We study how firms adjust the bundles of management practices they adopt over time, using repeated survey data collected in Germany from 2012 to 2018. By employing unsupervised machine learning, we leverage high-dimensional data on human resource policies to describe clusters of management...

The positive role of transformational leadership on productivity and mental wellbeing has long been established. Transformational leadership behavior may be particularly suited to navigate times of crisis which are characterized by high levels of complexity and uncertainty. We exploit...

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed whenthe ratio of volatilities is time-varying....

This paper deals with stress tests for credit risk and shows how exploiting the discretion when setting up and implementing a model can drive the results of a quantitative stress test for default probabilities. For this purpose, we employ several variations of a CreditPortfolioView-style model...

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...