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...

In this paper we assess the information content of seven widely cited early indicators for the euro area with respect to forecasting area-wide industrial production. To this end, we use various tests that are designed to compare competing forecast models. In addition to the standard...

In socio-economic sciences the RePEc network (Research Papers in Economics) has become an essential source for the gathering and the spread of both existing and new economic research. Furthermore, it is currently the largest bibliometric database in economic sciences containing 33 different...

We tackle the nowcasting problem at the regional level using a large set of indicators (regional, national and international) for the years 1998 to 2013. We explicitly use the ragged-edge data structure and consider the different information sets faced by a regional forecaster within each...

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 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...

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...

This paper applies component-wise boosting to the topic of regional economic forecasting. Component-wise boosting is a pre-selection algorithm of indicators for forecasting. By using unique quarterly real gross domestic product data for two German states (the Free State of Saxony and...

Over the last decade, the topic of regional economic forecasting has become increasingly prevalent in academic literature. The most striking problem in this context is data availability at a regional level. However, considerable methodological improvements have been made to address this problem....

It is well-known that the distribution of citations to articles in a journal is skewed. We ask whether journal rankings based on the impact factor are robust with respect to this fact. We exclude the most cited paper, the top 5 and 10 cited papers for 100 economics journals and recalculate the...