Quantifying risk and uncertainty in macroeconomic forecasts
This paper discusses methods to quantify risk and uncertainty in macroeconomic forecasts. Both, parametric and non-parametric procedures are developed. The former are based on a class of asymmetrically weighted normal distributions whereas the latter employ asymmetric bootstrap simulations. Both procedures are closely related. The bootstrap is applied to the structural macroeconometric model of the Bundesbank for Germany. Forecast intervals that integrate judgement on risk and uncertainty are obtained.
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