Innovation, catch-up, and leadership in science-based industries

Abstract

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