Knowledge that Transforms

This paper investigates the effects and conduct of macroprudential policies in China compared to those of monetary policy. Two types of structural VAR models, one with recursive zero restrictions and the other with sign restrictions on impulse responses, are used with monthly data. The main results of this paper are as follows. First, macroprudential policy has substantial effects on financial variables such as credit and house prices and macro variables such as output and inflation rate, as monetary policy does. Second, contractionary macroprudential policy is taken to stabilize credit in response to credit shocks, but monetary policy is not.

Banks play a crucial role in providing liquidity to borrowers, particularly during crises (Kashyap et al., 2002 [33]). The existence of multiple lending relationships between banks and borrowers has been seen as an element that reduces the risk of liquidity shortage for debtors (Detragiache et al., 2000). In this paper, we aim to show how the interaction of these two aspects with solvency and liquidity requirements might have implications for the stability of the banking system, which might still need to be fully analyzed. We show that if other sources of liquidity are unavailable or too costly for banks, multiple lending might be a key element in a systemic liquidity shortage and a large drop in lending to the economy. These findings are particularly relevant for understanding how macroeconomic shocks, such as the relatively recent outbreak of COVID-19, could impact the real economy, as well as for assessing the implications of alternative banking resolution mechanisms.

This paper estimates unobserved components (UC) models with real and financial trends and business and credit cycles to assess different measures of the credit cycle used by policymakers. The permanent components of the real and financial sectors are a Beveridge–Nelson and local linear trend, respectively. The business and credit cycles evolve jointly as a second-order vector autoregression . Bootstrap methods are applied to UC model estimates retrieved from classical optimization of the predictive likelihood of the Kalman filter . Results indicate the slope of the financial trend better predicts the credit to GDP ratio in the United States than the estimated business and credit cycles and the Basel gap. This suggests policymakers should consider permanent shocks to the financial sector when gauging the state of financial stability .

Using a model of strategic interactions between two countries, I investigate the gains to international coordination of financial regulation policies, and how these gains depend on global lending conditions. When one region – the core – sets global lending conditions, I show that coordinating regulatory policies makes the two regions better-off relative to the case of no cooperation. Global lending conditions set by the core are typically sub-optimal for the other region – the periphery –. To reduce this cost, the periphery can tighten its regulatory policy. Yet, in doing so, it fails to internalise a cross-border externality: when the periphery tightens its regulatory policy, agents in the core reduce cross-border borrowing, which tightens global lending conditions and hurts the periphery. The cooperative equilibrium can improve on this outcome. Both regions take into account the cross-border externality, leading to larger cross-border borrowing and less sub-optimal lending conditions for the periphery.

Climate-related risks have become a major concern for financial regulators and can pose a significant threat to financial stability. In this paper, we first propose a theoretical framework for the transmission of climate risks to financial institutions and the financial system. We then estimate the influence of physical and transition risks on the European financial system through bank-level and system-wide measures of financial stability. We find that Scope 3 greenhouse gas emissions, chronic and acute climate risks negatively affect financial stability at both the financial institution and system levels. Temperature anomalies, heat waves, wildfires and droughts are among the most significant risks. As Europe warms twice as fast as the rest of the world, our theoretical and empirical results urge regulators to mandatorily require the assessment and disclosure of corporate climate risks to allow banks to adjust their prudential capital requirements.

We study the effect of governments’ fiscal support on banks’ loan loss provisioning during the COVID-19 pandemic. In addition, we decompose fiscal support into direct support and liquidity support to examine the effect of different types of support measures on banks’ loan loss provisioning. Direct support generally refers to cash transfers, tax reliefs, and tax deferrals, while liquidity support generally refers to government-backed loans and equity injections. We find that direct support reduced banks’ loan portfolio risk whereas liquidity support did not. Moreover, we find the effect goes beyond a macroeconomic stabilization effect, suggesting that direct support directly contributed to mitigating banks’ loan portfolio risk during the pandemic. Our results are robust to controlling for other policy interventions, alternative model specifications, and an instrumental variable approach. We further discuss the policy implications of our analysis.

