We construct an index for measuring negative economic sentiment in Finland by using news titles collected from the Finnish broadcasting company Yle's archive. Our approach uses supervised machine learning text classification for detecting news titles featuring negative economic sentiment, and...

We construct sentiment indices for 20 countries from 1980 to 2019. Relying on computational text analysis, we capture specific language like 'fear', 'risk', 'hedging', 'opinion', and, 'crisis', as well as 'positive' and 'negative' sentiments, in news articles from the Financial Times. We assess...

We describe the evolution of forecasts in the run-up to recessions. The GDP forecasts cover 63 countries for the years 1992 to 2014. The main finding is that, while forecasters are generally aware that recession years will be different from other years, they miss the magnitude of the recession...

Most macroeconomic data is continuously revised as additional information becomes available. We suggest that revisions of data is an important source of uncertainty about the state of the economy. This paper evaluates the quality of major real macroeconomic Euro area variables, published by...

Most macroeconomic data is continuously revised as additional information becomes available. We suggest that revisions of data is an increasingly important source of uncertainty about the state of the economy and offer an alternative channel of uncertainty - data uncertainty. This paper adds on...

Because macroeconomic data is published with a substantial delay, assessing the health of the economy during the rapidly evolving Covid-19 crisis is challenging. We develop a fever curve for the Swiss economy using publicly available daily financial market and news data. The indicator can be...

This study utilizes the dynamic factor model of Giannone et al. (2008) in order to make now-/forecasts of GDP quarter-on-quarter growth rates in Switzerland. It also assesses the informational content of macroeconomic data releases for forecasting of the Swiss GDP. We find that the factor model...

We propose new forecast combination schemes for predicting turning points of business cycles. The combination schemes deal with the forecasting performance of a given set of models and possibly providing better turning point predictions. We consider turning point predictions generated by...

This paper presents new evidence on the benefits of conditioning quarterly model forecasts on monthly current-quarter data. On the basis of a quarterly Bayesian vector error corrections model, the findings indicate that such conditioning produces economically relevant and statistically...

Since November 2007, the Federal Open Market Committee (FOMC) of the U.S. Federal Reserve has regularly published participants’ qualitative assessments of the uncertainty attending their individual forecasts of real activity and inflation, expressed relative to that seen on average in the...