FIML estimates of a simultaneous equation econometric model can be obtained by iterating to convergence an instrumental variables formula that is perfectly consistent with the intuitive textbook-type interpretation of efficient instruments: instruments for an equation must be uncorrelated with...

Lecture notes for a course of Introductory Econometrics (linear regression model and ordinary least squares, including concepts of Linear Algebra and Inferential Statistics), and for a second course of Econometrics (simultaneous equations, instrumental variables, limited and full information...

When dealing with nonlinear econometric models, resort is often made to simulation techniques for the investigation of their dynamic properties. A spectral analysis using stochastic and analytic simulation is carried out on a nonlinear model of the Italian economy. The two approaces are...

In this paper, control variates are proposed to speed up Monte Carlo simulations to estimate expected error rates in multivariate classification.

Some analytic simulation techniques for the analysis of the reduced form and of the dynamic properties of econometric models are described. Comparisons are made with analytical methods available for linear models.

This manual describes the input requirements and the installation procedures of the program for stochastic simulation of econometric models, announced in Econometrica, volume 46, number 1, (January 1978). This program is available on magnetic tape, including samples (Klein-I and Klein-Goldberger...

This paper deals with methods to estimate standard errors of dynamic multipliers. These methods can be applied to nonlinear macroeconometric models, thus extending methods available in the literature for linear models.

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...