Opening the Black Box: Task and Skill Mix and Productivity Dispersion
September 2022
Working Paper Number:
CES-22-44
Abstract
An important gap in most empirical studies of establishment-level productivity is the limited information about workers' characteristics and their tasks. Skill-adjusted labor input measures have been shown to be important for aggregate productivity measurement. Moreover, the theoretical literature on differences in production technologies across businesses increasingly emphasizes the task content of production. Our ultimate objective is to open this black box of tasks and skills at the establishment-level by combining establishment-level data on occupations from the Bureau of Labor Statistics (BLS) with a restricted-access establishment-level productivity dataset created by the BLS-Census Bureau Collaborative Micro-productivity Project. We take a first step toward this objective by exploring the conceptual, specification, and measurement issues to be confronted. We provide suggestive empirical analysis of the relationship between within-industry dispersion in productivity and tasks and skills. We find that within-industry productivity dispersion is strongly positively related to within-industry task/skill dispersion.
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:
production,
productive,
manufacturing,
payroll,
industrial,
aggregate,
employee,
employ,
employed,
industry productivity,
labor,
productivity differences,
efficiency,
productivity measures,
measures productivity,
establishment,
regulation productivity,
workforce,
worker,
productivity dispersion,
occupation,
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Annual Survey of Manufactures,
Bureau of Labor Statistics,
Center for Economic Studies,
Ordinary Least Squares,
Total Factor Productivity,
Cobb-Douglas,
Bureau of Economic Analysis,
University of Maryland,
Longitudinal Business Database,
IQR,
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Department of Labor,
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North American Industry Classification System,
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