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Within a framework that includes economic activity, real interest rate, grants, and subsidies, we aim to explore the role of renewable energy, technological innovation, and particularly the environmentally damaging militarization in driving green growth, which fosters sustainable economic growth by ensuring the values of natural assets, considering OECD countries. Our examination affirms a positive proposition between the development of renewable energy, technological innovation, and green growth in the long run by implementing the cross-sectional dependency panel autoregressive-distributed lags (CS-ARDL) framework in a dynamic heterogeneous panel setting. The findings also suggest that militarization is antagonistic to green growth. Our decomposed analysis is compatible with our premier analysis, indicating a conducive impact of both biomass and non-biomass types of renewable energy on green growth. We also document a negative association between the real interest rate (RIR) and green growth, while income muddles the results. The robustness tests confirm the sensitivity of our main findings to the magnitude of the subsidies and grants provided to renewable energy. The paper concludes with several policy recommendations.

International trade in connection with carbon dioxide (CO 2 ) emissions has been well studied, but export quality in this context has not widely been considered yet. Hence, in this study, we fill this gap by exploring the effects of export quality, economic growth, urbanization, trade openness, and total energy use on CO 2 emissions in 63 developed and developing countries around the world. To achieve our objectives, we have used the recent techniques of panel quantile estimators as proposed in Powell ( 2016 ) and Canay. Econ J 14 (3): 368-386, ( 2011 ), along with several other estimation methods. Our overall empirical evidence shows that the existence of the Environmental Kuznets Curve (EKC) hypothesis depends heavily on the estimation method and on the development stage of the economies considered. Emissions are influenced by the same factors as in the EKC specification, as explored in sensitivity analysis. The results from the panel quantile regression model show that economic growth and total energy use are highly CO 2 emissions conducive, while urbanization increases environmental degradation at the higher quantiles, as does export quality, depending on the countries’ income levels. Consequently, improvements in export product quality should be prioritized through the production of cleaner products mainly in the lower and upper middle-income countries. There should also be a decrease in total energy use in countries of all income levels. Particularly, policy makers should promote a decrease in export products intensive of fossil fuel energy by prioritizing the use of more renewable energy sources.

This paper re-investigates the time-varying impacts of economic growth on carbon emissions in the G-7 countries over a long history. In doing so, the historical data spanning the period from the 1800s to 2010 (as constructed) for each country is examined using the time-varying cointegration and bootstrap-rolling window estimation approach. Unlike the previous environmental Kuznets curve (EKC) studies, using this methodology gives us avenue to detect more than one, two, or more turning points for the economic growth-carbon emissions nexus. The empirical findings show that the nexus between economic growth and carbon emission seems over a long history to be M-shaped for Canada and the UK; N-shaped for France; inverted N-shaped for Germany; and inverted M-shaped (W-shaped) for Italy, Japan, and the USA. In addition, the possible validity of EKC hypothesis is examined for both the pre-1973 and post-1973 sub-periods. Based on this investigation, we found that an inverted U-shaped is confirmed only for the pre-1973 period in France, Italy, and the USA. These empirical evidences provide new insights to policy makers to improve environmental quality using economic growth as an economic tool for the long run by observing changes in the environmental impact of this growth from year to year.

This article provides a fresh insight into the dynamic nexus between oil prices, the Saudi/US dollar exchange rate, inflation, and output growth rate in Saudi Arabia' economy, using novel Morlet' wavelet methods. Specifically, it implements various tools of methodology: the continuous wavelet power spectrum, the cross-wavelet power spectrum, the wavelet coherency, the multiple and the partial wavelet coherence to the annual sample period 1969-2014. Our results unveil that the relationships among the variables evolve through time and frequency. From the time-domain view, we show strong but non-homogenous linkages between the four variables. From the frequency-domain view, we uncover significant wavelet coherences and strong lead-lag relationships. From an economic view, the wavelet analysis shows that Saudi economy is still exposed to several global risk factors, which are mainly related to the oil market volatility, and the pegging of the local currency to the US dollar. Such risk factors strongly and negatively affect the real economic growth, exert more pressure on inflation, and substantially limit the freedom to pursue an independent monetary policy.

