Modern economic production and distribution are organized through supply chains, which can be represented as networks in which firms are nodes and supplier–buyer transactions are links. When a firm fails, its customers may reduce production because they lose an input, and its suppliers may also reduce production because they lose a buyer. If these disruptions spread to the customers and suppliers of affected firms, a local shock can propagate through the network. If your local bakery is closed, you can buy bread from another one —unless no other bakery can supply what you need; firms face an analogous situation when an input supplier is disrupted. Supplier replaceability is, therefore, a key component in quantifying systemic risk. In practice, detailed product-level substitution information is rarely available, so replaceability is typically approximated using economic sector classifications, which makes systemic-risk estimates sensitive to the degree of granularity in how economic activities are grouped. 

We study how a network-based measure of economic systemic risk depends on sector-classification granularity. Using the NACE hierarchy of economic activities, we examine how aggregate systemic-risk estimates change across levels of sector detail and how these estimates can be compared consistently across scales. This provides a practical framework for comparing systemic-risk estimates at different economic aggregation levels when detailed substitution data are unavailable.