Central Bank Digital Currencies (CBDC) have attracted considerable interest and its deployment on a global scale is imminent. However, CBDC face several challenges. They include: legal, technological, and political considerations. We summarize those challenges and add a few more that have not received much attention in the literature. We then focus on two forms of CBDC: a narrow version that only replaces notes and coins and a broader form with a deposit feature. The narrow CBDC is the most likely one to be first introduced. Next, relying on evidence of past episodes of financial innovation, and using cross-country data, we explore the hypothetical impact of CBDC on inflation and financial stability, based on the historical behaviour of the velocity of circulation and incorporating a CBDC’s impact using McCallum’s policy rule which sets the stance of monetary policy based on money growth. Our simulations suggest that CBDC need not produce higher inflation, but financial stability remains at risk. We provide some policy implications

This study empirically investigates the relationship between customer concentration and corporate risk-taking. We find that overall customer concentration significantly reduces corporate risk-taking. However, the relationship varies across different settings. Specifically, the negative relationship between customer-base concentration and corporate risk-taking is only significantly present in more marketized regions, more competitive industries, firms with lower market shares, less innovative and non-state-owned firms, and those without major governmental or state-owned-enterprise customers. Moreover, our panel threshold models indicate significant threshold effects. When customer-base concentration is below the first threshold (low concentration level), it is positively associated with corporate risk-taking. When customer-base concentration increases to above the second threshold, the association turns significantly negative, suggesting that a highly concentrated customer base prompts suppliers to take more precautionary measures and avoid excessive risk-taking. Overall, our findings suggest that the concentration of a supplier’s customer base significantly impacts its risk-taking behaviours

Recent innovations have made it feasible to transfer private digital currency without the intervention of an organization such as a bank. Any currency must prevent users from spending their balances more than once, which is easier said than done with purely digital currencies. Current digital currencies such as Bitcoin use peer-to-peer networks and open source software to stop double spending and create finality of transactions. This paper explains how the use of these technologies and limitation of the quantity produced can create an equilibrium in which a digital currency has a positive value. This paper also summarizes the rise of 24/7 trading on computerized markets in Bitcoin in which there are no brokers or other agents. The average monthly volatility of returns on Bitcoin is higher than for gold or a set of foreign currencies in dollars, but the lowest monthly volatilities for Bitcoin are less than the highest monthly volatilities for gold and the foreign currencies

We examine the role played by Mutual Guarantee Institutions (MGIs) in the lending policies undertaken by banks at the peak of the Great Crisis of 2007–2009. We address this issue by using a large database on Italian firms built from the credit files of UniCredit banking Group and focusing on small business. We provide an empirical analysis of the determinants of the probability that a borrowing firm will suffer financial tension and obtain two main innovative findings. First, we find that small firms supported by MGIs less likely experienced financial tensions even at that time of utmost financial stress. Second, our empirical evidence shows that MGIs played a signaling role beyond the simple provision of collateral. This latter finding suggests that the information provided by MGIs turned out to be key for bank–firm relations as scoring and rating systems – being typically based on pro-cyclical indicators – had become less informative during the crisis

In this study, we consider for the first time whether and how stock liquidity impacts corporate climate performance in China. We find that an increase in stock liquidity is highly associated with lower carbon emissions. To address endogeneity concerns, we exploit a unique quasi-natural experiment in China— the stock market liberalization (Shanghai-Shenzhen Hong Kong Stock Connect). Using difference-in-differences (DID) estimations, we find that carbon emissions for treatment firms substantially decrease after the stock market liberalization. The impact of stock liquidity is more pronounced for enterprises facing severe financial constraints, greater equity dependence, and operating in pollution-intensive sectors. Similarly, we find that external monitoring, carbon abatement investment, and green innovation are plausible channels through which stock liquidity drives carbon emissions reduction. We further find that the sensitivity of corporate climate performance to improved stock liquidity becomes stronger following the Paris Agreement. Overall, we uncover new evidence on the impact of stock liquidity on corporate climate performance, expanding our understanding of the role of financial markets towards a greener economy

