Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments October 28, 2022 erstellt
Description:
Using the full text of 200 million pages of 13,000 US local newspapers and state-of-the-art machine learning methods, we construct a novel 170-year-long time series measure of economic sentiment at the country and state level, which expands the existing measures in both the time series (by over a century) and the cross section. We show that our measure predicts economic fundamentals such as GDP (both nationally and locally), consumption, and employment growth, even after controlling for commonly-used predictors. Our measure is distinct from the information in expert forecasts, and leads its consensus value. We use the text to isolate information about current and future events and show that it is the latter that drives our predictability results