Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/267568 
Year of Publication: 
2019
Citation: 
[Journal:] Baltic Journal of Economics [ISSN:] 2334-4385 [Volume:] 19 [Issue:] 1 [Publisher:] Taylor & Francis [Place:] London [Year:] 2019 [Pages:] 155-175
Publisher: 
Taylor & Francis, London
Abstract: 
The paper deals with the identification of time-frequency regions describing cyclicality of bank loans before, during and after the 2008 crisis via wavelets. We bring new methods and findings about the short and medium cycles of loans provided to corporates and households in the Euro Area in 2000-2017 using seasonally unadjusted monthly data. We have recognized an impact of the crisis on data volatility which further influences the type of significance testing of wavelet spectrograms. To avoid this influence we propose: (1) an adaptive spectrogram testing based on Torrence and Compo approach and (2) robustness analysis via enhanced spectrogram modelling tested by the MC simulations. Both cross-checked approaches prove the sensitivity of standard wavelet tests on data volatility. The results confirm the usability of the new approaches and show that the crisis in 2008 influenced the cyclical behaviour of both categories of economic sectors, but in a different way.
Subjects: 
enhanced spectrogram
local-adaptive-based testing
spectrogram significant testing
Wavelets
JEL: 
C15
C63
G2
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.