Are linear models really unuseful to describe business cycle data?

Arbeitspapier

The authors use first differenced logged quarterly series for the GDP of 29 countries and the euro area to assess the need to use nonlinear models to describe business cycle dynamic behaviour. Their approach is model (estimation)-free, based on testing only. The authors aim to maximize power to detect non-linearities and, simultaneously, they purport avoiding the pitfalls of data mining. The evidence the authors find does not support some descriptions because the presence of significant non-linearities is observed for 2/3 of the countries only. Linear models cannot be simply dismissed as they are frequently useful. Contrarily to common knowledge, nonlinear business cycle variation does not seem to be a universal, undisputable and clearly dominant stylized fact. This finding is particularly surprising for the U.S. case. Some support for nonlinear dynamics for some further countries is obtained indirectly, through unit root tests, but this can hardly be invoked to support nonlinearity in classical business cycles.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Economics Discussion Papers ; No. 2017-5

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Model Construction and Estimation ; Business Fluctuations; Cycles
• Thema: business cycles ; nonlinear time series models ; testing

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Lopes, Artur Silva ; Zsurkis, Gabriel Florin
• Ereignis: Veröffentlichung
• (wer): Kiel Institute for the World Economy (IfW)
• (wo): Kiel
• (wann): 2017

Weitere Informationen

• Handle: http://hdl.handle.net/10419/149988
• Letzte Aktualisierung: 10.03.2025, 11:45 MEZ