This paper develops a formal framework based on multivariate spectral techniques for assessing the performance of multivariate dynamic models whose solution is approximated through simulation. The approach is especially suitable for models that focus on a particular frequency range , such as...

This paper develops a formal framework based on multivariate spectral techniques for assesssing the performance of multivariate dynamic models whose solution is approximated through simulation. The approach is especially suitable for models that focus on a particular frequency range , such as...

New results in the asymptotic theory of Markov processes are applied to analysis of the long-run behaviour exhibited by optimal growth models with unbounded productivity shock. The techniques developed here are geometrically intuitive, and are shown to imply global stability for a popular model...

SETSTOCH is a tool for linking Algebraic Modeling Languages with Specialized Stochastic Programming Solvers. Its main role is to retrieve from the modeling language a dynamically ordered core model (baseline scenario) that is then sent automatically to the Stochastic Solver. The user is thus...

In this article, the authors put forward another viewpoint which shows how a "small noise" (which may be Gaussian) can cause great fluctuations because of the unstable structure of the model skeleton (i.e. its deterministic part) and whihc permits nevertheless to undertake forecast methods in...

This paper discusses the intellectual origins of the so-called 'new economic geography' and provides its basic insights by means of a streamlined framework which stresses the generality of their implications.

A robust principal component analysis can be easily performed by computing the eigenvalues and eigenvectors of a robust estimator of the covariance or correlation matrix. In this paper the authors derive the influence functions and the corresponding asumptotic variances for these robust...

Bergin and Lipman (1996) show that the refinement effect from the random mutations in the adaptive population dynamics in Kandori, Mailath and Rob (1993) and Young (1993) is due to restrictions on how these mutation rates vary across population states. We here model mutation rates as...

Five decades ago, Bhattacharyya established a series of lower bounds for the variance of an unbiased estimator, since then called the Bhattacharyya bounds. In 1974 Blight and Rao have shown that the series of Bhattacharyya bounds converges to the variance of the best unbiased estimator. In this...