Correction: Information flow dynamics between geopolitical risk and major asset returns.

[This corrects the article DOI: 10.1371/journal.pone.0284811.].

Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets.

This study investigates tail dependence among five major cryptocurrencies, namely Bitcoin, Ethereum, Litecoin, Ripple, and Bitcoin Cash, and uncertainties in the gold, oil, and equity markets. Using the cross-quantilogram method and quantile connectedness approach, we identify cross-quantile interdependence between the analyzed variables. Our results show that the spillover between cryptocurrencies and volatility indices for the major traditional markets varies substantially across quantiles, implying that diversification benefits for these assets may differ widely across normal and extreme market conditions. Under normal market conditions, the total connectedness index is moderate and falls below the elevated values observed under bearish and bullish market conditions. Moreover, we show that under all market conditions, cryptocurrencies have a leadership influence over the volatility indices. Our results have important policy implications for enhancing financial stability and deliver valuable insights for deploying volatility-based financial instruments that can potentially provide cryptocurrency investors with suitable hedges, as we show that cryptocurrency and volatility markets are insignificantly (weakly) connected under normal (extreme) market conditions.

Information flow dynamics between geopolitical risk and major asset returns.

We quantify information flows between geopolitical risk (GPR) and global financial assets such as equity, bonds, and commodities, with a focus on the Russian-Ukrainian conflict. We combine transfer entropy and the I-CEEMDAN framework to measure information flows at multi-term scales. Our empirical results indicate that (i) in the short term, crude oil and Russian equity show opposite responses to GPR; (ii) in the medium and long term, GPR information increases the risk in the financial market; and (iii) the efficiency of the financial asset markets can be confirmed on a long-term scale. These findings have important implications for market participants, such as investors, portfolio managers, and policymakers.

Extreme dependencies and spillovers between gold and stock markets: evidence from MENA countries.

This study addresses whether gold exhibits the function of a hedge or safe haven as often referred to in academia. It contributes to the existing literature by (i) revisiting this question for the principal stock markets in the Middle East and North Africa (MENA) region and (ii) using the copula-quantile-on-quantile and conditional value at risk methods to detail the risks facing market participants provided with accurate information about various gold and stock market scenarios (i.e., bear, normal, bull). The results provide strong evidence of quantile dependence between gold and stock returns. Positive correlations are found between MENA gold and stock markets when both are bullish. Conversely, when stock returns are bearish, gold markets show negative correlations with MENA stock markets. The risk spillover from gold to stock markets intensified during the global financial and European crises. Given the risk spillover between gold and stock markets, investors in MENA markets should be careful when considering gold as a safe haven because its effectiveness as a hedge is not the same in all MENA stock markets. Investors and portfolio managers should rebalance their portfolio compositions under various gold and stock market conditions. Overall, such precise insights about the heterogeneous linkages and spillovers between gold and MENA stock returns provide potential input for developing effective hedging strategies and optimal portfolio allocations.

Frequency spillovers between green bonds, global factors and stock market before and during COVID-19 crisis.

This paper examines frequency dynamic spillovers in return and volatility and the hedging ability of Green Bonds, gold, silver, oil, the US dollar index, and volatility index against downside US stock prices before and during the COVID-19 pandemic outbreak and for the short and long run. To do so, we use the Diebold and Yilmaz (2014), the TVP-VAR model, and the frequency spillover index by Baruník and Krehlík (2018). We show that the short-term volatility spillovers dominate their long-term counterparts. Green Bond is net transmitters of spillovers in the system at the short term and net receivers at the long term. S&P500 and silver (USDX and oil) are net transmitters (receivers) of short- and long-term spillovers. Gold and VIX are net receivers of short-term spillovers and net transmitters of long-term spillovers. COVID-19 crisis has more effects on the short-term spillover, which reaches its highest level early 2020. COVID-19 and time horizons lead the direction and the magnitude of spillovers. The Quantile-on-Quantile regression analysis shows significant nonlinear relationships between markets under study. More interestingly, we show that green bonds and gold are safe haven assets for US equity investors during COVID-19. On the other hand, a mixed portfolio offers higher diversification benefits. Finally, hedging effectiveness is dependent on COVID-19 and time horizon.

Unbundling the dynamic impact of renewable energy and financial development on real per capita growth in African countries.

