Sammelbandbeitrag

Erschienen in: New Directions in Macromodeling

Herausgeberliste: Welfe, A.

Jahr der Veröffentlichung: 2004

Seiten: 213-234

ISBN: 978-0-444-51633-6

DOI Link: https://doi.org/10.1016/S0573-8555(04)69009-2

Auflage: 1st edition

Serientitel: Contributions to economic analysis

Serienzählung: 269

Abstract: 

For the modelling of time series, multivariate linear and non-linear systems of equations became a standard tool. These models are also applied for non-stationary processes. However, estimation results in finite samples might depend on the specification of the model dynamics.
We propose a method for automatic identification of the dynamic part of VEC-models. Model selection is based on a modified information criterion. The lag structure of the model is selected according to this objective function allowing for ‘holes’. The resulting complex discrete optimization problem is tackled using a hybrid heuristic combining ideas from threshold accepting (TA) and memetic algorithms. We present the algorithm and results of a simulation study indicating the performance both with regard to the dynamic structure and the rank selection in the VEC-model.

Harvard-Zitierstil: Winker, P. and Maringer, D. (2004) Optimal Lag Structure Selection in VAR and VEC Models, in Welfe, A. (ed.) New Directions in Macromodeling. 1st edition. Amsterdam: Elsevier, pp. 213-234. https://doi.org/10.1016/S0573-8555(04)69009-2

APA-Zitierstil: Winker, P., & Maringer, D. (2004). Optimal Lag Structure Selection in VAR and VEC Models. In Welfe, A. (Ed.), New Directions in Macromodeling (1st edition, pp. 213-234). Elsevier. https://doi.org/10.1016/S0573-8555(04)69009-2