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Dancing with the Stars: Innovation Through Interactions

Author

Listed:
  • Ufuk Akcigit
  • Santiago Caicedo
  • Ernest Miguelez
  • Stefanie Stantcheva
  • Valerio Sterzi

Abstract

An inventor's own knowledge is a key input in the innovation process. This knowledge can be built by interacting with and learning from others. This paper uses a new large-scale panel dataset on European inventors matched to their employers and patents. We document key empirical facts on inventors' productivity over the life cycle, inventors' research teams, and interactions with other inventors. Among others, most patents are the result of collaborative work. Interactions with better inventors are very strongly correlated with higher subsequent productivity. These facts motivate the main ingredients of our new innovation-led endogenous growth model, in which innovations are produced by heterogeneous research teams of inventors using inventor knowledge. The evolution of an inventor's knowledge is explained through the lens of a diffusion model in which inventors can learn in two ways: By interacting with others at an endogenously chosen rate; and from an external, age-dependent source that captures alternative learning channels, such as learning-by-doing. Thus, our knowledge diffusion model nests inside the innovation-based endogenous growth model. We estimate the model, which fits the data very closely, and use it to perform several policy exercises, such as quantifying the large importance of interactions for growth, studying the effects of reducing interaction costs (e.g., through IT or infrastructure), and comparing the learning and innovation processes of different countries.

Suggested Citation

  • Ufuk Akcigit & Santiago Caicedo & Ernest Miguelez & Stefanie Stantcheva & Valerio Sterzi, 2018. "Dancing with the Stars: Innovation Through Interactions," NBER Working Papers 24466, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:24466
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    References listed on IDEAS

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    1. Michele Pezzoni & Francesco Lissoni & Gianluca Tarasconi, 2014. "How to kill inventors: testing the Massacrator© algorithm for inventor disambiguation," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 477-504, October.
    2. Raffo, Julio & Lhuillery, Stéphane, 2009. "How to play the "Names Game": Patent retrieval comparing different heuristics," Research Policy, Elsevier, vol. 38(10), pages 1617-1627, December.
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    Citations

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    Cited by:

    1. MORI Tomoya & SAKAGUCHI Shosei, 2018. "Collaborative Knowledge Creation: Evidence from Japanese patent data," Discussion papers 18068, Research Institute of Economy, Trade and Industry (RIETI).
    2. Hiroyasu Inoue & Kentaro Nakajima & Yukiko Umeno Saito, 2019. "Localization of collaborations in knowledge creation," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 62(1), pages 119-140, February.
    3. Asier Minondo, 2020. "Who presents and where? An analysis of research seminars in US economics departments," Papers 2001.10561, arXiv.org.
    4. Lars Hornuf & Sabrina Jeworrek, 2018. "Crowdsourced Innovation: How Community Managers Affect Crowd Activities," CESifo Working Paper Series 7153, CESifo Group Munich.
    5. Hornuf, Lars & Jeworrek, Sabrina, 2018. "Crowdsourced innovation: How community managers affect crowd activities," IWH Discussion Papers 13/2018, Halle Institute for Economic Research (IWH).
    6. Santiago Caicedo, 2019. "Note on Idea Diffusion Models with Cohort Structures," Economica, London School of Economics and Political Science, vol. 86(342), pages 396-408, April.
    7. Favaro, Donata & Ninka, Eniel, 2019. "Inventors’ working relationships and knowledge creation: a study on patented innovation," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 45, pages 55-76.
    8. Ufuk Akcigit & John Grigsby & Tom Nicholas & Stefanie Stantcheva, 2018. "Taxation and Innovation in the 20th Century," NBER Working Papers 24982, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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