This paper measures China's financial resilience from the perspective of external risk shocks and analyzes its influencing factors for forecasting. First, we introduce an innovative financial resilience model comprising three submodels: the dynamic factor model, the TVP-VAR model, and a resilience characteristic measurement model that captures resistance and recoverability through absorption intensity and absorption duration. The results show a clear inverse relationship between absorption intensity and absorption duration, with resilience fluctuations exhibiting distinct phase characteristics. Notably, intervals of low resilience often correspond to specific risk events. Second, we apply the Lasso-logistic model for recursive estimation and forecasting financial resilience, while comparing its performance to that of the Logistic regression model. The results indicate that the Lasso-logistic model achieves, on average, a 10 % higher forecasting accuracy than the Logistic model does. Among the most important features identified by the model are macroeconomic and public expectation variables. The analysis shows that the stability of economic fundamentals and market participants' confidence in the future play pivotal roles in strengthening financial resilience and ensuring the stability of the financial system

In this paper, we measure the interdependence of three financial stress sub-indices (banking, securities and foreign exchange) for the major advanced economies during the 1981–2009 period using a single index based on the generalized variance decompositions developed by Diebold and Yilmaz (2012). We present spillover tables and indices that demonstrate financial stress innovations to and from other indices, in addition to spillover plots that show the dynamics of stress. Furthermore, we examine the relationship between financial stability and macroeconomic fundamentals by investigating the effects of financial stress on growth and on price levels. We proxy financial stability and monetary stability with a financial stress index (FSI) and a consumer price index (CPI), respectively, and examine their interdependence. Our findings indicate that the securities markets are the main net transmitters of stress to the other markets. In addition, up to 42.8% of the forecast error variance in all the markets examined emanates from stress spillovers. Finally, our findings highlight the interrelationship of financial and monetary stability

We find that increases in implied market volatility (a proxy for market fear) have a significant impact on returns of bank stocks, above and beyond systematic risk proxied by the expected excess market return during a bad economic regime. Large bank returns are favorably affected by increases in implied market volatility during the crisis, while small banks are adversely affected by increases in implied market volatility. We attribute the different effects among the size-categorized bank portfolios to the perception that large banks are protected by too-big-to-fail policies. Within the sample of small banks, the adverse share price response to increased implied market volatility is more pronounced for banks that rely more heavily on non-traditional sources of funds, use a high proportion of loans in their assets, have a higher level of non-performing assets, and have a relatively low provision for loan losses. The adverse effect of negative innovations in implied market volatility on small bank returns during the crisis is primarily driven by exposure of their loan portfolio to weak economic conditions

We investigate the asymmetric relationship between returns and implied volatility for 20 developed and emerging international markets. In particular we examine how the sign and size of return innovations affect the expectations of daily changes in volatility. Our empirical findings indicate that the conditional contemporaneous return-volatility relationship varies not only based on the sign of the expected returns but also upon their magnitude, according to recent results from the behavioral finance literature. We find evidence of an asymmetric and reverse return-volatility relationship in many advanced, Asian, Latin-American, European and South African markets. We show that the US market displays the highest reaction to price falls, Asian markets present the lowest sensitivity to volatility expectations, while the Euro area is characterized by a homogeneous response both in terms of direction and impact. These results may be safely attributed to cultural and societal characteristics. An extensive quantile regression analysis demonstrates that the detected asymmetric pattern varies particularly across the extreme distribution tails i.e., in the highest/lowest quantile ranges. Indeed, the classical feedback and leverage hypotheses appear not plausible, whilst behavioral theories emerge as the new paradigm in real-world applications

Partial credit guarantee schemes have experienced renewed interest from governments keen to promote financial access for small enterprises, not least as a response to the credit crunch in advanced economies. While the market can find uses for partial credit guarantees, the attractions for public policy can be illusory: indeed their most attractive feature for myopic politicians may be the ease with which the true cost of guarantees can be understated, at least at the outset. In practice, the actual fiscal cost of existing schemes has varied widely across countries and has represented a high per dollar subsidy in some cases. Despite the recent application of some innovative techniques, the social benefit of such schemes has proved difficult to estimate, not least because their goals have been vague. Operational design has influenced the cost and apparent effectiveness of different schemes and has also varied widely. Clear and precise goals, against which performance is regularly monitored, realistic pricing verified by consistent and transparent accounting, and attention to the incentive features of operational design, especially for the intermediaries, are among the prerequisites for such schemes to have a good chance of truly achieving improvements in social welfare