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, provides the information set includes a variable which Granger-causes output. We illustrate the results for post-WWII United States
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