The article examines different types of equilibrium models and their limitations. It discusses Dynamic-Stochastic General Equilibrium models, game theoretical models, and empirical GE models. The main focus is on how decision makers in these models obtain the necessary information for achieving equilibrium. The article also explores the challenges of dynamics, time, and expectations in general equilibrium models. It presents three alternative models, including Computable General Equilibrium models and Applied General Equilibrium models. Another approach involves creating econometric models based on the statistical properties of the data.