This study explores and evaluates cash holdings patterns, including cash-driven resilience capabilities for the manufacturing and service industries, and distinguishes between business group firms and stand-alone firms. Specifically, this study uses the ANOVA Kruskal-Wallis test to examine various cash-driven resilience capabilities and the weighted least-square (WLS) to test the stated research questions. The empirical outcomes uncover that non-resilient organizations predominate over resilient ones. Moreover, the study finds that various cash-driven resilience capabilities differ significantly from a statistical viewpoint. In the process, it contributes to the literature on the impacts of COVID-19 on both manufacturing and services industries. It also uses different empirical methodologies, including Driscoll-Kraay, pooled ordinary least squares, Rogers, White, and Newey-West Fixed effects between the group estimations and the generalised method of moments (GMM) estimator to check the robustness of the findings. Based on the findings, this study recommends that the management of manufacturing and service organizations focus on increasing organizational resilience potential. This study provides a platform for managers of the business group and the standalone firms to manage the liquidity so the companies should not face any liquidity crunch during adverse economic or epidemic conditions.

This study investigates the interconnectedness among the stocks of the publicly listed vaccine-producing companies before and after vaccine releases in 2020/21. In doing so, the study utilizes the daily frequency equity returns of the major vaccine producers, including Moderna, Pfizer, Johnson & Johnson, Sinopharm and AstraZeneca. First, the investigation applies the TVP-VAR Dynamic Connectedness approach to explore the time–frequency connectedness between the stocks of those vaccine producers. The empirical findings demonstrate that Moderna performs as the most prominent net volatility contributor, whereas Sinopharm is the highest net volatility receiver. Interestingly, the vaccine release significantly increases the stock market connectedness among our sampled vaccine companies. Second, the cross-quantile dependency framework allows for the observation of the interconnectedness under the bearish and bullish stock market conditions by splitting any paired variables into 19 quantiles when considering short-, medium- and long-memories. The results also show that a high level of connectivity among the vaccine producers exists under bullish stock market conditions. Notably, Moderna transmits significant volatility spillovers to Sinopharm, Johnson & Johnson and AstraZeneca under both the bearish and bullish conditions, though the volatility transmission from Moderna to Pfizer is less pronounced. The policy implication proposes that the vaccine release allows companies to increase their stock returns and induce substantial volatility spillovers from company to company.

We examine the relationship between return and volatility of the stock markets and macroeconomic fundamentals for the G-7 countries by using monthly data ranging from July 1985 to June 2015. To meet this end, we apply the spillover index approach based on the generalized VAR framework developed by Diebold and Yilmaz (2012, 2014). The empirical analysis shows strong interactions between the returns and volatilities of the G-7 stock markets and the considered set of corresponding macroeconomic factors including industrial production, money supply, interest rates, inflation, oil prices and exchange rates. The return and volatility spillover transmission/reception dynamics of the relationships between these stock markets and the macroeconomic fundamentals have changed after the global financial crisis of 2008. Our findings provide useful insights for investors and policy makers concerned with the unprecedented swings in the stock markets of G-7 countries.

This article seeks to identify and analyze the organizational determinants of women presence on Indian corporate boards. Using a sample set of 294 Indian firms between years 2004-2014, Tobit regression analysis indicates that firm size, family ownership and affiliation with the high-tech sector exhibit positive association with the number of female directors on corporate boards. Further, we do not find any significant impact of state-ownership on the number of women on those boards. Notably, the effects of the organizational variables are more pronounced for the proportion of female non-executive directors, as compared to female executive directors. We conclude that understanding the organizational characteristics in conjunction with business environment can provide useful insights into state of board gender diversity, particularly in developing countries.

In the wake of recent political developments worldwide, future oil supply prospects have become doubtful and uncertainty plays a non-negligible role in determining the dynamics of major macroeconomic variables. This study constructs a factor model with time-varying loadings to decompose the variance of important macroeconomic and financial series for the top 10 oil-producing countries into the contributions from country-specific uncertainty and common uncertainty. The relative importance of the uncertainty estimates in explaining volatility in production, investment, total exports, the exchange rate, and stock prices seems to vary over time, with evidence of alternating periods of high and low persistent uncertainty. Global uncertainty plays a primary role output growth, investment, exports, and stock prices in all countries. Globalization and trade openness contribute to amplifying the international transmission of volatility, explaining the increasing importance of the global uncertainty factor.