We test the usefulness of Machine Learning (ML) for sovereign risk assessment and pricing in the euro area along two important dimensions: i) their predictive accuracy compared to traditional econometrics methods and, ii) their assessment on what are the most important economic factors behind...

Regional banks as savings and cooperative banks are widespread in continental Europe. In the aftermath of the financial crisis, however, they had problems keeping their profitability which is an important quantitative indicator for the health of a bank and the banking sector overall. We use a...

In January 2007 the International Monetary Fund (IMF) published, on an ad hoc basis, a series of financial soundness indicators (FSIs) based on a common methodology (the IMF compilation Guide) for 62 countries, including all 27 European Union countries. The European Central Bank (ECB), jointly...

In January 2007 the International Monetary Fund (IMF) published, on an ad hoc basis, a series of financial soundness indicators (FSIs) based on a common methodology (the IMF compilation Guide) for 62 countries, including all 27 European Union countries. The European Central Bank (ECB), jointly...

Using an innovative approach of following the downgrade or credit rating decisions by rating agencies, this paper develops an early-warning system of bank financial distress and critically evaluates the reliability and stability of the potential indicators or factors of banks in 13 emerging...

This paper describes recent work to strengthen nowcasting capacity at the IMF's European department. It motivates and compiles datasets of standard and nontraditional variables, such as Google search and air quality. It applies standard dynamic factor models (DFMs) and several machine learning...

This paper describes recent work to strengthen nowcasting capacity at the IMF’s European department. It motivates and compiles datasets of standard and nontraditional variables, such as Google search and air quality. It applies standard dynamic factor models (DFMs) and several machine learning...

We estimate the relationships between innovation and Human Resources in Europe using theEuropean Innovation Scoreboard of the European Commission for 36 countries for the period 2010-2019. We perform Panel Data with Fixed Effects, Random Effects, Pooled OLS, Dynamic Panel and WLS. We found that...