Complexity and smart specialization: Comparing and evaluating knowledge complexity measures for European city-regions

Recent work in economic geography posits that regional diversification into related and complex knowledge fields boosts innovative output and economic development. While the theoretical arguments on the importance of complex knowledge creation for regional development are widely accepted and scholars have started using measures of knowledge complexity to inform policy decisions in the context of the EU’s smart specialization programme, the application of the theoretical concept to regional development policy raises a number of questions: First, what concept of knowledge complexity should be employed for policy analysis? Second, how is complexity operationalized empirically? Third, which
alternative empirical operationalization of knowledge complexity should be used for policy purposes? This paper offers the first systematic comparison of three theoretically sound measures of knowledge complexity and related 48 empirical operationalizations of those three complexity indices based on regional patent data from 1996-2017 for a consistent set of 197 European metropolitan regions. The results show that the choice of complexity measure and emprical operationalization produces widely varying results and that more theoretical and conceptual work on knowledge complexity is required before it can be employed widely for policy purposes, and in particular, to inform smart specialization policies.