Determination of vector error correction models in high dimensions / by Chong Liang and Melanie Schienle
Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Working paper series in economics ; no. 124 (January 2019)Publisher: Karlsruhe : Karlsruher Institut für Technologie, [2019]Description: 1 Online-Ressource (circa 41 Seiten) : IllustrationenSubject(s): Genre/Form: DOI: DOI: 10.5445/IR/1000092474Online resources: Summary: We provide a shrinkage type methodology which allows for simultaneous model selection and estimation of vector error correction models (VECM) when the dimension is large and can increase with sample size. Model determination is treated as a joint selection problem of cointegrating rank and autoregressive lags under respective practically valid sparsity assumptions. We show consistency of the selection mechanism by the resulting Lasso-VECM estimator under very general assumptions on dimension, rank and error terms. Moreover, with computational complexity of a linear programming problem only, the procedure remains computationally tractable in high dimensions. We demonstrate the effectiveness of the proposed approach by a simulation study and an empirical application to recent CDS data after the financial crisis.PPN: PPN: 1047196697No physical items for this record