Robots, Occupations, and Worker Age: A Production-unit Analysis of Employment
Liuchun Deng, Steffen Müller, Verena Plümpe, Jens Stegmaier
IWH Discussion Papers,
Nr. 5,
2023
Abstract
We analyse the impact of robot adoption on employment composition using novel micro data on robot use in German manufacturing plants linked with social security records and data on job tasks. Our task-based model predicts more favourable employment effects for the least routine-task intensive occupations and for young workers, with the latter being better at adapting to change. An event-study analysis of robot adoption confirms both predictions. We do not find adverse employment effects for any occupational or age group, but churning among low-skilled workers rises sharply. We conclude that the displacement effect of robots is occupation biased but age neutral, whereas the reinstatement effect is age biased and benefits young workers most.
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On the Employment Consequences of Automation and Offshoring: A Labor Market Sorting View
Ester Faia, Sébastien Laffitte, Maximilian Mayer, Gianmarco Ottaviano
Lili Yan Ing, Gene M. Grossman (eds), Robots and AI: A New Economic Era. Routledge: London,
2022
Abstract
We argue that automation may make workers and firms more selective in matching their specialized skills and tasks. We call this phenomenon “core-biased technological change”, and wonder whether something similar could be relevant also for offshoring. Looking for evidence in occupational data for European industries, we find that automation increases workers’ and firms’ selectivity as captured by longer unemployment duration, less skill-task mismatch, and more concentration of specialized knowledge in specific tasks. This does not happen in the case of offshoring, though offshoring reinforces the effects of automation. We show that a labor market model with two-sided heterogeneity and search frictions can rationalize these empirical findings if automation strengthens while offshoring weakens the assortativity between workers’ skills and firms’ tasks in the production process, and automation and offshoring complement each other. Under these conditions, automation decreases employment and increases wage inequality whereas offshoring has opposite effects.
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Robot Adoption at German Plants
Liuchun Deng, Verena Plümpe, Jens Stegmaier
Abstract
Using a newly collected dataset of robot use at the plant level from 2014 to 2018, we provide the first microscopic portrait of robotisation in Germany and study the potential determinants of robot adoption. Our descriptive analysis uncovers five stylised facts concerning both extensive and, perhaps more importantly, intensive margin of plant-level robot use: (1) Robot use is relatively rare with only 1.55% German plants using robots in 2018. (2) The distribution of robots is highly skewed. (3) New robot adopters contribute substantially to the recent robotisation. (4) Robot users are exceptional along several dimensions of plant-level characteristics. (5) Heterogeneity in robot types matters. Our regression results further suggest plant size, low-skilled labour share, and exporter status to have strong and positive effect on future probability of robot adoption. Manufacturing plants impacted by the introduction of minimum wage in 2015 are also more likely to adopt robots. However, controlling for plant size, we find that plant-level productivity has no, if not negative, impact on robot adoption.
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Development of Survey Questions on Robotics Expenditures and Use in U.S. Manufacturing Establishments
Catherine Buffington, Javier Miranda, Robert Seamans
Center for Economic Studies (CES) Working Paper Series,
Nr. 44,
2018
Abstract
The U.S. Census Bureau in partnership with a team of external researchers developed a series of questions on the use of robotics in U.S. manufacturing establishments. The questions include: (1) capital expenditures for new and used industrial robotic equipment in 2018, (2) number of industrial robots in operation in 2018, and (3) number of industrial robots purchased in 2018. These questions are to be included in the 2018 Annual Survey of Manufactures. This paper documents the background and cognitive testing process used for the development of these questions.
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