Rethinking the regional knowledge production function

hUallacháin, Breandán Ó; Leslie, Timothy F.

doi:10.1093/jeg/lbm027

Cited by 77 publications

(51 citation statements)

References 35 publications

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“…In other words, past studies discussed regions and states, but failed to account for the scale of spillover and possible neighboring spatial effects, or the methods and rationale used to define neighbors. The common unit of analysis was either the states [20,38] or metropolitan areas [17,31,32]. A few other studies have examined both the state and metropolitan levels [24,27,39].…”

Section: Literature Reviewmentioning

confidence: 99%

Observing regional divergence of Chinese nanotechnology centers

Motoyama¹,

Cao²,

Appelbaum³

2014

Technological Forecasting and Social Change

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Section: Literature Reviewmentioning

confidence: 99%

Observing regional divergence of Chinese nanotechnology centers

Motoyama¹,

Cao²,

Appelbaum³

2014

Technological Forecasting and Social Change

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“…Following the endogenous growth model of Redding's (1996), one may presume that firms' profit seeking R&D is closely related to their host region's base in education and training. Regions with deficiencies in education and training are also those that offer little incentive to local firms to undertake R&D. A number of empirical studies tend to suggest a positive effect of availability of skilled labour force on technological activities proxied by R&D or patent (Bania et al, 1992;Birdsall and Rhee, 1993;ÓhUallacháin and Leslie, 2007;Usai, 2008;Gumbau-Albert and Maudos, 2009). …”

Section: Input-related Factorsmentioning

confidence: 99%

Regional Heterogeneity and Firms’ Innovation: The Role of Regional Factors in Industrial R&D in India

Pradhan

2011

SSRN Journal

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This study makes an early attempt to estimate the magnitude and intensity of manufacturing firms' R&D by Indian states during the period 1991-2008 and analyses the role of regional factors on firm-level R&D activities. As there is little research on state-wise R&D performance of firms in India, this study serves an important contribution to the academic and policy realm. It has brought out the fact the total manufacturing R&D investment in India is unevenly distributed regionally with a few states accounting for disproportionate share of it. Regional heterogeneity or inter-state disparities in R&D has increased between the 1990s and the first decade of the twenty-first century. In view of this persistent regional heterogeneity in R&D, the study has developed and estimated an empirical model for a sample of 4545 Indian manufacturing firms with R&D facilities located in single state and that explicitly includes regional factors as probable factors affecting R&D. The three-step Censored Quantitle Regression results confirm that regional factors play an important role in shaping the R&D intensity of the sample of firms. This led us to some useful policy suggestions for regional governments to promote local firms' R&D activities.

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“…3 Comparable studies here are for example Varga (2000), Audretsch and Stephan (1999a) orÓ hUallacháin and Leslie (2007) to analyze the US and the Russian innovation system 4 . While studies like Fritsch and Franke (2004), Lee and Park (2005) or Wang and Huang (2007) operate on a firm basis, this study tackles the question from a regional perspective.…”

Section: Introductionmentioning

confidence: 99%

An alternative approach towards the knowledge production function on a regional level - applications for the USA and Russia

Perret

2018

IJIRD

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThe present study picks up on the aspect of knowledge generation -a key part of every national innovation system -in the context of the USA and the Russian Federation. Following Fritsch and Slavtchev (2006) a knowledge production function can be used to account for the efficiency of an innovation systems.In detail this study provides a quantile regression estimation of the knowledge production function to account for a possible non-linear relationship between knowledge inputs and knowledge output. Using regional data for researchers, expenditures on R& D and patent grants for the USA and the Russian Federation -motivated by the results of a kernel density estimation and transition matrices -a quantile regression is performed for a basic knowledge production function design; for Russia as well for an extended design.The results show that in both countries there exist groups of regions with smaller sized research systems that report significantly different dynamics and thus knowledge production functions than regions with larger sized research systems.

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Rethinking the regional knowledge production function

Cited by 77 publications

References 35 publications

Observing regional divergence of Chinese nanotechnology centers

Observing regional divergence of Chinese nanotechnology centers

Regional Heterogeneity and Firms’ Innovation: The Role of Regional Factors in Industrial R&D in India

An alternative approach towards the knowledge production function on a regional level - applications for the USA and Russia

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