How effective are bad bank resolutions? New evidence from Europe

The paper studies the effectiveness of bank resolutions using a comprehensive database on banks headquartered in 18 European countries over the period 2000–19. By means of difference-in-differences methodology, we find that impaired asset segregations – otherwise known as bad banks – have been more effective than state-funded recapitalisations of distressed banks. While recapitalised banks seem to have used the injected funds mainly to clean up their balance sheets by reducing problem loans and cutting down on lending, banks that segregated assets increased progressively their lending after the creation of the bad bank. For both types of banking crisis interventions, we find a significant ex-post reduction in the cost of bank funding and shift towards deposit funding

Climate bonds: Are they invested efficiently?

Achieving a Net-Zero goal is heavily reliant on transitioning to green methods, making it a top priority. Our research, which used the Generalized Least Squares (GLS) panel method, found that each Macro-region should invest at least 2% more per capita annually in Climate Bonds, a type of green bond. Although some studies have questioned the effectiveness of Climate Bonds, our focus is on their efficient use in countries that produce more fossil fuels. Our findings show that globally, a) Climate Bonds are underutilized in areas with higher per capita use of fossil fuels, and b) High-income countries are gradually reducing their reliance on fossil fuels, while low-income countries have always used very little (with a forecast of future growth). Allocating financial resources in the form of Climate Bonds for the green transition should consider per capita use of fossil fuels, as well as the heterogeneity of population growth and different Macro-Regional economic development. Developing countries, with their large populations, will require more financial resources for an ethically acceptable green transition in the future

Bank Market Structure, Systemic Risk, and Interbank Market Breakdowns

This paper explores theoretically the implications of bank market structure and banking system risks concentration for the functioning of interbank markets. It employs a simple model where banks are exposed to both credit and liquidity risk, there is no asymmetric information, no market power, no friction in secondary markets and deposit contracts are fully contingent. We show that (a) the concentration of risks induced by changes in bank market structure makes interbank market breakdowns more likely; (b) welfare monotonically decreases in risk concentration; and (c) risk concentration and a high probability of interbank market breakdowns can be driven by risk control diseconomies of scale and scope and increases in financial firms’ size. As banking systems become more concentrated, improvement of risk control technologies in financial institutions and in regulatory bodies appear as important as other policies considered in the literature to minimize the probability of interbank market breakdowns.bank market structure; systemic risk; interbank markets

COVID-19 Deaths Linked to Restrictions Stringency Lag: A G7 and Global Analysis, Implications for Public Policy

This study focuses on the results of the G7 countries from the analysis of daily data from 184 countries of the world during the COVID-19 epidemic. After an increase in restrictions, there is an increase in new COVID-19 deaths. To understand the influences on number of deaths by country, the analysis reveals that per capita income is significantly positively correlated with mortality from COVID-19. This suggests that the epidemic first hit rich countries the hardest through the correlation to the human development index. This finding was contrary to what was predicted by the Global Health Security Index on pre-pandemic preparedness. Within affluent countries, deaths and cases were higher among socio-economic challenged populations. This was supported by the number of deaths that are positively influenced by the GINI index that is an indicator of disparity of income and wealth. The research indicates that after an increase in restrictions, there is an increase in new COVID-19 deaths and cases. This along with the finding on the stringency index, correlated with the stringency lag, point to the effectiveness of policies being negatively correlated due to a lag in implementation and partial application. Moreover, the uncertainty or the variability of the stringency index has a negative impact on mortality. The “Power Distance” by was used to understand individual’s reaction to restrictions indicated by the stringency index and the stringency lag, COVID-19 death numbers were also found to be positively influenced by a countries “Power Distance”. These findings are key to the improve policy management of the virus. The Delta plus and Lambda variant’s increased transmissibility and potential vaccine resistance increases the urgency for policy makers to understand and immediately enforce the stringency of regulations in consideration of their countries Power Balance index, and to reduce the stringency lag of their policies to increase the effectiveness in reducing the transmission of COVID-19

