This paper presents a new method for identifying industry clusters. It draws on network analysis theory and relies on regional input-output tables as the information source. The methodology can be divided into two main blocks, data reduction and network partitioning. Data reduction starts by representing industries and products/services flows as a directed graph, where the links are represented as arrows indicating the flows directions. Based on several assumptions about how industries are related into a supply chain, the initial graph is transformed into an undirected graph by deriving relative weights from products/services flows. The second reduction is formulated as a minimization problem, resulting in a minimum spanning tree (MST) for a subset of the initial graph edges. The final clusters are obtained through selective deletions of edges in the MST, such that, each cluster contains a core industry.
HouSI: A heuristic for the delimitation of housing submarkets and price homogeneous areas
Python library with spatially constrained clustering algorithms
Interactive tool for visualizing the interindustry dynamics in Colombian economy.
The Center for Urban and Environmental Studies, Urbam, is a new RiSE's partner. Interesting projects are coming!
Doctor Xinyue Ye, a RiSE’s academic affiliate, was awarded the Regional Development and Planning (RDPSG) Emerging Scholar by the Association of American Geographers (AAG).
The VI World Conference of the Spatial Econometrics Association (SEA) Conference in Latin America
