Alejandro Perez-Laborda
Capital-skill complementarity and biased technical change across US sectors
Perez-Laborda, Alejandro; Perez-Sebastian, Fidel
Authors
Fidel Perez-Sebastian
Abstract
The goal of this paper is two-fold. First, we reexamine the evidence for the capital-skill complementarity (CSC) and the skill-biased technological change (SBTC) hypotheses at the sectoral level in the US economy for the period 1970-2005. Second, we quantify their effect on the evolution of the wage skill premium. To do so, we estimate a translog model with three production factors (skilled labor, unskilled labor, and capital) for different sets of industry aggregates suggested by the literature. At the aggregated level, we find that both CSC and SBTC explain a substantial part of the observed change in the skill premium. The CSC hypothesis also receives support across sectors, although SBTC often explains a larger part of the premium change. We also find that the relevance of CSC increases with the level of aggregation of the data. Besides, when we disaggregate capital into ICT and non-ICT, our results suggest that often ICT capital is not the primary source of CSC. However, ICT-CSC is the most important driver of the skill premium in specific sectors, such as financial and business services.
Citation
Perez-Laborda, A., & Perez-Sebastian, F. (2020). Capital-skill complementarity and biased technical change across US sectors. Journal of Macroeconomics, 66, Article 103255. https://doi.org/10.1016/j.jmacro.2020.103255
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 8, 2020 |
Online Publication Date | Sep 21, 2020 |
Publication Date | 2020-12 |
Deposit Date | Nov 4, 2020 |
Publicly Available Date | Sep 22, 2021 |
Journal | Journal of Macroeconomics |
Print ISSN | 0164-0704 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 66 |
Article Number | 103255 |
DOI | https://doi.org/10.1016/j.jmacro.2020.103255 |
Keywords | Capital-skill complementarity; Biased technical change; Skill premium; Labor share; Translog; ICT capital |
Public URL | https://hull-repository.worktribe.com/output/3585957 |
Publisher URL | https://www.sciencedirect.com/science/article/abs/pii/S0164070420301804?via%3Dihub |
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Copyright Statement
©2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
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