From Micro to Macro: Essays in Textual Analysis

Orientador(a): Marcelo Medeiros

This study exploits non-conventional data sources such as newspaper textual data and internet searches from Google Trends in two empirical problems: (i) analysing the impacts of mobility on cases and deaths due to Covid-19; (ii) nowcasting GDP in high-frequency. The first paper resorts to unstructured data to control for non-observable behavioural effects and finds that an increase in residential mobility significantly reduces Covid-19 cases and deaths over a 4-week horizon. The second paper uses unstructured data sources to nowcast GDP on a weekly basis, showing that textual data and Google Trends can significantly enhance the quality of nowcasts (measured by MSE, MAE and other metrics) compared to Focus’s market expectations as a benchmark. In both cases, unstructured data was revealed to be a valuable source of information not encoded in structured indicators.