Occupational Tasks, Automation, and Economic Growth: A Modeling and Simulation Approach
Georgios A. Tritsaris

TL;DR
This paper develops an analytical task-based model to understand how automation and AI influence economic growth, wages, and labor shares, highlighting the potential for policy interventions to independently affect wages and labor shares.
Contribution
It introduces a novel endogenous framework integrating knowledge accumulation with technological frictions, advancing understanding of automation's economic impacts.
Findings
Wages and labor shares can be influenced independently by different policy levers.
Labor share is sensitive to capital-labor ratio.
Wages increase with larger knowledge stocks.
Abstract
The Fourth Industrial Revolution commonly refers to the accelerating technological transformation that has been taking place in the 21st century. Economic growth theories which treat the accumulation of knowledge and its effect on production endogenously remain relevant, yet they have been evolving to explain how the current wave of advancements in automation and artificial intelligence (AI) technology will affect productivity and different occupations. The work contributes to current economic discourse by developing an analytical task-based framework that endogenously integrates knowledge accumulation with frictions that describe technological lock-in and the burden of knowledge generation and validation. The interaction between production (or automation) and growth (or knowledge accumulation) is also described explicitly. To study how automation and AI shape economic outcomes, I rely…
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Taxonomy
TopicsEconomic Growth and Productivity · Firm Innovation and Growth · Labor market dynamics and wage inequality
