Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/220361 
Year of Publication: 
2020
Series/Report no.: 
Kiel Working Paper No. 2158
Publisher: 
Kiel Institute for the World Economy (IfW), Kiel
Abstract: 
We propose a simple modification of Hamilton's (2018) time series filter that yields reliable and economically meaningful real-time output gap estimates. The original filter relies on 8 quarter ahead forecast errors of a simple autoregression of real GDP. While this approach yields a cyclical component that is hardly revised with new incoming data due to the one-sided filtering approach, it does not cover typical business cycle frequencies evenly, but mutes short and amplifies medium length cycles. Further, as the estimated trend contains high frequency noise, it can hardly be interpreted as potential GDP. A simple modification based on the mean of 4 to 12 quarter ahead forecast errors shares the favorable real-time properties of the Hamilton filter, but leads to a much better coverage of typical business cycle frequencies and a smooth estimated trend. Based on output growth and inflation forecasts and a comparison to revised output gap estimates from policy institutions, we find that real-time output gaps based on the modified and the original Hamilton filter are economically much more meaningful measures of the business cycle than those based on other simple statistical trend-cycle decomposition techniques, such as the HP or bandpass filter, and should thus be used preferably.
Subjects: 
business cycle measurement
potential output
trend-cycle decomposition
real-time data
inflation forecasting
output growth forecasting
JEL: 
C18
E32
E37
Document Type: 
Working Paper

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