Search

Purpose: This study aims to examine whether energy poverty impacts gender inequality and CO2 emissions in African countries with the biggest economies by gross domestic product (GDP) per capita from 1996 to 2020. Additionally, this study examines the existence of the gender Kuznets curve (GKC) and the environmental Kuznets curve (EKC) theories. Furthermore, it evaluates the connection between economic development and carbon emissions, on the one hand, and economic development and gender inequality on the other. Design/methodology/approach: This study uses the augmented Dickey–Fuller and Phillip–Perron unit root tests to determine the degree of integration between the variables. It also uses the Pedroni and Fisher–Combine Johansen cointegration tests to assess a long-run relationship between the variables. The authors adopted the pooled mean group (PMG)-autoregressive distributed lag model and used the E-Views 12 software to run the analysis. Findings: The empirical analysis approves the long-run correlation among the variables used in this study. Increased energy poverty and GDP increase CO2 emissions, whereas income square hurts CO2 emissions. These results are consistent with the EKC hypothesis, which proposes a non-linear relationship between CO2 emissions and economic growth in the studied areas (similar to an inverted U shape). Long-term foreign direct investment (FDI) has a negative correlation with CO2 emissions. On the contrary, energy poverty, GDPsq and FDI find a positive relationship with gender inequality, whereas GDP finds a negative association with gender inequality. The negative relationship between GDPsq and gender inequality establishes a "U"-shaped connection between income and gender inequality. Thus, it supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality. Originality/value: This study supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality. [ABSTRACT FROM AUTHOR]

In this research, the direct and indirect effects of foreign direct investment (FDI) inflows on carbon dioxide (CO2) emissions in India are examined, covering the period from 1980 to 2014. To quantify the indirect outcome of the existence of FDI on CO2 emissions, in this study, the three mediating channels of FDI are considered. The three broad mediating channels of FDI inflows are energy structure, industrial structure, and high-carbon technology, by which foreign direct investments affect India's carbon dioxide emissions. In this study, the unit root test, the Johansen cointegration, the Granger causality technique, and the seemingly unrelated regression (SUR) are used for the empirical analysis. The findings discover a process of cointegration in the long-run and reveal unidirectional causation between FDI inflows and CO2 emissions. The outcomes of the SUR estimation indicate that all the mediating factors substantially contribute to the level of CO2 emissions. In this paper, the findings reveal that FDI inflows affect the level of India's CO2 emissions mainly via mediating factors compared to their direct effect. Finally, in this research, it is recommended that the concerned authorities should prioritize the redistribution of foreign direct investment from high carbon-intensive technologies to less carbon-intensive and cleaner technologies for India's carbonless and sustainable future. [ABSTRACT FROM AUTHOR]

The dynamic interaction between crude oil prices and the prices of grains and oilseed is critical yet a complex issue in agriculture given the potential impact of the energy sector price fluctuations on production costs, transportation, and processing. This study explores the interactions between prices of crude oil, key grains, and oilseeds (maize, soybean, and wheat) in South Africa from 2018 to 2022. Utilising monthly data, this study employs the Auto-Regressive Distributed Lag (ARDL) model to assess the short-term and long-term relationships, and the Granger causality test to determine the causality directions. Results revealed a mixed long-term cointegration wherein crude oil prices and the prices of maize as well as soybean have a relationship, but no evidence of such a relationship exists for wheat prices. Additionally, no short-term effects were observed, suggesting that immediate fluctuations in crude oil prices do not influence the prices of maize, soybean, and wheat. Instead, short-term prices movements of the grains and oilseeds may be driven by other factors that could be of interest to policymakers. Furthermore, the Granger causality findings show no causality direction between prices of crude oil and the selected grain and oilseed. These findings challenge the presumed direct connection between energy and agricultural prices, thus offering policymakers a perspective to redirect their focus to formulate short-term price policy strategies that decrease dependability on crude oil to promote sustainability in the agricultural sector without disrupting the progress towards achieving Sustainable Development Goal 2 of ending hunger. [ABSTRACT FROM AUTHOR]

CO2 emissions are major drivers of climate change, causing global warming, extreme weather, and biodiversity loss. They disrupt ecosystems, deplete resources, and threaten public health and economic stability. Reducing CO2 emissions is essential for climate stability and sustainability. This study explores the complex relationships between CO2 emissions and factors such as the transportation sector, electricity consumption, foreign direct investment (FDI), international trade, and gross domestic product (GDP). The focus is on small- and medium-sized enterprises (SME) in Pakistan. Using time series data from 2000 to 2022. This study applies advanced econometric techniques, including nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least squares (DOLS), and fully modified ordinary least squares (FMOLS). The findings highlight that increased electricity consumption, international trade, transportation activities, and FDI contribute to higher CO2 emissions. However, FDI can also help reduce emissions, particularly through investments in green technologies. This study emphasizes the importance of transitioning to renewable energy and adopting sustainable practices across sectors such as electricity, trade, and transportation. Specifically, transportation and electricity consumption were found to significantly impact CO2 emissions, with a 10% increase in transportation activities resulting in a 5% rise in emissions. Conversely, FDI can reduce emissions by approximately 3% per unit of investment, largely due to green technology adoption. Additionally, integrating renewable energy and energy-efficient technologies in transportation can lead to a 20% reduction in emissions. Policymakers and experts must prioritize strategies that promote renewable energy adoption and integrate sustainable practices to reduce CO2 emissions and ensure long-term environmental sustainability. This research is innovative in its analysis of the interconnected effects of electricity consumption, trade, transportation, and FDI on CO2 emissions. By applying sophisticated econometric methods, it highlights the potential of FDI, particularly green investments, to mitigate environmental damage. This study, focusing on Pakistan, offers insights into how economic growth can be balanced with environmental sustainability. [ABSTRACT FROM AUTHOR]

