Urban spatial pattern as self-organizing system: An empirical evaluation of firm location decisions in Cleveland–Akron PMSA, Ohio

Economic models of urban spatial patterns have largely ignored complexity as an attribute of urban systems. Complexity theorists on the other hand have not made sufficiently serious and sustained attempts to verify empirically the relevance of complex systems models for urban spatial patterns. This research bridges this gap by simulating the evolution of an urban employment pattern as a self-organizing complex system and seeking its empirical validation. It estimates the model’s parameters by using firm data aggregated to the level of municipalities in Cleveland-Akron Consolidated Metropolitan Statistical Area in Ohio. The interaction among four parameters, forces of attraction and dispersion and their respective rates of dissipation with distance, are modeled as a two-dimensional complex system. The research compares the states of the modeled system with empirical data to present viable methods for verification, calibration and validation of such models.