Robots and Humans: The Role of Fiscal and Monetary Policies in an Endogenous Growth Model
ROBOTS AND HUMANS: THE ROLE OF FISCAL AND MONETARY POLICIES IN AN ENDOGENOUS GROWTH MODEL
This working paper develops a dynamic general equilibrium growth model to analyze how robotization, which replaces unskilled labor, interacts with fiscal and monetary policies. The authors find that while robotization increases economic growth and the skill premium, implementing targeted fiscal and monetary policies can mitigate wage inequality at the cost of an efficiency-equity trade-off. Overall, the presence of fiscal and monetary policies leads to higher long-run economic growth compared to a scenario without policies.
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Who issued it
Who it governs
Economists, researchers, and policymakers interested in the macroeconomic and distributional impacts of automation and Industry 4.0.
What the document contains
The document models the macroeconomic impacts of substituting unskilled labor with robots in an endogenous growth framework, focusing on how fiscal and monetary policy levers affect economic growth, skill premia, and welfare.
It does not provide specific legal regulations, governance frameworks for AI developers, or concrete legislative text for implementing a robot tax.
- Robotization reduces the unskilled-to-skilled-labor ratio, stimulating economic growth while increasing wage inequality.
- Fiscal and monetary policies can be used to mitigate the negative distributional effects of robotization.
- A policy-induced reduction in wage inequality introduces an efficiency-equity trade-off that dampens long-run economic growth.
- Despite trade-offs, long-run economic growth is higher with active fiscal and monetary policies than without them.
· Introduction · Theoretical Setup · Balanced Growth Path · Effects of Robotization and Fiscal and Monetary Policies · 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
Introduction
screening score · 2026-10-23
Fairness
2/5Non-discrimination and equitable treatment
In view of these issues, the modeling framework that we propose in this paper emphasizes the role of scal policy in the human capital accumulation and in the taxation of the use of robots in production
1 Introduction
screening score · 2026-10-23
Human Dignity
0/5Respect for the inherent worth of persons
Introduction
screening score · 2026-10-23
Human Oversight
0/5Humans remain in control of consequential decisions
Introduction
screening score · 2026-10-23
Privacy
0/5Protection of personal data and private life
Introduction
screening score · 2026-10-23
Transparency
0/5Openness about how AI systems work and are used
Introduction
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
Introduction
screening score · 2026-10-23
Impact Assessment
0/5Required assessment of an AI system's risks/impacts before or during use
Introduction
screening score · 2026-10-23