Characterizing the financial cycle: Evidence from a frequency domain analysis

Strohsal, Till; Proaño, Christian R.; Wolters, Jürgen

doi:10.1016/j.jbankfin.2019.06.010

Cited by 72 publications

(63 citation statements)

References 50 publications

(35 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The cycles are even somewhat larger and longer for the UK and Spain, but very small and short for Germany. Such an important role of medium-term fluctuations together with differences in cyclical characteristics across countries is also reported by Galati et al (2016) and Strohsal et al (2015). Using cross-spectral analysis, Schüler et al (2015) find strong comovements between house prices and credit at medium-term frequencies, although they report an average cycle length of less than 8 years for their composite financial cycles indicators of euro area countries.…”

Section: Introductionmentioning

confidence: 79%

“…We will discuss this model in Section 2. Other studies have used spectral methods (Schüler, Hiebert, & Peltonen, ) and autoregressive integrated moving average (ARIMA) models (Strohsal, Proaño, & Wolters, ) to assess cyclical properties of the series.…”

Section: Introductionmentioning

confidence: 99%

“…We will discuss this model in Section 2. Other studies have used spectral methods (Schüler, Hiebert, & Peltonen, 2015) and autoregressive integrated moving average (ARIMA) models (Strohsal, Proaño, & Wolters, 2015) to assess cyclical properties of the series. 1 The comovements between GDP and leverage cycles have so far been investigated by event studies (Jordà et al, 2015(Jordà et al, , 2016 and turning point analysis (Claessens, Kose, & Terrones, 2011, 2012.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Business, housing, and credit cycles

Rünstler

Vlekke

2017

J of Applied Econometrics

119

View full text Add to dashboard Cite

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 der dort genannten Lizenz gewährten Nutzungsrechte. Note: This Working Paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB. Terms of use: Documents in AbstractWe use multivariate unobserved components models to estimate trend and cyclical components in GDP, credit volumes and house prices for the U.S. and the five largest European economies. With the exception of Germany, we find large and long cycles in credit and house prices, which are highly correlated with a medium-term component in GDP cycles. Differences across countries in the length and size of cycles appear to be related to the properties of national housing markets. The precision of pseudo real-time estimates of credit and house price cycles is roughly comparable to that of GDP cycles. Studies have so far mostly used univariate non-parametric methods, i.e. band-pass filters and turning point analysis, to extract financial cycles. These methods require a priori assumptions on cyclical characteristics and are applied separately to each series. They are therefore not particularly suitable for assessing cyclical co-movements and evaluating the cyclical stance in real-time.Multivariate STSMs do not suffer from these shortcomings. We propose various modifications of the standard STSM to jointly model the cyclical dynamics in GDP and the financial series.In line with earlier studies, we find pronounced cycles in credit and house prices with a length of 12 to 18 years in most cases. There also arise important differences across countries. We find cycles to be particularly long and large for the U.K. and Spain, of more moderate length and size for the U.S., Italy, and France, and comparatively short and small for Germany. These differences turn out to be related to a specific structural characteristic of national housing markets: cycles are longer and larger for countries with high rates of private home ownership.Moreover, financial cycles are closely related to a medium-term component in the GDP cycle.More precisely, the multivariate estimates emphasize the presence of medium-term fluctuations in GDP, which are longer than the traditional business cycle (3 to 8 years). We find high correlations between the financial and GDP cycles in the medium term, but more moderate correlations over the business cycle. While previous studies have documented that peaks and troughs in financial cycles coincide with major turning points in ...

show abstract

Section: Introductionmentioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Business, housing, and credit cycles

Rünstler

Vlekke

2017

J of Applied Econometrics

119

View full text Add to dashboard Cite

show abstract

“…Frequency-based filters are used to extract the medium-term cyclical components of the indicators, which are then combined to provide an estimate of the financial cycle. Similar approaches have been adopted in the literature by Aikman et al (2015) for the credit cycle, and by Schüler et al (2015), Strohsal et al (2019) and Gonzalez et al (2015) for the financial cycle. The frequently cited analysis of Drehmann et al (2012) uses frequency-based filters, as well as turning point analysis.…”

Section: Frequency-based Filters Analysismentioning

confidence: 89%

Measuring the Financial Cycle in South Africa

Farrell

Kemp

2020

South African J Economics

View full text Add to dashboard Cite

We measure the financial cycle of South Africa using three different methodologies. The financial cycle is identified using credit, house prices and equity prices as indicators, and estimated using traditional turning-point analysis, frequency-based filters and an unobserved components modelbased approach. We then consider the financial cycle's main characteristics and examine its relationships with the business cycle. We confirm the presence of a financial cycle in South Africa that has a longer duration and a larger amplitude than the traditional business cycle. Developments in measures of credit and house prices are important indicators of the financial cycle, although the case for including equity prices in the measures is less certain. Periods where financial conditions are stressed are associated with peaks in the financial cycle, suggesting that the estimated financial cycle may have similar leading indicator properties to financial conditions or stress indices. JEL Classification: E44, E61, G21

show abstract

“…Recent empirical research has highlighted different frequencies of business cycles on the one hand, and financial cycles on the other (Drehmann et al, 2012;Borio, 2014;Aikman et al, 2015;Strohsal et al, 2015). While regular business cycle dynamics in real activity are considered to take place with periods of up to 8 years, financial cycles appear to have a lower frequency with cycle lengths between 8 and 30 years (Borio, 2014).…”

Section: Introductionmentioning

confidence: 99%

Short and medium term financial-real cycles: An empirical assessment

Stockhammer

Jump

Köhler

et al. 2019

Journal of International Money and Finance

View full text Add to dashboard Cite

Theories such as Minsky's financial instability hypothesis or New Keynesian financial accelerator models assign a key role to financial factors in business cycle dynamics. We present descriptive statistics and a simple estimation framework to examine the financial-real interaction mechanisms that are at the core of these theories. Specifically, we examine cycle frequencies in seven OECD countries over the period 1970 to 2015, and find that interest rates, business debt, and household debt exhibit cycle lengths of 4-6, 8-11, and 14-26 years, respectively. We then estimate bivariate VAR models which provide evidence for financialreal interaction mechanisms, (i) at high frequencies between interest rates and GDP, and (ii) at low frequencies between business debt and GDP. In contrast, there is no evidence for a cycle mechanism between household debt and GDP.

show abstract

Characterizing the financial cycle: Evidence from a frequency domain analysis

Cited by 72 publications

References 50 publications

Business, housing, and credit cycles

Business, housing, and credit cycles

Measuring the Financial Cycle in South Africa

Short and medium term financial-real cycles: An empirical assessment

Contact Info

Product

Resources

About