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Knowledge Production in Nanomaterials: An Application of Spatial Filtering to Regional Systems of Innovation

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  • Patuelli, Roberto
  • Grimpe, Christoph

Abstract

Nanomaterials are seen as a key technology for the 21st Century, and much is expected of them in terms of innovation and economic growth. They could open the way to many radically new applications, which would form the basis of innovative products. In this context, it seems all the more important for regions to put their own innovation systems in place, and to ensure that they offer a suitable location for such activities in order to benefit from the expected growth. Many regions have already done so by establishing ?science parks? and ?nanoclusters?. As nanomaterials are still in their infancy, both public research institutes and private businesses could play a vital role in the process. This paper investigates what conditions and configurations allow a regional innovation system to be competitive in a cutting-edge technology like nanomaterials. We analyse European Patent Office data at the German district level (NUTS-3) on applications for nanomaterial patents, in order to chart the effects of localised research and development (R&D) in the public and private sector. We estimate two negative binomial models in a knowledge production function framework and include a spatial filtering approach to adjust for spatial effects. Our results indicate that there is a significant positive effect of both public and private R&D on the production of nanomaterial patents. Moreover, we find a positive interaction between them which hints at the importance of their co-location for realising the full potential of an emerging technology like nanomaterials.

Suggested Citation

  • Patuelli, Roberto & Grimpe, Christoph, 2008. "Knowledge Production in Nanomaterials: An Application of Spatial Filtering to Regional Systems of Innovation," ZEW Discussion Papers 08-064, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  • Handle: RePEc:zbw:zewdip:7387
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    Cited by:

    1. Gianni Guastella & Frank G. van Oort, 2015. "Regional Heterogeneity and Interregional Research Spillovers in European Innovation: Modelling and Policy Implications," Regional Studies, Taylor & Francis Journals, vol. 49(11), pages 1772-1787, November.
    2. repec:zbw:rwirep:0311 is not listed on IDEAS
    3. Dirk Engel & Timo Mitze & Roberto Patuelli & Janina Reinkowski, 2013. "Does Cluster Policy Trigger R&D Activity? Evidence from German Biotech Contests," European Planning Studies, Taylor & Francis Journals, vol. 21(11), pages 1735-1759, November.
    4. Timo Mitze & Falk Strotebeck, 2012. "What Drives Regional Cooperative Behavior in German Biotechnology? Embedding Social Network Analysis in a Regression Framework," ERSA conference papers ersa12p629, European Regional Science Association.
    5. Roberto Patuelli & Andrea Vaona & Christoph Grimpe, 2010. "The German East‐West Divide In Knowledge Production: An Application To Nanomaterial Patenting," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 101(5), pages 568-582, December.
    6. repec:elg:eechap:14395_24 is not listed on IDEAS
    7. Joana Mendonça & Christoph Grimpe, 2016. "Skills and regional entrepreneurship capital formation: a comparison between Germany and Portugal," The Journal of Technology Transfer, Springer, vol. 41(6), pages 1440-1456, December.
    8. Yongwan Chun & Daniel A. Griffith & Monghyeon Lee & Parmanand Sinha, 2016. "Eigenvector selection with stepwise regression techniques to construct eigenvector spatial filters," Journal of Geographical Systems, Springer, vol. 18(1), pages 67-85, January.
    9. Janina Reinkowski, 2014. "Empirical Essays in the Economics of Ageing and the Economics of Innovation," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 53, March.
    10. Daisuke Murakami & Daniel Griffith, 2015. "Random effects specifications in eigenvector spatial filtering: a simulation study," Journal of Geographical Systems, Springer, vol. 17(4), pages 311-331, October.
    11. Mitze, Timo & Strotebeck, Falk, 2017. "Modeling interregional research collaborations in German biotechnology using industry directory data: A quantitative social network analysis," MPRA Paper 83392, University Library of Munich, Germany.
    12. James LeSage & Carlos Llano-Verduras, 2014. "Forecasting spatially dependent origin and destination commodity flows," Empirical Economics, Springer, vol. 47(4), pages 1543-1562, December.

    More about this item

    Keywords

    nanotechnology; innovation; patents; Germany; spatial autocorrelation; spatial filtering;

    JEL classification:

    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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