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 language | English (US) |
|---|---|
| Article number | 103909 |
| Journal | Research Policy |
| Volume | 49 |
| Issue number | 2 |
| DOIs | |
| State | Published - Mar 2020 |
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All Science Journal Classification (ASJC) codes
- Strategy and Management
- Management Science and Operations Research
- Management of Technology and Innovation
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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 journal › Article
TY - JOUR
T1 - Latent innovation in local economies
AU - Goetz, Stephan J.
AU - Han, Yicheol
PY - 2020/3
Y1 - 2020/3
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85076054130&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076054130&partnerID=8YFLogxK
U2 - 10.1016/j.respol.2019.103909
DO - 10.1016/j.respol.2019.103909
M3 - Article
AN - SCOPUS:85076054130
VL - 49
JO - Research Policy
JF - Research Policy
SN - 0048-7333
IS - 2
M1 - 103909
ER -