Knowledge that Transforms

We study the economics- and finance-scholars’ reaction to the 2008 financial crisis using machine learning language analyses methods of Latent Dirichlet Allocation and dynamic topic modelling algorithms, to analyze the texts of 14,270 NBER working papers covering the 1999–2016 period. We find that academic scholars as a group were insufficiently engaged in crises’ studies before 2008. As the crisis unraveled, however, they switched their focus to studying the crisis, its causes, and consequences. Thus, the scholars were “slow-to-see,” but they were “fast-to-act.” Their initial response to the ongoing Covid-19 crisis is consistent with these conclusions.

The financial stability of the eurozone depends on its macroeconomic stability and vice versa. We construct a macro DSGE model of the eurozone and its two main regions, the North and the South, with the aim of matching the macro facts of these economies by indirect inference and using the resulting empirically-based model to assess possible new policy regimes that could maintain financial stability. The model we have found to fit the facts suggests that substantial gains in stability and consumer welfare are possible if the fiscal authority in each region is given the freedom to respond to its own economic situation. Further gains could come with the restoration of monetary independence to the two regions, in effect creating a second ‘southern euro’ bloc. Enhanced fiscal flexibility increases fluctuations in debt and deficit ratios to GDP while keeping average ratios stable, maintaining solvency. A reformed Stability and Growth Pact could be limited to monitoring solvency.

We discuss the implications on banks and the economy of prudential regulatory intervention to soften the treatment of non-performing exposures (NPEs) and ease bank capital buffers. We apply these easing measures on a sample of Globally Systemically Important Banks (G-SIBs) and show that these banks can play a constructive role in sustaining economic growth during the COVID-19 pandemic. In addition, an empirical analysis shows that prudential regulatory responses to COVID-19 along with high regulatory capital and low non-performing loans ratios are positively associated with economic growth. Thus, banks should maintain high capital ratios in the medium-term horizon to absorb future losses, as the effect of COVID-19 on the economy might take time to fully materialize.

Relying on a hand-collected data set of European asset securitizations, we analyze risk retention, a key regulatory reform requirement after the global financial crisis. We find today’s ABS markets to be characterized by significant retention opacity, caused by differences in legal retention options and retained portions. To improve the transparency of effective, rather than nominal, risk retention in the market, we propose a new, simple metric that captures the share of expected loss retained by the issuer. As to policy conclusions, we suggest to change the existing regulation by dropping the mandatory minimum retention and replacing it with a requirement for full transparency about effective risk retention.

We propose a new measure of systemic financial distress that incorporates idiosyncratic and systemic risks in the financial system network. Using this measure, we develop an integrated stress test of bank liquidity and solvency risks based on the dynamics of financial distress within the banking system network. We apply this stress test framework to the US banking system and identify systemic vulnerability of individual banks as well as the resilience of the system as a whole to an economic shock. The framework helps us identify and monitor systemic interdependencies between banks. The proposed stress testing framework is useful for practical macroprudential monitoring and is informative for policy making.

Cyber incidents are becoming more sophisticated and their costs difficult to quantify. Using a unique database of cyber events across sectors in the US, we document the characteristics and drivers of cyber incidents. Cyber costs are higher for larger firms and for incidents that impact several organisations simultaneously. Events with malicious intent (i.e. cyber attacks) tend to be less costly, unless they are on the upper tail of the loss distribution. The financial sector is exposed to a larger number of cyber attacks but suffers lower costs, on average. The use of cloud services is associated with lower costs, especially when cyber incidents are relatively small. As cloud providers become systemically important, cloud dependence is likely to increase tail risks. Finally, we document that higher expenditure on IT is associated with future reduced costs from cyber incidents.

We examine a policy in which owners of banks provide funds in the form of a surety bond in addition to equity capital. This policy would require banks to provide the regulator with funds that could be invested in marketable securities. Investors in the bank receive the income from the surety bond as long as the bank is in business. The capital value could be used by bank regulators to pay off the banks’ liabilities in case of bank failure. After paying depositors, investors would receive the remaining funds, if any. Analytically, this instrument is a way of creating charter value but, as opposed to Keeley (1990) and Hellman, Murdock and Stiglitz (2000), restrictions on competition are not necessary to generate positive rents. We demonstrate that capital requirements alone cannot prevent the moral hazard problem arising from deposit insurance.

This study investigates the impact of banks’ strategic move to cloud computing on bank performance and risk-taking. Based on a novel index of banks’ exposure to cloud computing, we find that banks’ adoption of cloud computing is associated with lower cost efficiency, higher profit efficiency, and greater operational risk using data on Chinese banks over the period 2008–2019. We also find that cloud computing interacts with other newly emerging technologies, leading to synergy gains in cost efficiency and operational risk control but with a substitutive effect on profit efficiency from blockchain. The findings are of timely policy importance and practical relevance for regulators, policy-makers, and bank managers.

Using political corruption conviction data from the U.S. Department of Justice, we examine the impact of local corruption on firms’ debt maturity structure while exploring both demand-side and supply-side explanations. Our results support the demand-side story and indicate that firms in high corruption areas utilize less short-term debt to mitigate liquidity and refinancing risks. Consistent with this, we find the effect is more pronounced among firms with smaller size, lower asset redeployability, and higher volatility. Our findings remain robust to the inclusion of an array of controls expected to influence debt maturity preferences as well as time, industry, and state fixed effects. Moreover, a seemingly unrelated regression approach, instrumental variables regression, propensity score matching, placebo analyses, and alternative corruption measures corroborate our findings. Altogether, our results indicate that firms alter their debt maturity choices in response to local corruption to limit refinancing risk and the uncertainty created by corrupt government officials.

This paper studies the interaction between bank capital regulation, moral hazard and co-existence of traditional and shadow banks. Bank managers can choose between traditional banking and off-balance sheet special purpose vehicles (SPV), in a setup with deposit insurance and moral hazard. We first show that in the absence of SPV intermediation, capital requirements are ineffective at preventing the moral hazard problem originated by deposit insurance. We find that shadow banks can improve financial stability, when there is full information sharing. Finally, we analyze the case of neglected tail risk. We find that under such circumstances, the SPV will increase financial risk by exposing the system to extreme events.