 Latent innovation in local economiesStephan J. Goetz and Yicheol Han Research Policy, 2020, vol. 49, issue 2 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. Keywords: Latent innovation; Local economic growth; Input-output table (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:respol:v:49:y:2020:i:2:s0048733319302276 DOI: 10.1016/j.respol.2019.103909 Access Statistics for this article Research Policy is currently edited by M. Bell, B. Martin, W.E. Steinmueller, A. Arora, M. Callon, M. Kenney, S. Kuhlmann, Keun Lee and F. Murray More articles in Research Policy from Elsevier |
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