Dictionary approaches are at the forefront of current techniques for quantifying central bank communication. This paper proposes embeddings - a language model trained using machine learning techniques - to locate words and documents in a multidimensional vector space. To accomplish this, we...

One of the goals of Saudi Vision 2030 is to keep the unemployment rate at the lowest level to empower the economy. Prior research has shown that an increase in unemployment has a negative effect on a country's Gross Domestic Product (GDP). This paper aims to utilise cutting-edge technology such...

This paper provides a direct understanding of the twin transition from the innovative activity domain. It starts with a technological mapping of the technological innovations characterised by both climate change mitigation/adaptation (green) and labour-saving attributes. To accomplish the task,...

International organizations (IOs) of the United Nations (UN) system publish around 750 evaluation reports per year, offering insights on their performance across project, program, institutional, and thematic activities. So far, it was not feasible to extract quantitative performance measures...

The work by Baker et al. (2016), who propose a dictionary based method and estimate the level of economic policy uncertainty (EPU) based on the occurrence of specific terms in ten leading newspapers in the USA, is among the first ones to detect the potential of text data in economic research....

This paper evaluates whether publicly available daily news lead texts help nowcasting Swiss GDP growth. I collect titles and lead texts from three Swiss newspapers and calculate text-based indicators for various economic concepts. A composite indicator calculated from these indicators is highly...

Financial bubble theories emphasize the importance of behavioral mechanisms cen- tered around investor beliefs, which can be potentially gleaned from prevailing nar- ratives, that reflect investors’ psychological states and link them to economic events. By summarizing market narratives into...