Does Routine Labor Generate Routine Earnings?

46 Pages Posted: 12 Jun 2020 Last revised: 1 Feb 2021

See all articles by Yi Cao

Yi Cao

The Chinese University of Hong Kong, Shenzhen - School of Management and Economics

Nicholas Seybert

University of Maryland - Department of Accounting & Information Assurance

Date Written: February 1, 2021

Abstract

A substantial body of research investigates how skills and attributes of upper management affect firm policies and performance, but the impact of workers outside of upper management has received little attention due to scarcity of data involving lower-level workers. Prior research also suggests that operating uncertainty impedes managers’ ability to understand and predict their own firm’s future earnings performance, leading to accrual estimation errors, and that higher-ability managers are better able to transform economic predictability into smoother accruals and earnings. We predict and find that a firm’s utilization of routine labor (defined as labor at greater risk of future automation) contributes to firms’ and managers’ propensity to report more persistent and predictable accruals and earnings. Results indicate that routine labor generates the most predictable and persistent accruals when managers have higher ability and when firm efficiency is higher, when firms build up inventory and therefore accrue a greater proportion of labor cost, and when the routine labor supply is less impacted by external economic policy (in the form of state minimum wage increases). Taken together, our results suggest the characteristics of lower-level workers interact with those of managers, firms, and the economy to determine the persistence of accruals and earnings.

Keywords: routine, labor, automation, earnings, accruals, cash flow, persistence, predictability, analyst, forecast, occupations, managers, managerial ability

JEL Classification: G00, G30, M11, M41, M54

Suggested Citation

Cao, Yi and Seybert, Nicholas, Does Routine Labor Generate Routine Earnings? (February 1, 2021). Available at SSRN: https://ssrn.com/abstract=3605303 or http://dx.doi.org/10.2139/ssrn.3605303

Yi Cao

The Chinese University of Hong Kong, Shenzhen - School of Management and Economics ( email )

2001 Longxiang Road, Longgang District
Shenzhen, 518172
China

Nicholas Seybert (Contact Author)

University of Maryland - Department of Accounting & Information Assurance ( email )

Robert H. Smith School of Business
College Park, MD 20742-9157
United States

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