We construct a meta-ranking of 315 economics journals based on 38 different individual rankings. Our ranking incorporates both bibliometric measures from three different databases (Web of Knowledge, RePEc and Google Scholar) and previous rankings in the literature. Furthermore, we account for...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

In this paper we present the Ifo Investment Database, which provides annual investment data for 12 investment assets in 50 German industries from 1991 onward. The data is consistent with national accounts statistics provided by the German Federal Statistical Office and is based on investments in...

This paper investigates the potential for a further increase in trade between the fifteen old EU members and the twelve new countries having joined in 2004 and 2007 that results from a convergence of the new members' institutions towards the level of the EU-15 in accordance with the Acquis...

This articles investigates the recent trends in co-authorship in economics. Using data from more than 700.000 journal articles we show that the average number of authors per article has increased over the last years. This process is likely to be continued in the future. In a regression analysis...

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden-Württemberg) and Eastern Germany. We overcome the problem of a...

We examine how regularly scheduled macroeconomic announcements for the U.S., Germany and the euro area affect the German stock market, using high-frequency, minute-by-minute DAX data. Our study extends the literature on high-frequency announcement effects in several ways. First, we account for...

In this paper, we ask whether it is possible to forecast gross value-added (GVA) and its sectoral subcomponents at the regional level. With an autoregressive distributed lagmodel we forecast total and sectoral GVA for one German state (Saxony) with more than 300 indicators from different...