Causal Inference in Network Economics
This work addresses the challenge of causal analysis in complex network systems for researchers and practitioners, but it appears incremental as it builds on existing formalisms.
The paper tackles the problem of applying causal inference to network economics, such as traffic management and online marketplaces, by developing a framework that synthesizes variational inequalities with causal principles, though no concrete results or numbers are provided.
Network economics is the study of a rich class of equilibrium problems that occur in the real world, from traffic management to supply chains and two-sided online marketplaces. In this paper we explore causal inference in network economics, building on the mathematical framework of variational inequalities, which is a generalization of classical optimization. Our framework can be viewed as a synthesis of the well-known variational inequality formalism with the broad principles of causal inference