Racial Inequality and Bureaucracy in U.S. Manufacturing

How does bureaucracy affect racial inequality? Prior research finds that bureaucratization can institutionalize racial inequality but also that insufficient bureaucracy creates opportunities for discrimination. In this project, we propose a third mechanism (differential worker sorting) through which bureaucratic work environments affect inequality. To clarify these perspectives, we contrast worker-protective features of bureaucracy, like fixed pay and seniority protections, to performance-oriented features, which structure production targets and often incorporate high-powered incentives. We study Black-White earnings inequality by matching a large survey of U.S. manufacturing workplaces to employer-employee linked data. Bureaucratic workplaces pay relatively more to Black workers than do nonbureaucratic workplaces. These benefits are strongest for college-educated Black workers and are concentrated in firms with structured target setting rather than those with high-powered incentives or worker protections per se. Moreover, increased pay for Black workers stems mainly from bureaucratic workplaces selecting for relatively higher-skilled Black workers. These findings suggest that bureaucratic employers attract high-performing Black workers not by paying them more relative to White workers but by providing a formalized production context that supports clear performance targets.

This paper was accepted by Isabel Fernandez-Mateo, organizations.

Funding: This research uses data from the Census Bureau’s Longitudinal Employer-Household Dynamics Program, which was partially supported by the National Science Foundation [Grants SES-9978093, SES-0339191, and ITR-0427889], the National Institute on Aging [Grant AG018854], and grants from the Alfred P. Sloan Foundation. Any views expressed are those of the authors and not those of the U.S. Census Bureau. The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data used to produce this product. This research was performed at a Federal Statistical Research Data Center [Project Number 2176: Grants CBDRB-FY23-P2176-R10549 and CBDRB-FY24-P2176-R11457]. Funding support was provided by the Massachusetts Institute of Technology (MIT) Future of Work Initiative and the MIT Sloan School of Management.

Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.02358.