Systemic Risks and the Macroeconomy

This paper presents a modeling framework that delivers joint forecasts of indicators of systemic real risk and systemic financial risk, as well as stress-tests of these indicators as impulse responses to structural shocks identified by standard macroeconomic and banking theory. This framework is implemented using large sets of quarterly time series of indicators of financial and real activity for the G-7 economies for the 1980Q1-2009Q3 period. We obtain two main results. First, there is evidence of out-of sample forecasting power for tail risk realizations of real activity for several countries, suggesting the usefulness of the model as a risk monitoring tool. Second, in all countries aggregate demand shocks are the main drivers of the real cycle, and bank credit demand shocks are the main drivers of the bank lending cycle. These results challenge the common wisdom that constraints in the aggregate supply of credit have been a key driver of the sharp downturn in real activity experienced by the G-7 economies in 2008Q4-2009Q1.

Catch the Heterogeneity: The New Bank-Tailored Integrated Rating

The purpose of this article is to develop a bank-oriented rating approach, tailored by incorporating the various heterogeneity dimensions characterizing financial institutions, named “Bank-Tailored Integrated Rating” (BTIR). BTIR is able to catch the financial cycle, including the pandemic crisis, and the ongoing change in banking normative from a microeconomic perspective, and it is inherently coherent with the challenging frontier of forecasting tail risk in financial markets in similar ways as in De Nicolò and Lucchetta (2017), although their approach is macroeconomic) since it considers the downside risk in the theoretical framework. The method employed was an innovative integrated rating (IR) statistical and econometrical panel pre-selection analysis that takes into account the characteristics of risk and the greater heterogeneity of the banks. The result is a challenge rating procedure delivering forward-looking preselection requested by the new International Financial Reporting Standard (IFRS-9). The future direction is extremely promising given the increase in idiosyncratic and systemic risks in financial markets.The purpose of this article is to develop a bank-oriented rating approach, tailored by incorporating the various heterogeneity dimensions characterizing financial institutions, named "Bank-Tailored Integrated Rating" (BTIR). BTIR is able to catch the financial cycle, including the pandemic crisis, and the ongoing change in banking normative from a microeconomic perspective, and it is inherently coherent with the challenging frontier of forecasting tail risk in financial markets in similar ways as in De Nicole and Lucchetta (2017), although their approach is macroeconomic) since it considers the downside risk in the theoretical framework. The method employed was an innovative integrated rating (IR) statistical and econometrical panel pre-selection analysis that takes into account the characteristics of risk and the greater heterogeneity of the banks. The result is a challenge rating procedure delivering forward-looking preselection requested by the new International Financial Reporting Standard (IFRS-9). The future direction is extremely promising given the increase in idiosyncratic and systemic risks in financial markets

Emerging Stock Premia: Do Industries Matter?

This paper studies the dynamics of emerging excess returns in a industry-by-industry context. Differently from the recent financial literature, which mainly focuses on “total market indexes”, we perform a standard ex-post empirical analysis aimed at capturing the industries’ contribution to country stock performances. We obtain three key empirical findings. First, at industry level, we confirm the “high performance-high volatile nature” as well as the timevarying component of emerging excess returns. Second, at country level and in a dynamic context, we detect those industries that mainly contribute to the presence of emerging stock premia. Third, we show that some industries are much more exposed to global factors than others. We argue that these results display relevant implications for portfolio diversification and reflect consumption smoothing motive

Forecasting Tail Risks

This paper presents an early warning system as a set of multi-period forecasts of indicators of tail real and financial risks obtained using a large database of monthly US data for the period 1972:1-2014:12. Pseudo-real-time forecasts are generated from: (a) sets of autoregressive and factor-augmented vector autoregressions (VARs), and (b) sets of autoregressive and factor-augmented quantile projections. Our key finding is that forecasts obtained with AR and factor-augmented VAR forecasts significantly underestimate tail risks, while quantile projections deliver fairly accurate forecasts and reliable early warning signals for tail real and financial risks up to a 1-year horizon