Labor Market Power and Technological Change in US Manufacturing

We estimate plant-level production functions with Census microdata to separately identify product and labor market power in the US manufacturing sector. Wage markdowns rose substantially from 1 in 1972 to 2 in 2014, while price markups stayed flat at 1. Wage markdowns rose because marginal-revenue-product growth accelerates, not because wage growth stagnates. In local labor markets, wage-markdown growth is uncorrelated with employer-concentration growth. By contrast, we document strong associations with direct measures of information and communication technologies and indirect measures of management and automation technologies. Altogether, the evidence points to technological threat as a key driver of labor market power. We are grateful for the guidance of our advisors Erik Hurst, Chad Syverson, Ali Hortaçsu, Brent Neiman, and Luigi Zingales. We thank Carter Davis, Zach Flynn, Amit Gandhi, Luis Garicano, Mike Gibbs, John Grigsby, Arshia Hashemi, Shohini Kundu, Ben Marrow, Jordan Rosenthal-Kay, Alex Sollaci, and Uyen Tran, and participants in assorted seminars and workshops for comments. We appreciate Chang Hsieh, Huiyu Li, Pete Klenow, Pablo Ottonello, and Tom Winberry for their support with the data. This research was supported by the UChicago Stigler Center. All expressed views are those of the authors and not of the US Census Bureau, Analysis Group, or the Federal Reserve System. Results have been reviewed to ensure no confidential information is disclosed. First circulated draft with disclosed results: July 2019. Corresponding e-mail address: traina@uchicago.edu. The US labor share of income fell from 64% in the mid-1980s to 58% in 2012 (Elsby et al., 2013; Karabarbounis and Neiman, 2014). This fall was sharper in manufacturing, where the labor share fell from 57% to 41% (Kehrig and Vincent, 2021). Over the same period, average productivity decoupled from average pay (Bivens and Mishel, 2015; Stansbury and Summers, 2018), with the biggest gap in technology-intensive manufacturing (Brill et al., 2017). In this paper, we explore an emerging hypothesis for these trends: rising labor market power. We apply contemporary methods in production function estimation to US manufacturing microdata to measure labor market power over production workers. We focus on manufacturing for two reasons: (1) The sector is large, still accounting for 10% of US employment even after its sharp fall in labor share, and (2) data are available for comparable outputs and inputs from representative samples spanning over four decades. We define labor market power ∆ as the ratio of a firm’s marginal revenue product of labor RL and its wage W : ∆ = RL W . In an undistorted competitive benchmark model, this “markdown” should equal 1. With labor market power distortions, firms restrict their labor-input choice, creating a wedge on the margin between revenue productivity and pay. If intermediate-input markets are undistorted, and labor-input markets are distorted by market power only, we can equivalently write ∆ as the wedge between a cost-minimizing firm’s intermediateand labor-input choices: ∆ = RL W = fl fm CM WL (1) where fl fm is the elasticity ratio for labor to intermediates, and CM WL is the cost ratio for intermediates to labor. Though recovering the elasticity ratio fl fm requires production function estimation, the cost ratio CM WL is readily measurable with public data. The solid black line in Figure 1 plots the growth in the sector’s aggregate CM WL cost ratio using the NBER-CES Manufacturing Industry Database. We Labor market power is often called monopsony power after Robinson (1933). We use the more general term because our framework nests other forms of competition, e.g., oligopsony.