Industrialization is considered imperative for growth but energy transitions are paramount for inclusive and green growth especially for a region with low financial sector development to spur investment in renewable energy. This study thus unbundles the interrelation among renewable energy production, financial development, and real per capita growth in 32 selected African countries from the period of 1996 to 2018. These countries are categorized on the basis of oil-rich and non-oil-rich as well as income levels. The study employs Pooled Mean Group, Augmented Mean Group, and Dynamic OLS, and key findings are established. The findings reveal a significantly positive renewable energy-economic growth relationship in all the different groups. Financial development is also found to improve economic performance in all categories except in non-oil-rich African countries. These findings empirically support the need for cleaner energy in the production process to spur inclusive and green growth amidst current global concern for climate change and global warning. This study thus recommends the restructuring of the energy pricing system, provision of long-term finance, adoption of risk mitigation instruments, and improved institutional framework for private participation in renewable energy infrastructural development for growth sustainability in Africa.

Global energy markets connectedness: evidence from time-frequency domain.

We examine the presence of dependence across 51 energy markets classified into different regions from Jan 2007 to June 2021. In order to examine the presence of dependence across different energy markets, we apply standard and threshold dependence measures proposed by Diebold and Yilmaz, Int J Forecast 28:57-66, (2012) and Baruník and Krehlík, J Financ Econ 16(2):271-296, (2018). We highlight the presence of strong dependence between the energy markets at both regional level and across other regions. European and American energy markets are highly connected within the region over the long-run whereas Asia-Pacific and the African energy markets offer optimal diversification opportunities. Both short- and long-run dependence exists between Chinese and the Hong Kong energy markets and between the US and Canadian energy markets. We also witness substantial increase dependence across all the energy markets during different crisis periods.

Impacts of COVID-19 outbreak, macroeconomic and financial stress factors on price spillovers among green bond.

We examine the impacts of the COVID-19 pandemic and global risk factors on the upside and downside price spillovers of MSCI global, building, financial, industrial, and utility green bonds (GBs). Using copulas, CoVaR, and quantile regression approaches, we show symmetric tail dependence between MSCI global GB and both building and utility GBs. Moreover, the upper tail dependence between MSCI global GB and financial GB intensified during COVID-19. We find asymmetric risk spillovers from MSCI global GB to the remaining GBs. Finally, the COVID-19 spread, the Citi macro risk index, and the financial condition index contribute positively to the quantiles' risk spillovers. The spillover index method shows significant dynamic volatility spillovers from global GB to GB sectors that intensify during the pandemic outbreak, except for financial GB. The causality-in-mean and in-variance from COVID-19, Citi macro risk index, and US financial condition index to the downside and upside spillover effects are sensitive to quantiles.

Uncertainty measures and inflation dynamics in selected global players: a wavelet approach.

This study investigates the dynamic relationship between economic policy uncertainty (EPU), geopolitical risks (GPR), the interaction of EPU and GPR (EPGR), and inflation in the USA, Canada, the UK, Japan, and China. We employ the continuous wavelet transform (CWT) to track the evolution of model variables and the wavelet coherence (WC) to examine the co-movement and lead-lag status of the series across different frequencies and time. To strengthen the WC, we apply the multiple wavelet coherence (MWC) to determine how good the linear combination of independent variables co-moves with inflation across various time-frequency domains. The CWT reveals heterogeneous characteristics in the evolution of each variable across frequencies. Inflation across samples shows strong variance in the short-term and medium-term while the volatility fizzles out in the long-term. For the explanatory variables, a similar pattern holds for EPU except for Japan and China, where coherence is evident in the short-term. The USA's and Canada's GPR reveal strong coherence in the short- and medium-term. Also, the UK and China reflect strong coherence in the short-term but weak significance in the medium-term, while Japan's GPR reflects only strong coherence in the short-term. The EPGR shows strong variation in the short-and-medium-term in the samples except in China. The WC's phase-difference reflects bidirectional causalities and switches in signs among series across different scales and periods in the samples, while the MWC reveals the combined intensity, strength, and significance of both EPU and GPR in predicting inflation across frequency bands among the countries. Findings also show significant co-movement among series at date-stamped periods, corroborating critical global events such as the Asian financial crisis, Global financial crisis, and COVID-19 pandemic. The paper has policy implications.

Military spending, financial development, and ecological footprint in a developing country: insights from bootstrap causality and Maki cointegration.

Military spending is required for national sovereignty, but it comes at a cost. The ecological consequences of military activities remain insufficiently investigated, especially in developing countries, where military spending is on the rise due to terrorism and civil unrest created by different secessionists' groups. As such, this study has a maiden attempt to address this gap by exploring the effects of military spending on the ecological footprint (EF) using the bootstrap causality test and the Maki (2012) cointegration test under multiple structural breaks. The findings suggest that military spending increases the EF. Also, while energy consumption and economic growth degrade the environment, financial development enhances environmental wellbeing by reducing the ecological footprint. The causality results suggest a unidirectional causality from military spending to EF, while feedback causality exists between military spending and economic growth. The result of this study affirms the existence of destruction theory and also provides a better understanding of the links behind environmental degradation and is applicable for the design and implementation of environmental policies.

