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Frederik Lund-Thomsen

29 January 2024
RESEARCH BULLETIN - No. 115
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Abstract
When inflationary pressures started intensifying in 2022, the world’s major central banks faced a dilemma. They could rapidly tighten monetary policy at the risk of fuelling financial distress after years of ultra-low interest rates and balance sheet expansion. Or they could take a more gradual approach to fighting inflation that would protect the financial system, but risk high inflation becoming entrenched. While severe financial instability may be an unlikely event (or “tail risk”), it can have devastating macroeconomic consequences. Quantifying financial stability trade-offs therefore requires a way to gauge the three-way interaction between monetary policy, financial stability conditions and tail risks to the economy.
JEL Code
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
G01 : Financial Economics→General→Financial Crises
31 July 2023
WORKING PAPER SERIES - No. 2833
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Abstract
We propose a novel empirical approach to inform monetary policymakers about the potential effects of policy action when facing trade-offs between financial and macroeconomic stability. We estimate a quantile vector autoregression (QVAR) for the euro area covering the real economy, monetary policy and measures of ex ante and ex post systemic risk representing financial stability. Policy implications are derived from scenario analyses where the associated costs and benefits are functions of the projected paths of the potentially asymmetric distributions of inflation and economic growth, allowing us to take a risk management perspective. One exercise considers the intertemporal financial stability trade-off in the context of the global financial crisis, where we find ex post evidence in favour of monetary policy leaning against the financial cycle. Another exercise considers the short-term financial stability trade-off when deciding the appropriate speed of monetary policy tightening to combat inflationary pressures in a fragile financial environment.
JEL Code
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
G01 : Financial Economics→General→Financial Crises