Exploring the Unknown on Entrepreneurship, Coordination and Innovation Driven Growth

Notwithstanding the revival of attention recently displayed by the economic discipline about self-sustained processes of economic growth fueled by technological advances, an enormous gap still remains between what we historically know about technical change and its economic exploitation, on the one hand, and the ways we represent them in formal growth models, on the other. Building on some general properties of the empirical patterns of innovation and diffusion that seem to be neglected in a good deal of contemporary growth literature, we present a stylized computer-simulated model in which self-sustained growth appears as the outcome of a coordination process among heterogeneous agents locally interacting in a decentralized economy characterized by: (i) notionally endless opportunities of endogenously introducing innovations; (ii) path-dependency in learning achievements; (iii) dynamic increasing returns grounded upon collectively shared 'learning paradigms'. By means of extensive Montecarlo-like studies, we show that the model is able to generate GNP time-series exhibiting the statistical properties displayed by empirically observable data. Finally, we show simple but quite general settings in which collective economic growth finds its necessary condition in the presence of a number of 'irrationally' entrepreneurial agents.