The study of location and co-location of economic activities lies at the heart of economic geography and related disciplines, but the indices used to quantify these patterns are often defined ad hoc and lack a clear statistical foundation.

We propose a statistical framework to quantify location and co-location associations of economic activities using information-theoretic measures. We relate the resulting measures to existing measures of revealed comparative advantage, localization, specialization and co-agglomeration and show how different measures derive from the same general framework. To support the use of these measures in hypothesis testing and statistical inference, we develop a Bayesian estimation approach to provide measures of uncertainty and statistical significance of the estimated quantities.

We illustrate this framework in an application to an analysis of location and co-location patterns of occupations in US cities.

A. van Dam, A. Gomez-Lievano, F. Neffke, K. Frenken, An information-theoretic approach to the analysis of location and co-location patterns, Journal of Regional Science (2022).