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Most studies of automation focus on manufacturing or use aggregate data. In one of the first studies of the service sector using establishment-level data, we examine the impact of robot adoption on staffing in nursing homes.
The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced computational methods.
The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced computational methods.
This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!
This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!
This setting is important, because robots are increasingly being adopted in many countries to address the challenges posed by population aging. Japan, in particular, has been actively developing and deploying robots in nursing homes to deal with labor shortages, and since 2015 has subsidized nursing home purchase of robots. Analyzing 2017 data from Japanese nursing homes, we document that facilities that adopt robots are larger, with more functionally-impaired residents, greater numbers of care workers and nurses, many other assistive technologies, better management practices, and located in prefectures with higher planned subsidies for robots per nursing home. However, using variation in those robot subsidies as an instrumental variable, we find that robot adoption has little causal impact on overall staffing or wages, but leads to additional non-regular nurse hours, and increasing turnover of regular care workers. Robot adoption also reduces the wage share, consistent with compositional change in staffing toward non-regular workers. The tight labor market in Japan appears to have prompted nursing homes to adopt a more capital-intensive production process without many detrimental effects on labor. Our results contrast with recent findings that show negative effects of robots on employment and wages in the US manufacturing sector, suggesting that the impact of robots likely differs by labor market conditions and industry.
