Collective Learning, Innovation and Growth in a Boundedly Rational, Evolutionary World
We formulate a simple multiagent evolutionary scheme as a model of collective learning, i.e., a situation in which firms experiment, interact, and learn from each other. This scheme is then applied to a stylized endogenous growth economy in which firms have to determine how much to invest in R&D, where innovations are the stochastic product of their R&D activity, spillovers occur, but technological advantages are only relative and temporary and innovations actually diffuse, both at the intra- and interfirm levels. The model demonstrates both the existence of a unique long-run growth attractor (in the linear case) and distinct growth phases on the road to that attractor. We also compare the long-run growth patterns for a linear and a logistic innovation function, and produce some evidence for a bifurcation in the latter case.
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Volume (Year): 4 (1994)
Issue (Month): 3 (September)
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