Are linear models really unuseful to describe business cycle data?

Artur Silva Lopes and Gabriel Florin Zsurkis

No 2017-5, Economics Discussion Papers from Kiel Institute for the World Economy (IfW Kiel)

Abstract: 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.

Keywords: business cycles; nonlinear time series models; testing (search for similar items in EconPapers)
JEL-codes: C22 C51 E32 (search for similar items in EconPapers)
Date: 2017
New Economics Papers: this item is included in nep-mac
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https://www.econstor.eu/bitstream/10419/149988/1/879952415.pdf (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:ifwedp:20175

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