Research

During my PhD, my research has concentrated on developing methods for monitoring and estimating macroeconomic risk. This field focuses on understanding the effects of economy wide shocks on the uncertainty surrounding the economic outlook. Given the prevalence of unusually large fluctuations in economic aggregates in the recent past and the challenging policy environment that it creates, this literature has gained significant momentum in academic research as well as policy making institutions. Important examples include the Federal Reserve Bank and European Central Bank. 

Job Market Paper

Mixing it up: Inflation at risk
Measuring and monitoring macroeconomic uncertainty has become a key concern of contemporary monetary policy and an active field of academic research. In this paper, a joint approach is proposed that allows to construct risk measures that capture the unknown and non-standard distribution of inflation in a way that consistent with central bank preferences. In addition, two algorithms are proposed that enable to monitor how economic predictors affect the risk outlook and how they shift probability mass across the forecast distribution. Both are widely applicable, enhance the interpretability of abroad class of models, and are suitable for real-time applications. In the empirical exercises, the model yields superior point and density forecasts of U.S. CPI inflation. During the recent high-inflation period, inflation risk predominantly increased due to a recovery of the U.S. business cycle and rising commodity prices and was in part balanced by monetary policy and credit spreads.

Working Paper

Probabilistic quantile factor analysis (R&R in the Journal of Business & Economic Statistics) - With Dimitris Korobilis
This paper extends quantile factor analysis to a probabilistic variant that incorporates regularization and computationally efficient variational approximations. By means of synthetic and real data experiments it is established that the proposed estimator can achieve, in many cases, better accuracy than a recently proposed loss-based estimator. We contribute to the literature on measuring uncertainty by extracting new indexes of low, medium and high economic policy uncertainty, using the probabilistic quantile factor methodology. Medium and high indexes have clear contractionary effects, while the low index is benign for the economy, showing that not all manifestations of uncertainty are the same.

Publications in Academic Journals

Monitoring multicountry macroeconomic risk, with Dimitris Korobilis,
Journal of Econometrics, (forthcoming).
Published Version

Nowcasting GDP with a pool of factor models and a fast estimation algorithm, with Sercan Eraslan,
International Journal of Forecasting, Volume 39, Issue 3, July–September 2023, Pages 1460-1476.
Published Version, PDF 

What drives euro area financial market developments? The role of US spillovers and global risk, with Lennart Brandt, Arthur Saint Guilhem, and Ine Van Robays, 2021, ECB Working Paper, No. 2560/May 2021.
Online Version 


Manuscripts under preparation