Examining the linkage between economic policy uncertainty, coal price, and carbon pricing in China: Evidence from pilot carbon markets.

Economic policies affect companies' production decisions. And the energy consumption volume is an intuitive reflection of the enterprise's production decisions. In China, coal is the main source of carbon emissions and the most important energy source. Therefore, the coal market and the uncertainty of economic policies are both directly tied to the carbon market. This study explores both the direct impact of economic policy uncertainty and coal price on carbon prices as well as the indirect impact of economic policy uncertainty on carbon prices through coal prices by utilizing the DCC-GARCH model and the NARDL model. The findings indicate that the dynamic correlations between coal prices and the CEPU are always negative and that those between the price of carbon and the CEPU vary by area. Meanwhile, the dynamic correlations between coal and carbon prices are only positive in Shenzhen and Beijing. Both coal prices and economic policy uncertainty produce asymmetrical impacts on carbon prices. Some policy implications are provided for developing the carbon markets in light of the results drawn from the study.

Spillovers and connectedness in foreign exchange markets: The role of trade policy uncertainty.

This paper analyses the directional spillover effects and connectedness for both return and volatility of nine US dollar exchange rates of globally most traded currencies under the influence of trade policy uncertainty. We find two interesting results over the study period ranging from December 1993 to July 2019. First, there exists asymmetric spillovers and connectedness among the considered exchange rates when trade policy uncertainty is present. Second, the volatility spillover is stronger than the return connectedness between exchange rate and trade policy uncertainty. These findings are robust to the presence of economic policy uncertainty effects. Concomitantly, the trade policy uncertainty patterns are also found to be useful for predicting currency market dynamics. Our findings contribute to the debate on the impact of trade policy uncertainty on the global economy and financial sector.

Corporate immunity, national culture and stock returns: Startups amid the COVID-19 pandemic.

Small and medium-sized firms, particularly startups, are highly vulnerable to the COVID-19 pandemic because of their financial instability. Using a sample of listed startups across four countries, we investigate whether a startup's built-up capacity pre-COVID-19 can stimulate corporate immunity to endure the impact of the COVID-19 pandemic, reflected via stock performance. We find that the increase in the accumulated COVID-19 confirmed cases worsens stock returns and that the negative effect is alleviated if startups are greater in size as well as have low debt, large board size and CEO duality. Moreover, national cultural dimensions significantly moderate the relationship between stock returns and COVID-19. The COVID-19 negative impact is relieved in societies where people are more collectivistic and cooperative, less tolerant towards uncertainty, and more long-term oriented. Overall, our results support the consolidation of corporate capacities and suggest policymakers consider national culture when formulating COVID-19 or similar infectious pandemic strategies.

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 vaccination, fear and anxiety: Evidence from Google search trends.

Covid-19 vaccination was associated with a general feeling of hesitancy, and its arrival increased fear and economic anxiety. This paper investigates the impacts of Covid-19 vaccination on fear and economic anxiety using a worldwide sample of 194 countries observed from December 1st, 2020 to March 4th, 2021. The difference-in-differences investigation approach shows that with the vaccine's arrival, the Google search trends measuring fear and anxiety are increasing. The arrival of the vaccine has created a general feeling of fear, and people have a lack of confidence in the vaccine's efficiency to overcome the Covid-19 crisis. Specifically, anxiety increased when the delta variant was discovered in India. Governments' interventions must ensure that the Covid-19 vaccine does not have adverse side effects that can harm public health. We suggested that policy makers should focus on increasing the number of older adults willing to receive the vaccine. It can be effective in explaining the benefits of the vaccine, and denying false information about the vaccine and its serious side effects.

Assessing the performance of exchange traded funds in the energy sector: a hybrid DEA multiobjective linear programming approach.

