HBS professor William R. Kerr and doctoral candidate Scott Duke Kominers develop a theoretical model for analyzing the forces that drive agglomeration, or industrial clustering. The model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate.
It is rare that researchers systematically observe the forces like technology sharing, customer/supplier interactions, or labor pooling that lead to firm clustering. Instead, the data only portray the final location decisions that firms make (for example, firms that utilize one type of technology are clustered over 50 miles, while those using another technology are clustered over 100 miles). The researchers’ model identifies how these observable traits can be used to infer properties of the underlying clustering forces. Key concepts include:
- Most industries exhibit spatial clustering. The paper’s framework provides a theoretical foundation for inferring properties of agglomerative forces through observed spatial concentrations of industries.
- The model demonstrates that agglomeration clusters generally cover a substantially larger area than the micro-interactions among firms upon which they build. This structure is present, for example, in the technology and labor flows in Silicon Valley.
- Agglomerative forces with longer micro-interactions are associated with fewer, larger, and less-dense clusters. These patterns are evident in both technology clusters and industrial agglomerations.
We model spatial clusters of similar firms. Our model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate. Overlapping firm interactions yield agglomeration clusters that are much larger than the underlying agglomerative forces themselves. Empirically, we demonstrate that our model’s assumptions are present in the structure of technology and labor flows within Silicon Valley and its surrounding areas. Our model further identifies how the lengths over which agglomerative forces operate influence the shapes and sizes of industrial clusters; we confirm these predictions using variations across both technology clusters and industry agglomeration.