Working Paper: NBER ID: w28441
Authors: Azi Benrephael; 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.
Keywords: executive effort; firm value; earnings surprises; cumulative abnormal returns; agency theory
JEL Codes: D22; D82; G32; M52
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| effort provision (Y20) | firm value (G32) |
| favorable weather conditions (Q54) | reduce executive effort (M12) |
| higher effort provision by executives (M12) | subsequent earnings surprises (G14) |
| one-hour increase in average workday length (J29) | cumulative abnormal return (C22) |
| executives' effort levels change in response to firm performance (D22) | increases in effort when midyear performance aligns with targets (D29) |