Assessing when credit is excessive is important to understand macro-financial vulnerabilities and guide macroprudential policy. The Basel Credit Gap (BCG) – the deviation of the credit-to-GDP ratio from its long-term trend estimated with a one-sided Hodrick-Prescott (HP) filter—is the indicator preferred by the Basel Committee because of its good performance as an early warning of banking crises. However, for a number of European countries this indicator implausibly suggests that credit should go back to its level at the peak of the boom after the credit cycle turns, resulting in large negative gaps that might delay the activation of macroprudential policies. We explore two different approaches—a multivariate filter based on economic theory and a fundamentals-based panel regression. Each approach has pros and cons, but they both provide a useful complement to the BCG in assessing macro-financial vulnerabilities in Europe.

The countercyclical capital buffer (CCB) was proposed by the Basel committee to increase the resilience of the banking sector to negative shocks. The interactions between banking sector losses and the real economy highlight the importance of building a capital buffer in periods when systemic risks are rising. Basel III introduces a framework for a time-varying capital buffer on top of the minimum capital requirement and another time-invariant buffer (the conservation buffer). The CCB aims to make banks more resilient against imbalances in credit markets and thereby enhance medium-term prospects of the economy—in good times when system-wide risks are growing, the regulators could impose the CCB which would help the banks to withstand losses in bad times.

In 2011 the World Bank—with funding from the Bill and Melinda Gates Foundation—launched the Global Findex database, the world's most comprehensive data set on how adults save, borrow, make payments, and manage risk. Drawing on survey data collected in collaboration with Gallup, Inc., the Global Findex database covers more than 140 economies around the world. The initial survey round was followed by a second one in 2014 and by a third in 2017. Compiled using nationally representative surveys of more than 150,000 adults age 15 and above in over 140 economies, The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution includes updated indicators on access to and use of formal and informal financial services. It has additional data on the use of financial technology (or fintech), including the use of mobile phones and the Internet to conduct financial transactions. The data reveal opportunities to expand access to financial services among people who do not have an account—the unbanked—as well as to promote greater use of digital financial services among those who do have an account. The Global Findex database has become a mainstay of global efforts to promote financial inclusion. In addition to being widely cited by scholars and development practitioners, Global Findex data are used to track progress toward the World Bank goal of Universal Financial Access by 2020 and the United Nations Sustainable Development Goals. The database, the full text of the report, and the underlying country-level data for all figures—along with the questionnaire, the survey methodology, and other relevant materials—are available at www.worldbank.org/globalfindex.

This note provides guidance to facilitate the staff’s advice on macroprudential policy in Fund surveillance. It elaborates on the principles set out in the “Key Aspects of Macroprudential Policy,” taking into account the work of international standard setters as well as the evolving country experience with macroprudential policy. The main note is accompanied by supplements offering Detailed Guidance on Instruments and Considerations for Low Income Countries

This paper discusses the findings of the Financial System Stability Assessment for Sweden. The Swedish financial system is large and highly interconnected, putting a premium on the accompanying policy framework. Relative to the size of the domestic economy, the financial system is among Europe’s largest. It features complex domestic and international linkages, reflecting Sweden’s role as a regional financial hub. However, the macrofinancial risks have grown since 2011, for example the rising share of highly indebted households. Stress tests also suggest that banks and nonbanks are largely resilient to solvency shocks, but concerns persist about the ability of bank models to capture unexpected losses.

The IMF’s Vulnerability Exercise (VE) is a cross-country exercise that identifies country-specific near-term macroeconomic risks. As a key element of the Fund’s broader risk architecture, the VE is a bottom-up, multi-sectoral approach to risk assessments for all IMF member countries. The VE modeling toolkit is regularly updated in response to global economic developments and the latest modeling innovations. The new generation of VE models presented here leverages machine-learning algorithms. The models can better capture interactions between different parts of the economy and non-linear relationships that are not well measured in ”normal times.” The performance of machine-learning-based models is evaluated against more conventional models in a horse-race format. The paper also presents direct, transparent methods for communicating model results.

The paper explores the nexus between the financial and business cycles in a semi-structural New Keynesian model with a financial accelerator, an active banking sector, and an endogenous macroprudential policy reaction function. We parametrize the model for Luxembourg through a mix of calibration and Bayesian estimation techniques. The model features dynamic properties that align with theoretical priors and empirical evidence and displays sensible data-matching and forecasting capabilities, especially for credit indicators. We find that the credit gap, which remained positive during COVID-19 amid continued favorable financial conditions and policy support, had been closing by mid-2022. Model-based forecasts using data up to 2022Q2 and conditional on the October 2022 WEO projections for the Euro area suggest that Luxembourg's business and credit cycles would deteriorate until late 2024. Based on these insights about the current and projected positions in the credit cycle, the model can guide policymakers on how to adjust the macroprudential policy stance. Policy simulations suggest that the weights given to measures of credit-to-GDP and asset price gaps in the macroprudential policy rule should be well-calibrated to avoid unwarranted volatility in the policy response.

MCM conducted a survey in December 2010 to take stock of international experiences with financial stability and the evolving macroprudential policy framework. The survey was designed to seek information in three broad areas: the institutional setup for macroprudential policy, the analytical approach to systemic risk monitoring, and the macroprudential policy toolkit. The survey was sent to 63 countries and the European Central Bank (ECB), including all countries in the G-20 and those subject to mandatory Financial Sector Assessment Programs (FSAPs). The target list is designed to cover a broad range of jurisdictions in all regions, but more weight is given to economies that are systemically important (see Annex for details). The response rate is 80 percent. This note provides a summary of the survey’s main findings.

The paper proposes a simple, new, analytical framework for assessing the cost and benefits of macroprudential policies. It proposes a measure of net benefits in terms of parameters that can be estimated: the probability of crisis, the loss in output given crisis, policy effectiveness in bringing down both the probability and damage during crisis, and the output-cost of a policy decision. It discusses three types of policy leakages and identifies instruments that could best minimize the leakages. Some rules of thumb for policymakers are provided.

The Global Financial Stability Report examines current risks facing the global financial system and policy actions that may mitigate these. It analyzes the key challenges facing financial and nonfinancial firms as they continue to repair their balance sheets. Chapter 2 takes a closer look at whether sovereign credit default swaps markets are good indicators of sovereign credit risk. Chapter 3 examines unconventional monetary policy in some depth, including the policies pursued by the Federal Reserve, the Bank of England, the Bank of Japan, the European Central Bank, and the U.S. Federal Reserve.