Automation and the Rise of Superstar Firms

48 Pages Posted: 17 Mar 2022 Last revised: 14 Nov 2023

See all articles by Hamid Firooz

Hamid Firooz

Department of Economics, University of Rochester

Zheng Liu

Federal Reserve Banks - Federal Reserve Bank of San Francisco

Yajie Wang

University of Rochester; University of Missouri at Columbia - Department of Economics

Date Written: February 21, 2022

Abstract

Using an instrumental variable approach, we document evidence that the rise in
automation technology contributed to the rise of superstar firms. We explain this
empirical link in a general equilibrium framework with heterogeneous firms and
variable markups. Firms can operate a labor-only technology or, by paying a per-period fixed cost, an automation technology that uses both workers and robots.
Given the fixed cost, larger and more productive firms are more likely to automate.
Automation boosts labor productivity, enabling those large automating firms to
expand further, and thus raising industry concentration. Our calibrated model can
replicate the highly skewed automation usage toward superstar firms observed in
the Census data. Since robots can substitute for workers, increased automation raises
sales concentration more than employment concentration, consistent with empirical
evidence. In the model, automation raises aggregate productivity but exacerbates
markup distortions. Our calibration suggests that a modest subsidy for automating
firms improves welfare.

Keywords: Automation, industry concentration, superstar firms, markup, productivity

JEL Classification: E24, L11, O33

Suggested Citation

Firooz, Hamid and Liu, Zheng and Wang, Yajie, Automation and the Rise of Superstar Firms (February 21, 2022). Available at SSRN: https://ssrn.com/abstract=4040235 or http://dx.doi.org/10.2139/ssrn.4040235

Hamid Firooz (Contact Author)

Department of Economics, University of Rochester ( email )

Department of Economics
227 Harkness Hall
Rochester, NY 14627
United States

HOME PAGE: http://https://sites.google.com/view/hamidfirooz/home

Zheng Liu

Federal Reserve Banks - Federal Reserve Bank of San Francisco ( email )

101 Market Street
San Francisco, CA 94105
United States

Yajie Wang

University of Rochester ( email )

300 Crittenden Blvd.
Rochester, NY 14627
United States

HOME PAGE: http://www.yajiewang.info

University of Missouri at Columbia - Department of Economics ( email )

118 Professional Building
Columbia, MO 65211
United States
5853514816 (Phone)

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