A New Measure of Disclosure Quality: The Level of Disaggregation of Accounting Data in Annual Reports

• 成果类型: Article
• 署名作者: Chen, Shuping; Miao, Bin; Shevlin, Terry
• 署名单位: University of Texas System; University of Texas Austin; National University of Singapore; University of California System; University of California Irvine
• 刊物名称: JOURNAL OF ACCOUNTING RESEARCH
• ISSN/ISSBN: 0021-8456
• DOI: 10.1111/1475-679X.12094
• 发表日期: 2015
• 页码: 1017-1054
• 关键词: analysts forecast accuracy; economic consequences; information asymmetry; cost; earnings; equity; diversification; CLASSIFICATION; accruals; revenue

摘要

We construct a new, parsimonious, measure of disclosure quality-disaggregation quality (DQ)-and offer validation tests. DQ captures the level of disaggregation of accounting data through a count of nonmissing Compustat line items, and reflects the extent of details in firms' annual reports. Conceptually, DQ differs from existing disclosure measures in that it captures the fineness of data and is based on a comprehensive set of accounting line items in annual reports. Unlike existing measures, which are usually applicable for a subset of firms or are based on a subset of information items, DQ can be generated for the universe of Compustat industrial firms. We conduct three sets of validation tests by examining DQ's association with variables predicted by prior literature to be associated with information quality. DQ is negatively (positively) associated with analyst forecast dispersion (accuracy) and negatively associated with bid-ask spreads and cost of equity. These associations continue to hold after we control for firm fundamentals. Taken together, results from this battery of validation tests are consistent with our measure capturing disclosure quality.