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A model of innovation and learning with involuntary spillovers and absorptive capacity

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  • Mário Alexandre Patrício Martins Da Silva

Abstract

We develop a model of innovation and learning that incorporates explicitly the need for a firm to conduct its own research and development (R&D) in order to realize involuntary spillovers from other firms’ R&D activity and the development of absorptive capacity of research firms over time. The conclusions of the model follow directly from the functional forms that are used to describe the generation and absorption of technological knowledge. The first proposition formally characterizes the steady-state rate of growth of technology for the model. The analysis also shows how some of the key features of two distinct, pure modes of organization of the production of new knowledge, the R&D model and the new localized knowledge model, are implied by our model by simply drastically changing the relative magnitude of two exogenous parameters: the ease of learning and the pace of knowledge advance. The second proposition formally characterizes the connections implied by the model between involuntary spillovers and absorptive capacity. Analysis of the long-term interactions between involuntary spillovers of knowledge and absorptive capacity provides the essential insights into an understanding of the elements of a self-sustained process of endogenous growth. The third and last formal proposition of this paper accommodates firm-level arguments and the crucial role of a firm's absorptive capacity in taking advantage of its location in clusters, as implied by the theoretical model.

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  • Mário Alexandre Patrício Martins Da Silva, 2012. "A model of innovation and learning with involuntary spillovers and absorptive capacity," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 21(7), pages 613-630, October.
  • Handle: RePEc:taf:ecinnt:v:21:y:2012:i:7:p:613-630
    DOI: 10.1080/10438599.2011.606644
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    1. Antonelli, Cristiano, 2001. "The Microeconomics of Technological Systems," OUP Catalogue, Oxford University Press, number 9780199245536.
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