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Cited by 808

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

The Skill Complementarity of Broadband Internet *

Akerman, Anders, Gaarder, Ingvil, Mogstad, Magne·2015·The Quarterly Journal of Economics

Abstract

Does adoption of broadband internet in firms enhance labor productivity and increase wages? Is this technological change skill biased or factor neutral? We combine several Norwegian data sets to answer these questions. A public program with limited funding rolled out broadband access points and provides plausibly exogenous variation in the availability and adoption of broadband internet in firms. Our results suggest that broadband internet improves (worsens) the labor market outcomes and productivity of skilled (unskilled) workers. We explore several possible explanations for the skill complementarity of broadband internet. We find suggestive evidence that broadband adoption in firms complements skilled workers in executing nonroutine abstract tasks, and substitutes for unskilled workers in performing routine tasks. Taken together, our findings have important implications for the ongoing policy debate over government investment in broadband infrastructure to encourage productivity and wage growth.

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Metadata

Authors
Akerman, A., Gaarder, I., & Mogstad, M.
Venue
The Quarterly Journal of Economics
Published
2015-07-16
Volume
130
Issue
4
Pages
1781-1824
ISSN
  • 0033-5533 (ISSN-L)
  • 1531-4650
OpenAlex
W1959870581
Cited by
808
References
9
FWCI
77.68
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Skill Complementarity of Broadband Internet *. https://app.cochat.ai/papers/10.1093/qje/qjv028
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Akerman, A., Gaarder, I., & Mogstad, M. (2015). The Skill Complementarity of Broadband Internet *. The Quarterly Journal of Economics. https://doi.org/10.1093/qje/qjv028

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.