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Capital-skill complementarity and biased technical change across US sectors

Perez-Laborda, Alejandro; Perez-Sebastian, Fidel

Authors

Alejandro Perez-Laborda



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, 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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