Carbon dioxide emissions and environmental risks: Long term and short term.

The world is currently experiencing the environmental challenge of global warming, necessitating careful planning of carbon dioxide (CO2 ) emissions to deal with this problem. This study examines the environmental challenge posed by CO2 emissions from both a long and short-term perspective. In the long term, despite efforts made by countries, our change-point detection analysis shows that there has been no structural change in CO2 emissions since 1950. Without significant efforts, the carbon budget corresponding to the Paris Agreement's target will be exhausted by 2046. To achieve this target, a significant reduction in global CO2 emissions of 3.22% per year is necessary. In the short term, COVID-19 is thought to have relieved pressure on CO2 emissions. However, this study shows that CO2 emissions quickly returned to normal levels after a brief downturn, and we provide information on the order of CO2 emissions recovery for different sectors.

When do climate change legislation and clean energy policies matter for net-zero emissions?

Achieving the global decarbonization goal under global conflicts is becoming more uncertain. Within this context, this article seeks to examine the effects of global environmental management and efforts to achieve this goal. Specifically, it investigates the role of democracy, control of corruption, and civil society participation as mechanisms that moderate the impact of environmental policy and legislation, particularly clean energy policy and climate change legislation (laws and regulations), on carbon emissions in highly polluted countries. The empirical results show that (i) the effects of democracy-clean energy policies and climate change legislation are relatively small in reducing carbon emissions; (ii) the effect of controlling corruption-climate change regulations is strong in reducing emissions, meaning that governments with higher control of corruption are more effective at enacting and executing laws and regulations dealing with environmental challenges which help achieve desirable environmental outcomes; (iii) strong civil society participation helps the execution of clean energy policies and climate change legislation to curb emissions, and (iv) the robustness check also provides strong evidence that higher control of corruption can contribute to the effectiveness of these policies and legislation in reducing carbon emissions. Overall, these findings suggest that the efficiency of well-designed environmental policy and legislation should be supported by a combination of higher civil society participation and greater control of corruption that can efficiently enforce such policies and legislation.

COVID-19 and finance scholarship: A systematic and bibliometric analysis.

COVID-19 has posed unprecedented challenges to global finances because of its unparalleled global scope, with both concomitant shocks as well as the likely altering of risk assessments and forecasts for the foreseeable future. As the effects of COVID-19 on financial markets and institutions have been widely addressed by various literature, we systematically synthesize this literature. Through a comprehensive search process, we extract and review 818 articles. Appling bibliometric methods, we explore the trends among various research constituents involved in the field. Using multi-dimensional scaling, we identify the intellectual structure of research in the domain and outline four distinct themes. We also identify the evolution and shifts in research within the short span of three years since the inception of COVID-19. Through detailed content analysis, various future research directions are proposed.

In search of hedges and safe havens during the COVID-19 pandemic: Gold versus Bitcoin, oil, and oil uncertainty.

This paper investigates the potential hedging and safe-haven properties of several alternative investment assets, including gold, Bitcoin, oil, and the oil price volatility index (OVX), against the risks of the Saudi stock market and its constituent sectors in different phases of the COVID-19 pandemic. Using daily data, we employ the bivariate dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) technique to model volatilities and conditional correlations. Our findings show that all investigated alternative investment assets had a time-varying hedging role in the Saudi stock market, which became expensive during the early stages of the COVID-19 pandemic. Our results also show that the optimal weights for gold were substantially higher than those of other assets, reaching a peak during the pandemic, implying that investors consider gold a flight-to-safety asset. Additionally, we find that gold and OVX were strong hedges and could have served as weak safe havens for investors during the early stages of the COVID-19 pandemic, while the remaining assets generally lacked these properties and could be merely used as diversifiers. Our empirical findings offer several key implications for policymakers and portfolio managers in Saudi Arabia that may be applicable to similar markets. In particular, we show that OVX-based products can serve as a promising hedging asset for stock markets in oil-exporting countries.

The gender gap in access to finance: Evidence from the COVID-19 pandemic.

Using gender as a theoretical framework, we analyse the dynamics of debt and equity financing during the COVID-19 pandemic for a cross-country sample of 8,921 private firms. We provide evidence of a slight gender bias in debt financing, with creditors favouring female entrepreneurs when dealing with cash flow problems during the COVID-19 pandemic. We find no evidence of gender bias in equity financing. The results are robust after controlling for a larger number of firm-specific characteristics and selection bias. We challenge the assumption of "gender-based discrimination" in the debt market, speculating that in the context of high uncertainty, prototypical forms of femininity may be advantageous as financial institutions seek to hedge their risk by favouring more conservative borrowers.

Cross-influence of information and risk effects on the IPO market: exploring risk disclosure with a machine learning approach.

The paper examines whether the structure of the risk factor disclosure in an IPO prospectus helps explain the cross-section of first-day returns in a sample of Chinese initial public offerings. This paper analyzes the semantics and content of risk disclosure based on an unsupervised machine learning algorithm. From both long-term and short-term perspectives, this paper explores how the information effect and risk effect of risk disclosure play their respective roles. The results show that risk disclosure has a stronger risk effect at the semantic novelty level and a more substantial information effect at the risk content level. A novel aspect of the paper lies in the use of text analysis (semantic novelty and content richness) to characterize the structure of the risk factor disclosure. The study shows that initial IPO returns negatively correlate with semantic novelty and content richness. We show the interaction between risk effect and information effect on risk disclosure under the nature of the same stock plate. When enterprise information transparency is low, the impact of semantic novelty and content richness on the IPO market is respectively enhanced.

