For a nonlinear system of simultaneous equations, the mode of the joint distribution of the endogenous variables in the forecast period is proposed as alternative to the more usual deterministic or mean predictors. A first method follows from maximizing the joint density of a subset of the...

The drawbacks of predictors obtained with the usual deterministic solution methods in nonlinear systems of stochastic equations have been widely investigated in the literature. Most of the proposed therapies are based on some estimation of the conditional mean of the endogenous variables in the...

A programming language has been developed at the IBM Scientific Center of Pisa (Italy) to manage interactively the economic time series of a large data base.

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...

Bilateral import prices are assumed to be the main explanatory variables in an import allocation model. Since official statistics are not available, the construction of these indices has been undertaken, using the data on bilateral trade by commodities supplied by OECD. Data are stored in 126...

The stochastic simulation of an econometric model is an application of Monte Carlo methods. Deterministic simulation is performed setting error terms to zero. Stochastic simulation, on the contrary, takes into account the disturbance terms, solving the model after adding a vector of...

The estimation of limited dependent variable panel data models usually involves objective functions in which integrals appear without a closed form solution: this is the case of the panel data Tobit model with random effects. Recently, simulation methods have shown to be useful in the inference...

An Interactive Management of Time Series user can create new functions which cannot be reconstructed by means of existing functions, and use them as operators of the language.

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...

This paper describes the application of a reordering algorithm to the equations of econometric models. The algorithm was proposed in 1970 by Van der Giessen and is here applied to the equation format required by the program for stochastic simulation developed at the IBM Scientific Center in Pisa.