AbstractThis paper studies the dynamics of fundamental research. We develop a simple model where researchers allocate their effort between improving existing fields and inventing new ones. A key assumption is that scientists derive utility from recognition from other scientists. We show that the economy can be either in a regime where new fields are constantly invented, and then converges to a steady state, or in a cyclical regime where periods of innovation alternate with periods of exploitation. Our analysis provides a rigorous foundation to the Kuhnian theory of scientific evolution. We show that scientists' care for reputation has a strong impact on research dynamics and tends to favor innovation. Especially, innovation fads may emerge. We also study welfare and find that the academic reputational reward system can help align scientists' short-term incentives with society's long-term interests.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Theory.
Volume (Year): 145 (2010)
Issue (Month): 5 (September)
Contact details of provider:
Web page: http://www.elsevier.com/locate/inca/622869
Research dynamics Innovation cycles Scientific fads;
Other versions of this item:
- Bramoullé, Yann & Saint-Paul, Gilles, 2010. "Research Cycles," Open Access publications from University of Toulouse 1 Capitole http://neeo.univ-tlse1.fr, University of Toulouse 1 Capitole.
- Yann Bramoullé & Gilles Saint-Paul, 2007. "Research Cycles," Cahiers de recherche 0704, CIRPEE.
- Bramoullé, Yann & Saint-Paul, Gilles, 2007. "Research Cycles," CEPR Discussion Papers 6075, C.E.P.R. Discussion Papers.
- Bramoullé, Yann & Saint-Paul, Gilles, 2006. "Research Cycles," IDEI Working Papers 422, Institut d'Économie Industrielle (IDEI), Toulouse.
- O39 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Other
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
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