Environmental degradation is a pressing issue, particularly in resource-dependent regions like the Gulf Cooperation Council (GCC) countries. While significant research has explored the environmental impacts of economic growth and resource use globally, limited attention has been given to the unique dynamics in the GCC, including the role of ICT development, trade openness, and FDI inflows. This research examines how information and communication technology (ICT) development, economic growth, trade openness, foreign direct investment (FDI) inflows, and electricity consumption influenced environmental degradation in GCC countries from 1990 to 2022. Using panel data analysis, the study finds that ICT expansion and increased electricity consumption significantly contribute to higher CO2 emissions, exacerbating environmental degradation. Economic growth follows the Environmental Kuznets Curve (EKC) pattern, where environmental harm initially increases with growth but can decline as economies diversify and adopt cleaner technologies. Trade openness and FDI inflows, particularly in resource-intensive industries, also contribute to environmental degradation, supporting the pollution haven hypothesis. However, these factors present opportunities for sustainable development if paired with stricter environmental regulations and cleaner technology adoption. The study highlights the need for GCC policymakers to prioritize renewable energy investments, enforce stronger environmental policies, and promote energy efficiency to balance economic growth with environmental sustainability. Recommendations for future research include exploring other environmental factors and assessing the role of technological innovations in reducing emissions. [ABSTRACT FROM AUTHOR]

This study aims to investigate how Foreign direct investment (FDI) and trade openness influenced economic growth in BRICS countries from 1990 to 2022, using the Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) and System Generalized Method of Moments (System-GMM) methods. Our findings show that these two variables boost economic growth by 0.172, 0.021, 0.291, and 0.072%, respectively. Additionally, the results indicate that BRICS countries have demonstrated greater resilience in terms of FDI and trade before and after the COVID-19 pandemic and the Russia-Ukraine war, underscoring the effectiveness of their investment and trade policies in maintaining economic growth amidst global disruptions. [ABSTRACT FROM AUTHOR]

Purchasing Power Parity (PPP) doctrine has been a significant topic in the domain of international finance and economics. Several studies have been conducted on the issue of testing the soundness of the PPP hypothesis but a very few studies have been done for developing nations, particularly for India. This study tried to empirically test the PPP hypothesis for Indian rupee/US dollar (INR/USD) rate using quarterly data for the period 2001:1 – 2024:2. The stationarity of the relevant variables is examined by using the econometric tool of Augmented Dickey Fuller (ADF) and Phillip - Perron (PP) tests. To confirm empirical validity of PPP hypothesis, OLS regression technique is used. Autocorrelation problem is removed with the help of AR1 (Cochrane-Orcutt) and maximum likelihood procedures. The PPP model is estimated in naïve static form as well as the partial adjustment framework. The partial adjustment framework helps to find out the speed with which the actual exchange rate moves towards and reaches its equilibrium level. The empirical findings show that absolute PPP does not work well in its naïve static form, but it works well in partial adjustment framework with 2.5 quarters being speed of adjustment. The relative PPP is found to work well in both frameworks with 1.5 quarters as speed of adjustment. Thus, the policymakers may use the PPP hypothesis for exchange rate forecasting. Also, it is suggested that the policymakers should carefully consider the effect of internal or external shocks on PPP and tailor their monetary policy measures accordingly. [ABSTRACT FROM AUTHOR]

