Several methods have been proposed in the last few years for evaluating uncertainty in forecasts produced by nonlinear econometric models. Some methods resort to Monte Carlo, while others resort to different simulation techniques. This work aims at comparing these methods by means of experiments...

It is purpose of this paper to evidence, in the behaviour of the Mini-DMS model for the French economy, some stochastic properties which may confirm, strengthen or sometimes contradict the results obtained from the standard simulation analysis, which is purely deterministic. In particular, the...

Multipliers are often used for selecting alternative policies in economic planning and forecasting. Particular variables like employment, trade balance, inflation or government budget usually impose constraints on the policy action. Therefore a criterion to be preferred to the raw multiplier...

The evaluation of policy actions by means of a large scale econometric model often begins with the analysis of multipliers. A large value of a multiplier, with the right sign, suggests that the policy instrument should be very effective in moving up or down the given target variable. However,...

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 well known macroeconometric model of the Italian economy is updated to produce forecasts at 1974.

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 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...

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...

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...