This paper proposes a two-step approach to build portfolio models. The first step employs the Data Envelopment Analysis (DEA) to select assets attaining efficient financial performance according to a set of indicators used as inputs and outputs. The second step builds interval multiobjective portfolio models to obtain the optimal composition of efficient portfolios previously identified with respect to investor preferences. The usefulness of this proposed methodology is illustrated through a selected sample of diversified Exchange Traded Funds (ETFs) operating in the US energy sector. Our results with respect to all models and time horizons mainly show that: (i) ETFs related to nuclear energy are more often viewed as efficient according to all DEA models considered; (ii) the efficient portfolios do not contain any ETFs related to the renewable energy sector; and (iii) natural gas and oil are the sectors that have the most ETFs represented in efficient portfolios. Supplementary Information: The online version contains supplementary material available at 10.1007/s10479-021-04323-6.

Carbon emissions determinants and forecasting: Evidence from G6 countries.

We examine the explanatory and forecasting power of economic growth, financial development, trade openness and FDI for CO2 emissions in major developed economies within the context of the debate on curbing CO2 emissions Post-Paris Agreement (COP21). Using data from G-6 countries from 1978 to 2014 and employing a set of empirical approaches, we find weak evidence of the Environmental Kuznets Curve, while economic growth, capital market expansion, and trade openness are found to be major drivers of carbon emissions. Carbon emissions are also weakly and negatively affected by stock market capitalization and FDI. Moreover, the forecasting performance is quite good, particularly by augmenting the model with energy consumption and oil prices. With respect to climate commitments, our empirical findings reveal important policy implications.

Covid-19 pandemic and tail-dependency networks of financial assets.

This study provides evidence on the frequency-based dependency networks of various financial assets in the tails of return distributions given the extreme price movements under the exceptional circumstance of the Covid-19 pandemic, qualified by the IMF as the Great Lockdown. Our results from the quantile cross-spectral analysis and tail-dependency networks show increases in the network density in both lower and upper joint distributions of asset returns. Particularly, we observe an asymmetric impact of the Covid-19 because the left-tail dependencies become stronger and more prevalent than the right-tail dependencies. The cross-asset tail-dependency of equity, currency and commodity also increases considerably, especially in the left-tail, implying a higher degree of tail contagion effects. Meanwhile, Bitcoin and US Treasury bonds are disconnected from both tail-dependency networks, which suggests their safe-haven characteristics.

On the efficiency of foreign exchange markets in times of the COVID-19 pandemic.

We employ multifractal detrended fluctuation analysis (MF-DFA) to provide a first look at the efficiency of forex markets during the initial period of the ongoing coronavirus disease 2019 (COVID-19), which has disrupted the global financial markets. We use high-frequency (5-min interval) data of six major currencies traded in forex markets during the period October 1, 2019 to 31 March 31, 2020. Before applying MF-DFA, we examine the inner dynamics of multifractality through seasonal and trend decompositions using loess. Overall, the results confirm the presence of multifractality in forex markets, which demonstrates, in particular, (i) a decline in the efficiency of forex markets during the COVID-19 outbreak and (ii) heterogeneous effects on the strength of multifractality of exchange rate returns under investigation. The largest effect is observed for the Australian dollar, which shows the highest (lowest) efficiency before (during) the COVID-19 pandemic, assessed in terms of low (high) multifractality. The Canadian dollar and the Swiss Franc exhibit the highest efficiency during the COVID-19 outbreak. Our findings may help policymakers shape a comprehensive response to improve forex market efficiency during such a black swan event.

Carbon emissions-income relationships with structural breaks: the case of the Middle Eastern and North African countries.

This article revisits the carbon dioxide (CO2) emissions-GDP causal relationships in the Middle Eastern and North African (MENA) countries by employing the Rossi (Economet Theor 21:962-990, 2005) instability-robust causality test. We show evidence of significant causality relationships for all considered countries within the instability context, whereas the standard Granger causality test fails to detect causal links in any direction, except for Egypt, Iran, and Morocco. An important policy implication resulting from this robust analysis is that the income is not affected by the cuts in the CO2 emissions for only two MENA countries, the UAE and Syria.