An ongoing debate in the literature on efficiency of higher education institutions concerns the indicator for research output in the empirical analysis. While several studies chose to use the number of publications, others rely on the overall amount of research grants. The present study...

The monthly ifo Business Survey is the basis for numerous economic indicators, such as the ifo Business Climate Index Germany. Moreover, the anonymized micro data can be used for a wide range of research projects. In order to obtain robust results, the panel of survey participants must be large...

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...

The ifo Business Climate Index for Germany is considered as the most important leading indicator for the German economy. Media reports often refer to the mood in German boardrooms. Based on a survey conducted in May 2023, we show that most of the around 9,000 respondents to the monthly ifo...

Using new survey data on quantitative growth expectations of firms in Germany, we show that firms resort to local information when forming expectations about aggregate growth. Firms extrapolate from the economic situation in their county, industry growth and their individual business situation....

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 lag model we forecast total and sectoral GVA for one German state (Saxony) with more than 300 indicators from different...

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...

We introduce archetypal analysis as a tool to describe and categorize scientists. This approach identifies typical characteristics of extreme ('archetypal') values in a multivariate data set. These positive or negative contextual attributes can be allocated to each scientists under...