IDEAS home Printed from https://ideas.repec.org/p/usi/wpaper/473.html
   My bibliography  Save this paper

Patterns of Discovery

Author

Listed:
  • Mauro Caminati
  • Serena Sordi
  • Arsenio Stabile

Abstract

From a given directed weighted network of knowledge links between technology fields, the paper develops a multisector dynamic model of incremental innovation and R&D activity in these fields. The model is focused on the equilibrium share distribution of these variables, which is proved to be locally stable, with reference to a simple low dimensional case. Simulation methods suggest that local, and also global, stability extend to any model dimension. It is also shown how different network structures map to different asymptotic share distributions. Using the NBER patents and patent citation data files, the analytical framework is then used to analyse some general features of the pattern of knowledge creation and transfer in the period 1975-1999. From a descriptive viewpoint, the changes in the share distribution of innovation activity predicted by the model match reasonably well the actual changes in the period

Suggested Citation

  • Mauro Caminati & Serena Sordi & Arsenio Stabile, 2006. "Patterns of Discovery," Department of Economics University of Siena 473, Department of Economics, University of Siena.
  • Handle: RePEc:usi:wpaper:473
    as

    Download full text from publisher

    File URL: http://repec.deps.unisi.it/quaderni/473.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Devine, Warren D., 1983. "From Shafts to Wires: Historical Perspective on Electrification," The Journal of Economic History, Cambridge University Press, vol. 43(2), pages 347-372, June.
    2. Hall, B. & Jaffe, A. & Trajtenberg, M., 2001. "The NBER Patent Citations Data File: Lessons, Insights and Methodological Tools," Papers 2001-29, Tel Aviv.
    3. Adam B. Jaffe & Manuel Trajtenberg, 2005. "Patents, Citations, and Innovations: A Window on the Knowledge Economy," MIT Press Books, The MIT Press, edition 1, volume 1, number 026260065x, December.
    4. Pavitt, Keith, 1998. "Technologies, Products and Organization in the Innovating Firm: What Adam Smith Tells Us and Joseph Schumpeter Doesn't," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 7(3), pages 433-452, September.
    5. Martin L. Weitzman, 1998. "Recombinant Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 113(2), pages 331-360.
    6. Cowan, Robin, 2004. "Network models of innovation and knowledge diffusion," Research Memorandum 016, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    7. David, Paul A, 1990. "The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox," American Economic Review, American Economic Association, vol. 80(2), pages 355-361, May.
    8. Mauro Caminati, 2006. "Knowledge growth, complexity and the returns to R&D," Journal of Evolutionary Economics, Springer, vol. 16(3), pages 207-229, August.
    9. Stanley Reiter, 1992. "Knowledge, Discovery and Growth," Discussion Papers 1011, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mauro Caminati & Arsenio Stabile, 2010. "The Pattern Of Knowledge Flows Between Technology Fields," Metroeconomica, Wiley Blackwell, vol. 61(2), pages 364-397, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mauro Caminati & Arsenio Stabile, 2010. "The Pattern Of Knowledge Flows Between Technology Fields," Metroeconomica, Wiley Blackwell, vol. 61(2), pages 364-397, May.
    2. Mauro Caminati, 2012. "Self sustaining R&D networks," Department of Economics University of Siena 653, Department of Economics, University of Siena.
    3. Arianna Martinelli & Önder Nomaler, 2014. "Measuring knowledge persistence: a genetic approach to patent citation networks," Journal of Evolutionary Economics, Springer, vol. 24(3), pages 623-652, July.
    4. Huo, Dong & Motohashi, Kazuyuki, 2014. "Dilemma in Individual Collaboration for Invention: Should We be Similar or Diverse in Knowledge?," MPRA Paper 56185, University Library of Munich, Germany.
    5. Lone Engbo Christiansen, 2008. "Do Technology Shocks Lead to Productivity Slowdowns? Evidence from Patent Data," IMF Working Papers 2008/024, International Monetary Fund.
    6. Hopkins, Michael M. & Martin, Paul A. & Nightingale, Paul & Kraft, Alison & Mahdi, Surya, 2007. "The myth of the biotech revolution: An assessment of technological, clinical and organisational change," Research Policy, Elsevier, vol. 36(4), pages 566-589, May.
    7. Jingong Huang, 2017. "Technology Network Innovation and Distribution," 2017 Meeting Papers 24, Society for Economic Dynamics.
    8. Ufuk Akcigit & Murat Celik & Daron Acemoglu, 2014. "Young, Restless and Creative: Openness to Disruption and Creative Innovations," 2014 Meeting Papers 377, Society for Economic Dynamics.
    9. Svante Prado, 2014. "Yeast or mushrooms? Productivity patterns across Swedish manufacturing industries, 1869–1912," Economic History Review, Economic History Society, vol. 67(2), pages 382-408, May.
    10. Jeffrey Ding & Allan Dafoe, 2021. "Engines of Power: Electricity, AI, and General-Purpose Military Transformations," Papers 2106.04338, arXiv.org.
    11. Olsson, Ola, 2001. "Why Does Technology Advance in Cycles?," Working Papers in Economics 38, University of Gothenburg, Department of Economics.
    12. Aghion, Philippe & Akcigit, Ufuk & Howitt, Peter, 2014. "What Do We Learn From Schumpeterian Growth Theory?," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 2, chapter 0, pages 515-563, Elsevier.
    13. Lorenz, Steffi, 2015. "Diversität und Verbundenheit der unternehmerischen Wissensbasis: Ein neuartiger Messansatz mit Indikatoren aus Innovationsprojekten," Discussion Papers on Strategy and Innovation 15-01, Philipps-University Marburg, Department of Technology and Innovation Management (TIM).
    14. Timo Boppart & Kevin E. Staub, 2012. "Online accessibility of academic articles and the diversity of economics," ECON - Working Papers 075, Department of Economics - University of Zurich.
    15. Sergey Lychagin & Joris Pinkse & Margaret E. Slade & John Van Reenen, 2016. "Spillovers in Space: Does Geography Matter?," Journal of Industrial Economics, Wiley Blackwell, vol. 64(2), pages 295-335, June.
    16. Clifford Bekar & Kenneth Carlaw & Richard Lipsey, 2018. "General purpose technologies in theory, application and controversy: a review," Journal of Evolutionary Economics, Springer, vol. 28(5), pages 1005-1033, December.
    17. Harald Edquist & Magnus Henrekson, 2006. "Technological Breakthroughs and Productivity Growth," Research in Economic History, in: Research in Economic History, pages 1-53, Emerald Group Publishing Limited.
    18. Martinelli, Arianna, 2012. "An emerging paradigm or just another trajectory? Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry," Research Policy, Elsevier, vol. 41(2), pages 414-429.
    19. Yi Deng, 2005. "The Value of Knowledge Flows: Evidence from Patent Citations Data," Computing in Economics and Finance 2005 374, Society for Computational Economics.
    20. Martin Fiszbein, 2017. "Agricultural Diversity, Structural Change and Long-run Development: Evidence from the U.S," NBER Working Papers 23183, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    directed weighted network; knowledge spillovers; share distribution; incremental innovation and R&D dynamics; local stability; simulation; patents and patent citations;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:usi:wpaper:473. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Fabrizio Becatti (email available below). General contact details of provider: https://edirc.repec.org/data/desieit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.