Little is known about how socioeconomic characteristics of executive teams affect corporate governance in banking. Exploiting a unique dataset, we show how age, gender, and education composition of executive teams affect risk taking of financial institutions. First, we establish that age,...

Single equation models are well established among academics and practitioners to perform temporal disaggregation of low frequency time series using available related series. In this paper, we propose an extension that exploits information from the cross-sectional dimension. More specifically, we...

There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such as private consumption or unemployment. However, applications on forecasting GDP are rather rare. In this paper we incorporate Google search data into a Bridge Equation Model, a...

Data revisions to national accounts pose a serious challenge to policy decision making. Well-behaved revisions should be unbiased, small and unpredictable. This paper shows that revisions to German national accounts are biased, large and predictable. Moreover, using filtering techniques designed...

The German economy is an important economic driver in the Euro-area in terms of gross domestic product, labour force and international integration. We provide a state of the art estimate of the German output gap between 1995 and 2022 and present a nowcasting scheme that accurately predicts the...

We study how millions of highly granular and weekly household scanner data combined with novel machine learning techniques can help to improve the nowcast of monthly German inflation in real time. Our nowcasting exercise targets three hierarchy levels of the official consumer price index. First,...