DP756 Information, Forecasts and Measurement of the Business Cycle

Author(s): George W. Evans, Lucrezia Reichlin
Publication Date: January 1993
Keyword(s): Business Cycles, Cycle, Forecast, Granger Casuality, Information, Integrated Series, Trend
JEL(s): C32, E32
Programme Areas: International Macroeconomics
Link to this Page: cepr.org/active/publications/discussion_papers/dp.php?dpno=756

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.