This article presents an original spatial methodology based on a network analysis approach in order to identify and to track spatial similarities among economic activities as well as to analyse their interdependence. Traditionally, such interdependence is analysed using input-output matrices (IO) that track economic flows across sectors. However, models based on IO do not allow to analyse spatial interdependence. In our approach, instead, we make use of local employment patterns. In particular, using sectoral employment of 8091 Italian municipalities across 18 economic activities, our approach allows to identify spatial inter-linkages in terms of employment patterns. By comparing such local employment patterns, our methodology shows inter-linkages among activities, which are important for understanding the transmission of exogenous shocks. Our analysis highlights similarities among economic activities, and allows to identify central activities (hubs) and their relationship with each other. Moreover, simulating the spread of an exogenous shock through the economic structure allows us to identify important activities not only in economic terms but also in terms of centrality and connectivity.
Network analysis local employment patterns business cycles financial sector spatial economic analysis