Research

Research Projects

Reading Between the Lines: Uncovering Inflation Expectations from Multilingual Media Coverage
Work in progress: This paper examines how households’ inflation perceptions and expectations respond to European Central Bank (ECB) communication when filtered through national media in Germany, France, Italy, and Spain. Using 55,490 newspaper articles from 2013 to 2025, I construct measures of the frequency and tone of ECB-related coverage and link them to survey-based inflation perceptions and expectations. The results reveal substantial cross-country differences in both exposure and qualitative framing: German media frequently connect ECB communication to inflation, Italian media emphasize financial markets, France employs a more negative framing and Spanish coverage shows highly volatile tone. Estimates from a Bayesian VAR show stronger prominence of high inflation in media shifts inflation expectations persistently in Germany and France. These findings highlight the limits of centralized monetary communication in a multilingual currency union.

Using Natural Language Processing to Identify Monetary Policy Shocks [Working Paper]
with Marc Schranz and Larissa Schwaller
Abstract: Identifying the causal effects of monetary policy is challenging due to the endogeneity of policy decisions. In recent years, high-frequency monetary policy surprises have become a popular identification strategy. To serve as a valid instrument, monetary policy surprises must be correlated with the true policy shock (relevant) while remaining uncorrelated with other shocks (exogenous). However, market-based monetary policy surprises around Federal Open Market Committee (FOMC) announcements often suffer from weak relevance and endogeneity concerns. This paper explores whether text analysis methods applied to central bank communication can help mitigate these concerns. We adopt two complementary approaches. First, to improve instrument relevance, we extend the dataset of monetary policy surprises from FOMC announcements to policy-relevant speeches by the Federal Reserve Board chair and vice chair. Second, using natural language processing techniques, we predict changes in market expectations from central bank communication, isolating the component of monetary policy surprises driven solely by communication. The resulting language-driven monetary policy surprises exhibit stronger instrument relevance, mitigate endogeneity concerns and produce impulse responses that align with standard macroeconomic theory.

The Phillips Trade-off from a Historical Perspective: A Multi-Country Analysis
Abstract: I estimate Bayesian VARs and use two identification strategies to analyse the impact of structural disturbances on the unemployment-inflation trade-off for different monetary regimes in seven countries. Using two to four sub-samples per country, I obtain three key results. First, sub-periods starting in the 1970s are associated with stronger responses from economic variables, leading to greater positive and negative Phillips trade-offs. Second, I observe a muted reaction to some shocks after the Great Financial Crisis. Finally, I find that the United States and the Euro Area often present unique reactions to structural disturbances. Altogether, results over the sub-samples differ significantly. Hence, using shorter samples, fixed coefficients, and including multiple countries proves vital in understanding economic forces.

Other Projects

Comparing the pandemic recession of 2020 to the historical recession experience
with Nina Dorta and Christian Hepenstrick
Economic Note at the Swiss National Bank, 2022

The Impact of Permanent and Transitory Shocks on Monetary Aggregates: A Structural VAR Approach
Master Thesis, 2020