Task-Specific Technical Change and Comparative Advantage
Lukas Althoff and
Hugo A. Reichardt
No 1602, Working Papers from Barcelona School of Economics
Abstract:
Artificial intelligence (AI) reshapes workers' comparative advantage by altering the tasks they perform and the skills those tasks require. We develop a dynamic task-based model to quantify the general-equilibrium effects of task-specific technical change. Workers have multidimensional skills, choose occupations, and accumulate skills on the job; occupations combine tasks, and productivity depends on how workers' skills match task requirements. We develop a computationally efficient procedure to estimate the model using panel data and a new database of task-level skill requirements. We apply the model to AI, allowing it to augment, automate, and simplify tasks. We find that AI narrows wage inequality and raises average wages across scenarios ranging from slow to rapid AI progress. The key equalizing force is simplifi- cation: by lowering tasks' skill requirements, AI lets lower-skill workers compete for previously inaccessible jobs. Adoption costs, highest for lower-skill workers, dampen but do not eliminate the decline in inequality.
Keywords: artificial intelligence; comparative advantage; multidimensional skills; occupational choice; skill-accumulation; task-based models; wage inequality (search for similar items in EconPapers)
JEL-codes: E24 J24 J31 J62 O33 (search for similar items in EconPapers)
Date: 2026-10
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Persistent link: https://EconPapers.repec.org/RePEc:bge:wpaper:1602
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