In this research, we propose the bootstrap procedure as a method for train/test splitting in machine learning algorithms for classification. We show that this resampling method can be a reliable alternative to cross validation and repeated random test/train splitting algorithms. The bootstrap...

Innovations, be they radical new products or technology improvements are widely recognized as a key factor of economic growth. To identify the factors triggering innovative activities is a main concern for economic theory and empirical analysis. As the number of hypotheses is large, the process...

This paper provides new evidence on the sustainability of public finances in German states (Laender) by exploiting a newly compiled database covering the years 1950-2011. Unlike previous studies on Germany, we analyze fiscal sustainability by applying second generation panel cointegration...

By using a prospective, nation-wide, population-based out-of-hospital cardiac arrest (OHCA) database (All-Japan Utstein Registry, January 1, 2005 to December 31, 2012), we examined the disparity in emergency medical services across Japan and found significant disparities among prefectures. By...

Location-based social media data is, increasingly, an important facilitator of exploring the movement of goods and people in and between countries across the globe. Typical examples include Twitter, Facebook, Foursquare. As with all social media data outputs, the fundamental value of...

We represent the dynamic relation among variables in vector autoregressive (VAR) models as directed graphs. Based on these graphs, we identify so-called strongly connected components (SCCs). Using this graphical representation, we consider the problem of variable selection. We use the relations...

This paper proposes a new Index for measuring intra-generational redistribution in PAYG pension schemes. This index solely requires information on contributions and pension benefits of retirees, eliminating the involvement of the contribution side in a PAYG pension scheme. As an application, we...

We combine the factor augmented VAR framework with recently developed estimation and identification procedures for sparse dynamic factor models. Working with a sparse hierarchical prior distribution allows us to discriminate between zero and non-zero factor loadings. The non-zero loadings...

We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental...

Textual data and analysis can derive new insights and bring valuable business insights. These insights can be further leveraged by making better future business decisions. Sources that are used for text analysis in financial industry vary from internal word documents, email to external sources...