A well known macroeconometric model of the Italian economy is updated to produce forecasts at 1974.

In nonlinear econometric models, the evaluation of forecast errors is usually performed, completely or partially, by resorting to stochastic simulation. However, for evaluating the specific contribution of errors in estimated structural coefficients, several alternative methods have been...

The numerical example which completes the paper by Goldberqer, Nagar and Odeh, on the estimated asymptotic covariance matrix of the reduced form coefficients for the Klein-I model estimated by Two Stage Least Squares (2SLS), has led to some misinterpretations of the properties of the model. In...

This paper describes some analytic simulation experiments performed on a nonlinear macroeconometric model of the Italian economy. The proposed techniques extend to nonlinear models methods that are available, in the literature, for linear econometric models. The results can be profitably used...

Markov Switching models have been successfully applied to many economic problems. The most popular version of these models implies that the change in the state is driven by a Markov Chain and that the state is an exogenous discrete unobserved variable. This hypothesis seems to be too...

This paper is concerned with the contribution to forecast errors of errors in the estimated structural coefficients of a macro-econometric model (simultaneous equations). Its main purpose is to perform, on several "real-world" models, an empirical comparison of alternative techniques available...

In econometric models specified as systems of simultaneous equations, forecast errors can be regarded as random variables whose variances can be investigated, analyzed and estimated. This book summarizes results available in the literature for linear and nonlinear econometric models, when...

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,...

The drawbacks of predictors 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...