This paper develops Bayesian econometric methods for posterior inference in non-parametric mixed frequency VARs using additive regression trees. We argue that regression tree models are ideally suited for macroeconomic nowcasting in the face of extreme observations, for instance those produced...

This report uses a standard gravity setup to analyse the determinants of e-commerce, using data on online credit card payments by private Spanish customers of the multinational bank BBVA. The results show that the gravity model applies well to credit card payments, explaining up to 95% of the...

Computational methods to gauge investor sentiment from commonly used online data sources that rely on machine learning classifiers and lexicons have shown considerable promise, but suffer from measurement and classification errors. In our work, we develop a simple, direct and unambiguous...

The aims of this paper are twofold: first, we attempt to express the threshold of a single "A" rating as issued by major international rating agencies in terms of annualised probabilities of default. We use data from Standard & Poor’s and Moody’s publicly available rating histories to...