A computationally efficient branch-and-bound strategy for finding the subsets of the most statistically significant variables of a vector autoregressive (VAR) model from a given search subspace is proposed. Specifically, the candidate submodels are obtained by deleting columns from the...

Algorithms for computing the subset Vector Autoregressive (VAR) models are proposed. These algorithms can be used to choose a subset of the most statistically-significant variables of a VAR model. In such cases, the selection criteria are based on the residual sum of squares or the estimated...

The journal Computational Statistics and Data Analysis aims to have regular issues on computational econometrics. Of particular interest are papers in important areas of econometric applications where both computational techniques and numerical methods have a major impact. The goal is to provide...