A statistical measure of the containment of Covid-19 is proposed to describe seven possible outcomes ranging from the worst outcome of ‘beyond control’ and the best outcome of ‘under control with rapid progress towards zero infections’. This measure is used to examine the performance of 10 countries with emphasis on the role of government-imposed measures of social distancing (lockdown, etc.). The results show that social distancing is effective, even though it is difficult to separate the effect of government measures from that of social distancing triggered by personal initiatives. The experience of Sweden shows that social distancing as a personal initiative is inadequate for the purpose of containing the virus. The experience of Brazil shows that taking the virus lightly brings about serious consequences.

Although financial development is essential for economic development, excessive financialization of the economy is believed to exert a negative effect on output growth. In this article, empirical evidence is presented on the relation between economic growth and financialization as measured by the ratio of credit to GDP and the ratio of publicly traded shares to GDP. The empirical results are based on annual time series data for six country groups as well as cross-sectional data covering a large number of countries. The model is initially specified with unobserved components and estimated in a time-varying parametric framework to account for missing variables. Thereafter, the issue of linear versus quadratic specifications is examined. The results are robust with respect to model specification, estimation method, data type and variable definition, showing in general that financialization has a negative impact on growth. Some evidence is also presented to support the notion of the financial Kuznets curve.

Four econometric issues associated with the estimation and testing of the environmental Kuznets curve (EKC) are considered: (i) model specification with respect to the order of the polynomial, (ii) model specification with respect to the use of linear or log-linear specifications, (iii) integration and cointegration considerations, and (iv) missing variables and time trends. These issues are examined in reference to Australian data on four measures of CO2 emissions and three measures of per capita income. While evidence is provided for an inverted U-shaped EKC, the results cannot be generalized. It is concluded that without the use of sensitivity analysis, the results are typically fragile.

A simulation exercise is used to demonstrate the difficulty to outperform the random walk in exchange rate forecasting if forecasting accuracy is judged by the Root Mean Square Error (RMSE) or similar criteria that depend on the magnitude of the forecasting error. It is shown that, as the exchange rate volatility rises, the RMSE of the model rises faster than that of the random walk. While the literature considers this finding to be a puzzle that casts a big shadow of doubt on the soundness of international monetary economics, the results show that failure to outperform the random walk, in both in-sample and out-of-sample forecasting, should be the rule rather than the exception. However, the results do not imply that the random walk is unbeatable, because it can be easily outperformed if forecasting accuracy is judged according to criteria such as direction accuracy and profitability.

This study examines the impact of environmental regulation on the Singapore stock market using the event study methodology. Several asset pricing models are used to estimate sectoral abnormal returns. Additionally, we estimate the change in systematic risk after the introduction of the carbon tax and related regulation. We conduct various robustness tests, including the Corrado non-parametric ranking test, the Chesney non-parametric conditional distribution approach, a representation of market integration, and Fama–French five-factor model. We find evidence showing that the environmental regulations tend to achieve their desired effects in Singapore in which several big polluters (including industrial metals and mining, forestry and papers, and electrical equipment and services) were negatively affected by the announcements of environmental regulations and carbon tax. In addition, our results indicate that the electricity sector, one of the biggest polluters, was negatively affected by the announcement of environmental regulations and carbon tax. We also find that environmental regulations seem to boost the performance of environmentally-friendly sectors whereby we find the alternative energy industry (focusing on new renewable energy technologies) experienced a sizeable positive reaction following the announcements of these regulations.