Equilibrium models intended to overcome limits

Abstract

This chapter will critically examine today’s common ways to build equilibrium models. These specifically include Dynamic-Stochastic General Equilibrium models, game theoretical models and empirical GE models. Each of these types of equilibrium model try to address the issues of how a model’s decision makers get the information needed to guarantee the attainment of a state of equilibrium. The chapter addresses the alleged limits of general equilibrium models (particularly the issues of dynamics, time and expectations), the current attempts to overcome the limits of general equilibrium models, and three empirical alternatives to Walrasian general equilibrium models. These alternatives include the Computable General Equilibrium models and the Applied General Equilibrium models. The third model involves building econometric models only after evaluating the statistical properties of the data before using them in the model.