The maximum entropy methodology is applied to the Schelling model of urban segregation in order to obtain a reliable prediction of the stable configuration of the system without resorting to numerical simulations. We show that this approach also provides an implicit equation describing the...

An information-theoretic thought experiment is developed to provide a methodology for predicting endowment distributions in the absence of information on agent preferences. The allocation problem is first presented as a stylised knapsack problem. Although this knapsack allocation is intractable,...

An information-theoretic thought experiment is developed to clarify why the maximum entropy methodology is appropriate for predicting the equilibrium state of economic systems. As a first step, object allocation problems, modeled as knapsack problems, are shown to be equivalent to congestion...

The present paper aims to test a new model comparison methodology by calibrating and comparing three agent-based models of financial markets on the daily returns of 18 indices. The models chosen for this empirical application are the herding model of Gilli & Winker, its asymmetric version by...

The paper proposes a new algorithm for finding the confidence set of a collection of forecasts or prediction models. Existing numerical implementations for finding the confidence set use an elimination approach where one starts with the full collection of models and successively eliminates the...

The maximum entropy methodology is applied to the Schelling model of urban segregation in order to obtain a reliable prediction of the stable configuration of the system without resorting to numerical simulations. We show that this approach also provides an implicit equation describing the...