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Title: How Task-Biased is Capital-Embodied Innovation?

Citation Type: Working Paper

Publication Year: 2022

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DOI: 10.2139/SSRN.3996417

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Abstract: This paper develops a measure of Capital-Embodied Innovation (CEI). The measure counts the number of patents applied to capital goods by matching patent documents with Wikipedia articles on capital goods. Using occupation-level variations on the sets of capital goods from O*NET, we document that CEI is biased toward abstract and non-routine occupations. Furthermore, we highlight the heterogeneous effects of CEI across the capital good-occupation relationship. When the capital good performs a similar function as the occupational task (task-substituting capital), the CEI reduces the relative demand for labor. In case the capital good performs a different function than the occupation tasks (task-complementing capital), the CEI raises relative demand for labor. Abstract occupations have disproportionately more CEI on task-complementing capital than non-abstract occupations. A model-based counterfactual implies that the employment growth between the 1980s and the 2010s would be significantly less biased towards abstract task occupations without CEI. The degree of job polarization and occupational wage inequality would have also been lower without CEI.

Url: https://papers.ssrn.com/abstract=3996417

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Authors: Park, Hyejin; Shim, Younghun

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Pages: 1-62

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Data Collections: IPUMS USA

Topics: Methodology and Data Collection, Population Data Science

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