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Uncovering the Hidden Effort Problem

Author

Listed:
  • Azi Ben-Rephael
  • Bruce I. Carlin
  • Zhi Da
  • Ryan D. Israelsen

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

  • Azi Ben-Rephael & Bruce I. Carlin & Zhi Da & Ryan D. Israelsen, 2021. "Uncovering the Hidden Effort Problem," NBER Working Papers 28441, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:28441
    Note: CF IO LS
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    More about this item

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • M52 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Compensation and Compensation Methods and Their Effects

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