The allocation of budgets for renewable energy (RE) technology is significantly influenced by geopolitical risks (GPRs), reflecting the intricate interplay among global political dynamics, social media narratives, and the strategic investment decisions essential for advancing sustainable energy solutions. Against the backdrop of increasing worldwide initiatives to transition to RE sources, it is crucial to understand how GPR affects funding allocations, informing policy decisions, and fostering international collaboration to pursue sustainable energy solutions. Existing work probes the nonlinear effect of GPR on RE technology budgets (RTB) within the top 10 economies characterized by substantial research and development investments in RE (China, USA, Germany, Japan, France, South Korea, India, the United Kingdom, Australia, and Italy). Past research largely focused on panel data techniques to delve the interconnection between GPR and RE technology, overlooking the distinctive characteristics of individual economies. Contrarily, existing investigation implements the "Quantile-on-Quantile" tool to explore this association on an economy-particular basis, enhancing the precision of our analysis and offering both a comprehensive global perspective and nuanced perceptions for entire countries. The findings manifest a significant reduction in funding for RE technology associated with GPR across various quantile levels in the chosen economies. The disparities in results spotlight the necessity for policymakers to perform thorough assessments and carry out competent strategies to address the variations in GPR and RTB.
One of humanity's most significant problems in the twenty-first century revolves around how to balance the mitigation of environmental pollution while achieving sustainable economic development. Despite increased awareness and dedication to climate change, the planet is still seeing a drastic decrease in the volume of pollutant emissions. This study explores the long-run and causal impact of economic growth, financial development, urbanization, and gross capital formation on Malaysia's CO2 emissions based on the STIRPAT framework. The current paper employs recently developed econometric techniques such as Maki co-integration, auto-regressive distribution lag (ARDL), fully modified OLS (FMOLS), dynamic ordinary least square (DOLS), and wavelet coherence and gradual shift causality tests to investigate these interconnections. The advantage of the gradual shift causality test is that it can capture the causality in the presence of a structural break(s). The findings from the Maki co-integration and ARDL bounds tests reveal evidence of cointegration among the variables. The ARDL test reveals that economic growth, gross capital formation, and urbanization exert a positive impact on CO2 emissions. Furthermore, the wavelet coherence test reveals that there is a significant dependency between CO2 emissions and economic growth, gross capital formation, and urbanization. The Toda Yamamoto and Gradual shift causality tests reveal that there is a (a) unidirectional causality from urbanization to CO2 emissions, (b) unidirectional causality from economic growth to CO2 emissions, and (c) unidirectional causality from gross capital formation to CO2 emissions.
The gravest challenge for economic sustainability is the undetermined growth in the financial and economic risks of the nation, which need to be overcome with adequate measures without compromising economic growth. The uncertainty of economic factors produces fluctuations in the financial sector and makes them more vulnerable. However, the existing literature has not significantly focused on the economic and financial risk challenge for sustainable economic growth. Therefore, to fill the gap, an in-depth study is imperative to explore the association between these risks. To do so, this study incorporates both economic and financial risk to determine how risks are interconnected across time (frequency) and how they are linked by utilizing quarterly data from 1984-Q1 to 2020-Q4 and by applying both the "wavelet power spectrum (WPS)" and "wavelet coherence (WTC)" approaches, to examine the time-frequency dependency of each variable on the other. The findings of WTC revealed that the economic and financial risks have a positive dependency on each other in India at high, medium, and low frequencies. Likewise, the wavelet power spectrum outcomes reflect the high economic and financial risks vulnerability during 1991, 1992, and 1996. In addition, for the robustness check, the study employed both the "quantile regression (QR)" and "quantile-on-quantile regression (QQR)". Both the QQR and QR endorsed the positive association between FR and ER. Hence, our paper is the first research of its kind for the Indian economy, and it extends to the existing literature by examining the link between the two most significant indicators in terms of both time and frequency dependency. The findings in our paper offer excellent perspectives for investors and policymakers to assess prospects for investment and policy changes if necessary.
In the face of mounting climate change challenges, reducing emissions has emerged as a key driver of environmental sustainability and sustainable growth. Despite the fact that research has been conducted on the environmental Kuznets curve (EKC), few researchers have analyzed this in the light of economic complexity. Thus, the current research assesses the effect of economic complexity on CO2 emissions in the MINT nations while taking into account the role of financial development, economic growth, and energy consumption for the period between 1990 and 2018. Using the novel method of moments quantile regression (MMQR) with fixed effects, an inverted U-shape interrelationship is found between economic growth and CO2 emissions, thus validating the EKC hypothesis. Energy consumption and economic complexity increase CO2 emissions significantly from the 1st to 9th quantiles. Furthermore, there is no significant interconnection between financial development and CO2 emissions across all quantiles (1st to 9th). The outcomes of the causality test reveal a feedback causal connection between economic growth and CO2, while a unidirectional causality is established from economic complexity and energy use to CO2 emissions in the MINT nations. Based on the findings, we believe that governments should stimulate the financial sector to provide domestic credit facilities to industrialists, investors, and other business enterprises on more favorable terms so that innovative technologies for environmental protection can be implemented with other policy recommendations.
The recent progress report of Sustainable Development Goals (SDG) 2023 highlighted the extreme reactions of environmental degradation. This report also shows that the current efforts for achieving environmental sustainability (SDG 13) are inadequate and a comprehensive policy agenda is needed. However, the present literature has highlighted several determinants of environmental degradation but the influence of geopolitical risk on environmental quality (EQ) is relatively ignored. To fill this research gap and propose a inclusive policy structure for achieving the sustainable development goals. This study is the earliest attempt that delve into the effects o of geopolitical risk (GPR), financial development (FD), and renewable energy consumption (REC) on load capacity factor (LCF) under the framework of load capacity curve (LCC) hypothesis for selected Asian countries during 1990-2020. In this regard, we use several preliminary sensitivity tests to check the features and reliability of the dataset. Similarly, we use panel quantile regression for investigating long-run relationships. The factual results affirm the existence of the LCC hypothesis in selected Asian countries. Our findings also show that geopolitical risk reduces environmental quality whereas financial development and REC increase environmental quality. Drawing from the empirical findings, this study suggests a holistic policy approach for achieving the targets of SDG 13 (climate change).
This paper analyzes the dynamic impact of economic, social, and governance factors on PM2.5 concentrations in 89 countries from 2006 to 2019. Using the GMM-PVAR approach and Impulse-Response Functions, we examine how shocks to specific variables affect PM2.5 concentrations over a 10-year period. Our findings reveal that the influence of these factors on PM2.5 levels varies over time. For example, a shock in urbanization has no effect on PM2.5 concentrations in the first year, but in the second year, pollution increases significantly. In the third period, PM2.5 levels decrease, but they rise again in the fourth period, albeit not significantly. By the fifth period, pollution decreases until a new equilibrium is reached in the sixth period. Additionally, a shock in financial development, government effectiveness, industrialization, trade openness, or GDP has no effect on PM2.5 concentrations in the initial period. However, during the second period, air pollution decreases, followed by an increase in the third period and a decrease again in the fourth period. These dynamic patterns highlight the need for environmental policies that consider the evaluation time horizon. Our analysis is supplemented by the Granger causality test, guiding specific policy recommendations based on our findings.