About

I am currently a Postdoctoral Research Associate at the Economic Statistics Centre of Excellence (ESCoE) , based in the Department of Economics at King’s Business School , King’s College London.

I received my PhD in Economics from King’s Business School, King’s College London, in August 2026, under the supervision of George Kapetanios and Francesca Monti .

My research interests lie in time-series econometrics and applied macroeconomics. My current research investigates the sources of business-cycle fluctuations and how macroeconomic risk builds during periods of financial stress.

Before starting my PhD, I worked at the European Central Bank. I hold an MSc in Economics from Universidad Carlos III de Madrid and a BSc in Economics from the National and Kapodistrian University of Athens.

Research

Working papers

Markov-switching models with high-dimensional transition probabilities

with George Kapetanios

2026

Abstract

This paper develops a penalised maximum-likelihood estimator for Markov-switching vector autoregressive (VAR) models that allows transition probabilities to depend on a high-dimensional set of predictors. By applying ℓ₁ (Lasso) regularisation to the transition probability coefficients, the approach performs variable selection and aids parameter estimation. We implement a modified Expectation-Maximisation (EM) algorithm that accommodates latent regimes while solving a convex, penalised multinomial logit problem for transition coefficients at each maximisation step. Monte Carlo experiments show that the estimator recovers sparse transition structures as sample size increases, tends to select parsimonious models in moderate samples, and remains effective for regime inference in high-dimensional settings. An empirical application to Growth-at-Risk with 129 macro-financial predictors on US data, demonstrates the estimator's ability to select distinct sets of predictors governing entry into and exit from growth vulnerability regimes.

Working paper

Demand and supply shocks over the business cycle

2025

Presentations: Bank of England (Seminar); 5th Sailing the Macro & 12th Ghent Workshop on Empirical Macroeconomics (Poster)

Abstract

This paper examines which structural forces account for U.S. business cycle fluctuations. It combines a trend-cycle Bayesian VAR with a joint max-share identification scheme that offers an alternative to set-identification under sign restrictions. Separating trend from cycle, the framework decomposes business cycle dynamics into four structural components-monetary policy, non-policy demand, cost-push, and oil supply shocks-consistent with New Keynesian theory. The results indicate that demand forces dominate real activity and account for a large share of nominal fluctuations at short horizons, while supply forces become pivotal for inflation at medium-run business cycle frequencies (6-32 quarters). Together, the four shocks account for most of the cyclical variation in both output and inflation.

Working paper