The Return and Volatility Connectedness of NFT Segments and Media Coverage: Fresh Evidence Based on News About the COVID-19 Pandemic.

We study the relationship between return and volatility of non-fungible tokens (NFT) segments and media coverage during the outbreak of the COVID-19 pandemic in a connectedness framework. We document media coverage as a net transmitter of spillover for both the return and volatility of NFT segments. We find that NFTs representing the Utilities segment is a major transmitter of spillover. Our findings have important implications for portfolio managers, regulators, and policymakers.

The spatial distribution dynamic and convergence of CO2 emissions in Iran's provinces.

It is essential to study CO2 emissions intensity as the most critical factor affecting temperature increase and climate change in a country like Iran, which ranked seven regarding CO2 emissions intensity. Investigating the convergence of CO2 emissions intensity is essential in recognizing its dynamics in identifying the effectiveness of government environmental policies. In this paper, using the Markov chain and spatial Markov chain methods, the convergence of CO2 emissions intensity from fossil-fuel consumption has been investigated in 28 provinces of Iran from 2002 to 2016. The empirical results showed that convergence clubs and neighbors significantly influenced the transition probability of regions to clubs with high and low CO2 emissions. Therefore, if a province had a neighbor with low (high) CO2 emissions intensity, the transition probability of this province to the club with low (high) CO2 intensity increased. Therefore, in provinces that have neighbors with low (high) CO2 emissions intensity, the transition probability to the club with low (high) CO2 intensity increases.

COVID-19 pandemic's impact on intraday volatility spillover between oil, gold, and stock markets.

This study examines the volatility spillovers between the US stock market (S&P500 index) and both oil and gold before and during the global health crisis (GHC). We apply the FIAPARCH-DCC model to the 15-minute intraday data. The results showed negative (positive) conditional correlations between the S&P500 and gold (oil). The time-varying conditional correlations between markets were higher during COVID-19 spread. Moreover, gold offers more diversification gains than oil does during the pandemic. Hedging is more expensive during a pandemic than before. Oil provides higher hedging effectiveness (HE) than gold for all sub-periods. HE was lower during the COVID-19 outbreak for both oil and gold. These findings have important implications for both equity investors and policymakers.

Investigation of economic and financial determinants of carbon emissions by panel quantile regression analysis: the case of Visegrád countries.

This study determines the impacts of gross domestic product, domestic bank credits given to private sector, and military expenditures on carbon emissions based on 1990-2019 time period. The panel quantile regression approach is applied for the Visegrád group countries. Our empirical results reveal that domestic bank credit given to private sector has a positive and meaningful impact on carbon emissions at medium and high quantile levels. On the other hand, it has been determined that gross domestic product has a reducing impact on carbon emissions, but military expenditures have an increasing impact on carbon emissions. Besides, as consequences of such tests, the difference between the quantiles, that is, the heterogeneous structure was revealed. A separate model was created with a different panel quantile approach for robustness control, and the results were compared by giving different values to penalty term. These results provide strong evidence for decision-makers and implementers.

Renewable energy-economic growth nexus revisited for the USA: do different approaches for modeling structural breaks lead to different findings?

It can be observed from the existing energy literature the previous papers investigating the influence of renewables consumption on GDP for the USA commonly ignore structural breaks in the US economy. Hence, the purpose of this paper is to examine the impact of renewable energy consumption on economic growth for the USA using quarterly data over the period 1977Q1-2019Q3 through unit root and cointegration methods based on different approaches in modelling structural breaks. Our empirical evidence confirms that all unit root tests give similar outputs and show all the variables become stationary at 1st differences. Besides, cointegration tests show highly different results in terms of the statistical significance of the coefficients. For instance, the cointegration test without structural breaks indicates that renewable energy consumption has no impact on economic growth. With sharp structural breaks in the cointegration approach, there is no cointegration between the variables. The empirical findings of the cointegration test with sharp and gradual breaks imply that renewable energy consumption has positive effects on economic growth. This paper discusses the implications of the empirical findings.

Liquidity connectedness in cryptocurrency market.

