Contributions published at Department of Banking and Finance (Pablo Koch Medina)

In this paper, we survey a large sample of Swiss households to measure sustainable finance literacy, which we define as the knowledge and skill of identifying and assessing financial products according to their reported sustainability-related characteristics. To this end, we use multiple-choice questions. Furthermore, we measure Swiss private investors' level of awareness about sustainable financial products using open-ended questions. We find that Swiss households, which are generally highly financially literate by international standards, exhibit low levels of sustainable financial literacy compared to the current working definitions of sustainable finance. Moreover, despite its low level, knowledge about sustainable finance is a significant factor in the reported ownership of sustainable products. The empirical results also show a relatively low level of awareness. Generally, these empirical findings suggest a need to create transparent regulatory standards and strengthen information campaigns about sustainable financial products.

This article examines the impact of non-pharmaceutical interventions on the initial exponential growth of the infected population and the final exponential decay of the infected population. We employ a Bayesian dynamic model to test whether there is learning, a random walk pattern, or another type of learning with evolving epidemiological data over time across 168 countries and 41,706 country-date observations. Although we show that Bayesian learning is not taking place, most policy measures appear to assert some effect. In particular, we show that economic policy variables are of importance for the main epidemiological parameters derived from the policy learning model. In an empirical second-stage application, we further investigate the underlying dynamics between the epidemiological parameters and household debt repayments, a key economic variable, in the UK. Results show no Bayesian learning, although a higher transmission rate would increase household debt repayments, while the recovery rate would have a negative impact. Therefore, suboptimal learning is taking place.

The COVID-19 pandemic demonstrated the fragility of international, national, regional, and local risk management systems. It revealed an urgent need to improve risk planning, preparedness, and communication strategies. In parallel, it created an opportunity to drastically re-think and transform societal processes and policies to prevent future shocks originating not only from health, but also combined with those related to climate change and biodiversity loss. In this perspective, we examine how to improve integrated risk assessment and management (IRAM) capacities to address interconnected shocks. We present the results from a series of workshops within the framework of the University of Zurich and University of Geneva. Initiative "Shaping Resilient Societies: A Multi-Stakeholder Approach to Create a Responsive Society". This initiative gathered experts from multiple disciplines to discuss their perspectives on resilience; here we present the key messages of the "Pandemics, Climate and Sustainability” thinking group. We identify a roadmap and selected research areas concerning the improvement of IRAM analysis capacities, practices, policies. We recommend the development of robust data systems and science-policy advice systems to address combined shocks emerging from health, biodiversity loss and climate change. We posit that further developing the IRAM framework to include these recommendations will improve societal preparedness and response capacity and will provide more empirical evidence supporting decision-making and the selection of strategies and measures for integrated risk reduction.

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 show that firm valuations fell after a key expense became more visible in financial statements. FAS 123-R required firms to deduct option compensation costs from earnings, instead of disclosing them in footnotes. Firms that granted high option pay experienced earnings reductions, while fundamentals remained unchanged. These firms were more likely to miss earnings forecasts, and they experienced recommendation downgrades and valuation declines. Our findings suggest that market participants exhibited limited attention to option costs before FAS 123-R. As we reuse the FAS 123-R natural experiment, we show how one can address confounding channels by integrating reduced-form and structural estimation.

How financial investors may react to policy events related to sustainability and climate change mitigation in particular, is a key question with implications for sustainable finance and financial stability. We address this question by carrying out a multi-period difference-in-difference approach on a confidential database of securities holdings of the European Central Bank, and we provide evidence of several effects related to the Paris Agreement. In aggregate, investors reduced their participation in the equities of high-carbon firms in response to the agreement, and the trend reverted after the US’s announcement of withdrawal from the agreement. However, the reaction varies across categories and geographies of the securities holders, their ownership size, and the emissions of owned firms. In particular, transition risk has been taken up by less regulated financial institutions and the BRIC countries. Our results highlight that the redirection of global financial flows towards climate action requires clear and unanimous signals from the global community of policy makers.

Using Iran’s unexpected flood in April 2019 as a natural experiment, we show that local branches bridge the time gap between the disaster and governmental aids by immediately increasing their lending for two months following the flood. Analyzing proprietary information on more than 53,000 farmers, we find that farmers with a stronger relationship with their branch - particularly younger and females - are more likely to receive a recovery loan. Our findings underscore that despite recent technological advancements, relationship-based branch banking is still important for agrarian societies during catastrophic events.

Do financial crises affect long‐term public health? To answer this question, we examined the relationship between the 2007–2009 Global Financial Crisis (GFC) and the 2020–2022 COVID‐19 pandemic. Specifically, we examined the relationship between the financial losses derived from the GFC, and the health outcomes associated with the first wave of the pandemic. European countries that were more affected by the financial crisis had more deaths relative to coronavirus cases. An analogous relationship emerged across Spanish provinces and US states. Part of the transmission from finances to health outcomes appears to have occurred through cross‐sectional differences in health care facilities.

Reduced water availability poses risks for many economic activities. This paper studies how water risks affect hydroelectricity generation in Europe and the US and whether these risks are priced in by financial markets. To this end, we build a novel dataset for the period 2015–2022, which combines plant-specific hydroelectricity generation with geo-specific water physical risks and equity returns. We find that water risks, measured using model-based aggregate water risk metrics as well as precipitation anomalies, are significantly associated with reduced electricity generation, although the effect disap- pears after two months. We then link the power plants in our sample to the equity returns of their owners to investigate whether financial markets adequately price water risks. Using a portfolio sorts approach, we find weak evidence of a negative risk pre- mium. Given the real negative effect of water risks on generation, we conclude that the lack of a positive risk premium amounts to mispricing of water risks by financial markets.

A major concern regarding sustainable investing is that it may crowd out political support for government interventions targeting negative externalities. We test the validity of this concern in a preregistered experiment shortly before a real referendum on a climate law with a representative sample of the Swiss population (N = 2,051). We find that the opportunity to invest in a climate conscious fund does not erode individuals’ support for climate regulation. Our experimental results are consistent with actual voting and investing behavior across Switzerland. We conclude that the spillover effects of sustainable investing on individual political behavior are limited.

We show that engagement on environmental, social, and governance issues can benefit shareholders by reducing firms’ downside risks. We find that the risk reductions (measured using value at risk and lower partial moments) vary across engagement types and success rates. Engagement is most effective in lowering downside risk when addressing environmental topics (primarily climate change). Further, targets with large downside risk reductions exhibit a decrease in environmental incidents after the engagement. We estimate that the value at risk of engagement targets decreases by 9% of the standard deviation after successful engagements, relative to control firms.

We study how banks use "regulatory adjustments" to inflate their regulatory capital ratios and whether this depends on forbearance on the part of national authorities. Using the 2011 EBA capital exercise as a quasi-natural experiment, we find that banks substantially inflated their levels of regulatory capital via a reduction in regulatory adjustments — without a commensurate increase in book equity and without a reduction in bank risk. We document substantial heterogeneity in regulatory capital inflation across countries, suggesting that national authorities forbear their domestic banks to meet supranational requirements, with a focus on short-term economic considerations.

We study binary opinion formation in a large population where individuals are influenced by the opinions of other individuals. The population is characterised by the existence of (i) communities where individuals share some similar features, (ii) opinion leaders that may trigger unpredictable opinion shifts in the short term (iii) some degree of incomplete information in the observation of the individual or public opinion processes. In this setting, we study three different approximate mechanisms: common sampling approximation, independent sampling approximation, and, what will be our main focus in this paper, McKean–Vlasov (or mean-field) approximation. We show that all three approximations perform well in terms of different metrics that we introduce for measuring population level and individual level errors. In the presence of a common noise represented by the major influencers opinions processes, and despite the absence of idiosyncratic noises, we derive a propagation of chaos type result. For the particular case of a linear model and particular specifications of the major influencers opinion dynamics, we provide additional analysis, including long term behavior and fluctuations of the public opinion. The theoretical results are complemented by some concrete examples and numerical analysis, illustrating the formation of echo-chambers, the propagation of chaos, and phenomena such as snowball effect and social inertia.

Decentralized Finance (‘DeFi’) has gained tremendous momentum over the past three years by using novel approaches to disintermediating financial institutions in the provision of financial services. However, empirical research in this field is still rare, and a more comprehensive understanding of the domain is a missing component in academic research. This paper develops a taxonomy based on a comprehensive literature analysis to structure this emerging field systematically. The taxonomy includes three perspectives (strategy, organization, technology) and seven dimensions (blockchain, value proposition, token type, business process, price mechanism, protocol type, integration type) as well as thirty-six characteristics. The application of the taxonomy to 278 DeFi start-ups reveals that most of the DeFi start-ups focus on Ethereum (36.3%) and have a focus on analytics and automation (52%), while, surprisingly only a few incorporate decentralized governance approaches (3.3%), provide decentralized exchanges (14%) or integrate off-chain data.

