SOURCE-LINKED INTELLIGENCE

Automation and Occupational Network

CORDIS · observation · Publication date unknown

loyee microdata to quantify both direct and systemic effects of robotics and AI adoption. The first contribution is the construction of a task-based occupational input–output network, using O*NET and Large Language Models (LLMs) to capture productive interdependencies between occupations at an unprecedented level of detail. The second contribution is the identification of tasks that can be automated within the occupational input–output network, to analyse how automation alters the input–output relationships between occupations that depend on those tasks. The third contribution is an occupational model that embeds these shocks into a general equilibrium setting, disciplined with linked employer–employee data from Australia, allowing us to trace equilibrium feedbacks on wages, employment, and occupational mobility. By combining micro-level task structures with macroeconomic modelling, the project moves beyond aggregate measures of automation risk, offering a systemic perspective on technological diffusion. The expected outcomes include new empirical measures of automation spillovers, s

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recordType

award

status

SIGNED

region

EU

value

309153.72

unit

EUR