For multivariate datasets with missing values, we present a procedure of statistical inference and state its "optimal" properties. Two main assumptions are needed: (1) data are missing at random (MAR); (2) the data generating process is a multivariate normal linear regression. Disentangling the...

Given a set of continuous variables with missing data, we prove in this paper that the iterative application of a simple “least-squares estimation/multivariate normal simulation” procedure produces an efficient parameters estimator. There are two main assumptions behind our proof: (1) the...

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 paper presents an interactive computer package to handle and process economic data organized as time series. It is expected to provide help and great benefits to econometric model builders.

In this paper the results of six different estimation methods appliead to a linear aggregated model of the Italian economy are at first displayed. Afterwards, the inherent dynamic characteristics and the simulation properties of the six sets of estimates are analyzed. In no case the obtained...

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"...