Robots, Occupations, and Worker Age: A Production-unit Analysis of Employment
Liuchun Deng, Steffen Müller, Verena Plümpe, Jens Stegmaier
European Economic Review,
November
2024
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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Risky Oil: It's All in the Tails
Christiane Baumeister, Florian Huber, Massimiliano Marcellino
NBER Working Paper,
No. 32524,
2024
Abstract
The substantial fluctuations in oil prices in the wake of the COVID-19 pandemic and the Russian invasion of Ukraine have highlighted the importance of tail events in the global market for crude oil which call for careful risk assessment. In this paper we focus on forecasting tail risks in the oil market by setting up a general empirical framework that allows for flexible predictive distributions of oil prices that can depart from normality. This model, based on Bayesian additive regression trees, remains agnostic on the functional form of the conditional mean relations and assumes that the shocks are driven by a stochastic volatility model. We show that our nonparametric approach improves in terms of tail forecasts upon three competing models: quantile regressions commonly used for studying tail events, the Bayesian VAR with stochastic volatility, and the simple random walk. We illustrate the practical relevance of our new approach by tracking the evolution of predictive densities during three recent economic and geopolitical crisis episodes, by developing consumer and producer distress indices that signal the build-up of upside and downside price risk, and by conducting a risk scenario analysis for 2024.
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Homepage
Geopolitical turn intensifies crisis – structural reforms even more urgent The German economy will continue to tread water in 2025. In their spring report, the leading economic…
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Research Data Centre
Research Data Centre (IWH-RDC) Direct link to our Data Offer The IWH Research Data Centre offers external researchers access to microdata and micro-aggregated data sets that…
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Alumni
IWH Alumni The IWH maintains contact with its former employees worldwide. We involve our alumni in our work and keep them informed, for example, with a newsletter. We also plan…
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Centre for Evidence-based Policy Advice
Centre for Evidence-based Policy Advice (IWH-CEP) The Centre for Evidence-based Policy Advice (IWH-CEP) of the IWH was founded in 2014. It is a platform that bundles and…
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Guiding Theme and Research Profile
Tasks of the IWH Guided by its mission statement , the IWH places the understanding of the determinants of long term growth processes at the centre of the research agenda. Long…
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Organisation of Research
Tasks of the IWH Guided by its mission statement , the IWH places the understanding of the determinants of long term growth processes at the centre of the research agenda. Long…
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Searching where Ideas Are Harder to Find – The Productivity Slowdown as a Result of Firms Hindering Disruptive Innovation
Richard Bräuer
IWH Discussion Papers,
No. 22,
2023
Abstract
This paper proposes to explain the productivity growth slowdown with the poaching of disruptive inventors by firms these inventors threaten with their research. I build an endogenous growth model with incremental and disruptive innovation and an inventor labor market where this defensive poaching takes place. Incremental firms poach more as they grow, which lowers the probability of disruption and makes large incremental firms even more prevalent. I perform an event study around disruptive innovations to confirm the main features of the model: Disruptions increase future research productivity, hurt incumbent inventors and raise the probability of future disruption. Without disruption, technology classes slowly trend even further towards incrementalism. I calibrate the model to the global patent landscape in 1990 and show that the model predicts 52% of the decline of disruptive innovation until 2010.
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East Germany
The Nasty Gap 30 years after unification: Why East Germany is still 20% poorer than the West Dossier In a nutshell The East German economic convergence process is hardly…
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