Since regional economies are exposed to the region common shock, the degree of co-
movement of each region's business cycle is strong, possibly exaggerating or biasing the …

In many system state forecasting applications, the prediction is performed based on multiple
datasets, each corresponding to a distinct system condition. The traditional methods dealing …

We propose two methods to choose the variables to be used in the estimation of the
structural parameters of a singular DSGE model. The first selects the vector of observables …

Strong consistency and asymptotic normality of a Gaussian quasi-maximum likelihood
estimator for the parameters of a causal, invertible, and identifiable vector autoregressive …

In many applications of system state forecasting, the prediction is performed using multi-
dimensional data sets. The traditional methods for dealing with multi-dimensional data sets …

In this article, we investigate the theoretical behavior of finite lag VAR (n) models fitted to
time series that in truth come from an infinite-order VAR (∞) data-generating mechanism …

This paper develops a new methodology for identifying the structure of VARMA time series
models. The analysis proceeds by examining the echelon form and presents a fully …

This work is a comparative study of different univariate and multivariate time series
predictive models as applied to Bitcoin, other cryptocurrencies, and other related financial …

We study the benefits of forecast combinations based on forecast-encompassing tests
relative to uniformly weighted forecast averages across rival models. For a realistic …

The IMF reports that, over 60% of foreign trade income and 40% of government revenue of
Iran comes from the oil and gas sectors, which has always been a source of volatilities in the …