VAR_BASED ESTIMATION OF THE VECTOR MOVING AVERAGE MODEL AND LINKS BETWEEN WHOLESALE AND RETAIL INVENTORIES

John Galbraith, Victoria Zinde-Walsh and Aman Ullah

Departmental Working Papers from McGill University, Department of Economics

Abstract: We examine a simple estimator for the multivariate moving average model based on vector autoregressive approximation. In finite samples the estimator has a bias which is low where roots of the determinantal equation are well away from the unit circle, and more substantial where one or more roots have modulus near unity. We also examine the sacrifice involved in specifying a vector model for processes which are in fact univariate, and show that the representation estimated by this multivariate technique is asymptotically invertible. This estimator has significant computational advantages over Maximum Likelihood. Moreover, as reported by Galbraith and Zinde-Walsh (1994) for the special case of the univariate model, this estimator can be more robust to mis-specification than ML. The estimation method is applied to a VMA model of wholesale and retail inventories, using Canadian data on overall aggregate, non-durable and durable inventory investment, and allows us to examine the propagation of shocks between the two classes of inventory.

Pages: 20 pages
Date: 1999-01
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mcl:mclwop:1999-03

Access Statistics for this paper

More papers in Departmental Working Papers from McGill University, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Shama Rangwala ( this e-mail address is bad, please contact ).