There is growing recognition that prolonged U.S. monetary policy easing has extraterritorial spillovers, driving up financial system leverage elsewhere in the world. Faced with financial stability threats that are not of their own making, what can these countries do? Specifically, is there a role for macroprudential tools, capital controls or foreign exchange intervention in safeguarding financial stability from risks arising externally? We examine the efficacy of these policy interventions by exploring whether preventative or reactive policy interventions can mitigate such risks. Using a sample of 950 bank and nonbank financial firms across 28 non-U.S. economies over the past two decades, we show that if policymakers are able to implement policies prior to an additional consecutive decline in U.S. interest rates, financial institutions do not increase their leverage by as much as they otherwise would. By contrast, it is more difficult to counter the spillovers with reactive policy interventions.

We study the relationship between climate change and financial systemic risk. First, we test whether, to what extent and how quickly the systemic risk of US banking and insurance sectors reacts to billion-dollar weather and climate disasters. We prove that some extreme events can exacerbate financial systemic risk and provide insights about the different timing at which the reaction of the systemic risk measures takes place. Second, we investigate through quantile regressions how the performance of green and brown market indexes affects the systemic risk of the two US financial sectors. We observe that higher levels of the green indexes reduce systemic risk more than a raise in brown indexes, with an increasing magnitude in tail conditions. A raise in the riskiness of the green indexes seems to significantly increase systemic risk, with the effect being stronger than that of an increase in the riskiness of brown indexes. Our results confirm the importance of the adoption of appropriate policies aiming at contrasting the raise in the frequency and severity of climate disasters. Our findings are also important in the perspective of the likely increase (decrease) in the exposure of financial firms towards green (brown) companies, induced by the policy decisions taken to combat climate change, and in terms of the implications for banks’ and insurers’ risk management models and procedures.

Using unique hand-collected data for 336 large banks across 48 countries, together with values of national culture, our empirical analysis uncovers three new robust findings. First, variations of bank risk-taking across national culture and CEO power are more pronounced when cultural values and CEO power indicators are high. Second, while the individualism dimension of national culture has a moderating influence, the uncertainty avoidance dimension has a reinforcing effect, on the relationship between CEO power and bank risk-taking. In more detail, the results for the average marginal effect of CEO power on risk for different cultural values show that CEO power has a negative (positive) or insignificant impact on bank risk-taking when the value of individualism (uncertainty avoidance) is low; however, the impact becomes positive (negative) and statistically significant as the value of individualism (uncertainty avoidance) increases. Third, intra-cultural diversity matters: ‘tight’ cultures (e.g., strong social norms) are more pronounced than ‘loose’ cultures (e.g., heterogeneous values) in influencing bank risk.

The financial intermediation wedge of the banking sector used to co-move positively with the federal funds rate, but the post-GFC era saw a disconnect between them. We develop a flexible price dynamic general equilibrium with banks’ liquidity creation to offer an explanation. In a corridor system, the financial wedge and policy rate are shown to co-move, and the pass-through of monetary policy onto both inflation and output obtains. However, the post-GFC floor system obviates the need for the financial wedge to cover the cost of obtaining reserves, so the wedge and the policy rate indeed disconnect in equilibrium; furthermore, we show that the disconnect obstructs monetary expansions from generating inflation. In this environment, tightening bank capital requirement leads to disinflationary pressure. Money-financed fiscal expansions that subsidise non-bank sectors’ borrowing costs improve output and reduce default risks but increase inflation. The model uses banks’ liquidity creation via credit extension to provide a rationale for both the pre-pandemic disinflation and the post-pandemic inflation. The results hold both on the dynamic paths and in the steady state, and the role of money enlarges the Taylor rule determinacy region.