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...

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...

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...

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...

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...

The setup of our study is the Principal Component Analysis for dependent Hilbert space valued random vectors with examples taken from the ARH (1) model. We prove that convergence rates of the j ^(th) empirical random projection operator II from n to j for almost sure convergence and convergence...

The aim of this paper is to relate some recent results on Levy processes (see Schoutens and Teugels, 1998) to a recent study of the author (1996) on multidimensional natural exponential families. In this way, we consider a natural construction of Sheffer polynomials associated to a d-dimensional...