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- GIORGIO PAULETTO
- 1998

The simulation of large macroeconometric models containing forward-looking variables can become impractical when using exact Newton methods. The diiculties generally arise from the use of direct methods for the solution of the linear system in the Newton step. In such cases, nonstationary iterative methods, also called Krylov methods, provide an interesting… (More)

- GIORGIO PAULETTO
- 1997

In this paper, diierent strategies to exploit the sparse structure in the solution techniques for macroeconometric models with forward-looking variables are discussed. First, the stacked model is decomposed into recursive submodels without destroying its original block pattern. Next, we concentrate on how to eeciently solve the sparse linear system in the… (More)

- M Gilli, G Pauletto, M Garbely
- 1992

The ordering of the equations for a nonlinear model plays an important role in the performance of solution algorithms using iterative processes. The paper comments on what is often referred to be an optimal ordering.

- Hugo Benitez-Silva, Michael Boozer, +4 authors Amy Chasse
- 2002

This paper presents one of the first formal dynamic models of job search by older individuals. It also presents an empirical analysis of job search behavior among this population using the Health and Retirement Study. Several factors currently compound to make the topic of this research an important one in the agenda of the Economics of Aging: ongoing… (More)

- Giorgio Pauletto
- NAA
- 2000

Monte Carlo (MC) methods have proved to be flexible, robust and very useful techniques in computational finance. Several studies have investigated ways to achieve greater efficiency of such methods for serial computers. In this paper, we concentrate on the parallelization potentials of the MC methods. While MC is generally thought to be “embarrassingly… (More)

- Hugo Benı́tez-Silva, Günter J. Hitsch, Giorgio Pauletto, John Rust
- 2000

We compare alternative numerical methods for approximating solutions to continuous-state dynamic programming (DP) problems. We distinguish two approaches: discrete approximation and parametric approximation. In the former, the continuous state space is discretized into a finite number of points N, and the resulting finite-state DP problem is solved… (More)

- Erricos John, Olivier Besson, +12 authors Martin Buecker
- 2000

S Financial networks Anna Nagurney, University of Massachusetts, USA In this tutorial we discuss models, qualitative properties, as well as algorithms for the study and computation of a variety of nancial equilibrium problems which can be visualized as network problems. In particular, we identify the network structure of the individual portfolio… (More)

- Manfred Gilli, Giorgio Pauletto
- IJHPCA
- 1993

This paper investigates parallel solution methods to simulate large-scale macroeconometric models with forward-looking variables. The method chosen is the Newton-Krylov algorithm. We concentrate on a parallel solution to the sparse linear system arising in the Newton algorithm, and we empirically analyze the scalability of the GMRES method, which belongs to… (More)

This paper examines how design thinking and serious games approaches can be used to support participation through the analysis of three case studies. Indeed we will analyze these approaches in three different contexts: (i) a state-owned multi-utilities company; (ii) a political party; (iii) an information system strategic committee. Our analysis framework… (More)