Extended XBRL taxonomies and Financial Analysts' Information

• In Event: XBRL and Auditing

Abstract

In this study, we investigate how the use of extended tags in eXtensible Business Reporting Language (XBRL) filings is associated with financial analysts’ information. XBRL allows firms to tag data in their financial reports. This data is machine readable and searchable, which reduces cost of accessing and using that data (i.e. information processing costs). Prior research suggests that XBRL in general reduces information processing costs. However, the SEC allows firms to provide customize tags in their XBRL filings which, on the one hand, may allow firms to voluntarily customize financial statements to provide more firms specific information by highlighting concepts that are not included in the standard set of tags. On the other hand, customized tag may inhibit information search, obfuscate financial statement numbers, and ultimately reduce the usefulness of XBRL data. We address the question of how the use of firm-specific (extended) tags is associated with the firm’s information environment. We consider the extension rate at the document level, within the disclosure related sections of the XBRL filing, and within the financial statements. We use properties of financial analysts’ earnings forecasts as proxies for investors' information. We contend that extensions in the disclosure section of the XBRL filing is more likely intended to provide firm-specific information whereas extensions within the financial statements likely make information less useful. We find that the overall extension rate is negatively related to the firm’s information environment. However, after controlling for the overall extension rate, we find some evidence that extended disclosures and extensions within the balance sheet and income statement is associated with lower forecast error while extensions within the cash flow statement are related be higher forecast error and dispersion. Our study is relevant to regulators creating policies about XBRL, both in the US and around the world.

Author

• Joseph Johnston, The City University of Hong Kong