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...

Many prominent forecasters publish their projections at an annual frequency. However, for applied work, an estimate of the underlying quarterly forecasts is often indispensable. We demonstrate that a simple state-space model can be used to obtain good estimates of the quarterly forecasts...

We analyze four economic sentiment indicators for the German economy regarding their ability to forecast economic activity. Using cross correlations and Granger causality tests we find that the ifo business expectations (ifo), the Purchasing Managers Index (PMI) and the ZEW Indicator of Economic...

While there is an extensive literature concerning forecasting with many predictors, there are but few attempts to allow for non-linearity in such a "data-rich environment". Using macroeconomic data, we show that substantial gains in forecast accuracy can be achieved by including both squares and...

We investigate to what extent it is feasible to improve model-based near-term GDP forecasts by combining them with judgmental (quarterly) forecasts by professional analysts (Consensus survey) in a real-time setting. Our analysis covers the G7 countries over the years 1999-2013. We consider as...

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In the empirical application, we forecast U.S. business cycle turning points with state-level employment data. We find that forecasts...