Economic Notes最新文献

Community banks (CBs), despite holding a fairly small share of US banking assets, provide vital financial services to key segments of the economy and fill a void untapped by larger non-community banks (Non-CBs). They face challenges brought on by a fast-changing banking landscape, evolving technology, and ever-increasing regulatory burden. To remain competitive and to gain scale-related efficiencies, CBs have been seeking mergers even as greater institutional size causes a departure from the classical relationship-based business model. This study examines performance of US CBs and Non-CBs post the Great Recession to reveal how size of these institutions may affect their business operations. Empirical findings show that CBs, compared with their larger counterparts, tend to maintain higher levels of liquidity and lower levels of capital, and demonstrate a greater dependence on core deposits, confirming that CBs focus on deposit taking and soft information-based lending strategies. Furthermore, this study suggests that CBs should not be considered a homogenous group operating under a singular business model and cautions that regulatory dialectics aimed at the banking industry should not employ a one-size-fits-all approach.

A hidden Markov model is proposed for the analysis of time-series of daily log-returns of the last 4 years of Bitcoin, Ethereum, Ripple, Litecoin, and Bitcoin Cash. These log-returns are assumed to have a multivariate Gaussian distribution conditionally on a latent Markov process having a finite number of regimes or states. The hidden regimes represent different market phases identified through distinct vectors of expected values and variance–covariance matrices of the log-returns, so that they also differ in terms of volatility. Maximum-likelihood estimation of the model parameters is carried out by the expectation–maximisation algorithm, and regimes are singularly predicted for every time occasion according to the maximum-a-posteriori rule. Results show three positive and three negative phases of the market. In the most recent period, an increasing tendency towards positive regimes is also predicted. A rather heterogeneous correlation structure is estimated, and evidence of structural medium term trend in the correlation of Bitcoin with the other cryptocurrencies is detected.

The rise of cryptocurrencies during the last decade has caused growing concerns among national and international regulators. One of the risks identified is that these instruments may constitute an innovative tool for criminals when laundering money. This risk has been confirmed by numerous recent cases which have underlined the criminogenic potential of cryptocurrencies. Through the V antimoney laundering (AML) Directive, the European legislator has first regulated this emerging issue. This legislation extends the AML duties to two players of the cryptocurrencies market: exchangers and wallet providers. This choice, however, does not exploit the opportunities offered by cryptocurrencies and fails to provide a customized regulatory framework. By maintaining a traditional regulatory approach centered on intermediaries it misses the key innovation of blockchain technology: disintermediation. Compared with traditional online money flows, intermediaries are not necessary nor fundamental in the cryptocurrencies environment. Failing to adapt to this reality, the Directive is employing chivalry to fight a trench war. To guarantee the integrity of this market, the policymaker has to abandon the traditional intermediary-centred approach in favor of a strategy that seizes the new opportunities offered by blockchain. This paper advocates for a shift from an individual-centered approach to financial crime control to a transaction-centered one.

This paper empirically characterises the value effect detected in the Italian stock market for the sample period 2000–2018 based on the value premium offered for the acquisition of a value stock. Bids on value stock (as opposed to bids on growth stocks) generate a large and statistically significant average return on the holding of the target in the deal window. Returns on target stocks for a bid make up to two-thirds of the average return on the long side of the Fama and French high book-to-market minus low book-to-market (HML) portfolio. The other significant component of the average return of HML is due to short-selling small-growth stocks. As evidenced in previous literature, this is often difficult to implement from a practical point of view.

The trilogy among economic growth, social capital (SC), and financial development is examined based on three hypotheses: first, SC is important in the finance-growth nexus. Second, there is a threshold effect of SC in the finance-growth nexus. Third, the SC-finance-growth trilogy depends on the countries' income level. Building data set for 70 countries, some interesting results were obtained: (i) the marginal effects of both SC and finance promote economic growth at higher levels; (ii) there is evidence of a threshold effect of SC, as finance enhances more growth when SC is below the threshold level; (iii) higher-income countries tend not to benefit from the SC-finance-growth trilogy. These results suggest that the influence of SC on growth trajectory is exaggerated in the literature. The study recommends that policymakers should pursue other sources of economic growth aside SC, while ensuring that the level of SC does not deteriorate.

Asset pricing theories imply the existence of a long run relation between real housing prices and rents. The long run relation predicts, that in each time period real housing prices should be equal to the expected present discounted value of subsequent real rents. We use the annual time series for the 1991–2016 period in Italy as evidence regarding the present discounted value relation. Considering the stochastic properties of the aggregate time series, cointegration tests do not deliver conclusive results. In a dynamic vector autoregression model, real housing prices are shown to properly anticipate forthcoming real rents, though they exhibit excess volatility. In the sample period, movements of housing prices relatively to the long run relation predict successive real returns. While rational speculative bubbles might produce excess volatility of housing prices, other explanations are required for the predictability of real housing returns.