Are linear models really unuseful to describe business cycle data?

• Main Author: Lopes, Artur Silva
• Publication Date: 2019
• Other Authors: Zsurkis, Gabriel Florin
• Format: Article
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: http://hdl.handle.net/10400.5/17720
• topic: Business cycles; non-linear time series models; testing; unit roots

We use first differenced logged quarterly series for the GDP of 29 countries and the euro area to assess the need to use non-linear models to describe business cycle dynamic behaviour. Our approach is model (estimation)-free, based on testing only. We aim to maximize power to detect non-linearities while, simultaneously, avoiding the pitfalls of data mining. The evidence we find does not support some descriptions because the presence of significant non-linearities is observed for two-thirds of the countries only. Linear models cannot be simply dismissed as they are frequently useful. Contrarily to common knowledge, non-linear 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 non-linear dynamics for some further countries is obtained indirectly, through unit root tests, but this can hardly be invoked to support non-linearity in classical business cycles.