In this article, we seek to shed new light on the sources of industrial leadership and catch-up in science-based industries. We propose an evolutionary model that incorporates scientists' training and migration, endogenous R&D decisions, and the possibility of funding capital accumulation through debt. The analysis of the model allows us to characterize a robust pattern of industrial catch-up. Likewise, the sensitivity analysis shows which parameters act as pro-catch-up factors or slow down the process. The identification of stationary-state conditions of the model helps us to interpret the simulations, and highlights crucial interactions between technology-supporting institutions and market demand at the basis of industrial catch-up. Finally, the robustness analysis reveals further interdependencies among innovation, scientist mobility, and demand. Copyright 2012 The Author 2011. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved., Oxford University Press.
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