This paper attempts to develop a financial vulnerability indicator for China as a barometer for the state of financial vulnerability in the Chinese financial market, possibly for real-time application. Twelve variables from different sectors are utilised to extract a common vulnerability...

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...

The COVID-19 pandemic has affected people's lives and increased the banking solvency risk. This research aimed to build an early warning and early action simulation model to mitigate the solvency risk using the system dynamics methodology and the Powersim Studio 10© software. The addition of an...

This study provides the first attempt to evaluate whether a logit early warning system (EWS) for systemic banking crises can produce better predictions when political indicators are used alongside traditional macro-financial indicators. Based on a dataset covering 32 advanced economies for the...

This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the...

The paper investigates the life-cycle of the 2008-2009 financial crisis by linking the Macroeconomic Imbalance Procedure (MIP) Scoreboard of the European Commission to the crisis database of the European Systemic Risk Board (ESRB). The novelty of the analysis is that early warning capacity of...

The European Commission’s Scoreboard of Macroeconomic Imbalances is a rare case of a publicly released early warning system. It was published first time in 2012 by the European Commission as a reaction to public debt crises in Europe. So far, the Macroeconomic Imbalance Procedure takes a...

From the perspective of an emerging country - Chile - we analyze the recommendations of the Basel Committee of Banking Supervision (BCBS) regarding the design and implementation of indicators to guide countercyclical capital buffer (CCyB) policy decisions. We analyze the sensitivity of the...

We use European and simulated Hungarian data to search for the univariate one-sided credit-to-GDP gap that predicts systemic banking crises most accurately. The credit-to-GDP gaps under review are optimized along four dimensions: (1) definition of outstanding credit, (2) forecasting method for...

Die 7-Tage-Inzidenz ist als Entscheidungsgrundlage für ein adäquates Management der Corona-Pandemie zunehmend ungeeignet. Eine hohe Impfquote unter den vulnerablen, älteren Bevölkerungsgruppen und ein erhöhtes Infektionsgeschehen unter den Jüngeren hat die Bedeutung der Inzidenzwerte für...

Across many low- and middle-income countries, a sizable share of young people drop out of school before completing a full course of basic education. Early warning systems that accurately identify students at risk of dropout and support them with targeted interventions have shown results and are...

Early warning systems are too important tools in predicting the crisis in financial institutions say banks and stock markets. A consequence of crashes in a specified stock or stock market is financial crisis. This paper considers designing an early warningsystem based on random walk theory and...

In this paper, we investigate the growing prominence of credit in the systemic banking crisis prediction literature. Through the application of the signal extraction model and multivariate probit panel regression, we evaluate the performance of the absolute change in credit-to-GDP ratio as an...

Since the Treaty of Lisbon, national parliamentary chambers in the European Union can issue reasoned opinions on legislative proposals by the European Commission. These individual reasoned opinions lead to a review if at least one third of all chambers raise such concerns. Hence, coordination...

This Occasional Paper presents a formal statistical evaluation of potential early warning indicators for real estate-related banking crises. Relying on data on real estate-related banking crises for 25 EU countries, a signalling approach is applied in both a non-parametric and a parametric...

In several recent studies unit root methods have been used in detection of financial bubbles in asset prices. The basic idea is that fundamental changes in the autocorrelation structure of relevant time series imply the presence of a rational price bubble. We provide cross-country evidence for...

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...

Volatility clustering and fat tails are prominently observed in financial markets. Here, we analyze the underlying mechanisms of three agent-based models explaining these stylized facts in terms of market instabilities and compare them on empirical grounds. To this end, we first develop a...

This paper presents a model for predicting crises in small businesses using early-warning signals. It summarises the results of two separate studies carried out in Finland (with 72 percent response) and the UK (26 percent) on the decision process of corporate analysts (Finland) and bank managers...

We set up an early warning system for financial crises based on the Random Forrest approach. We use a novel set of predictors that comprises financial development indicators (e.g. levels of credit to GDP ratio) in addition to conventional imbalances measures (e.g. credit gaps). The evaluation of...