Var_based Estimation Of The Vector Moving Average Model And Links Between Wholesale And Retail Inventories
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.
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||Jan 1999|
|Contact details of provider:|| Postal: 855 Sherbrooke St. W., Montréal, Québec, H3A 2T7|
Phone: (514) 398-3030
Fax: (514) 398-4938
Web page: http://www.repec.mcgill.ca
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:mcl:mclwop:1999-03. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shama Rangwala)
If references are entirely missing, you can add them using this form.