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This paper examines the effect of geopolitical risk (GPR) on return and volatility dynamics in Middle East and North African (MENA) countries by using an ADCC-GARCH model and a spillover approach. Unlike previous studies, we include the GPR index to capture risk associated with wars, terrorist acts, and political tensions. Moreover, we test for both static and dynamic analysis using a rolling window. In brief, the findings highlight that GPR does not contribute to the return spillovers among MENA financial markets. However, the dynamic analysis provides evidence of the high level of responsiveness of the total spillover index to major political events (e.g., the Arab Spring uprising and political tension between Qatar and other Gulf Cooperation Council countries). More interestingly, Qatar, Kingdom of Saudi Arabia, and the United Arab Emirates are identified as the main transmitters of return spillovers to the rest of the MENA markets. Overall, our results are essential in understanding the impact of the GPR on return spillover among MENA countries, and are of particular importance to policymakers, market regulators, portfolio managers and investors.

This study aims to analyze the impact of oil shocks on the external balance of Saudi Arabia, as one of the largest net oil-exporting countries. To this end, a time-varying parameter vector autoregression model (TVP-VAR) is estimated by using quarterly data covering the period between 1991: Q1 and 2021: Q4. We find that identifying the source of shocks plays an important role in understanding the time-varying impact of shocks on its economy. Our findings indicate that the global oil production shocks excluding Saudi Arabia have a negative and significant impact on the trade balance and are greater than the impact of the Saudi oil production shocks, which is not significant for most of the period. In addition, we found that oil price shocks have more profound and much greater impacts than global and domestic oil supply shocks. This may be attributed to the fact that oil price shocks are more than oil supply shocks, and supply shocks are linked to oil price shocks. However, impulse responses show that the effects of oil shocks are volatile over time and their effects are generally more pronounced during and immediately after global shocks. Our findings have serious implications for the trade balance of Saudi Arabia, particularly in the low and volatile oil price environment.

Unlike the previous literature, this study develops a comprehensive index of CEO education that considers levels and quality in bachelor’s, master’s, and doctoral (PhD) programs and examines how they relate to corporate policies such as capital expenditures, research and development expenditures (R&D), leverage, liquidity, and dividends. The findings indicate that the quality and level of PhD education are positively associated with R&D and liquidity but are negatively associated with leverage and capital expenditures. The quality and level of master’s education negatively impact R&D, leverage, and liquidity. Bachelor’s degree is positively associated with dividends and leverage but negatively impacts R&D and liquidity. The propensity score matching, however, does not support the baseline results concerning the positive impact of having a bachelor’s degree on capital expenditures. Extended analyses suggest that powerful CEOs with a higher level and quality of education tend to make decisions with excessive risk or poor-quality decision-making. Additionally, the media’s intensive coverage of CEOs with a higher level and quality of education increases their desire to pursue conservative corporate policies.

Purpose This paper aims to investigate the relationship between investor attention and market activity (return, volatility and volume) using a sample of 14 clean energy cryptocurrencies (hereafter green cryptocurrency), namely, Chia, Cardano, Stellar, Tron, Ripple, Nano, IOTA, EOS, Bitcoin Green, Alogrand, Hedara, Polkadot, FLOW and Tezos. Design/methodology/approach This paper use 26040 crypto-day observations and a range of econometric techniques, including Dynamic Granger causality, Panel vector autoregression (VAR), Impulse response function and the decomposition of forecast error variance. Findings Based on 26040 crypto-day observations, this paper finds a bidirectional Granger causal relationship between investor attention and all measures of market activity, namely, return, absolute volatility, squared volatility and volume. The panel VAR and impulse response function demonstrate that market activity in the green crypto ecosystem, especially volatility and volume, is considerably responsive to changes in investor attention proxied by Google search volume (hereafter Google search volume (GSV)). The findings also demonstrate a significant asymmetric effect of return and volume on investor attention since past negative shocks “or bad news” in return and volume are more likely to grab the investor’s attention. All in all, our study emphasizes the crucial role of investor attention in the green crypto ecosystem. Originality/value (i) The research is the first to shed light on investor attention in the green cryptocurrency market. (ii) The paper uses a wide range of green cryptocurrencies to offer a comprehensive picture of the green cryptocurrency ecosystem. (iii) This paper is the first to use the panel Granger causality to investigate investor attention in the cryptocurrency market which provides several advantages over the conventional Granger causality approach. (iv) This paper is the first to provide novel empirical evidence on the prevalent influence of investor attention in the green crypto market.

