A new algorithm is developed to solve models with heterogeneous agents and aggregate uncertainty. Projection methods are the main building blocks of the algorithm and – in contrast to the most popular solution procedure – simulations only play a very minor role. The paper also develops a new...

This paper provides a general framework for the quantitative analysis of stochastic dynamic models. We review the convergence properties of some numerical algorithms and available methods to bound approximation errors. We then address the convergence and accuracy properties of the simulated...

This paper introduces a behavioural model and an algorithm that allow define classes of investors and draw the size each of them from financial data. The nonparametric pricing kernel estimated from stocks and options quotes allows to derive an estimate of the market utility. At the micro level...

We derive the well-known continuity principle for adjoint variables for preannounced or anticipated changes in parameters for continuoustime, infinite-horizon, perfect foresight optimization models. For easy and intuitive numerical computation of the resulting multi point boundary value problem...

We derive the well-known continuity principle for adjoint variables for preannounced or anticipated changes in parameters for continuous-time, infinite-horizon, perfect foresight optimization models. For easy and intuitive numerical computation of the resulting multi point boundary value problem...

This article deals with practical problems of fitting empirical data with generalized lambda distribution. Given method based on moment matching is illustrated on a practical example.