This paper develops a new Early Warning System (EWS) model for predicting financial crises, based on a multinomial logit model. It is shown that EWS approaches based on binomial discrete-dependent-variable models can be subject to what we call a post-crisis bias. This bias arises when no...

This paper develops a broad concept of systemic risk, the basic economic concept for the understanding of financial crises. It is claimed that any such concept must integrate systemic events in banking and financial markets as well as in the related payment and settlement systems. At the heart...

This paper analyzes the predictability of emerging market currency crises by comparing the often used probit model to a new method, namely a multi-layer perceptron artificial neural network (ANN) model. According to the results, both models were able to signal currency crises reasonably well...

Although many papers have already proposed empirical models of currency crises, the timing of such crises has received relatively little attention so far. Most papers use indeed a static specification and impose the same lag structure across all explanatory variables. This, by construction,...

We identify a set of “rules of thumb” that characterise economic, financial and structural conditions preceding the onset of banking and currency crises in 36 advanced economies over 1970–2010. We use the Classification and Regression Tree methodology (CART) and its Random Forest (RF)...

This paper shows the existence of a central bank trilemma. When a central bank is involved in financial intermediation, either directly through a central bank digital currency (CBDC) or indirectly through other policy instruments, it can only achieve at most two of three objectives: a socially...

The contribution of this paper is to revisit the Early Warning System (EWS) literature by analysing selected episodes of financial market crisis, i.e. those preceded by a spell of credit and real estate expansions. The aim is to disentangle instances when this constitutes a natural phenomenon...

This study seeks to answer whether it is possible to design an early warning system framework that can signal the risk of fiscal stress in the near future, and what shape such a system should take. To do so, multiple models based on econometric logit and the random forest models are designed and...

This paper describes a machine learning technique to timely identify cases of individual bank financial distress. Our work represents the first attempt in the literature to develop an early warning system specifically for small European banks. We employ a machine learning technique, and build a...

This paper uses data on bilateral foreign exposures of domestic banking systems in order to construct early warning models for financial crises that take into account cross-country spill-overs of vulnerabilities. The empirical results show that incorporating cross-country financial linkages can...