2017
DOI: 10.1002/jae.2604
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Business, housing, and credit cycles

Abstract: Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in… Show more

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Cited by 121 publications
(103 citation statements)
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“…Recent studies have also explored the interactions between business and financial cycles either across countries (Claessens, Kose, and Terrones, 2012) or on a country-by-country basis (Galati et al, 2016;Rünstler and Vlekke, 2016). To our knowledge, so far only one paper has proposed a joint dating of business and credit cycles with a specific focus on Italy (Bartoletto et al, 2017), by applying a local turning-point dating algorithm to the level of real GDP and credit aggregates.…”
Section: Introductionmentioning
confidence: 99%
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“…Recent studies have also explored the interactions between business and financial cycles either across countries (Claessens, Kose, and Terrones, 2012) or on a country-by-country basis (Galati et al, 2016;Rünstler and Vlekke, 2016). To our knowledge, so far only one paper has proposed a joint dating of business and credit cycles with a specific focus on Italy (Bartoletto et al, 2017), by applying a local turning-point dating algorithm to the level of real GDP and credit aggregates.…”
Section: Introductionmentioning
confidence: 99%
“…This latter belongs to the class of estimated band-pass filters, which are used to extract cycles falling within a pre-defined band of frequency: usually, 8 to 32 quarters for business cycles and 32 to 120 quarters for financial cycles. However, as stressed by Rünstler and Vlekke (2016), if the filter bands do not overlap, estimates of the two cycles are uncorrelated by construction. This is a restriction one would like to test rather than impose a priori.…”
Section: Introductionmentioning
confidence: 99%
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“…The statistical approach uses the state space form, with the components being obtained from the Kalman filter and smoother. Lucas and Koopman (2005), Galati et al (2016), Rünstler and Vlekke (2016) and Grinderslev et al (2017) have used unobserved components time series models (UCTSMs) to measure financial cycles.…”
Section: Model-based Approachesmentioning
confidence: 99%
“…For more general discussions, see Cogley and Nason (1995), Osborn (1995) and Hamilton (2017). 14 As Rünstler and Vlekke (2016) argue "while Drehmann et al (2012) regard financial and business cycles as 'different phenomena', such finding emerges from their choice of frequency bands for the extraction of GDP (8 to 32 quarters) and financial cycles (32 to 120 quarters): once the filter bands do not overlap, estimates of the two cycles are uncorrelated by construction." where h is a time lag, λ is the frequency (−∞ < λ < ∞), e i = cos( ) + i sin ( ) and i = √ −1 .…”
Section: Nonparametric Estimation Of the Spectral Densitymentioning
confidence: 99%