Economic complexity as tool to assess the territorial development: a novel empirical approach inspired by network theory applied to patent data

The economic and fitness complexity (EFC), a novel approach in economic geography and innovation studies, is a data-driven empirical method that applies complex systems and network theory techniques. It is adept at analyzing high-dimensional data using bipartite graphs and dimensionality reduction methods, providing detailed insights into economic activities. These techniques help uncover latent patterns and relationships in economic activities. The EFC method plays a crucial role in assessing the complexity of patents and the economic diversification ability of municipalities in investing in advanced technologies. Hence, EFC’s framework offers new insights into economic complexity and innovation systems. The paper presents an analysis of Italian patents in 2021–2023 at the NUTS3 level, combining with patent information and economic sectors, following the International Patent Classification and the Italian one on ATECO codes. Patent data are a key indicator of technological innovation analysis. The analysis of the fitness distribution of Italian municipalities points out a significant disparity between the northern and southern regions. In northern Italy, many municipalities, including smaller ones, exhibit good fitness index values, indicating a more widespread distribution of economic capabilities in the northern regions compared to the south. The further objective of the work was to describe the level of innovation of municipalities through patents and to understand whether this process identifies municipalities and areas that already fall within industrial districts