This paper examines whether data from business tendency surveys are useful for forecasting the macro economy (GDP, unemployment, price and wage inflation, interest rates, exchange-rate changes etc.) in the short run. The starting point is a so-called dynamic factor model (DFM), which is used both as a framework for dimension reduction in forecasting and as a procedure for filtering out unimportant idiosyncratic noise in the underlying survey data. In this way, it is possible to model a rather large number of noise-reduced survey variables in a parsimoniously parameterised vector autoregression (VAR). To assess the forecasting performance of the procedure, comparisons are made with VARs that either use the survey variables directly, are based on macro variables only, or use other popular summary indices of economic activity. A revised version of this paper has been published in the Journal of International Forecasting, No 21, 2000".
51 Seiten p.