Latent innovation in local economies

Stephan J. Goetz, Yicheol Han

Research output: Contribution to journalArticle

Abstract

We propose a measure of latent innovation in local economies based on spillovers among industries in terms of inter-industry sales and purchases as well as spatial proximity. The proposed measure captures innovation that is not reflected in typical NSF-based statistics such as patents, R&D spending, or science and engineering workers. When the results are mapped for the U.S., regions that one would expect to be highly innovative also show up as such. To determine whether this measure helps to explain economic growth beyond traditional factors such as human capital and agglomeration, and conventional measures of innovation, we estimate simple regression models with income and employment growth as dependent variables. The proposed innovation measure is statistically significant even after we control for rival causes of growth. We suggest that our measure is preferable to conventional innovation indicators for understanding where in the U.S. innovation, more broadly defined, is occurring.

Original languageEnglish (US)
Article number103909
JournalResearch Policy
Volume49
Issue number2
DOIs
StatePublished - Mar 2020

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Innovation
Local economy
Industry
Sales
Agglomeration
Statistics
Economics

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Management of Technology and Innovation

Cite this

Goetz, Stephan J. ; Han, Yicheol. / Latent innovation in local economies. In: Research Policy. 2020 ; Vol. 49, No. 2.
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Latent innovation in local economies. / Goetz, Stephan J.; Han, Yicheol.

In: Research Policy, Vol. 49, No. 2, 103909, 03.2020.

Research output: Contribution to journalArticle

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