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

Dan Givoly, Yifan Li, Ben Lourie, Alexander Nekrasov

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
JournalReview of Accounting Studies
DOIs
StateAccepted/In press - Jan 1 2019

Fingerprint

Incremental
Informativeness
Key performance indicators
Factor demand
Information content
Analysts
Voluntary disclosure
Analysts' forecasts
Earnings forecasts
News
Industry
Investors

All Science Journal Classification (ASJC) codes

  • Accounting
  • Business, Management and Accounting(all)

Cite this

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abstract = "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.",
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AU - Li, Yifan

AU - Lourie, Ben

AU - Nekrasov, Alexander

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