Forecasting oil commodity spot price in a data-rich environment.

Statistical properties that vary with time represent a challenge for time series forecasting. This paper proposes a change point-adaptive-RNN (CP-ADARNN) framework to predict crude oil prices with high-dimensional monthly variables. We first detect the structural breaks in predictors using the change point technique, and subsequently train a prediction model based on ADARNN. Using 310 economic series as exogenous factors from 1993 to 2021 to predict the monthly return on the WTI crude oil real price, CP-ADARNN outperforms competing benchmarks by 12.5% in terms of the root mean square error and achieves a correlation of 0.706 between predicted and actual returns. Furthermore, the superiority of CP-ADARNN is robust for Brent oil price as well as during the COVID-19 pandemic. The findings of this paper provide new insights for investors and researchers in the oil market.

Managing bank performance under COVID-19: A novel inverse DEA efficiency approach.

The evolution of the COVID-19 pandemic is highly unpredictable; however, its impacts are limited to neither a single sector nor a single country. This study evaluates the performance and efficiency of 49 Islamic banks across 10 countries during 2019-2020 to assess how those banks can preserve their performance and remain resilient in the aftermath of the COVID-19 pandemic. Using the conventional inverse data envelopment analysis (InvDEA) approach, we show that because of reductions in their outputs, 31 out of the 49 banks studied would need to reduce their inputs so that their efficiency can remain unchanged. However, we show that only 10 banks need to make such adjustments to maintain their efficiency levels using our proposed InvDEA efficiency model. The adjustment for those 10 banks would help in reducing more inputs, suggesting more cost savings, and improving the overall efficiency of the examined banks, compared with the other 31 banks.

COVID-19 crisis and risk spillovers to developing economies: Evidence from Africa.

This study provides new evidence on how risk spillovers occur from the United States to developing economies in Africa during the COVID-19 pandemic. The results show that downside risk exposures of African markets, financial firms and banks particularly increased during Phase I (30 January to 30 April 2020). The nature and magnitude of downside risk exposures of African financial markets were similar to those of the United States. Our results also reveal that the United States is a net transmitter of risk spillovers while Nigeria, South Africa, Egypt and Morocco are net recipients. Our conclusions offer guidance to risk managers, policymakers and investors.

Systemic risk-sharing framework of cryptocurrencies in the COVID-19 crisis.

We use the Conditional Value-at-Risk (CoVaR) model to develop the systemic contagion index (SCI) for cryptocurrencies and examine their spillover effects. The SCI exhibits the highest value during the COVID-19 period, indicating evidence of pandemic-driven contagion channels. Similarly, cryptocurrency systemic networks show that the COVID-19 period induced increased interconnections, highlighting a higher number of systemic contagion channels. Our study has practical implications for investors to identify the systemic vulnerability of each cryptocurrency and make informed decisions during the crisis and non-crisis periods.

COVID-19 media coverage and ESG leader indices.

This study examines the dynamic connectedness between COVID-19 media coverage index (MCI) and ESG leader indices. Our findings provide evidence that MCI plays a role in facilitating the transmission of contagion to advanced and emerging equity markets during the pandemic. The connectedness between MCI and ESG leader indices is more pronounced around March and April 2020 at the peak of the pandemic. The US is a net receiver of shocks reaffirming that it was the most affected country during the pandemic. Our results provide implications for investors, portfolio managers, and policymakers in mitigating financial risks during the pandemic.

The energy-growth nexus revisited: An analysis of different types of energy.

This study revisits the nexus between energy consumption and economic growth by considering several energy use types (i.e., total energy, fossil fuel energy, and renewable energy). For this purpose, a dynamic fixed effects (DFE) estimator is applied to the autoregressive distributed lag (ARDL) model built on an extended version of the neoclassical production function. This study examines a global sample of 107 countries during 1996-2014, classified into three subsamples of countries based on income level. Overall, the findings show that, in the short run, the use of total energy and fossil fuel energy significantly and positively contribute to higher income in total and per-capita terms. However, the growth effects of renewable energy consumption appear to vary across subsamples. In the long run, the impacts of energy on economic growth are mostly insignificant, supporting the view that conservative energy policies do not harm economic growth.

Financial contagion during COVID-19 crisis.

This study examines how financial contagion occurs through financial and nonfinancial firms between China and G7 countries during the COVID-19 period. The empirical results show that listed firms across these countries, financial and non-financial firms alike, experience significant increase in conditional correlations between their stock returns. However, the magnitude of increase in these correlations is considerably higher for financial firms during the COVID-19 outbreak, indicating the importance of their role in financial contagion transmission. They also show that optimal hedge ratios increase significantly in most cases, implying higher hedging costs during the COVID-19 period.

COVID-19 and oil price risk exposure.

This study investigates oil price risk exposure of financial and non-financial industries around the world during the COVID-19 pandemic. The empirical results show that oil supply industries benefit from positive shocks to oil price risk in general, whereas oil user industries and financial industries react negatively to positive oil price shocks. The COVID-19 outbreak appears to moderate the oil price risk exposure of both financial and non-financial industries. This brings important implications in risk management of energy risk during the pandemic.