In this study we develop an early warning system (EWS) to forecast currency crises in emerging countries in Asia and Latin America, using logit regression on monthly data from 1992 to 2011. We found that macroeconomic and institutional variables are valuable indicators for forecasting crises....

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 paper revisits the Swedish banking crisis (1919-26) that materialized as post war deflation replaced wartime inflation (1914-18). Inspired by Fisher's 'debt deflation theory', we employ survival analysis to 'predict' which banks would fail, given certain ex-ante bank characteristics. Our...

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...

During the COVID-19 pandemic, house prices and mortgage credit rose at a longunseen pace. It is unclear, however, whether such increases are warranted by the underlying market and macroeconomic fundamentals. This paper offers a new structural two-market disequilibrium model that can be estimated...

The road map presents a potential pathway to strengthen Uzbekistan's national hydrometeorological (hydromet) and multi-hazard early warning systems and services, based on the needs of the user community. It is based on a technical evaluation and assessment of the needs and capacities of...

We develop a sovereign default risk index using natural language processing techniques and 10 million news articles covering over 100 countries. The index is a highfrequency measure of countries' default risk, particularly for those lacking marketbased measures: it correlates with sovereign CDS...

A reflection on the lackluster growth over the decade since the Global Financial Crisis has renewed interest in preventative measures for a long-standing problem. Advances in machine learning algorithms during this period present promising forecasting solutions. In this context, the paper...

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...

The U.S. Subprime Crisis and the subsequent Great Recession have highlighted a renewed interest in the proper design and implementation of Early Warning Systems (E.W.S.), in order to help deter the onset of subsequent extreme financial events, through the implementation of adequate crisis...

Risk analysis and scenario testing are two of the core activities carried out by economists at central banks. With the increasing adoption of machine learning to enhance decision-support systems, and the amount of collected data spiking, institutions provide countless use-cases for the...

A traveling air pressure disturbance of several hPa for a short period (5–10 min) can generate tsunami-like waves in coastal areas owing to a multi-resonant mechanism. Pressure-forced meteotsunamis have been reported over the Korean Peninsula on a regular basis in recent years; however, the...

The UK financial sector is a highly competitive system that has, historically, demonstrated resilience to crisis. All that changed with the banking crisis of 2007-08, affecting not just individual banks but a whole array of interconnected financial institutions, leading to a panic that spread...

Can the upturns and downturns in financial variables serve as early warning indicators of banking crises? Using data from 59 advanced and emerging economies, we show that financial overheating can be detected in real time. Equity prices and output gap are the best leading indicators in advanced...

This research contributes to bank liquidity risk management by employing supervised machine learning models to provide banks with early warnings of liquidity stress using market-based indicators. Identifying increasing levels of stress as early as possible provides management with a crucial...

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...

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...

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...

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...

Using high-quality nation-wide social security data combined with machine learning tools, we develop predictive models of income support receipt intensities for any payment enrolee in the Australian social security system between 2014 and 2018. We show that off-the-shelf machine learning...

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...

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...

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...

Asset encumbrance is a central concept in the context of banks’ liquidity crises, as it is associated with their capacity to obtain secured funding. This occasional paper summarises the work carried out by the task force on asset encumbrance, bringing together analyses by the ECB and those...

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...