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 estimation method of Two Stage Least Squares (2SLS) with Principal Components (2SPC) is applied to a medium-sized nonlinear econometric model of the Italian Economy.

Experiments of stochastic simulation on a nonlinear macroeconometric model are described in this paper. The results are used both for improving the validation of a model of the Italian economy and for revisiting the heuristic value of the stochastic simulation methodology.

This paper presents a Monte-Carlo study on the practical reliability of numerical algorithms for FIML-estimation in nonlinear econometric models. The performance of different techniques of Hessian approximation in trust-region algorithms is compared regarding their "robustness" against "bad"...

This paper is a survey (in Italian) of the estimation methods for econometric systems of nonlinear simultaneous equations

Starting from a consistent and asymptotically normally distributed structural estimate of a dynamic econometric model, this paper provides an analytical derivation of the asymptotic distribution of spectra and cross spectra of the jointly dependent variables. A numerical example is provided on...

For some structural econometric models, the contribution of the off-diagonal blocks of the coefficients covariance matrix to the asymptotic standard errors of multipliers and forecasts is empirically evaluated.

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...

This article describes the application to an operational medium-size econometric model, mini-DMS, of methods associating, to deterministic forecasts, a measure of the uncertainty due to the stochastic nature of behavioural equations. After having described the theoretical and practical...