Hello, I’m Eve. It seems intuitive that introducing robots into the workplace would mean not only lowering labor costs, but also lowering wage rates. However, Soi Disant For pundits trying to argue that automation will raise wage levels, it’s useful to look at the obvious facts.
Written by Adachi Daisuke, Assistant Professor at Aarhus University. Vox EU
Industrial robots have the potential to transform jobs and wages. In this column, we study how the rise of robot capital has affected wage polarization across different U.S. occupations. We find that substitutability between robots and labor varies by occupation and is particularly pronounced in manufacturing and material movement jobs. Robotization has slowed wage growth in these occupations, leading to greater wage polarization. Potential policies to address these distributional effects include retraining programs and tax policies to manage the pace of robot adoption without stifling innovation.
The rapid introduction of industrial robots into manufacturing processes in recent years has sparked considerable debate among policymakers and economists. The debate centers on the transformative impact of automation on employment and wage distribution, especially in economies with large industrial sectors such as the United States. In this column, we examine how the rise of robot capital affected wage polarization across occupations between 1990 and 2007 and identify the mechanisms driving these changes.
The expanding role of robots in industry
Industrial robots have revolutionized factory production over the past three decades, with the global robotics market expanding at a rate of 12% per year (IFR 2021). However, these advances have not affected all workers uniformly. Concerns over the uneven distribution of the impacts of robotics have led policymakers to consider measures such as taxing robot adoption to mitigate potential harms. Previous studies have explored the broader employment effects of robot proliferation (e.g., Acemoglu and Restrepo 2020) and the impact of robot taxes (e.g., Humlum 2021). However, understanding the substitutability of robots and workers in specific occupations remains important to assess the full impact of automation.
Research Summary
My research (Apache 2024) uses a new dataset on the acquisition costs of Japanese-made robots, called the Japan Robot Shock (JRS), to take a closer look at the substitutability of robots with workers across different occupations. I address identification challenges related to the correlation between automation shocks and the JRS by developing a general equilibrium model of robot automation in a large open economy and constructing optimal instrumental variables suggested by the model.
My analysis reveals that the elasticity of substitution (EoS) between robots and labor varies by occupation. For production and material transfer jobs, the elasticity of substitution is high at 3, significantly higher than the substitutability between other capital goods and labor. This indicates that robots are much more substitutable for workers in these roles than they are in other occupations. The findings suggest that robotization contributed significantly to wage polarization in the United States from 1990 to 2007.
Impact on wage distribution
A high elasticity of substitution in production-related occupations indicates that robotization has disproportionately affected workers in these sectors, slowing wage growth compared to other occupations. Specifically, robotization reduced the relative wages of workers in the middle 10 percent of the occupational wage distribution, while increasing the wage ratios at the 90th and 50th percentiles by 6.4%. This measure of wage inequality, popularized by Goos and Manning (2007) and Autor et al. (2008), highlights the growing gap between high- and middle-wage workers.
Comparative analysis with existing literature
My study complements previous work by providing detailed estimates of the within-occupation elasticity of substitution between robots and workers. Acemoglu and Restrepo (2020) find that wage and employment growth is lower in regions with high robot penetration. Humlum (2021) shows that there is wide variation in the real wage impact of robots across occupations. By focusing on the US labor market and using occupation-level robot cost data, my study provides a more nuanced understanding of the substitutability of robots and workers and its impact on wage distribution.
Policy considerations
The findings highlight the need for targeted policy interventions to address the adverse distributional effects of automation. Possible measures include retraining programs for workers in highly vulnerable occupations and tax policies designed to manage the pace of robot adoption without stifling innovation. Given the significant impact of robotization on wage polarization, policymakers will need to carefully consider how to balance the benefits of technological progress with the need to ensure fair labor market outcomes.
Conclusion
The integration of robots into industrial processes has had a significant impact on US wage distribution, particularly by exacerbating wage polarization. My research highlights the importance of understanding the specific dynamics of robot-worker substitutability in occupations to fully grasp the broader economic impacts of automation. As debates over robot taxes and other policy measures continue, our findings provide valuable insights for developing strategies to promote economic growth while mitigating the negative impacts of automation on workers.
Author’s note: The main study on which this column is based (Adachi 2024) is Discussion Paper of the Research Institute of Economy, Trade and Industry (RIETI) in Japan.
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