%0 Journal Article
%T Finding Starting-Values for the Estimation of Vector STAR Models
%A Frauke Schleer
%J Econometrics
%P 65-90
%D 2015
%I MDPI AG
%R 10.3390/econometrics3010065
%X This paper focuses on finding starting-values for the estimation of Vector STAR models. Based on a Monte Carlo study, different procedures are evaluated. Their performance is assessed with respect to model fit and computational effort. I employ (i) grid search algorithms and (ii) heuristic optimization procedures, namely differential evolution, threshold accepting, and simulated annealing. In the equation-by-equation starting-value search approach the procedures achieve equally good results. Unless the errors are cross-correlated, equation-by-equation search followed by a derivative-based algorithm can handle such an optimization problem sufficiently well. This result holds also for higher-dimensional Vector STAR models with a slight edge for heuristic methods. For more complex Vector STAR models which require a multivariate search approach, simulated annealing and differential evolution outperform threshold accepting and the grid search.
%K Vector STAR model
%K starting-values
%K optimization heuristics
%K grid search
%K estimation
%K non-linearieties
%U http://www.mdpi.com/2225-1146/3/1/65