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...

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.

We propose to combine smoothing, simulations and sieve approximations to solve for either the integrated or expected value function in a general class of dynamic discrete choice (DDC) models. We use importance sampling to approximate the Bellman operators defining the two functions. The random...

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...

In this paper, we examine techniques for the analytical and numerical solution of statedependent differential-difference equations. Such equations occur in the continuous time modelling of vintage capital growth models, which form a particularly important class of models in modern economic...

The paper presents an algorithm that solves two-point boundary-value problems that arise in economic control models in continuous time with an infinite time horizon and several state variables. The algorithm can determine optimal trajectories that converge to an isolated equilibrium point. It...

With constrained portfolios, contingent claims do not generally have a unique price, for which there are no arbitrage opportunities. We generalize earlier results of El Karoui and Quenez (1995) and Cvitanic and Karatzas (1993) by showing that there is an interval of no-arbitrage prices, when...

A new algorithm is developed to solve models with heterogeneous agents and aggregate uncertainty that avoids some disadvantages of the prevailing algorithm that strongly relies on simulation techniques and is easier to implement than existing algorithms. A key aspect of the algorithm is a new...

This chapter is concerned with numerical simulation of dynamic economic models. We focus on some basic algorithms and study their accuracy and stability properties. This analysis is useful for an optimal implementation and testing of these procedures, as well as to evaluate their performance....

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...