nowcasting and forecasting quarterly world GDP using mixed-frequency models. We find that a recently proposed indicator that …

-related sentiment from each article using an annotated dataset from Media Tenor International and a Long Short-Term Memory neural … network. This sentiment is then applied to adjust the sign of daily topic distributions estimated through the Latent Dirichlet … Allocation algorithm. For the forecasting experiment, we select 10 sign-adjusted topics that show strong correlations with GDP …

This paper derives new theoretical results for forecasting with Global VAR (GVAR) models. It is shown that the presence … Purchasing Managers Indices (PMIs) for forecasting global (48 countries) growth, and compare forecasts from AugGVAR models with a … number of data-rich forecasting methods, including Lasso, Ridge, partial least squares and factor-based methods. It is found …

-time out-of-sample forecasting comparison study with one of the most widely used data sets in the newer forecasting literature … for forecasting consumption developments. …

sentiment indexes from the texts of the most read economic newspapers in Spain. The data are collected through the scraping of … the Digital Periodical and Newspaper Library website. To compute the sentiment, an existing emotional lexicon for Spanish … words has been customized, allowing for inferring sentiment for words in texts. The resulting indexes are later compared to …

novel contribution of this paper is that along with sentiment analysis using commonly used lexicons, we devised a method …