Information, forecasts and measurement of the business cycle
The Beveridge-Nelson (BN) technique provides a forecast-based method of decomposing a variable such as output, into trend and cycle when the variable is integrated of order one (I (1)). This paper considers the multivariate generalization of the BN decomposition when the information set includes other I (1) and/or stationary variables. We show that the relative importance of the cyclical component depends on the information set, and in particular that multivariate BN decompositions necessarily ascribe more importance to the cyclical component than does the univariate decomposition, provided the information set includes a variable which Granger-causes output. We illustrate the results for post-war data for the United States.
(This abstract was borrowed from another version of this item.)
To our knowledge, this item is not available for
download. To find whether it is available, there are three
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:||Apr 1994|
|Date of revision:|
|Publication status:||Published in: Journal of Monetary Economics (1994) v.33 n° 2,p.233-254|
|Contact details of provider:|| Postal: CP135, 50, avenue F.D. Roosevelt, 1050 Bruxelles|
Web page: http://difusion.ulb.ac.be
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:ulb:ulbeco:2013/10155. 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: (Benoit Pauwels)
If references are entirely missing, you can add them using this form.