Causal dynamic effects in regional systems of technological activities: a SVAR approach

摘要

This paper analyzes the causal relationships in regional technological systems within a structural vector autoregression framework. Applying a data-driven independent component analysis, it shows how the regional dynamics of economic, research, innovation and educational activities affect each other instantaneously and over time. By matching differently classified data on employees, patents and graduates, the analysis is based on a unique database which embraces multi-dimensional aspects for five clearly separated industries. The findings on how industry specific growth processes unfold are explained by referring to the type of industry and its knowledge base. For instance, it is found that more engineering-oriented industries like machine tools show a success-driven pattern, whereas science-based industries show a stronger dependence on universities. Such knowledge on the causal relations is of utmost relevance to the design and implementation of policy instruments.