City as Neural Platform - Toward New Economics of a City

We propose and develop a new conceptual framework for the economic analysis of cities, as a contribution toward a new interdisciplinary science of cities. The standard economic analysis of cities is based on a spatial market model of (production, transactional and consumption) externalities in which cities are agglomerative engines of economic growth. The new framework we propose takes the spatial agglomerative economic model as the starting point, but develops this toward: (1) a dynamic game-theoretic analysis of cities (as infrastructures and protocols) that compete for globally mobile resources, and; (2) a model of cities as two-sided markets (i.e. platforms) seeking to solve matching problems between idiosyncratic resources, (3) neural model of the city based on solving problems through information processing and learning. This suggests a new way of analyzing the mechanism underlying the economic performance of cities and potentially leads to new policy implications.