Template-type: ReDIF-Paper 1.0
Author-Name: Katja Drechsel
Author-Name-First: Katja
Author-Name-Last: Drechsel
Author-Person: pdr65
Author-Name: Dr. Rolf Scheufele
Author-Name-First: Rolf
Author-Name-Last: Scheufele
Author-Person: psc357
Title: Bottom-up or Direct? Forecasting German GDP in a Data-rich Environment
Abstract: This paper presents a method to conduct early estimates of GDP growth in Germany. We employ MIDAS regressions to circumvent the mixed frequency problem and use pooling techniques to summarize efficiently the information content of the various indicators. More specifically, we investigate whether it is better to disaggregate GDP (either via total value added of each sector or by the expenditure side) or whether a direct approach is more appropriate when it comes to forecasting GDP growth. Our approach combines a large set of monthly and quarterly coincident and leading indicators and takes into account the respective publication delay. In a simulated out-of-sample experiment we evaluate the different modelling strategies conditional on the given state of information and depending on the model averaging technique. The proposed approach is computationally simple and can be easily implemented as a nowcasting tool. Finally, this method also allows to retrace the driving forces of the forecast and hence enables the interpretability of the forecast outcome.
Length: 57 pages
Creation-Date: 2012
Contact-Email: forschung@snb.ch
File-URL: https://www.snb.ch/en/publications/research/working-papers/2012/working_paper_2012_16
File-Format: text/html
Number: 2012-16
Classification-JEL: E32, E37, C52, C53
Keywords: Contemporaneous aggregation, nowcasting, leading indicators, MIDAS, forecast combination, forecast evaluation
Handle: RePEc:snb:snbwpa:2012-16