A package for analytic simulation of econometric models

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.Econometric models; structural form; reduced form; analytic simulation; stochastic simulation; impact multipliers; dynamic multipliers; forecast errors; asymptotic standard errors

Simulation properties of alternative methods of estimation: an application to a model of the Italian economy

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 results show a clear cut prevalence of one estimation method on the others, at least as far as the used indicators are concerned.Econometric models; estimation methods; simulation

Monte Carlo methods in econometrics: a package for the stochastic simulation

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, using as a sample the Klein model-l. To finish, the performances of the program are analyzed in terms of storage requirements and computation time.Monte Carlo; econometric models; stochastic simulation

Interactive management of time series

The main purpose of this data base is to offer the researcher a supply of information which can be analyzed, revised and updated in a repetitive way. This can be accomplished by an interactive approach. It is possible to use data from the central file (official data) and from a private single user file. It is possible to write regression equations, as well as algebraic expressions defining transformations of the economic variables.Economic data base; interactive access; transformation of variables; regression analysis

Divergences in the results of stochastic and deterministic simulation of an Italian non linear econometric model

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 simulation are discussed, with particular emphasis on the problem of the existence of divergences in the results of the two methods of simulation.Stochastic simulation; nonlinear econometric model; divergences of results; model of the Italian economy

The asymptotic distribution of impact multipliers for a non-linear structural econometric model,

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 detail, as well as the numerical (computational) aspects. Numerical results are finally displayed for an econometric model well known in the literature.Asymptotic standard errors; impact multipliers; econometric models

Some results on the stochastic simulation of a nonlinear 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.Stochastic simulation; macroeconometric model; Italian economy

Interactive management of time series

At tbe IBM Pisa Scientific Center an interactive package has been developed under CP-67/CMS, which is particularly helpful when the data to be processed are time series. The interactive facilities of the operating system CP-67/CMS are strenghtened in such a way as to allow an easy interactive correction procedure during the execution of any command. The central file of time series data is available to be interactively shared among several users. Each user can also keep and use her/his own private series. Time series can have annual, semestral, quarterly or monthly entries. Arithmetic, algebraic and trigonometric operators, special operators - mean, variance, maximum, minimum, lagging, variation rate, first difference and selection of a part of a series - are supplied for interactive use. When applied to a time series, monadic operators - logarithm, exponential, etc - return a new series with different numeric data. When applied to two time series with the same periodicity (e.g. both with annual data, etc) dyadic operators - mm, subtraction, etc - return a new series referring to the period common to both the original series. Three interactive methods of estimation are supplied: ordinary least squares (OLS), two stage least squares (TSLS), limited information single equation (LISE). Correlation matrix and graphic plotting routines are provided. In addition it is easy for users with some experience of computer processing to insert special functions in the IMTS environment.Interactive programming language; time series; algebraic transformation; monadic operators; dyadic operators; econometric models

Significance of the characteristic roots of linearized econometric models

This paper shows how to compute asymptotic standard errors of the characteristic roots of a nonlinear econometric model. The system of simultaneous equations is linearized in the neighborhood of a given point, then characteristic roots and related standard errors are computed.Nonlinear econometric models; characteristic roots; eigenvalues; asymptotic standard errors

Asymptotic properties of dynamic multipliers in nonlinear econometric models

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.Macroeconometric models; multipliers; asymptotic standard errors; inconsistency