Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for estimating models where the likelihood function does not have a simple analytical expression. They adjust for the bias (inconsistency) produced by the estimation of an auxiliary model...

In this note we suggest a new iterative least squares method for estimating scalar and vector ARMA models. A Monte Carlo study shows that the method has better small sample properties than existing least squares methods and compares favourably with maximum likelihood estimation as well.

We propose a model diagnostic device to compare different linear and non linear parametric time series models of real GDP business cycle.The comparison appears of remarkable economic importance since different models have very different implications in term of long run persistence of negative...

Several papers have shown that high-inflation contributes to mean reversion in real exchange rates. This paper studies the Chilean peso (CLP) and Mexican peso (MXN) real exchange rates over 1980-2003. Three datasets are used: two with quarterly and monthly bilateral data (against the U.S....

This paper shows how to cope with a problem of model selection and simplification using the principle of coherence (Gabriel (1969): A procedure involving testing a set of models ought not accept a model while rejecting a more general model). The mathematical lattice theory is used to define a...

The motivation for this paper is to determine the potential economic value of advanced modelling methods for devising trading decision tools for 10-year Government bonds. Two advanced methods are used: time-varying parameter models with the implementation of state space modelling using a Kalman...