Detail publikace

Cyclicality in Lending Activity of Euro Area in pre- and post- 2008 Crisis: A Local-Adaptive-Based Testing of Wavelets

Originální název

Cyclicality in Lending Activity of Euro Area in pre- and post- 2008 Crisis: A Local-Adaptive-Based Testing of Wavelets

Anglický název

Cyclicality in Lending Activity of Euro Area in pre- and post- 2008 Crisis: A Local-Adaptive-Based Testing of Wavelets

Jazyk

en

Originální abstrakt

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 recognised 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.

Anglický abstrakt

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 recognised 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.

BibTex


@article{BUT156297,
  author="Jitka {Poměnková} and Eva {Klejmová} and Zuzana {Kučerová}",
  title="Cyclicality in Lending Activity of Euro Area in pre- and post- 2008 Crisis: A Local-Adaptive-Based Testing of Wavelets",
  annote="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 recognised 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.",
  address="Taylor & Francis Group",
  chapter="156297",
  doi="10.1080/1406099X.2019.1596466",
  howpublished="online",
  institution="Taylor & Francis Group",
  number="1",
  volume="19",
  year="2019",
  month="march",
  pages="155--175",
  publisher="Taylor & Francis Group",
  type="journal article in Web of Science"
}