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.
|Date of creation:||Jan 1993|
|Date of revision:|
|Contact details of provider:|| Postal: Centre for Economic Policy Research, 77 Bastwick Street, London EC1V 3PZ.|
Phone: 44 - 20 - 7183 8801
Fax: 44 - 20 - 7183 8820
|Order Information:|| Email: |
When requesting a correction, please mention this item's handle: RePEc:cpr:ceprdp:756. 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: ()
If references are entirely missing, you can add them using this form.