Opening the Black Box: Task and Skill Mix and Productivity Dispersion

57 Pages Posted: 7 Nov 2022 Last revised: 31 Aug 2024

See all articles by G. Jacob Blackwood

G. Jacob Blackwood

Amherst College

Cindy Cunningham

U.S. Bureau of Labor Statistics

Matthew Dey

Bureau of Labor Statistics

Lucia Foster

U.S. Census Bureau - Center for Economic Studies

Cheryl Grim

U.S. Census Bureau - Center for Economic Studies

John Haltiwanger

University of Maryland - Department of Economics; National Bureau of Economic Research (NBER); Institute for the Study of Labor (IZA)

Rachel Nesbit

U.S. Census Bureau

Sabrina Wulff Pabilonia

U. S. Bureau of Labor Statistics - Division of Productivity Research & Program Development

Jay Stewart

Bureau of Labor Statistics; IZA Institute of Labor Economics

Cody Tuttle

University of Texas at Austin

Zoltan Wolf

U.S. Census Bureau - Center for Economic Studies

Date Written: November 2022

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.

Suggested Citation

Blackwood, G. Jacob and Cunningham, Cindy and Dey, Matthew and Foster, Lucia and Grim, Cheryl and Haltiwanger, John C. and Nesbit, Rachel and Pabilonia, Sabrina Wulff and Stewart, Jay and Tuttle, Cody and Wolf, Zoltan, Opening the Black Box: Task and Skill Mix and Productivity Dispersion (November 2022). NBER Working Paper No. w30620, Available at SSRN: https://ssrn.com/abstract=4269912

G. Jacob Blackwood (Contact Author)

Amherst College ( email )

Amherst, MA 01002
United States

Cindy Cunningham

U.S. Bureau of Labor Statistics

Behavioral Science Research Center
Washington, DC
United States

Matthew Dey

Bureau of Labor Statistics ( email )

2 Massachusetts Avenue, NE
Washington, DC 20212
United States

Lucia Foster

U.S. Census Bureau - Center for Economic Studies ( email )

4700 Silver Hill Road
Washington, DC 20233
United States

Cheryl Grim

U.S. Census Bureau - Center for Economic Studies ( email )

Suitland Federal Center
Washington, DC 20233
United States

John C. Haltiwanger

University of Maryland - Department of Economics ( email )

College Park, MD 20742
United States
301-405-3504 (Phone)
301-405-3542 (Fax)

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Institute for the Study of Labor (IZA) ( email )

P.O. Box 7240
Bonn, D-53072
Germany

Rachel Nesbit

U.S. Census Bureau ( email )

4600 Silver Hill Road
D.C., WA 20233
United States

Sabrina Wulff Pabilonia

U. S. Bureau of Labor Statistics - Division of Productivity Research & Program Development ( email )

2 Massachusetts Avenue, NE
Washington, DC 20212
United States
202-691-5614 (Phone)

Jay Stewart

Bureau of Labor Statistics ( email )

2 Massachusetts Avenue, NE
Washington, DC 20212
United States

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Cody Tuttle

University of Texas at Austin ( email )

2317 Speedway
Austin, TX Texas 78712
United States

Zoltan Wolf

U.S. Census Bureau - Center for Economic Studies ( email )

4700 Silver Hill Road
Washington, DC 20233
United States

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