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A Task-Based Theory of Occupations with Multidimensional Heterogeneity

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Abstract

I develop an assignment model of occupations with multidimensional heterogeneity in production tasks and worker skills. Tasks are distributed continuously in the skill space, whereas workers have a discrete distribution with a finite number of types. Occupations arise endogenously as bundles of tasks optimally assigned to a type of worker. The model allows us to study how occupations respond to changes in the economic environment, making it useful for analyzing the implications of automation, skill-biased technical change, offshoring, and worker training. Using the model, I characterize how wages, the marginal product of workers, the substitutability between worker types, and the labor share depend on the assignment of tasks to workers. I introduce automation as the choice of the optimal size and location of a mass of identical robots in the task space. Automation displaces workers by replacing them in the performance of tasks, generating a cascading effect on other workers as the boundaries of occupations are redrawn.

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  • Sergio Ocampo, 2022. "A Task-Based Theory of Occupations with Multidimensional Heterogeneity," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20222, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    • Handle: RePEc:uwo:hcuwoc:20222
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    Cited by:

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    2. Freund, L. B., 2022. "Superstar Teams: The Micro Origins and Macro Implications of Coworker Complementarities," Cambridge Working Papers in Economics 2276, Faculty of Economics, University of Cambridge.
    3. Sugat Chaturvedi & Kanika Mahajan & Zahra Siddique, 2024. "Using Domain-Specific Word Embeddings to Examine the Demand for Skills," Research in Labor Economics, in: Big Data Applications in Labor Economics, Part B, volume 52, pages 171-223, Emerald Group Publishing Limited.

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    Keywords

    occupations; tasks; automation; assignment; skill mismatch;
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