This paper suggests a causal framework for disentangling individual level treatment effects and interference effects, i.e., general equilibrium, spillover, or interaction effects related to treatment distribution. Thus, the framework allows for a relaxation of the Stable Unit Treatment Value...

We propose a novel time-varying parameters mixed-frequency dynamic factor model which is integrated into a dynamic model averaging framework for macroeconomic nowcasting. Our suggested model can efficiently deal with the nature of the real-time data flow as well as parameter uncertainty and...

We study the implications of the Eurosystem's expanded Asset Purchase Programme (APP) for the bank lending business of euro area banks with euro area non-financial corporations (NFCs) using microeconometric matching techniques. Based on confidential bank-level data on quantitative balance sheet...

In response to strong revenue and income losses that a large share of the self-employed faced during the COVID-19 pandemic, the German federal government introduced a €50bn emergency aid program. Based on real-time online-survey data comprising more than 20,000 observations, we analyze the...

The economic policy response to COVID-19 lockdowns included a variety of measures. Their effects on non-financial firms, however, remain unclear. To shed light on the effect of transfers, we investigate the effect of German emergency aid transfers (November-December aid), a program designed for...

In this paper we apply statistical inference techniques to build neural network models which are able to explain the prices of call options written on the German stock index DAX. By testing for the explanatory power of several input variables serving as network inputs, some insight into the...

In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...