Purpose This paper aims to analyse the determinants of the proportion of quantitative data in financial statement footnote disclosures. Quantitative data represents “hard” information and has been considered to be… Click to show full abstract
Purpose This paper aims to analyse the determinants of the proportion of quantitative data in financial statement footnote disclosures. Quantitative data represents “hard” information and has been considered to be more persuasive than qualitative data. The primary focus is on income tax footnotes because revenue agents use them as a reference in tax audits, and citizen groups use them to analyse tax inequalities. This study posits that firms with lower effective tax rates (“tax aggressive” firms) disclose less quantitative data in their income tax footnotes. Design/methodology/approach The multivariate analysis uses data from the contents of income tax footnotes extracted from 10-K filings in eXtensible Business Reporting Language (XBRL). It uses the alphanumeric characters identified in the income tax footnotes to calculate the proportion of quantitative data relative to the entire footnote disclosure as the dependent variable in a multivariate regression analysis. Findings The findings show that firms which avoid more taxes disclose less quantitative data in income tax footnotes after controlling for the readability of the income tax footnotes and the entire annual report. Therefore, firms seem to reduce the publication of measurable data accessible to revenue agencies and citizen groups. Originality/value This analysis provides evidence that firms weigh the financial reporting requirements and tax audit risks when they disclose quantitative income tax data. Also, it supports the Financial Accounting Standards Board’s (FASB’s) proposal to require more disaggregated income tax disclosure. To the researcher’s knowledge, this is the first analysis that focuses on the determinants of disclosing quantitative data in income tax footnotes.
               
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