Environmental, social, and governance (ESG) criteria take a central role in fostering sustainable development in economies. This paper introduces a class of novel Natural Language Processing (NLP) models to assess corporate disclosures in the ESG subdomains. Using over 13.8 million texts from reports and news, specific E, S, and G models were pretrained. Additionally, three 2k datasets were developed to classify ESG-related texts. The models effectively explain variations in ESG ratings, showcasing a robust method for enhancing transparency and accuracy in evaluating corporate sustainability. This approach addresses the gap in precise, transparent ESG measurement, advancing sustainable development in economies.

Some dynamical contagion models for default risk have been proposed in the literature, where a system (composed of individual debtors) evolves as a Markov process conditionally on the observation of its stochastic environment, with interacting intensities. The Markovian assumption necessitates that the environment evolves autonomously and is not influenced by the transitions of the system. We extend this classical literature and allow a default system to have a contagious impact on its environment. With a certain probability, the transition of a debtor to the default state has an impact on the system's environment. This in turn affects the transition intensities of the other debtors inside the system. Therefore, in our framework, contagion can either be contained within the default system (i.e., direct contagion from a counterparty to another) or spill from the default system over its environment (indirect contagion). This type of model is of interest whenever one wants to capture within a model possible impacts of the defaults of a class of debtors on the more global economy and vice versa.

We develop a new method for characterizing global solutions to search and matching models with aggregate shocks and heterogeneous agents. We formulate general equilibrium as a high dimensional partial differential equation (PDE) with the distribution as a state variable. Solving this problem has previously been intractable because the distribution impacts agent decisions through the matching mechanism rather than through aggregate prices. We overcome these challenges by developing a new deep learning algorithm with efficient sampling in a high dimensional state space. This allows us to study search markets that are not “block recursive”. In applications to labor search models, we show that while block recursivity may approximately hold under symmetric shocks, it fails to capture the dynamics when shocks have an asymmetric impact. Business cycles have a “cleansing” effect by amplifying positive assortative matching in recessions, and the magnitude of the countercyclicality depends on the bargaining process between workers and firms.

Standard economic models view risk taking and time discounting as two independent dimensions of decision making. However, mounting experimental evidence demonstrates striking parallels in patterns of risk taking and time discounting behavior and systematic interaction effects, which suggests that there may be common underlying forces driving these interactions. Here, we show that the inherent uncertainty associated with future prospects together with individuals’ proneness to probability weighting generates a unifying framework for explaining a large number of puzzling behavioral findings: delay-dependent risk tolerance, aversion to sequential resolution of uncertainty, preferences for the timing of the resolution of uncertainty, the differential discounting of risky and certain outcomes, hyperbolic discounting, subadditive discounting, and the order dependence of prospect valuation. Furthermore, all these phenomena can be accommodated by the same set of preference parameter values and plausible levels of inherent uncertainty.

We assess the impact of the leverage ratio capital requirements on the risk-taking behaviour of banks both theoretically and empirically. Conceptually, introducing binding leverage ratio requirements into a regulatory framework with risk-based capital requirements induces banks to re-optimise, shifting from safer to riskier assets (higher asset risk). Yet, this shift would not be one-for-one due to risk weight differences, meaning the shift would be associated with a lower level of leverage (lower insolvency risk). The interaction of these two changes determines the impact on the aggregate level of risk. Empirically, we use a difference-in-differences setup to compare the behaviour of UK banks subject to the leverage ratio requirements (LR banks) to otherwise similar banks (non-LR banks). Our results show that LR banks did not increase asset risk, and slightly reduced leverage levels, compared to the control group after the introduction of leverage ratio in the UK. As expected, these two changes led to a lower aggregate level of risk. Emperical results indicate that credit default swap spreads on the 5-year subordinated debt of LR banks decreased relative to non-LR banks post leverage ratio introduction, suggesting the market viewed LR banks as less risky, especially during the COVID 19 stress.

External imbalances played a pivotal role leading to the global financial crisis and were an important cause of turmoil. While current account (flow) imbalances narrowed in the aftermath of the crisis, the net international investment position (NIIP) (stock) imbalances persisted. This study explores the implications of countries’ net foreign positions on systemic risk. Using a sample of 470 banks located in 49 advanced economies, emerging countries, and developing economies over 2000–2020, we find robust empirical evidence that banks can reduce their systemic risk exposure when the countries in which they are incorporated improve their NIIPs and maintain creditor status vis-à-vis the rest of the world. However, only the equity component of the NIIP is responsible for this outcome, whereas debt flows are not significant. Similarly, we find that the mitigating effect of an external balance sheet on systemic risk is derived from valuation gains rather than from the incremental net acquisition of assets or liabilities represented by the current account. Our findings are particularly relevant for policymakers seeking to improve banks’ resilience to adverse shocks and maintain financial stability.