Abstract
This article represents one of the first attempts at building a direct measure of occupational exposure to robotic labour-saving technologies. After identifying robotic and labour-saving robotic patents, the underlying 4-digit CPC (Cooperative Patent Classification) code definitions, together with O*NET (Occupational Information Network) task descriptions, are employed to detect functions and operations which are more directed to substituting the labour input and their exposure to labour-saving automation. This measure allows us to obtain fine-grained information on tasks and occupations according to their text similarity ranking. Occupational exposure by wage and employment dynamics in the United States is then studied, and complemented by investigating industry and geographical penetration rates.
| Original language | English |
|---|---|
| Pages (from-to) | 332-361 |
| Number of pages | 30 |
| Journal | World Economy |
| Volume | 47 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
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SDG 10 Reduced Inequalities
All Science Journal Classification (ASJC) codes
- Accounting
- Finance
- Economics and Econometrics
- Political Science and International Relations
Keywords
- labour markets
- labour-saving technology
- natural language processes
- technological unemployment
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