Monetary policy, the financial cycle and ultra-low interest rates - PowerPoint PPT Presentation

Monetary policy, the financial cycle and ultra-low interest rates Mikael Juselius DNB Workshop on “Estimating and Interpreting Financial Cycles” Amsterdam , 2 September 2016 The views presented here are the authors’ and do not necessarily reflect those of the Sisäinen Bank of Finland, the Bank for International Settlements or the Bank of Thailand.

Why do real interest rates decline? The long-term decline in real interest rates 1 Graph 1 Per cent 1 Real rates are generated by subtracting realised PCE core inflation from nominal interest rates. Source: National data. Mikael Juselius Sisäinen

Mainstream view • An exogenous fall in the natural interest rate – Secular stagnation: weak capital demand, rising propensity to save, lower trend growth (Summers 2014) – High propensity to save in EMEs + investors’ demand for safe assets (Bernanke 2015, Broadbent 2015) • Supported by low inflation and belief in the Phillips curve… • …but inflation not a perfect signal of the cycle: – Sectoral misallocation, positive supply shocks etc. – Difficult to separate historical inflation trends from cycles – Leads to estimates of natural rate that permits buildups of financial imbalances (Summers 2014, Bean et al 2015) Mikael Juselius Sisäinen

We present an alternative view • Partly endogenously due to financial imbalances? – Financial booms and busts can have lasting effects (eg Cerra and Saxena 2008, Ball 2014)… – …with little prior reaction in inflation ( eg IMF, 2013) • To study this possible connection: – We augment the Laubach-Willimans (LW) natural interest rate filter with financial factors – Financial imbalances from Juselius and Drehmann (2015) – Informal ”guess” at how these imbalances enter the filter Mikael Juselius Sisäinen

Measuring financial imbalances • Long-run relationships for credit-to-GDP: – Leverage (credit-to-assets): (𝑑 𝑢 − 𝑧 𝑢 ) − (𝑞 𝐵,𝑢 − 𝑞 𝑢 ) – Debt service ratio (DSR): 𝑑 𝑢 − 𝑧 𝑢 + 𝛾𝑗 𝑀,𝑢 – Both relationships are in US data, 1985-2015 – Can be estimated from pre-crisis samples – Deviations from long-run relationships ( leverage gap and debt service gap ) as measures of the financial cycle • Rate spread to link policy and lending rates: 𝑗 𝑀,𝑢 − 𝑗 𝑢 – Also in the data Mikael Juselius Sisäinen

The gaps Evolution of the leverage and debt service gaps Graph 2 Per cent Source: Authors’ calculations. Mikael Juselius Sisäinen

Key empirical findings 120 Pre-crisis trend GDP DSR 115 Lev Potential accounting for imbalances Lev 110 DSR Post-crisis trend 105 20 Leverage DSR 10 0 -10 -20 2005q3 2007q3 2009q3 2011q3 2013q3 Sisäinen

Augmented LW filter ∗ = 𝛾 5 (𝑧 𝑢− 1 − 𝑧 𝑢− 1 𝑢 + 𝜘 5 𝑢 𝑧 𝑢 − 𝑧 𝑢 ∗ ∗ ) − 𝜒 52 𝑚𝑓𝑤 ) − 𝜒 51 (𝑠 𝑢 − 𝑠 𝑢 ∗ = 2 𝑧 𝑢− 1 𝑧 𝑢 ∗ ∗ + 𝜘 6 𝑢 + 𝑧 𝑢− 2 (𝜌 𝑢 − 𝜌 ∗ ) = 𝛾 7 (𝜌 𝑢− 1 − 𝜌 ∗ ) + 𝜒 7 (𝑧 𝑢 − 𝑧 𝑢 ∗ ) + 𝜘 7 𝑢 ∗ = 𝛾 8 𝑠 𝑢− 1 1 𝑠 𝑢 ∗ ) + 𝜘 8 𝑢 ∗ + ( 1 − 𝛾 8 ) ( 𝑨 𝑢 + 𝜍 4 ∆𝑧 𝑢 𝑨 𝑢 = 𝛾 9 𝑨 𝑢− 1 + 𝜘 9 𝑢 𝑢 = 𝛾 10 𝑚𝑓𝑤 𝑢− 1 + 𝜒 101 (𝑠 𝑢 − 𝑠 𝑢 𝑢− 1 + 𝜘 10 𝑢 𝑚𝑓𝑤 ∗ ) + 𝜒 102 𝑒𝑡𝑠 Mikael Juselius Sisäinen

