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Falk Mazelis

Monetary Policy

Division

Monetary Policy Strategy

Current Position

Senior Economist

Fields of interest

Macroeconomics and Monetary Economics

Email

Falk.Mazelis@ecb.europa.eu

Education
2017

PhD in Economics, Humboldt University Berlin

2011

MSc in Industrial Engineering (Dipl.-Ing.), Technical University Berlin

Professional experience
2017-

Senior Economist - Monetary Policy Strategy Division, Directorate General Monetary Policy, European Central Bank

2015-2017

Research Associate - Collaborative Research Center 649 "Economic Risk" and Institute for Economic Theory II, Humboldt University Berlin

2016

Visiting Student Research Collaborator - Princeton University (Bendheim Center for Finance)

2014-2015

PhD Trainee - European Systemic Risk Board, European Central Bank

2011-2014

Fellow - German Research Foundation, Berlin

2010

Summer Analyst - Investment Banking Division, Barclays Investment Bank, London

2009

Intern - Corporate Finance and Transaction Services, Deloitte, Munich

10 September 2021
WORKING PAPER SERIES - No. 2587
Details
Abstract
We analyse the implications of asymmetric monetary policy rules by estimating Markov-switching DSGE models for the euro area (EA) and the US. The estimations show that until mid-2014 the ECB’s response to inflation was more forceful when inflation was above 2% than below 2%. Since then, the ECB’s policy can be characterised as symmetric, and we quantify the macroeconomic implications of this policy change. We uncover asymmetries also in the Fed’s policy, which has responded more strongly in times of crisis. We compute an optimal simple rule for the EA and the US in an environment with the effective lower bound and a low neutral real rate, and find that it prescribes a stronger response to inflation and the output gap when inflation is below target compared to when it is above target. We document its stabilisation properties had this optimal rule been implemented over the last two decades.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
19 May 2021
WORKING PAPER SERIES - No. 2555
Details
Abstract
This paper presents a toolkit for generating optimal policy projections. It makes five contributions. First, the toolkit requires a minimal set of inputs: only a baseline projection for target and instrument variables and impulse responses of those variables to policy shocks. Second, it solves optimal policy projections under commitment, limited-time commitment, and discretion. Third, it handles multiple policy instruments. Fourth, it handles multiple constraints on policy instruments such as a lower bound on the policy rate and an upper bound on asset purchases. Fifth, it allows alternative approaches to address the forward guidance puzzle. The toolkit that accompanies this paper is Dynare compatible, which facilitates its use. Examples replicate existing results in the optimal monetary policy literature and illustrate the usefulness of the toolkit for highlighting policy trade-offs. We use the toolkit to analyse US monetary policy at the height of the Great Financial Crisis. Given the Fed’s early-2009 baseline macroeconomic projections, we find the Fed’s planned use of the policy rate was close to optimal whereas a more aggressive QE program would have been beneficial.
JEL Code
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
27 November 2020
WORKING PAPER SERIES - No. 2495
Details
Abstract
We estimate the effects of interest rate forward guidance (FG) using a parsimonious VAR, augmented with survey forecast data. The identification strategy of FG shocks via sign and zero restrictions is successfully tested by the recovery of true IRFs from simulated data. The identified shocks from the VAR suggest that FG has a stronger effect on macro variables and deviations are more instantaneous compared to the hump-shaped response following unanticipated changes in monetary policy. We apply this evidence to calibrate free parameters of an otherwise estimated DSGE model in order to dampen the FG Puzzle.
JEL Code
C54 : Mathematical and Quantitative Methods→Econometric Modeling→Quantitative Policy Modeling
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
24 June 2020
WORKING PAPER SERIES - No. 2426
Details
Abstract
This paper develops a simple, consistent methodology for generating empirically realistic forward guidance simulations using existing macroeconomic models by modifying expectations about policy announcements. The main advantage of our method lies in the exact preservation of all other shock transmissions. We describe four scenarios regarding how agents incorporate information about future interest rate announcements: “inattention”, “credibility”, “finite planning horizon”, and “learning”. The methodology consists of describing a single loading matrix that augments the equilibrium decision rules and can be applied to any standard DSGE, including large-scale policy-institution models. Finally, we provide conditions under which the forward guidance puzzle is resolved.
JEL Code
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
23 June 2020
WORKING PAPER SERIES - No. 2424
Details
Abstract
Forward guidance operates via the expectations formation process of the agents in the economy. In standard quantitative macroeconomic models, the expectations are unobserved state variables and little scrutiny is devoted to analysing the dynamic behaviour of these expectations. We show that the introduction of survey and financial market-based forecasts in the estimation of the model disciplines the expectations formation process in DSGE models. When the model-implied expectations are matched to observed expectations, the additional information of the forecasts restrains the agents’ expectations formation. We argue that the reduced volatility of the agents’ expectations dampens the model reactions to forward guidance shocks and improves the out-of-sample forecast accuracy of the model. Furthermore, we evaluate the case for introducing a discount factor as a reduced form proxy for a variety of microfounded approaches, proposed to mitigate the forward guidance puzzle. Once data on expectations is considered, the empirical support to introduce a discount factor dissipates.
JEL Code
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles
E47 : Macroeconomics and Monetary Economics→Money and Interest Rates→Forecasting and Simulation: Models and Applications
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
13 May 2020
WORKING PAPER SERIES - No. 2406
Details
Abstract
Macroprudential policies are often aimed at the commercial banking sector, while a host of other non-bank financial institutions, or shadow banks, may not fall under their jurisdiction. We study the effects of tightening commercial bank regulation on the shadow banking sector. We develop a DSGE model that differentiates between regulated, monopolistic competitive commercial banks and a shadow banking system that relies on funding in a perfectly competitive market for investments. After estimating the model using euro area data from 1999 – 2014 including information on shadow banks, we find that tighter capital requirements on commercial banks increase shadow bank lending, which may have adverse financial stability effects. Coordinating macroprudential tightening with monetary easing can limit this leakage mechanism, while still bringing about the desired reduction in aggregate lending. In a counterfactual analysis, we compare how macroprudential policy implemented before the crisis would have dampened the business and lending cycles.
JEL Code
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
Network
Research Task Force (RTF)
20 February 2020
WORKING PAPER SERIES - No. 2376
Details
Abstract
This paper examines the interactions of macroprudential and monetary policies. We find, using a range of macroeconomic models used at the European Central Bank, that in the long run, a 1% bank capital requirement increase has a small impact on GDP. In the short run, GDP declines by 0.15-0.35%. Under a stronger monetary policy reaction, the impact falls to 0.05-0.25%. The paper also examines how capital requirements and the conduct of macroprudential policy affect the monetary transmission mechanism. Higher bank leverage increases the economy's vulnerability to shocks but also monetary policy's ability to offset them. Macroprudential policy diminishes the frequency and severity of financial crises thus eliminating the need for extremely low interest rates. Countercyclical capital measures reduce the neutral real interest rate in normal times.
JEL Code
E4 : Macroeconomics and Monetary Economics→Money and Interest Rates
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
G20 : Financial Economics→Financial Institutions and Services→General
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
27 March 2019
WORKING PAPER SERIES - No. 2257
Details
Abstract
We estimate the natural rate of interest for the US and the euro area in a semi-structural model comprising a Taylor rule. Our estimates feature key elements of Laubach and Williams (2003), but are more consistent with using conventional policy rules: we model inflation to be stationary, with the output gap pinning down deviations of inflation from its objective (rather than relative to a random walk). We relax some constraints on the correlation of latent factor shocks to make the original unobserved-components framework more amenable to structural interpretation and to reduce filtering uncertainty. We show that resulting natural rate metrics are more consistent with estimates from structural models.
JEL Code
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy