Tracing the Path from Science to Technology

The transfer of scientific knowledge to technology is a fundamental driver of economic growth. For this reason, the interactions between scientific and technological (S&T) activities have long been of interest to economists, and there are reasons to believe that enhancing our understanding of such interactions is increasing in importance. For instance, despite the emergence of new major technologies such as Artificial Intelligence, productivity growth is stagnating. This points to a possible new productivity paradox, where a stronger capacity to translate scientific findings into productive technological change may still be needed. However, there are few data sources available for empirical investigations. In this project we develop a new large-scale database that singles out scientific articles cited in patent documents – Non-Patent Literature (NPL) citations – and links them with scientific article bibliographic information (SNPL data). These citations reveal a close technological relatedness of patented inventions with scientific articles and can therefore be used to study S&T interactions.