Journal of Financial Stability最新文献

Basel III features requirements on bank capital and liquidity along with disclosure requirements. I study these prudential tools by developing a general equilibrium model with bank runs in a global game framework, where leverage, liquidity, interest rates, and the probability of a banking crisis are all determined endogenously. With timely disclosure about bank assets, the unregulated economy has efficient liquidity but excessive leverage due to a pecuniary externality, warranting a leverage restriction. Delayed disclosure gives rise to bank risk shifting, making leverage even more excessive and liquidity insufficient, which warrants joint requirements on leverage and liquidity. Empirical predictions and policy implications are derived and discussed.

Financial regulation has introduced bail-ins (i.e. enforced debt-to-equity swaps) as a tool for orderly bank resolution, and hence it is the authorities’ task to decide when to apply this tool in a resolution. We present a quantitative framework to support this decision by computing the systemic impact of a bail-in. Our model takes into account systemic feedback effects using state-of-the-art multilayer contagion models, which we extend to include liquidation losses. Using real-world data for the Austrian banking system, we perform an empirical assessment of the systemic risk impact of idiosyncratic and systemic shocks. Our results show that bail-ins have the potential to reduce systemic risk compared to insolvencies for the Austrian banking system. They also incur lower social cost than bail-outs, but only for moderate, idiosyncratic crises. Our findings quantitatively corroborate earlier discussions that bail-ins may be an inadequate tool to deal with systemic crises. This suggests that the bail-in mechanism alone may not be sufficient to rule out future bail-outs.

We analyse the double materiality of climate physical and transition risks in the euro area economy and banking sector. First, by tailoring the EIRIN Stock-Flow Consistent behavioural model, we provide a dynamic balance sheet assessment of the Network for Greening the Financial System (NGFS) scenarios. We find that an orderly transition achieves early co-benefits by reducing CO₂ emissions (12% less in 2040 than in 2020) while supporting growth in economic output. In contrast, a disorderly transition worsens the economic performance and financial stability of the euro area. Further, in a disorderly transition with higher physical risks, real GDP decreases by 12.5% in 2050 relative to an orderly transition. Second, we analyse how firms’ expectations about climate policy credibility (climate sentiments) affect investment decisions in high or low-carbon goods. Firms that trust an orderly policy introduction do anticipate the carbon tax and switch earlier to low-carbon investments. This, in turn, accelerates economic decarbonization and decreases the risk of carbon-stranded assets for investors. Our results highlight the crucial role of early and credible climate policies to signal investment decisions in the low-carbon transition.

This paper shows how the combined endogenous reaction of banks and investment funds to an exogenous shock can amplify or dampen losses to the financial system compared to results from single-sector stress testing models. We build a new model of contagion propagation using a very large and granular data set for the euro area. Based on the economic shock caused by the Covid-19 outbreak, we model three sources of exogenous shocks: a default shock, a market shock and a redemption shock. Our contagion mechanism operates through a dual channel of liquidity and solvency risk. Our analysis reveals that adding the fund sector to our model for banks leads to additional losses through fire sales and a further depletion of banks’ capital ratios by around one percentage point. The main driver of additional bank losses are endogenous market losses generated by investment funds’ asset liquidation.

In this paper we provide a framework to study the network topology of generalized forecast error variance decomposition (GFEVD) derived from multi-country, multi-variable time series models. Our dynamic variance decomposition network is based on a Bayesian Global Vector Autoregressive (GVAR) model, a suitable macroeconometric method to consider simultaneous multi-level interdependencies across variables. We demonstrate the usefulness of our methodology to analyze the network structure of shock propagation in longitudinal time series and, in particular: (a) the shortest paths of contagion; (b) the clusters of shock transmission; (c) the role of nodes in the risk transmission channels. We illustrate our method through an empirical application to a set of 12 European countries’ Industrial Production, Retail Trade and Economic Sentiment indices over the period 01/2000–11/2021.

This paper explores the relationship between environmental, social and governance (ESG) information and systemic risk, an increasingly important issue for both regulators and investors. While ESG ratings are widely used to assess a company’s non-financial performance, the impact of these factors on financial stability and systemic risk is still under debate. By extending the Forecast Error Variance Decomposition (FEVD) method with a double regularization on both the underlying vector autoregressive (VAR) parameters and the covariance matrix of the VAR residuals, we are able to address the curse of dimensionality within each estimation. This allows us to examine how vulnerable a company is and how much systemic impact a company has given its specific ESG. Looking at a larger sample of European stocks over the period 2007–2022, we empirically show that both the best and worst ESG performers have the largest impact on the financial system in normal times. However, during a crisis, companies with the best ESG ratings generate significant spillovers throughout the system. These findings highlight the importance of incorporating ESG factors into systemic risk assessments and monitoring companies’ ESG performance to ensure financial stability. Policymakers can benefit from this research by supporting investment in high ESG companies to mitigate relevant spillovers during stressed market conditions, when such companies are more interconnected.

The breakdown of the interbank market was a critical moment in the unfolding of the global financial crisis of 2007–2008. We argue that the adequate pricing of risks is critical for the functioning of a market of such vital importance as the interbank market. We use a unique panel data set that allows us to quantify counterparty risk and different types of systemic risks associated with interbank exposures. We use a simultaneous equation model for interbank lending and deposit rates to study whether counterparty risk and systemic risk are adequately priced. As expected, we find that riskier banks on average pay a higher deposit rate. However, on average, banks grant a discount in their lending rates to riskier banks. For systemic risk, we also find mixed results. The positive effect on the deposit rate declines, but the negative effect on the lending rate remains. We argue that the mixed results regarding the pricing of systemic risk might ex-post justify parts of the Basel III reform package that forces systemically important banks to hold higher capital buffers.

In this cover paper, we introduce a Special Issue (SI) published after the fourth edition of a series of financial stability conferences organized by Bank of Mexico, CEMLA, Bank of Canada, Zurich University and the Journal of Financial Stability in November 2021. Before providing our perspective on why the research papers included into the SI are of great relevance, we give a brief and personal overview of recent directions in financial stability research in general, esp., related to topics accentuated by the COVID-19 pandemic or post-pandemic economic and financial conditions and their complexity. Papers published in the SI cover four topics of research in the financial stability field, featuring some outstanding and innovative projects presented during the conference. The first topic is on interconnectedness and shock transmission in the financial system, diving deep into asset fire sales, interconnectedness of various segments of the financial system, in addition to banks, on the optimality of systemic risk capital buffers, and on how risks are priced in the interbank market network. The second one touches upon climate change risks looking at investors’ reactions to international climate policy developments, in particular on the Paris Agreement front and how to jointly model physical and transition risk in the banking system, including the important concept of double materiality. The third topic is represented by projects focused on policy analysis for systemic risk mitigation, specifically dealing with macroprudential policy instruments and crisis mitigation policies. Finally, research papers in the last topic on big data and market data focus on the innovative ways to explore the growing body of data sources, such as data collected by regulators, including credit register data, supervisory data and market data on financial transactions, to better understand sources and implications of systemic risk.

We examine the impact of fire sales on the UK financial system through commonly held assets across different financial sectors. In particular, we model indirect contagion via fire sales across UK banks and non-banks subject to different types of constraints. We find that performing a stress simulation that does not account for common asset holdings across multiple sectors can severely underestimate the fire sale losses in the financial system. In addition, pro-rata liquidation strategy would result in a higher level of fire sale losses in the system as whole, but a waterfall strategy may produce a higher spillover effect for a passive institution (or a passive sector) that chooses not to promptly liquidate any of its assets during distress while other institutions decide to do so.