This study examines the long-run income and price elasticities of oil demand in 21 OECD countries using quarterly data from 1980:Q1 to 2021:Q3. We find that oil demand is inelastic with respect to both income and prices at 0.117 and −0.179, respectively. The cointegration tests reveal instability in oil price elasticities over time. The time-varying panel data estimates support these findings, showing significant variations in elasticities influenced by oil market dynamics and global events. Income elasticities reached their highest levels during the COVID-19 pandemic, while price elasticities ranged from −0.396 to 0.275. Significantly, the sign of oil price elasticities shifted from negative to positive after 2015, contrary to the law of demand, probably because of declining oil prices during that period. The largest positive and statistically significant price elasticity occurred in early 2020, which can be attributed to the COVID-19-induced decline in oil prices. Overall, this analysis contributes to understanding oil demand dynamics and highlights the impact of economic and oil market factors on elasticities.

This study examines the convergence of renewable energy consumption in G-7 countries. We employ LM unit root and RALS version of LM unit root tests with endogenously determined with structural one or two breaks. Despite the increase in renewable energy consumption in G-7 countries, it is important to identify whether renewable energy consumption converges across these countries to formulate appropriate policies to support sustainable energy consumption and reduce CO2 emissions. Our analysis indicated that Germany, Italy, and Canada exhibit evidence of convergence. However, after employing both the LM and RALS versions of the LM unit root tests, which consider level shifts with one or two breaks or trend shifts with one or two breaks, we found that there is no evidence of convergence for France, Japan, and the United Kingdom. Overall, our results highlight the importance of formulating country-specific policies to support renewable energy consumption and reduce CO2 emissions. Policymakers need to identify the drivers of renewable energy consumption and adopt appropriate measures to ensure that the countries can meet their climate goals while also ensuring energy security.

This paper examines the effects of oil and natural gas prices on the oil and gas sectors of the BRIC countries (Brazil, Russia, India, and China) over the period over from 20013 to 2022. Unlike previous studies, it employs a time-varying capital asset pricing model based on the estimation of state-space mode. In brief, the findings highlight significant changes in the asset-pricing model parameters across all countries, indicating the limitations of using time-invariant estimates. Specifically, Brazil shows the highest volatility in oil price risk, followed by Russia, both being oil-exporting countries, while market beta values remain relatively stable. Time-varying estimates further suggest that natural gas parameters are relatively lower and less significant than those of oil prices. The Russian-Ukrainian conflict's energy crisis adversely affects the performance of oil and gas sectoral stock returns. This war has had a negative and significant impact on China's oil-gas stock return.

This paper examines the effects of the COVID-19 pandemic on the travel-tourism stock markets. Specifically, it considers the five most visited countries: France, Spain, the US, China, and Italy. Unlike previous studies, it estimates time-varying VAR (TVP-VAR) models, including daily observations of confirmed COVID-19 cases, economic activity, CDS spreads and the returns of travel-tourism sectors. In brief, our findings indicate that the effects of COVID-19 vary across countries, as well as over time. Specifically, increasing numbers of cases initially had a negative and significant impact on the travel-tourism stock returns of all countries. However, this effect had become insignificant by early April 2020. The travel-tourism markets of the European countries were seen to be more heavily affected by COVID-19 when compared to China and the US, with China seeming to have been the least affected country of all. Overall, our results are essential in understanding the impact of the COVID-19 pandemic on the travel-tourism stock markets, and are of particular importance to policymakers, portfolio managers and investors.

This paper investigates the key factors driving the capital gains overhang (hereafter CGO) in the US stock market. We used a sample of 3865 non-financial US companies with 331,023 observations from January 2001 through December 2020. The data is analyzed using a panel regression model. It contributes to the literature by using a new set of firm characteristics, namely, liquidity proxied by turnover, company beta, leverage, EPS, cash flow to price, market to book ratio, and size. This research is interesting as it provides an alternative to the behavioral finance point of view that serves only limited stylized facts. We find that CGO is increasing in some firm attributes, namely earnings per share, leverage, growth, and size, and decreasing in others, namely turnover, beta, and cash flow to price. Our results are robust to cross-sectional regression that checks the stability of estimates over time and to subsample analyses. Finally, our results remain the same even after accounting for endogeneity.

This article examines the effects of the COVID-19 pandemic on the travel-tourism stock markets. Specifically, it considers the five most visited countries: France, Spain, the US, China, and Italy. Unlike previous studies, it estimates time-varying VAR (TVP-VAR) models, including daily observations of confirmed COVID-19 cases, economic activity, CDS spreads, and the returns of travel-tourism sectors. In brief, our findings indicate that the effects of COVID-19 vary across countries, as well as over time. Specifically, increasing numbers of cases initially had a negative and significant impact on the travel-tourism stock returns of all countries. However, this effect had become insignificant by early April 2020. The travel-tourism markets of the European countries were seen to be more heavily affected by COVID-19 when compared to China and the US, with China seeming to have been the least affected country of all. Overall, our results are essential in understanding the impact of the COVID-19 pandemic on the travel-tourism stock markets, and are of particular importance to policymakers, portfolio managers, and investors.