We examine the dynamics of liquidity connectedness in the cryptocurrency market. We use the connectedness models of Diebold and Yilmaz (Int J Forecast 28(1):57-66, 2012) and Baruník and Krehlík (J Financ Econom 16(2):271-296, 2018) on a sample of six major cryptocurrencies, namely, Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Ripple (XRP), Monero (XMR), and Dash. Our static analysis reveals a moderate liquidity connectedness among our sample cryptocurrencies, whereas BTC and LTC play a significant role in connectedness magnitude. A distinct liquidity cluster is observed for BTC, LTC, and XRP, and ETH, XMR, and Dash also form another distinct liquidity cluster. The frequency domain analysis reveals that liquidity connectedness is more pronounced in the short-run time horizon than the medium- and long-run time horizons. In the short run, BTC, LTC, and XRP are the leading contributor to liquidity shocks, whereas, in the long run, ETH assumes this role. Compared with the medium term, a tight liquidity clustering is found in the short and long terms. The time-varying analysis indicates that liquidity connectedness in the cryptocurrency market increases over time, pointing to the possible effect of rising demand and higher acceptability for this unique asset. Furthermore, more pronounced liquidity connectedness patterns are observed over the short and long run, reinforcing that liquidity connectedness in the cryptocurrency market is a phenomenon dependent on the time-frequency connectedness.

Are there wages from "sin"? Working conditions spillover from paying bribe in Vietnam.

This paper examines how bribe payment by enterprises in Vietnam affects employees' working conditions, particularly wage benefits and other non-monetary compensations. We exploit the variation in the interaction of the score for the transparency of the local government in a specific province, the district-sector share of enterprises engaging in bribe payment, and the sector average size of the enterprise owner's social network that are public officers as an exogenous variation in the likelihood of engaging in bribe payment. The results of the analysis reveal that when an enterprise pays bribe, it reduces the wages of its employees by approximately 27.6% (mostly for those within the highest wage bracket). Employees' membership of a trade union, enterprise' performance, capacity for inter-jurisdictional mobility, investment in human capital development, and formality status are likely operative channels of impact. Plain English Summary Enterprises' engagement in bribe payment has negative impacts on the wages of employees. Corruption and bribe payment are endemic in many developing countries and they come at a cost to the broader society. Several studies have been conducted on how corruption impacts the welfare of individuals and households, the productivity, and effective and efficient functioning of firms and government, but we contribute to this debate by considering how bribe payment at the firm level affects employees' welfare. We argue that bribe payment by an enterprise has potential effects on the wages and other non-monetary compensations of their employees. Depending on the size of the bribe and the profit level of the enterprise, bribe payment may reduce or improve an enterprises' cash flow. In an event that the enterprise incurs a cost for paying bribe, it may transfer the cost to its employees by either cutting their wages or adjusting other pecuniary benefits that they receive. On the other hand, if the enterprise benefits from paying bribe, employees' wages and other benefits could either increase as a spillover effect or remain unchanged depending on several factors, including the enterprise's appetite for further bribe payment in anticipation of reaping more benefits in the long term. We use a unique dataset from the survey of Vietnamese small- and medium-scale manufacturing enterprises to validate these propositions and the channels through which they operate. The results of the analysis show that when an enterprise pays bribe, it reduces the wages of its employees (mostly for those within the highest wage bracket) by approximately 27.6%. Our result further shows that employees' membership of a trade union, an enterprise's performance and its capacity to move between different jurisdictions of operation, investment in human capital development, and formality status are the potential channels through which the identified impact operates. These findings support the need for anti-corruption policies, which could have other spillover effects on decent labor outcomes in Vietnam and other developing countries.

Does energy consumption reinforce environmental pollution? Evidence from emerging Asian economies.

Steadily improving per capita income level, energy consumption, and delivery of financial services in South and Southeast Asian countries has remained a subject of discussion among policymakers. Because these endeavors have not only elevated their growth trajectory but also widened the scope for carbon emissions, especially in the preceding two decades. In order to confirm this argument, therefore, in the present study, we intended to examine their dynamic impacts on carbon emissions. In this pursuit, by using the second-generation unit-root test, cointegration test, and panel regression procedures, we investigated the moderating impact of energy solutions on the association between per capita income and CO2 emissions and financial development and CO2 emissions from 1976 to 2015. The computed results revealed that the energy's interaction with the linear per capita income significantly escalated carbon emissions in the long run. However, the impact of energy's interaction with the squared per capita income on carbon emissions is found insignificant but positive in the long run. On the other hand, the interaction of energy with financial development provided a negative but insignificant coefficient. Based on the outcomes, we can ascertain that, at the lower level of income, energy consumption leads to environmental pollution, whereas at the higher level of income, its harmful effect on carbon emissions becomes weak in the given regions. By taking a cue from the computed results, we proposed a policy framework that might help these regions to navigate the energy-led environmental challenges in the coming years.