In any dataset with individual forecasts of economic variables, some forecasters will perform better than others. However, it is possible that these ex post differences reflect sampling variation and thus overstate the ex ante differences between forecasters. In this paper, we present a simple...

This paper presents a MIDAS type mixed frequency VAR forecasting model. First, we propose a general and compact mixed frequency VAR framework using a stacked vector approach. Second, we integrate the mixed frequency VAR with a MIDAS type Almon lag polynomial scheme which is designed to reduce...

We provide a wind power forecasting methodology that exploits many of the actual data's statistical features, in particular both-sided censoring. While other tools ignore many of the important stylized facts or provide forecasts for short-term horizons only, our approach focuses on medium-term...

Von der Preisentwicklung geht derzeit ein erhebliches Risiko für die weitere wirtschaftliche Entwicklung aus. Die Teuerungen bei Lebensmitteln und Energie haben die Kaufkraft der Arbeitnehmer reduziert und dämpfen auf diese Weise die Erholung des privaten Verbrauchs, auf der die...

Nach langen Jahren stagnierender und sogar rückläufiger Produktionsentwicklung folgt auf 2006 und 2007 auch 2008 eine positive Gesamtbilanz der Bauwirtschaft. Der konjunkturelle Ausblick auf das Jahr 2009 ist allerdings getrübt. Die deutsche Bauproduktion wird preisbereinigt 2009 fast...

GDP forecasters face tough choices over which leading indicators to follow and which forecasting models to use. To help resolve these issues, we examine a range of monthly indicators to forecast quarterly GDP growth in a major emerging economy, Russia. Numerous useful indicators are identified...

Data on Google searches help predict the unemployment rate in the U.S. But the predictive power of Google searches is limited to short-term predictions, the value of Google data for forecasting purposes is episodic, and the improvements in forecasting accuracy are only modest. The results,...

In this paper a Bayesian vector autoregressive model for nowcasting the seasonally non-adjusted unemployment rate in EU-countries is developed. On top of the official statistical releases, the model utilizes Google search data and the effect of Google data on the forecasting performance of the...

There are over 3 billion searches globally on Google every day. This report examines whether Google search queries can be used to predict the present and the near future unemployment rate in Finland. Predicting the present and the near future is of interest, as the official records of the state...