Causal Inference in Network Economics

TL;DR

This paper introduces a novel framework combining variational inequalities with causal inference to analyze equilibrium problems in network economics, applicable to diverse real-world systems.

Contribution

It develops a new mathematical approach that integrates variational inequalities with causal inference principles for network economic models.

Findings

Framework unifies variational inequalities and causal inference

Applicable to traffic, supply chains, and online marketplaces

Provides new tools for causal analysis in network systems

Abstract

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