Konferenzbeitrag
Reliable Real-time Output Gap Estimates Based on a Modified Hamilton Filter
We propose a simple modification of the time series filter by Hamilton (2018b) that yields reliable and economically meaningful real-time output gap estimates. The original filter relies on 8-quarter ahead forecasts errors of an autoregression. While this approach yields a cyclical component of GDP 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 short business cycles are muted and medium length business cycles are amplified. Further, the estimated trend is as volatile as GDP and can thus hardly be interpreted as potential GDP. A simple modification that is 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 Hamilton filter are economically much more meaningful measures of the business cycles than those based on other simple statistical trend-cycle decomposition techniques such as the HP or the Bandpass filter.
- Sprache
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Englisch
- Erschienen in
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Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2019: 30 Jahre Mauerfall - Demokratie und Marktwirtschaft - Session: Applied Macroeconometrics I ; No. A13-V1
- Klassifikation
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Wirtschaft
Methodological Issues: General
Business Fluctuations; Cycles
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Thema
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Output gap
potential output
trend-cycle decomposition
Hamilton filter
real-time data
inflation forecasting
- Ereignis
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Geistige Schöpfung
- (wer)
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Quast, Josefine
Wolters, Maik H.
- Ereignis
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Veröffentlichung
- (wer)
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ZBW - Leibniz-Informationszentrum Wirtschaft
- (wo)
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Kiel, Hamburg
- (wann)
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2019
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Konferenzbeitrag
Beteiligte
- Quast, Josefine
- Wolters, Maik H.
- ZBW - Leibniz-Informationszentrum Wirtschaft
Entstanden
- 2019