We analyze how financial stability concerns discussed during Federal Open Market Committee (FOMC) meetings influence the Federal Reserve's monetary policy imple- mentation and communication. Utilizing large language models (LLMs) to analyze FOMC minutes from 1993 to 2022, we measure both...

We construct an Economic Policy Uncertainty (EPU) index for Malta based on the methodology of Baker, Bloom and Davis (2015) using articles published between 2004 and 2022 from four Maltese news portals. The index spikes during general elections and other significant local or international...

While many digital technologies provide opportunities for creating business models with an impact on sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy demand. In our study, we present a novel approach...

Dieses Working Paper untersucht den Einsatz von Generative AI Anwendungen zur Prognose von Leitzinsentscheidungen der Federal Reserve. Es bewertet, ob diese Anwendungen eingesetzt werden können, um Leitzinsänderungen vorherzusagen, und vergleicht ihre Vorhersagegenauigkeit mit den...

We document the importance of local information in mass media for the political engagement of citizens and accountability of politicians. We study this in the context of Canada, where until 1958, competition in television markets was suppressed—Canadians received either public or private...

This paper measures the exposure of industries and occupations to 40 digital technologies that emerged over the past decade and estimates their impact on European employment. Using a novel approach that leverages sentence transformers, we calculate exposure scores based on the semantic...

This paper introduces a novel database of text features extracted from the speeches of 53 central banks from 1996 to 2023 using state-of-the-art NLP methods. We establish four facts: (1) central banks with floating and pegged exchange rates communicate differently, and these differences are...

I contribute to previous research on the efficient integration of forecasters' narratives into business cycle forecasts. Using a Bidirectional Encoder Representations from Transformers (BERT) model, I quantify 19,300 paragraphs from German business cycle reports (1998-2021) and classify the...