Key performance indicators as supplements to earnings: Incremental informativeness, demand factors, measurement issues, and properties of their forecasts

• 成果类型: Article
• 署名作者: Givoly, Dan; Li, Yifan; Lourie, Ben; Nekrasov, Alexander
• 署名单位: Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; California State University System; San Francisco State University; University of California System; University of California Irvine; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
• 刊物名称: REVIEW OF ACCOUNTING STUDIES
• ISSN/ISSBN: 1380-6653
• DOI: 10.1007/s11142-019-09514-y
• 发表日期: 2019
• 页码: 1147-1183
• 关键词: VALUE-RELEVANCE; ANALYSTS FORECASTS; leading indicators; incentives

摘要

The documented decline in the information content of earnings numbers has paralleled the emergence of disclosures, mostly voluntary, of industry-specific key performance indicators (KPIs). We find that the incremental information content conveyed by KPI news is significant for many KPIs yet diminished when details about the computation of the KPI are absent or when the computation changes over time. Consistent with analysts responding to investor information demand, we find that analysts are more likely to produce forecasts for a KPI when that KPI has more information content and when earnings are less informative. We also analyze the properties of analysts' KPI forecasts and find that KPI forecasts are more accurate than mechanical forecasts and their accuracy exceeds that of earnings forecasts. Our study contributes to the literature on the information content of KPIs as well as research on the properties of analysts' forecasts. We provide evidence on whether and how to regulate voluntary disclosures.