Journal of Geographical Systems

, Volume 18, Issue 2, pp 125–157 | Cite as

Exploring the spatially varying innovation capacity of the US counties in the framework of Griliches’ knowledge production function: a mixed GWR approach

  • Dongwoo Kang
  • Sandy Dall’erba
Original Article


Griliches’ knowledge production function has been increasingly adopted at the regional level where location-specific conditions drive the spatial differences in knowledge creation dynamics. However, the large majority of such studies rely on a traditional regression approach that assumes spatially homogenous marginal effects of knowledge input factors. This paper extends the authors’ previous work (Kang and Dall’erba in Int Reg Sci Rev, 2015. doi: 10.1177/0160017615572888) to investigate the spatial heterogeneity in the marginal effects by using nonparametric local modeling approaches such as geographically weighted regression (GWR) and mixed GWR with two distinct samples of the US Metropolitan Statistical Area (MSA) and non-MSA counties. The results indicate a high degree of spatial heterogeneity in the marginal effects of the knowledge input variables, more specifically for the local and distant spillovers of private knowledge measured across MSA counties. On the other hand, local academic knowledge spillovers are found to display spatially homogenous elasticities in both MSA and non-MSA counties. Our results highlight the strengths and weaknesses of each county’s innovation capacity and suggest policy implications for regional innovation strategies.


Knowledge production function Knowledge spillovers Spatial heterogeneity Mixed geographically weighted regression (MGWR) 

JEL Classification

C21 O31 R11 



We would like to thank the Editor-in-Chief Dr. Manfred M. Fischer and two anonymous reviewers for their helpful comments and suggestions.


This study was supported by the National Science Foundation Grant (SMA-1158172). Any opinions, findings and conclusions or recommendations expressed in this article are those of the authors and do not necessarily reflect the views of the National Science Foundation.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Korea Labor InstituteSejong-siKorea
  2. 2.Department of Agricultural and Consumer Economics and Regional Economics Applications LaboratoryUniversity of Illinois at Urbana-ChampaignUrbanaUSA

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