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Financial cycles Mathias Drehmann DNB Workshop on “Estimating and Interpreting Financial Cycles” Amsterdam, 2 September 2016 The views presented are those of the author and do not necessarily represent those of the Bank for International Settlements Restricted What is the financial cycle? The broad concept of the financial cycle encapsulates joint fluctuations in a wide set of financial variables Financial cycles are characterised by financial booms and busts that can lead to serious financial and macroeconomic strains Restricted 2 There are many ways to measure the financial cycle Initial literature focused on early warning indicators (EWIs) for crises or identified credit booms statistically Does not allow for characterizing the full financial cycle But EWIs can be used to construct financial cycle measures Use variants of the classical business cycle dating method Claessens et al (2011), Drehmann et al (2012),… Use statistical filters Aikman et al (2015), Drehmann et al (2012), De Bonis & Silvestrini (2014), Runstler & Vlekke (2015), Galati et al (2016).. Use long-run relationships (Juselius and Drehmann (2015)) Restricted 3 Drehmann, Borio, Tsatsaronis (2012) Frequency based filters (Christiano and Fitzgerald, 2005, Comin and Gertler, 2006) Turning-point method (Burns and Mitchell, 1946, Harding and Pagan, 2002) Short term cycle (business cycle) Medium term cycle Frequency based filters Turning-points 5-32 quarters Local maxima\minima: 5q window Minimum cycle length: 5 quarters 8-30 years Local maxima\minima: 9q window Minimum cycle length: 5 years Restricted 4 Explore potential series Business cycle: GDP Financial cycle: Credit to the private non-financial sector Credit-to-GDP ratio Property prices Equity prices Asset prices Because of lack of data do not include other financial variables (e.g. spreads, profits, write-offs, leverage…) 7 countries (AU, DE, JP, NO, SE, UK, US) with 11 banking crises Quarterly data from 1960 to 2011 Restricted 5 Medium-term versus short–term: Filters Volatility of medium-term component greater than short-term one for all variables Medium-term component becomes larger after 1985 Table 1 Relative volatility of short- and medium-term cycles: individual series1 (Frequency-based analysis) AU DE GB JP NO SE US Credit 4.52 1.80 3.73 4.34 6.28 6.78 3.87 Credit/GDP 7.36 2.83 5.28 3.39 4.99 5.98 4.92 House prices 1.75 2.19 2.42 3.05 2.21 4.91 3.91 Equity prices 1.72 1.40 1.77 2.14 1.30 1.42 1.41 AAP2 1.95 3.94 2.56 3.36 1.60 1.48 1.75 GDP 3.25 1.73 1.93 3.06 2.55 1.84 1.51 1 The figures refer to the ratio of the standard deviation of the medium-term cyclical component to that of the short-term component over the entire sample period. A number greater (smaller) than 1.0 means that the medium-term cyclical component is more (less) volatile than the short-term component. Cells shown in bold denote cases where the ratio of medium- to short-term component volatility for the corresponding series is higher that the corresponding ratio for GDP. Acronyms used here and in subsequent tables and graphs: AU = Australia; DE= Germany; GB= United Kingdom; JP = Japan; NO = Norway; SE = Sweden; US = United States. 2 Aggregate asset price index. Restricted 6 What happens around crisis? All domestic crises coincide with medium term cyclical peaks Independent of the method Peaks in medium term cycles often coincide with crises For credit and property prices 40-50% of peaks coincide with crises (65-70% after 1985) For short term cycles the relationship much weaker (1830%) → Medium-term frequencies are key! Restricted 7 Aggregation Frequency based filters Average of individual series Turning-point method (Harding and Pagan (2005)) Peak in the common cycle if - there is a cluster when all individual series peak - individual series are closest to their peak within the cluster Impose same constraints as on dating method for individual series Cluster width 3 years 3 to 6 yeas (weak) Restricted 8 Which series should underpin the financial cycle? The financial cycle is derived from credit, the credit-to-GDP ratio and property prices Equity prices (and thus aggregate asset prices) are not included Greater short-term volatility Medium-term cyclical peaks occur often without crisis Medium-term cycle not well aligned with credit series or property prices - Low concordance (turning-point method) - Low correlation (frequency based filters) Restricted 9 Peaks in the financial cycle are close to crises or periods of