Stochastic simulation with antithetic variates is used to evaluate the bias of deterministic simulation in nonlinear econometric models. Application to the Klein-Goldberger model exemplifies the potentiality of the method.

Results of stochastic simulation experiments are described in this paper. The model experimented with is a large scale macroeconometric model, developed at the University of Bonn for the German economy (Model 5).

Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for estimating stochastic differential equations. They adjust for the bias (inconsistency) caused by discretization of the underlying stochastic process, which is in continuous time. The...

The importance of the simulation (both deterministic and stochastic) in the validation process of a non linear econometric model is underlined. Synthetic results of a large set of simulations on a non linear model of the Italian economy are presented. The benefits and the risks of the stochastic...

The problem of deriving asymptotic statistical properties of impact multipliers from a consistent estimate of a structural non-linear econometric model is discussed. The theoretical aspects, which generalize the results derived by Goldberger, Nagar and Odeh for linear models, are analyzed in...

The estimator of the coefficient covariance matrix proposed in White (1982) can be used to robustify the classical Wald test. Sampling experiments recently performed on linear regressions and simultaneous equation models, however, suggest that such an estimator tends to underestimate the...

Through Monte Carlo experiments, this paper compares the performances of different gradient optimization algorithms, when performing full information maximum likelihood (FIML) estimation of econometric models. Different matrices are used (Hessian, outer products matrix, GLS-type matrix, as well...

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...

Experiments of stochastic simulation on a macro model of the Italian economy; this paper describes the first results produced by the research team.

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...