Robot Adoption at German Plants
Jahrbücher für Nationalökonomie und Statistik,
Using a newly collected dataset at the plant level from 2014 to 2018, we provide the first microscopic portrait of robotization in Germany and study the correlates of robot adoption. Our descriptive analysis uncovers five stylized facts: (1) Robot use is relatively rare. (2) The distribution of robots is highly skewed. (3) New robot adopters contribute substantially to the recent robotization. (4) Robot users are exceptional. (5) Heterogeneity in robot types matters. Our regression results further suggest plant size, high-skilled labor share, exporter status, and labor shortage to be strongly associated with the future probability of robot adoption.
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Robots, Occupations, and Worker Age: A Production-unit Analysis of Employment
IWH Discussion Papers,
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.
Automation with Heterogeneous Agents: The Effect on Consumption Inequality
IWH Discussion Papers,
In this paper, I study technological change as a candidate for the observed increase in consumption inequality in the United States. I build an incomplete market model with educational choice combined with a task-based model on the production side. I consider two channels through which technology affects inequality: the skill that an agent can supply in the labor market and the level of capital she owns. In a quantitative analysis, I show that (i) the model replicates the increase in consumption inequality between 1981 and 2008 in the US (ii) educational choice and the return to wealth are quantitatively important in explaining the increase in consumption inequality.
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On the Employment Consequences of Automation and Offshoring: A Labor Market Sorting View
Lili Yan Ing, Gene M. Grossman (eds), Robots and AI: A New Economic Era. Routledge: London,
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.