Abstract This paper reports a broad study using epidemic-related counting data of COVID-19 disease caused by the novel coronavirus (SARS-CoV-2). The considered dataset refers to 119 countries’ daily counts of reported cases and deaths in a fixed period. For the data analysis, it has been...

Despite revolutionizing the work of practicing economists by providing a direct link between neo-classical economic theory and revealed market preference data, Random Utility Theory has yet to guide research applications in global market sustainability. With the worldwide adverse socio-economic...

This paper provides a detailed assessment of the real-time forecast accuracy of a wide range of vector autoregressive models (VAR) that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed-frequency time-varying...

We use Google search data with the aim of predicting unemployment, CPI and consumer confidence for the US, UK, Canada, Germany and Japan. Google search queries have previously proven valuable in predicting macroeconomic variables in an in-sample context. To our knowledge, the more challenging...

This dissertation focuses on describing and explaining business cycle dynamics. Motivated by the extraordinary strong economic downturn in 2008/2009, it emphasis the importance of modeling nonlinearities. This thesis should be regarded as a contribution to applied econometrics and can be...

A stylized fact from laboratory experiments is that there is much heterogeneity in human behavior. We present and demonstrate a computationally practical non-parametric Bayesian method for characterizing this heterogeneity. In addition, we define the concept of behaviorally distinguishable...