This study investigates the nexus between electricity consumption, fossil fuel dependency, renewable energy adoption, population growth, trade activities, economic growth, and environmental pollution in India. The primary objective is to understand how these factors interrelate and influence each other, focusing on their implications for sustainable development. The study used data from the World Bank from 2000 to 2023; the methodology adopted includes vector autoregression modeling, Granger causality tests, cointegration analysis, impulse response functions, and variance decomposition. These econometric techniques were selected due to their ability to capture dynamic relationships, determine causality, and identify long-term equilibrium among the variables. The findings reveal that economic growth significantly increases electricity consumption and fossil fuel usage, leading to higher carbon dioxide emissions. On the other hand, renewable energy adoption reduces environmental pollution. The study also highlights the complex interplay between population growth, urbanization, and trade activities in shaping India's energy demand and environmental outcomes. The implications of these findings are critical for India's sustainable development. The results suggest that while economic growth is essential, it must be balanced with sustainable energy practices to mitigate environmental pollution. The findings emphasize the need for policy interventions that promote renewable energy, enhance energy efficiency, and enforce environmental regulations. Recommendations include accelerating renewable energy adoption, implementing stringent energy efficiency standards, and developing integrated policies that simultaneously address the economic, energy, and environmental dimensions. These actions will help India achieve a sustainable balance between economic growth and environmental protection, ensuring a healthier future for its population. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to assess the long-run and short-run drivers of real house prices in Nigeria from 1991Q1 to 2020Q4. Design/methodology/approach: Vector autoregression and cointegration tests were used to assess the key drivers of Nigeria's real house prices in the long run and short run. Findings: The empirical findings revealed that household disposable income is the most important determinant of house prices in Nigeria. House prices increased by 1.6% and 60.8% in response to a 1% increase in disposable income in the long run and short run, respectively, while real mortgage credits pushed up house prices by 5% and have no long-run effects, suggesting that most Nigerians depend on their money income rather than credits in securing a home. In addition, prices of oil sector products and real interest rates had negative and significant relationship with house prices, while positive correlations were found for real effective exchange rate and real housing investments regardless of the time horizon. The impact of construction costs and cement prices was also documented. Originality/value: This is likely a pioneering study of its kind to focus on the determinants of real house prices in Nigeria. It is probably the first study, the best of the author's knowledge, to empirically examine the impact of the oil sector on house prices in the country. [ABSTRACT FROM AUTHOR]

Du, J.; Yan, B., and Su, X., 2025. Empirical analysis of financial agglomeration, industrial infrastructure, and economic growth of the marine industry: Using the PVAR model to analyze China's marine economy. Journal of Coastal Research, 41(1), 122–130. Charlotte (North Carolina), ISSN 0749-0208. To promote the high-quality development of China's marine economy, based on the panel data of 11 coastal provinces and cities from 2006 to 2016, the panel vector autoregression (PVAR) model was used to analyze the dynamic relationships among financial agglomeration, upgrades in marine industrial structure, and economic development. Based on the cointegration test, a long-term stable relationship was found between the three variables of financial agglomeration, marine industry structure upgrades, and the development of the marine economy, where financial agglomeration inhibits the growth of the marine economy, and a suitable interaction mechanism cannot be formed between the two, whereas upgrading of the marine industry structure is conducive to the development of the marine economy. In the short term, financial agglomeration can promote the upgrading of the marine industry structure, but the long-term effect is not ideal; in the long run, the development of the marine economy can encourage improvement in the level of financial agglomeration. In the short term, the development of the marine economy is mainly affected by itself and the upgraded marine industry structure, but in the long run, the inhibitory effect of financial agglomeration to the marine economy is greater. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to analyze the downside risk for the stock indices of BRICS countries. The study also aimed to study the interrelationship, directional influence and interdependence among the stock exchanges of BRICS economies to provide insights for policymakers, fund managers, investors and other stakeholders. Design/methodology/approach: The authors used Value at Risk (VaR) as an indicator of downside risk and time series econometrics for measuring the long run relationship, directional influence and interdependence. Findings: The calculated VaR estimates, long-run linkages and strong interdependence among these indices especially with the returns of Brazil exerting a notable impact on the returns of other BRICS nations. These results emphasize the significance of taking into account cross-country spillover effects and domestic market dynamics in the context of portfolio management and risk assessment strategies. Further, from the extended results of variance decomposition analysis, the authors find that Brazil's, China's and South African stock market returns have a significantly lagged impact on their own stock market, while Russia's and India stock market returns do not have a significantly lagged impact on their own stock markets. Originality/value: To the best of the authors' knowledge, this is the first study comprehensively analyzing the BRICS indices downside risk through the historical simulation method of VaR estimation, which is an unexplored area of risk management. [ABSTRACT FROM AUTHOR]

In this research, the direct and indirect effects of foreign direct investment (FDI) inflows on carbon dioxide (CO2) emissions in India are examined, covering the period from 1980 to 2014. To quantify the indirect outcome of the existence of FDI on CO2 emissions, in this study, the three mediating channels of FDI are considered. The three broad mediating channels of FDI inflows are energy structure, industrial structure, and high-carbon technology, by which foreign direct investments affect India’s carbon dioxide emissions. In this study, the unit root test, the Johansen cointegration, the Granger causality technique, and the seemingly unrelated regression (SUR) are used for the empirical analysis. The findings discover a process of cointegration in the long-run and reveal unidirectional causation between FDI inflows and CO2 emissions. The outcomes of the SUR estimation indicate that all the mediating factors substantially contribute to the level of CO2 emissions. In this paper, the findings reveal that FDI inflows affect the level of India’s CO2 emissions mainly via mediating factors compared to their direct effect. Finally, in this research, it is recommended that the concerned authorities should prioritize the redistribution of foreign direct investment from high carbon-intensive technologies to less carbon-intensive and cleaner technologies for India’s carbonless and sustainable future.