Key Performance Indicators as Supplements to Earnings: Incremental informativeness, Demand Factors, Measurement Issues, and Properties of Their Forecasts

Review of Accounting Studies, Forthcoming

54 Pages Posted: 22 Jun 2017 Last revised: 26 Mar 2019

See all articles by Dan Givoly

Dan Givoly

Pennsylvania State University, Smeal College of Business

Yifan Li

San Francisco State University

Ben Lourie

University of California, Irvine

Alexander Nekrasov

University of Illinois at Chicago

Date Written: March 21, 2019

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 it is diminished when details about the computation of the KPI are absent or when the computation of the KPI 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 we 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 and increases our understanding of the factors that affect this content. We provide evidence pertinent to the debate on whether and how to regulate KPI disclosures. This study further contributes to research on the properties of analysts’ forecasts.

Keywords: Key Performance Indicators, KPI, Measurement Issues, Analyst Forecasts, KPI Surprises, Announcement Surprises, Non-Financial Forecasts

JEL Classification: M41, G14

Suggested Citation

Givoly, Dan and Li, Yifan and Lourie, Ben and Nekrasov, Alexander, Key Performance Indicators as Supplements to Earnings: Incremental informativeness, Demand Factors, Measurement Issues, and Properties of Their Forecasts (March 21, 2019). Review of Accounting Studies, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2990730 or http://dx.doi.org/10.2139/ssrn.2990730

Dan Givoly

Pennsylvania State University, Smeal College of Business ( email )

305 Business Building
University Park, PA 16802
United States
814-865-0587 (Phone)
814-863-8393 (Fax)

Yifan Li

San Francisco State University

United States

Ben Lourie

University of California, Irvine ( email )

Irvine, CA 92697-3125
United States

Alexander Nekrasov (Contact Author)

University of Illinois at Chicago ( email )

1200 W Harrison St
Chicago, IL 60607
United States

HOME PAGE: http://business.uic.edu/profiles/alexander-nekrasov/

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