Extracting business cycle fluctuations: What do time series filters really do?

Arbeitspapier

Various methods are available to extract the “business cycle component” of a given time series variable. These methods may be derived as solutions to frequency extraction or signal extraction problems and differ in both their handling of trends and noise and their assumptions about the ideal time-series properties of a business cycle component. The filters are frequently illustrated by application to white noise, but applications to other processes may have very different and possibly unintended effects. This paper examines several frequently used filters as they apply to a range of dynamic process specifications and derives some guidelines for the use of such techniques.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Staff Report ; No. 289

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Business Fluctuations; Cycles
• Subject: frequency domain, spectral analysis, signal extraction ; Zeitreihenanalyse ; Konjunktur ; Statistische Verteilung ; Schätztheorie ; USA

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Estrella, Arturo
• Event: Veröffentlichung
• (who): Federal Reserve Bank of New York
• (where): New York, NY
• (when): 2007

Further information

• Handle: http://hdl.handle.net/10419/60592
• Last update: 10.03.2025, 11:41 AM CET