Robots and Labor Regulation: A Cross-Country/Cross-Industry Analysis
This working paper empirically investigates the relationship between labor regulations and the adoption of industrial robots across nineteen Western countries and eight non-service sectors between 2006 and 2016. The authors find that high levels of statutory employment protection are generally negatively associated with robot adoption due to increased adjustment costs. However, this correlation is positively mediated by sectoral capital intensity, suggesting firms also use robots as substitutes for labor to reduce workers' bargaining power and hold-up risks.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, economists, and policymakers interested in the institutional drivers of robot adoption and labor market dynamics.
What the document contains
The paper examines the empirical relationship between labor regulations (specifically dismissal laws, fixed-term contracts, and industrial action rules) and the adoption of industrial robots across 19 countries and various non-service sectors between 2006 and 2016.
The document does not provide policy recommendations, ethical frameworks for artificial intelligence, or legal compliance guidelines for companies deploying automation technologies.
- High levels of statutory employment protection are negatively associated with overall industrial robot adoption.
- Labor regulations that increase adjustment costs make investment riskier and slow down overall automation.
- Sectoral capital intensity positively mediates the relationship between labor regulation and robot adoption.
- Firms in capital-intensive sectors utilize industrial robots as potential substitutes for workers to limit hold-up opportunities and reduce employee bargaining power.
- Only labor regulation provisions that pose substantive constraints on dismissal show a statistically significant correlation with robot adoption.
· 1 Introduction · 2 Labor Regulation and Determinants of Robot Adoption · 3 Empirical Strategy · 4 Empirical Results · 5 Concluding remarks
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
0/5Clear responsibility for AI outcomes
screening score · 2026-10-23
Fairness
0/5Non-discrimination and equitable treatment
screening score · 2026-10-23
Human Dignity
0/5Respect for the inherent worth of persons
screening score · 2026-10-23
Human Oversight
0/5Humans remain in control of consequential decisions
screening score · 2026-10-23
Privacy
0/5Protection of personal data and private life
screening score · 2026-10-23
Transparency
0/5Openness about how AI systems work and are used
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
screening score · 2026-10-23
Impact Assessment
0/5Required assessment of an AI system's risks/impacts before or during use
screening score · 2026-10-23