ABSTRACT

This paper provides direct evidence of automation's role in production using establishment-level data from the U.S. Census Bureau's Survey of Manufacturing Technology. The data indicate that more automated plants have lower production labor share and higher capital share, higher labor productivity, and a smaller fraction of workers in production who receive higher wages. To understand the connection between automation and total factor productivity, we estimate a CES model of production where a plant chooses the degree of automation by adjusting the relative weight of capital and production labor given their relative price. The results indicate that, in the presence of heterogeneity in the extent of automation, productivity estimates are more dispersed and skewed relative to Cobb-Douglas residuals, and that the choice of functional form affects the level of productivity estimates. Overall, broad and deep automation is concentrated in larger plants with higher total factor productivity and lower labor share, consistent with a role for automation in contributing to dispersion in input utilization and market share.

摘要

本文使用美国人口普查局制造技术调查的企业级数据提供了自动化在生产中的作用的直接证据。数据表明，自动化程度越高的工厂，生产劳动力份额越低，资本份额越高，劳动生产率越高，生产中获得较高工资的工人比例越小。为了理解自动化和全要素生产率之间的联系，我们估计了一个 CES 生产模型，其中工厂通过调整资本和生产劳动力相对价格的相对权重来选择自动化程度。结果表明，在自动化程度存在异质性的情况下，生产率估计相对于柯布-道格拉斯残差更加分散和偏斜，函数形式的选择会影响生产率估计的水平。总体而言，广泛而深入的自动化集中在全要素生产率较高、劳动力份额较低的大型工厂，这与自动化在分散投入利用率和市场份额方面的作用是一致的。