Filter estimates Posterior estimates for the parameters in the reduced form system 1 Table 3 Parameter Posterior Equation Explained Prior Prior std Posterior std (loading on) (5) ∗ 𝛾 5 0.70 0.20 0.699 0.061 𝑧 𝑢 − 𝑧 𝑢 ( 𝑧 𝑢− 1 − 𝑧 𝑢− 1 ∗ ) 𝜒 51 0.30 0.20 0.051 0.046 ( 𝑠 ∗ ) 𝑢 − 𝑠 𝑢 𝜒 52 0.30 0.20 0.069 0.010 ( 𝑚𝑓𝑤 𝑢 ) (7) 0.70 0.20 0.936 0.016 (𝜌 𝑢 − 𝜌 ∗ ) 𝛾 7 (𝜌 𝑢− 1 − 𝜌 ∗ ) 𝜒 7 0.30 0.20 0.028 0.009 ( 𝑧 𝑢 − 𝑧 𝑢 ∗ ) 𝜌 ∗ 2.00 0.20 1.951 1.776 (8) ∗ 𝛾 8 0.70 0.20 0.617 4 𝑠 𝑢 ∗ ) ( 𝑠 𝑢− 1 (9) 𝑨 𝑢 𝛾 9 0.70 0.20 0.632 0.282 ( 𝑨 𝑢− 1 ) (10) 𝑢 𝛾 10 0.70 0.20 0.979 0.017 𝑚𝑓𝑤 𝑢− 1 ) ( 𝑚𝑓𝑤 0.30 0.20 0.109 0.098 𝜒 101 ( 𝑠 ∗ ) 𝑢 − 𝑠 𝑢 𝜒 102 0.30 0.20 0.149 0.033 𝑢− 1 ) ( 𝑒𝑡𝑠 1 Results from estimating system (5)-(10) using a Kalman filter. Mikael Juselius Sisäinen

Natural rate and output gap The financial cycle: implications for the natural rate and trend output 1 Graph 6 Output gap Natural rate Potential output Per cent Per cent Log levels 1 The finance-neutral variables are the result of estimating system (5)-(10). The Laubach-Williams variables are taken from Laubach and Williams (2015b). Sources: Laubach and Williams (2015b); national data; authors’ calculations. Mikael Juselius Sisäinen

Counterfactual evaluation • Alternative policy rule: + 𝜌 ∗ + 1.5 (𝜌 𝑢− 1 − 𝜌 ∗ ) + 0.5 (𝑧 𝑢− 1 − 𝑧 𝑢− 1 𝑢− 1 ∗ ∗ 𝑗 𝑢 = 𝜍𝑗 𝑢− 1 + ( 1 − 𝜍) 𝑠 ) − 𝜇 𝑒𝑡𝑠 𝑢− 1 • Starts from some 𝑢 0 by following these steps: 1. Derive the natural rate 𝑠 ∗ and the output gap ( 𝑧 𝑢 0 − 1 − 𝑧 𝑢 0 − 1 ∗ ) using the estimated 𝑢 0 − 1 filter. + 𝜌 ∗ + 0.5 𝜌 𝑢 0 − 1 − 𝜌 ∗ + 1 𝑧 𝑢 0 − 1 − 2. Set policy rate for 𝑢 0 as 𝑗 𝑢 0 = 𝜍𝑗 𝑢 0 − 1 + ( 1 − 𝜍) 𝑠 𝑢 0 − 1 ∗ 𝑢 0 − 1 if this leads to 𝑗 𝑢 0 > 0 or set 𝑗 𝑢 0 = 0 otherwise. ∗ 𝑧 𝑢 0 − 1 − 𝜇 𝑒𝑡𝑠 3. Use the estimated VAR with exogenous policy rates (Annex 3) and generate predictions of all variables in the system for time 𝑢 0 conditional on the new policy rate, the retained errors 𝜗 𝑢 0 and outliers Γ𝑡 𝑢 0 . 4. Redo steps 1 to 3 for 𝑢 0 + 1 , 𝑢 0 + 2 … until the end of the sample. • Obvious Lucas critique! Mikael Juselius Sisäinen

Results Leaning against the financial cycle improves outcomes Graph 7 GDP Inflation Log levels Per cent Nominal short run money market rate Real short run money market rate Per cent Per cent 1 In the counterfactual experiment, we set policy based on the augmented Taylor rule that takes account of the finance neutral natural rate, the finance-neutral output g ap and the debt service gap in line with equation (14) with ρ=0.9 and λ=0.75. Results are based on the VAR system (3a, Annex 3) where policy rates are exogenous. We retain the historical errors and outliers of the VAR estimates to derive the evolution of the variables in the counterfactual. The counterfactual policy starts in either in 2003 Q1 or 1996 Q1. Sources: National data; authors’ calculations. Mikael Juselius Sisäinen

Results Leaning against the financial cycle improves outcomes Graph 7 Leverage gap Debt service gap Per cent Per cent Natural rate Per cent 1 In the counterfactual experiment, we set policy based on the augmented Taylor rule that takes account of the finance neutral natural rate, the finance-neutral output g ap and the debt service gap in line with equation (14) with ρ=0.9 and λ=0.75. Results are based on the VAR system (3a, Annex 3) where policy rates are exogenous. We retain the historical errors and outliers of the VAR estimates to derive the evolution of the variables in the counterfactual. The counterfactual policy starts in either in 2003 Q1 or 1996 Q1. Sources: National data; authors’ calculations. Mikael Juselius Sisäinen

Conclusion • Allowing for financial factors yields – Role for endogenous decline in interest rates – Natural rates perhaps not a useful concept – Nominal rates matter through debt servicing – Raising rates in times of high debt servicing difficult -> tempting to lower rates or keep them fixed • Policy evaluation (mind: Lucas critique!) – Policy has a first-order impact on financial imbalances – Can lead to boom-bust dynamics and even permanent losses (gains?) – Substantial counterfactual gains from systematic leaning Mikael Juselius Sisäinen

Thank you for your attention! Mikael Juselius Sisäinen

Annex Mikael Juselius Sisäinen

CI results Results for the long-run relationships 1 Table 1 Rank test statistics 2 Rank 0 1 2 3 p-value 0.00*** 0.00*** 0.02** 0.16 Cointegrating vectors 𝑠 𝑗 𝑀 , 𝑢 (𝑑𝑠 − 𝑧) 𝑢 𝑗 𝑢 𝑞 𝐵 , 𝑢 𝛾 𝑚𝑓𝑤 1 -1 (3) - - 1 5.54*** - 𝛾 𝑒𝑡𝑠 𝛾 𝑡𝑞𝑠 - 1 -1 (3) 1 Stars indicate the level of significance. Where ***/**/* correspond to the 1% / 5% / 10% significance level. 2 Rank test: p-values of the null hypothesis that the rank is less or equal to the specific integer. 3 Coefficient restricted to -1, which cannot be rejected. Test statistics are reported in Annex 2. Mikael Juselius Sisäinen

US gaps Mikael Juselius Sisäinen

Stability: US gaps Real-time estimates of the gaps 1 In per cent Graph A6.1 Leverage gap 2 Debt service gap 1 Real-time estimates include an updated estimation of the aggregate asset price index. 2 Gaps are estimated with a sample that starts 1985 Q1 and ends in Q1 of the year indicated in the legend. Source: Authors’ calculations. Mikael Juselius Sisäinen