Co-evolutionary patterns of GVC-trade and knowledge flows in the mining industry

Although evolutionary economics has extensively analyzed the evolution of industries in relation to innovation and technology lifecycles, the interplay between industry lifecycles and evolutionary patterns of knowledge networks has not been fully explored yet. This work aims to bridge this gap by analyzing the co-evolutionary patterns of knowledge and trade flows in the mining industry, using social network tools in combination with the Schumpeterian tradition of analysis. The study focuses on three Latin American countries: Brazil, Chile, and Peru, where the mining sector plays a significant role in the economy, particularly in the context of energy and digital transitions. Our findings suggest that the innovation network and the global value chain-trade network display divergent co-evolutionary patterns: while the former tends to be stable and concentrated, the latter shows increasing fragmentation and turbulence. The analysis also shows remarkable evolutionary evidence at the country level.