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Josef Ruzicka

9 November 2023
We empirically analyze the interaction of monetary policy with financial stability and the real economy in the euro area. For this, we apply a quantile vector autoregressive model and two alternative estimation approaches: simulation and local projections. Our specifications include monetary policy surprises, real GDP, inflation, financial vulnerabilities and systemic financial stress. We disentangle conventional and unconventional monetary policy by separating interest rate surprises into two factors that move the yield curve either at the short end or at the long end. Our results show that a build-up of financial vulnerabilities tends to be accompanied initially by subdued financial stress which resurges, however, over a medium-term horizon, harming economic growth. Tighter conventional monetary policy reduces inflationary pressures but increases the risk of financial stress. [...]
JEL Code
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
G01 : Financial Economics→General→Financial Crises
G10 : Financial Economics→General Financial Markets→General
14 February 2019
This paper presents a tractable, transparent and broad-based domestic cyclical systemic risk indicator (d-SRI) that captures risks stemming from domestic credit, real estate markets, asset prices, and external imbalances. The d-SRI increases on average several years before the onset of systemic financial crises, and its early warning properties for euro area countries are superior to those of the total credit-to-GDP gap. In addition, the level of the d-SRI around the start of financial crises is highly correlated with measures of subsequent crisis severity, such as GDP declines. Model estimates suggest that the d-SRI has significant predictive power for large declines in real GDP growth three to four years down the line, as it precedes shifts in the entire distribution of future real GDP growth and especially of its left tail. The d-SRI therefore provides useful information about both the probability and the likely cost of systemic financial crises many years in advance. Given its timely signals, the d-SRI is a useful analytical tool for macroprudential policymakers.
JEL Code
G01 : Financial Economics→General→Financial Crises
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling