Welcome to my personal website!
I am a macroeconomist by training with experience in central banking and academic research.
Currently seconded to the European Central Bank, I previously worked as a senior economist in the modelling unit at Norges Bank.
I hold a PhD in Economics (2018) from the Université Paris 1 Pantheon-Sorbonne, and my research interests include macroeconomic modelling, and macro-financial linkages.
Recently, I have written a package for policy work and research with DSGE models: MacroModelling.jl
You can find the materials for the workshop here: MacroModelling.jl workshop
MacroModelling.jl is a Julia (Bezanson et al., 2017) package for developing and solving dynamic stochastic general equilibrium (DSGE) models. These kinds of models describe the behavior of a macroeconomy and are particularly suited for counterfactual analysis (economic policy evaluation) and exploring / quantifying specific mechanisms (academic research).
The goal of this package is to reduce coding time and speed up model development by providing functions for working with discrete-time DSGE models. The user-friendly syntax, automatic variable declaration, and effective steady state solver facilitate fast prototyping of models. The package includes several pre-defined models from prominent economic papers, providing an immediate starting point for users. The target audience for the package includes central bankers, regulators, graduate students, and others working in academia with an interest in DSGE modelling.
The package supports programmatic model definition. Once the model is defined, the package finds the solution for the model dynamics knowing only the model equations and parameter values. The model dynamics can be solved for using first, (pruned) second, and (pruned) third-order perturbation solutions (Andreasen et al., 2017; O. Levintal, 2017; Villemot, 2011), leveraging symbolic and automatic differentiation. Furthermore, the package can be used to calibrate parameters, match model moments, and estimate the model on data using the Kalman filter (Durbin & Koopman, 2012). The package is designed to be user-friendly and efficient. Once the functions are compiled and the non-stochastic steady state (NSSS) has been found, the users benefit from fast and convenient functions to generate outputs or change parameters.
MacroModelling.jl: A Julia package for developing and solving dynamic stochastic general equilibrium models
Should monetary policy lean against financial stability risks? This has been a subject of fierce debate over the last decades. We contribute to the debate about “leaning against the wind” (LAW) along two lines. First, we extend the Svensson (2017) framework to address a critique that the framework does not consider the lower-frequency financial cycle. We then evaluate the costs and benefits of LAW in the extended framework for the euro area and find that the costs outweigh the benefits. Second, we assess the costs and benefits of monetary and macroprudential policy. We find that macroprudential policy has net marginal benefits in addressing risks to financial stability in the euro area, whereas monetary policy has net marginal costs. This would suggest that an active use of macroprudential policies targeting financial stability risks would alleviate the burden on monetary policy to “lean against the wind.”
“Leaning Against the Wind”, Macroprudential Policy and the Financial Cycle
Leaning against persistent financial cycles with occasional crises
We study conditions under which a leaning against the wind (LAW)-type monetary policy is advisable to address risks to financial stability. We do so within a regime-switching dynamic stochastic general equilibrium (DSGE) model with endogenous crises and persistent financial cycles based on partly backward-looking house price beliefs. Under empirically plausible financial cycles, LAW increases inflation volatility because it amplifies the effects of supply shocks on inflation. It also leads to a lower average inflation, resulting in more frequent episodes of a binding lower bound on interest rates. LAW is advisable only if (i) the central bank puts more weight on output stability or (ii) financial cycles are less persistent than observed.
Using supervisory loan-level data on corporate loans, we show that banks facing high levels of non-performing loans relative to their capital and provisions were more likely to grant forbearance measures to the riskiest group of borrowers. More specifically, we find that risky borrowers are more likely to get an increase in the overall limit or the maturity of a loan product from a distressed lender. As a second step, we analyse the effectiveness of this practice in reducing the probability of default. We show that the most common measure of forbearance is effective in the short run but no forbearance measure significantly reduces the probability of default in the long run. Our evidence also suggests that forbearance and new lending are substitutes for banks, as high shares of forbearance are negatively correlated with new lending to the same group of borrowers. Taken together, these findings can help policy makers shape surveillance and regulation in a future recovery from the Covid-19 pandemic.
Forbearance Patterns in the Post-Crisis Period
We develop a macroprudential contagion stress test framework to examine how a network of Norwegian banks can amplify a shock to bank capital at the macro level. The framework looks at how fire sales of common asset holdings can lead to valuation losses for banks (indirect contagion), and how recapitalisation of banks can lead to direct contagion. We perform Monte Carlo simulations to quantify contagion-driven systemic risk and to evaluate the importance of the mechanisms in our model. Using data for 22 banks from 2019 Q2 we find that losses due to contagion can reach 2 percentage points (pp) of the banking sector's Common Equity Tier 1 (CET1) ratio, but most likely losses are around one-fourth of this. The losses result almost exclusively from indirect contagion. Further, we find that losses are high in the cases where banks quickly run into funding problems. We also find that market liquidity and which assets banks' fire sale first (pecking order) are important determinants of the results. Last but not least, losses due to contagion are highly correlated with losses on covered bonds.
A macroprudential contagion stress test framework
The first part of our study shows that in a static analysis the currently proposed regulatory framework is not sufficient and for shocks of a size comparable to that of 2007-2009 bailouts would still be needed at the expense of the European taxpayer, even if the Banking Union architecture of 2023 were already in place today. The second part of the study finds that the costs to the economy go much further than the billions necessary to bail out banks. Building on a non-linear dynamic macroeconomic model whose baseline scenario coincides with the Commission’s forecasts, we estimate the costs at the euro area level of a medium-sized financial shock (-10% losses in banks’ assets compared to 2007-2009) occurring in 2014 at a cumulated loss of EUR 1 trillion in GDP (approximately -9.4% of the 2016 forecast GDP), job losses amounting to 1.91 million (-1.19% supposing a total workforce of 161.3 million according to the model forecast for 2016) and an increase of EUR 51.4 billion in government debt in 2016 (+0.5% of the 2016 forecast debt). Needless to say, the cost would be much higher in the absence of the
resolution pillar of the Banking Union (which is not scheduled to be fully in place until 2023).
The most effective remedy, according to our simulations, is to increase the banking sectors’ equity ratio target to 9% or more and to lower dividends, in order to make the economy more shock-resistant in the medium term. The study does not claim that an equity ratio target of 9% is the optimal value, although we suspect it to be close to the lower bound, below which the purpose of dampening the impact of a significant shock cannot be reached. We show that the cost of implementing this increased equity ratio is more than offset by the reduction in losses caused by a financial shock. In addition, the separation of retail banks from investment banks, euro area deposit guarantees and a review of fiscal policy seem to provide more efficient tools to mitigate the effects of a new crash than what is currently programmed by the European Banking Union project. An augmented Single Resolution Fund (SRF) with more timely implementation would also certainly reduce the cost of a new crash, but would be insufficient to prevent turmoil in the euro area economy.
Making the European Banking Union Macro-Economically Resilient: Cost of Non-Europe Report
European Central Bank (Secondment) · since 2022
DG Macroprudential Policy & Financial Stability - Systemic Risk & Financial Institutions, Stress Test Modelling · Frankfurt (Germany)
Norges Bank (Senior Economist) · 2018 - 2022
Financial Stability Department - Modelling Unit · Oslo (Norway)
European Central Bank (Short Term Research Analyst & PhD Traineeship) · 2017 - 2018
DG Research - Financial Research · Frankfurt (Germany)
DG Macroprudential Policy & Financial Stability - Stress Test Modelling/Macro-Financial Linkages
Central Bank of Ireland (PhD Traineeship) · 2016 - 2017
Financial Stability Division - Research · Dublin (Ireland)
BNP Paribas (Internship) · 2012
Equity and Commodity Derivatives Trading - German Retail Market Making Desk · Paris (France)
Nomura - Investment Banking (Internship) · 2011
Technology/Media/Telecom Mergers & Acquisitions Team · London (UK)
ESCP Europe - Master in Management · Paris (France) and London (UK) · 2010 - 2012
Universität Münster - BSc in Business Administration · Münster (Germany) · 2007 - 2010