Monopsony in the U.S. labor market

(Re)distribution

Posted

February 2024

| By

Chen Yeh

Claudia Macaluso

Brad J. Hershbein

Research summaries

Research Paper

What is this research about and why did you do it?

Policy makers in the US have increasingly been proposing measures to mitigate a perceived increase in employers’ market power (or monopsony). While the ensuing debate has been heated, it is complicated by the lack of direct evidence on market power in labor markets. In this article, we show that US labor markets are far from perfectly competitive: the degree of employers' market power is substantial and widespread in the U.S. manufacturing sector. Furthermore, we provide insights and measures on how to construct statistics that reflect an aggregate economy’s labor market power.

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How did you answer this question?

Direct measures of labor market power are hard to come by. As a result, we first show that a typical measure for a firm’s labor market power, i.e. markdown, can be expressed as a function of only output elasticities and revenue shares under certain conditions. The latter are available in most firm-level data sets whereas we estimate the former by applying production function estimation techniques from the Industrial Organization (IO) literature on confidential US manufacturing data. Importantly, we show that certain drawbacks of these estimation techniques that the literature has highlighted do not apply to the measurement of markdowns. Lastly, we formalize how to aggregate firm-level markdowns and estimate it with data from the US Census Bureau.

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What did you find?

US labor market power is much more prominent than previously conjectured. On average, markdowns are equal to 1.53; implying that workers receive only 65 cents on each dollar generated in the margin. While monopsony forces are present in every US manufacturing subsector, its degree varies a lot across these subsectors.

Markdowns are estimated under the assumption of a translog specification for gross output. Each industry group in manufacturing corresponds to the manufacturing categorization of the U.S. Bureau of Economic Analysis, which approximately follows a 3-digit NAICS specification. The distributional statistics are calculated using sampling weights provided in the data. Source: Authors' calculations from ASM/CM data in 1976-2014.

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Furthermore, we find that the aggregate markdown has been evolving in a non-monotone manner. Importantly, it diverges from previously-available proxies on labor market power (e.g., local employment concentration) and it has not been uniformly increasing over time; debunking narratives of monopsony causing declining labor shares.

Note: The solid black line shows the time series for the aggregate markdown and the dashed orange line shows the time series of local employment concentration. Both are normalized to their initial respective values in 1977. Source: Authors' own calculations from quinquennial CM data from 1977 - 2012.

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What implications does this have for the study (research and teaching) of wealth concentration or economic inequality?

This paper shows that employers are able to withhold significant portions of workers’ marginal gains to their revenues; identifying a potential source of entrepreneurs’ earnings/wealth at the expense of workers. Furthermore, we show that labor market power can have a different impact on different types of workers (e.g., production versus non-production workers).

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What are the next steps in your agenda?

The current paper is agnostic on the sources of labor market power. Future work will focus on these sources through, for example, mergers and acquisitions, and its implications for the design of antitrust policy for labor markets.

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