Forecasting with Dynamic Models using Shrinkage-based Estimation
George Kapetanios () and
Additional contact information
George Kapetanios: Queen Mary, University of London
No 635, Working Papers from Queen Mary University of London, School of Economics and Finance
The paper provides a proof of consistency of the ridge estimator for regressions where the number of regressors tends to infinity. Such result is obtained without assuming a factor structure. A Monte Carlo study suggests that shrinkage autoregressive models can lead to very substantial advantages compared to standard autoregressive models. An empirical application focusing on forecasting inflation and GDP growth in a panel of countries confirms this finding.
Keywords: Shrinkage; Forecasting (search for similar items in EconPapers)
JEL-codes: C13 C22 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-for
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed
Downloads: (external link)
Working Paper: Forecasting with Dynamic Models using Shrinkage-based Estimation (2008)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:qmw:qmwecw:wp635
Access Statistics for this paper
More papers in Working Papers from Queen Mary University of London, School of Economics and Finance Contact information at EDIRC.
Bibliographic data for series maintained by Nicholas Owen ().