stress Country Date Close to crises GB 2009q1 SE 2009q1 US 2007q3 JP 1992q2 GB 1991q1 AU 1990q3 US 1990q3 SE 1990q2 NO 1989q3 GB 1973q4 Average Time to closest Time to closes crises peak using filters Country Date Not close to crises -6 5 NO 2009q2 -2 4 AU 2009q1 0 0 DE 1998q4 2 -3 SE 1980q4 -3 -2 US 1979q3 -3 -2 DE 1973q4 -2 -5 JP 1973q4 5 3 5 -2 0 0 -0.4 -0.2 Average Time to closest Time to closes crises peak using filters -74 -77 35 43 42 135 76 3 1 9 -2 -1 -1 -2 25.7 1.0 Restricted 10 Different financial cycle dating methods generally coincide Spain United Kingdom United States Source: BIS, 2016, 86th Annual Report Restricted 11 The EWI method Built on the EWI literature Large credit-to-GDP gaps, i.e. deviations of the credit-toGDP ratio from a long-run trend, are useful early warning indicators. (eg Drehmann et al (2011), Detken et al (2014), Schularick and Taylor (2012)…) Real residential property prices start to fall ahead of financial crises Restricted 12 The signalling quality of different EWIs AUCs for different forecast horizons Graph 2 Credit-to-GDP gap Debt-service-ratio (DSR) Non-core liabilities Credit growth Property price growth GDP growth The horizontal-axis denotes the forecast horizons in quarters before crises. The vertical-axis denotes AUC. The horizontal line at 0.5 highlights the value of an uninformative indicator. A solid blue line indicates that the specific variable for the given horizon is statistically different from an uninformative indicator, while a dashed blue line indicates the opposite. A hollow blue circle shows that the signal is stable in the sense that it does not reverse direction within the forecast horizon until the crisis. Red diamonds highlight that the specific variable is statistically the best indicator for this particular horizon. Other indicators that are not statistically different from best-performing indicator are marked by solid blue circles. Source: Drehmann and Juselius (2013). Restricted 13 The EWI method (II) Define peak (trough) in financial cycle: Peak: positive credit-to-GDP gap and real property price growth turns persistently negative Trough: negative credit-to-GDP gap and real property price growth turns persistently positive Restricted 14 Different financial cycle dating methods generally coincide Spain United Kingdom United States Source: BIS, 2016, 86th Annual Report Restricted 15 Decomposing the financial cycle Juselius and Drehmann (2015) (JD) decompose the financial cycle into two long run relationships: Leverage (credit-to-assets ratio): (𝑐𝑡 − 𝑦𝑡 ) − (𝑝𝐴,𝑡 − 𝑝𝑡 ) Debt service ratio (DSR): 𝑐𝑡 − 𝑦𝑡 + 𝛽𝑖𝐿,𝑡 Restricted 16 Estimation strategy JD estimate VAR in error correction form Δ𝑐𝑟 𝑟 Δ𝑦 𝑟 Δ𝑝𝐴𝑟 Δ𝑖𝑟 with 2 = 𝜇 + 𝛼 𝑙𝑒𝑣 𝑑𝑠𝑟 𝑡 + 𝑡−1 Π𝑖 𝑖=1 Δ𝑐𝑟 𝑟 Δ𝑦 𝑟 Δ𝑝𝐴𝑟 Δ𝑖𝑟 + Γ𝑠𝑡 + 𝜖𝑡 𝑡−𝑖 𝑙𝑒𝑣 = 𝑐𝑟𝑡𝑟 − 𝑦𝑡𝑟 − 𝑝𝐴𝑟 − 𝜇𝑙 𝑑𝑠𝑟 = 𝑐𝑟𝑡𝑟 − 𝑦𝑡𝑟 + 𝛽𝑖𝑟 − 𝜇𝑑 𝑐𝑟𝑡𝑟 real credit to the private non-financial sector, 𝑦𝑡𝑟 real GDP, 𝑝𝐴𝑟 real aggregate asset price index, 𝑖𝑟 nominal lending rate on the stock of debt Quarterly US data from 1985 until 2013. Restricted 17 DSR and leverage in the US Restricted 18 Effects on growth Effects can work in same direction or off-set each other Big shocks or non-linearities not needed for sharp downturns DSR gap effect on expenditure explosive Long-lasting and large real effects Interaction between gaps lead to endogenous cycles Restricted 19 (Pseudo) real-time prediction of the Great Recession -1 0 -1 1 0 2 1 2 Expenditure growth 3 Credit growth 2005q3 2007q3 -2 Actual Simulation 05 Long-run average 2009q3 2011q3 2013q3 2005q3 2007q3 2009q3 2011q3 2013q3 Restricted 20 The gaps and the financial cycle? DSR gap negative positive negative Boom (credit ↑, GDP↑) Late boom (credit ↑, GDP ~) positive Recovery (credit ↓, GDP ~) Bust (credit ↓, GDP ↓) Leverage gap Restricted 21 1 1985q1 1990q1 1995q1 2000q1 2005q1 2010q1 2015q1 -40 0 0 -20 -10 -20 0 0 10 20 20 1 40 GB 30 US 1985q1 1990q1 1995q1 2000q1 2005q1 2010q1 2015q1 boom late_boom boom late_boom bust recovery bust recovery lev dsr lev dsr Restricted 22 Different financial cycle dating methods generally coincide Spain United Kingdom United States Source: BIS, 2016, 86th Annual Report Restricted 23 Conclusion Key empirical findings Financial cycles are longer than business cycles Peaks of the financial cycle coincide with serious strains in financial systems\crisis. There are different methods to identify financial cycles From a high-level perspective, they lead to similar results From a day-to-day policy perspective, differences are large Restricted 24