Uncovering the Hidden Effort Problem

52 Pages Posted: 8 Feb 2021 Last revised: 18 Sep 2022

See all articles by Azi Ben-Rephael

Azi Ben-Rephael

Rutgers Business School - Rutgers University

Bruce Carlin

Rice University

Zhi Da

University of Notre Dame - Mendoza College of Business

Ryan D. Israelsen

Michigan State University - Department of Finance

Date Written: February 2021

Abstract

We use machine learning to analyze minute-by-minute Bloomberg online status data and study how the effort provision of top executives in public corporations affects firm value. While executives likely spend most of their time doing other activities, Bloomberg usage data allows us to characterize their work habits. We document a positive effect of effort on unexpected earnings, cumulative abnormal returns following firm earnings announcements, and credit default swap spreads. We form long-short, calendar-time, effort portfolios and show that they earn significant average daily returns. Finally, we revisit several agency issues that have received attention in the prior academic literature on executive compensation.

Suggested Citation

Ben-Rephael, Azi and Carlin, Bruce and Da, Zhi and Israelsen, Ryan D., Uncovering the Hidden Effort Problem (February 2021). NBER Working Paper No. w28441, Available at SSRN: https://ssrn.com/abstract=3781328

Azi Ben-Rephael (Contact Author)

Rutgers Business School - Rutgers University ( email )

HOME PAGE: http://https://sites.google.com/site/abenreph

Bruce Carlin

Rice University ( email )

6100 South Main Street
Houston, TX 77005-1892
United States

Zhi Da

University of Notre Dame - Mendoza College of Business ( email )

Notre Dame, IN 46556-5646
United States

Ryan D. Israelsen

Michigan State University - Department of Finance ( email )

315 Eppley Center
East Lansing, MI 48824-1122
United States

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