arguments behind the XBRL mandate is that the technical standard can help improve processing efficiency for data aggregators. This paper aims to empirically test the data processing efficiency hypothesis.\n\n\nDesign/methodology/approach\nTo test the data processing efficiency hypothesis, the authors adopt a two-sample research design by using data from Compustat: a pooled sample (N = 61,898) and a quasi-experimental sample (N = 564). The authors measure data processing efficiency as the time lag between the dates of 10-K filings on the SEC’s EDGAR system and the dates of related data finalized in the Compustat database.\n\n\nFindings\nThe statistical results show that after controlling for potential effects of firm size, age, fiscal year and industry, XBRL has a non-significant impact on data efficiency. It suggests that the data processing efficiency benefit may have been overestimated.\n\n\nOriginality/value\nThis study provides some timely empirical evidence to the debate as to whether XBRL can improve data processing efficiency. The non-significant results suggest that it may be necessary to revisit the mandate of XBRL reporting in the USA and many other countries.\n","PeriodicalId":46371,"journal":{"name":"International Journal of Accounting and Information Management","volume":"94 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Accounting and Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijaim-07-2021-0155","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 1
Abstract
Purpose
The US Securities and Exchange Commission (SEC) requires public companies to file structured data in eXtensible Business Reporting Language (XBRL). One of the key arguments behind the XBRL mandate is that the technical standard can help improve processing efficiency for data aggregators. This paper aims to empirically test the data processing efficiency hypothesis.
Design/methodology/approach
To test the data processing efficiency hypothesis, the authors adopt a two-sample research design by using data from Compustat: a pooled sample (N = 61,898) and a quasi-experimental sample (N = 564). The authors measure data processing efficiency as the time lag between the dates of 10-K filings on the SEC’s EDGAR system and the dates of related data finalized in the Compustat database.
Findings
The statistical results show that after controlling for potential effects of firm size, age, fiscal year and industry, XBRL has a non-significant impact on data efficiency. It suggests that the data processing efficiency benefit may have been overestimated.
Originality/value
This study provides some timely empirical evidence to the debate as to whether XBRL can improve data processing efficiency. The non-significant results suggest that it may be necessary to revisit the mandate of XBRL reporting in the USA and many other countries.
期刊介绍:
The International Journal of Accounting & Information Management focuses on publishing research in accounting, finance, and information management. It specifically emphasizes the interaction between these research areas on an international scale and within both the private and public sectors. The aim of the journal is to bridge the knowledge gap between researchers and practitioners by covering various issues that arise in the field. These include information systems, accounting information management, innovation and technology in accounting, accounting standards and reporting, and capital market efficiency.