Five alternative techniques have been applied to measure the degree of uncertainty associated with the forecasts produced by a macro-model of the French economy, the Mini-DMS developed at INSEE. They are bootstrap, analytic simulation on coefficients, Monte Carlo on coefficients, parametric...

In this paper, a package implemented at the Scientific Center of IBM Italy in Pisa for the stochastic simulation of linear and non-linear econometric models is presented. After a survey on the adopted methodologies, the input requirements and the produced output are described in some details,...

We introduce an algorithm for solving dynamic economic models that merges stochastic simulation and projection approaches: we use simulation to approximate the ergodic measure of the solution, we construct a fixed grid covering the support of the constructed ergodic measure, and we use...

The stochastic simulation of an econometric model is an application of Monte Carlo methods. Deterministic simulation is performed setting error terms to zero. Stochastic simulation, on the contrary, takes into account the disturbance terms, solving the model after adding a vector of...

It is purpose of this paper to evidence, in the behaviour of the Mini-DMS model for the French economy, some stochastic properties which may confirm, strengthen or sometimes contradict the results obtained from the standard simulation analysis, which is purely deterministic. In particular, the...

We use the stochastic simulation algorithm, described in Judd, Maliar and Maliar (2009), and the cluster-grid algorithm, developed in Judd, Maliar and Maliar (2010a), to solve a collection of multi-country real business cycle models. The following ingredients help us reduce the cost in...

The drawbacks of forecasts obtained with the usual deterministic solution methods in nonlinear systems of stochastic equations have been widely investigated in the literature. Most of the proposed therapies are based on some estimation of the conditional mean of the endogenous variables in the...

Several methods have been proposed in the last few years for evaluating uncertainty in forecasts produced by nonlinear econometric models. Some methods resort to Monte Carlo, while others resort to different simulation techniques. This work aims at comparing these methods by means of experiments...

Несмотря на ожидаемую нехватку пригодных для расширения сельскохозяйственного производства земель в мире, процессы забрасывания сельскохозяйственных земель...