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 how the relative importance of the cyclical component depends on the size of the information set, and is necessarily higher with multivariate BN decompositions. The results are illustrated using post-WWII United States data. An explanation is also provided for the empirical finding of a positive association of the multivariate BN cycle with output growth.