The present paper makes a contribution to fill in a gap left open by dynamic theory and evolutionary economics as well. While the "closed loop" dynamic theory has explanation power in analyzing evolving economic systems at the price of neglecting the possible occurrence of non anticipated...

The present paper makes a contribution to fill in a gap left open by dynamic theory and evolutionary economics as well. While the "closed loop" dynamic theory has explanation power in analyzing evolving economic systems at the price of neglecting the possible occurrence of non anticipated...

We propose a nonparametric approach to multiple calibration of numerical general equilibrium models, where counterfactual equilibria are solutions to the Walrasian inequalities. We present efficient approximation schemes for deciding the solvability of Walrasian inequalities

A theory of general economic equilibrium with incomplete financial markets is developed with many new features, including currency-denominated prices which enable treatment of currency-based derivative instruments and collateralized contracts. Prices in such models with standard market structure...

This paper derives a second-order approximation to the solution of rational expectations, dynamic, general equilibrium models. To illustrate its applicability, the method is used to solve the dynamics of a simple neoclassical model. The paper closes with a brief description of a set of MATLAB...

We analyze the theoretical moments of a nonlinear approximation to real business cycle model with stochastic volatility and recursive preferences. We find that the conditional heteroskedasticity of stochastic volatility operationalizes a time-varying risk adjustment channel that induces...

A general and practical competitive market model for trading indivisible goods is introduced. There are a group of buyers and a group of sellers, and several indivisible goods. Each buyer is initially endowed with a sufficient amount of money and each seller is endowed with several units of each...