Investigating the role of capital formation to achieve carbon neutrality in India

Spatio-temporal dynamics and influencing factors of carbon emissions (1997-2019) at county level in mainland China b

Global warming caused by extensive carbon emissions is a critical global issue. However, the lack of county-level carbon emissions data in China hampers comprehensive research. To bridge this gap, we employ a deep learning method on nighttime light data sets to estimate county-level carbon emissions in mainland China from 1997 to 2019. Our key contributions include the successful derivation of more reliable data, revealing the evolution of spatial dynamics and emissions epicenters. Moreover, we identify a novel inverted N-shaped relationship between gross domestic product per capita and carbon emissions in the eastern and western regions, as well as an N-shaped relationship in the central region, challenging mainstream wisdom. Additionally, we highlight the significant impacts of population density, industrial structure, and carbon intensity on carbon emissions. Our study also unveils the nuanced effects of government spending, which exhibits both inhibitory and region-specific influences. These findings serve to enhance our understanding of the factors influencing carbon emissions and contribute to informed decision-making in addressing climate change-related challenges.

Research and development for a carbon-neutral future and the status of EKC in G7 economies: evidence from CSARDL approach

Climate change issues present substantial obstacles to the global community's stability and humanity's overall welfare. Reducing carbon emissions is crucial in attaining environmental sustainability and addressing the consequences of SDG 13 (climate actions). The G7 nations, representing some of the largest economies globally and significantly contributing to global carbon emissions, have achieved certain advancements in mitigating their carbon footprint. Nevertheless, the attainment of carbon neutrality continues to pose a substantial obstacle. This study examines the mechanisms leading to environmental sustainability in G7 economies, explicitly emphasizing the contribution of research and development (R&D) toward attaining carbon neutrality. The present study utilizes G7 data from 1990 to 2020 to conduct an empirical analysis employing a cross-sectional autoregressive distributed lag (CSARDL) panel model. The primary objective of this investigation is to examine the influence of R&D expenditure (R&DE) on carbon emissions metric ton (CO2Mt). Furthermore, this study investigates the current state of the EKC in the economies of the G7 nations, as well as the influence of renewable energy (RE) and non-renewable energy (NRE) on CO2Mt. The results suggest that R&DE is critical in mitigating CO2Mt and attaining carbon neutrality. The study also validates the EKC implies a negative and non-linear relationship between growth and CO2Mt. Moreover, renewable and non-renewable energy validate their respective negative and positive effects on CO2Mt. The findings of our study offer valuable insights for policymakers in the G7 nations, aiding them in developing effective regulatory measures for achieving carbon neutrality goals.

An empirical assessment of the tripartite nexus between environmental pollution, economic growth, and agricultural production in Sub-Saharan African countries

A lot of attention has been paid to environmental pollution worldwide, due to the increase in anthropogenic activities. Massive investment in non-renewable energy options raises questions regarding environmental sustainability and how to maximize food and non-food output while still preserving a healthy ecosystem. To this end, the present study explores the three-way nexus between economic growth, CO₂ emission, and agriculture-value added will accounting for other control variables across a balanced panel of selected African economies from 1997 to 2020. Panel econometrics method of the generalized method of moments (two-step difference GMM) is used to obtain a robust result. From the present study, the environmental pollution model shows that economic growth significantly contributes to environmental pollution in Africa. Additionally, the food price index, capital, and FDI promote pollution, while agricultural production and labor decrease pollution. In the case of the economic growth model, the findings reveal that environmental pollution supports the growth-led pollution hypothesis. Also, the food price index and capital ameliorate economic growth, while foreign direct investments decrease economic growth. Finally, the agricultural production model indicates that economic growth increases agricultural production when the interaction term between GDPC and FDI is included in the model. In summary, the combination of explanatory variables, environmental pollution, capital, and foreign direct investment decreases agricultural production. On the contrary, the food price index and labor promote agricultural production in Africa. Furthermore, the study provides a lot of policies for authorities and stakeholders in Sub-Saharan African countries and other developing economies.

The asymmetric influence of environmental-related technological innovation on climate change mitigation: what role do FDI and renewable energy play?

This study aims to provide a new perspective on environmental studies by examining the influence of environmental-related technological innovation, foreign direct investment, renewable energy consumption, and economic growth on the climate change index (CCI), a novel proxy for environmental quality indicators. From the econometric standpoint, this study employs the "non-linear autoregressive distributed lag" model and spectral causality over the period of 1999-2018 for India. The results show that positive shocks to economic growth have detrimental long- and short-term effects on environmental quality, whereas negative shocks have no effect. While a positive shock has an insignificant impact, a negative shock to environmental technology innovation has a long-term negative impact on environmental quality. This study provides evidence for the pollution halo hypothesis in India. Besides, a long-term negative shock to the usage of renewable energy fosters environmental degradation. Furthermore, in short-, medium-, and long-term frequency, spectral causality demonstrates unidirectional causation from CCI to environmental-related technological innovation. Bidirectional causation is demonstrated between the CCI and renewable energy consumption in the short and medium term. In addition, environmental-related technological innovation and foreign direct investment are demonstrating a bidirectional relationship in the short term. This study has advocated the Sustainable Development Goals (SDGs)-centric policy paradigm, which can assist the Indian government in achieving SDG-13 (mitigating climate change) and SDG-7 (clean energy consumption).

An empirical investigation of the relationships between nuclear energy, economic growth, trade openness, fossil fuels, and carbon emissions in France: fresh evidence using asymmetric cointegration

The intention behind the current analysis is to join the debate over the main factors to consider in the global fight against climate change. Thereby, the Non-linear Autoregressive Distributed Lag (NARDL) approach is applied to assess the impacts of nuclear energy, fossil fuels, income, and trade on carbon emissions in France from 1980 to 2020. In addition, the relevance of the Environmental Kuznets Curve (EKC) presumption is tested. The main results stipulate that nuclear energy lessens CO₂ emissions in France. However, fossil fuels and trade openness enhance these emissions. On the other hand, the current analysis confirms the presence of an inverted U-shaped curve relating economic growth to carbon emissions. Therefore, the EKC hypothesis is supported in our case. Indeed, by calculating the turning point, it is possible to extract the turning year corresponding to 2008. Furthermore, an asymmetric causality test is performed in order to identify the possible non-linear causal links between the potential drivers of carbon emissions. First, the causal linkage between CO₂ emissions and GDP is bidirectional. Furthermore, a unidirectional causal link between CO₂ emissions and non-renewable energies and a dual directional causal link between pollutant emissions and trade are identified. These empirical results are intended to guide the French government in the implementation of relevant energy and trade-related strategies in order to attain the ambitious targets of carbon emissions reduction. In fact, France should reduce imports of fossil fuels to curtail the positive effect of trade on carbon emissions. In addition, it is recommended to substitute fossil energies with renewable energies gradually by using adequate instruments and boosting research and innovation to mitigate the adverse influences of non-renewable energies on environmental quality. Finally, our findings confirm the positive role played by nuclear energy in the fight against climate change.

Can Renewable Energy and Export Help in Reducing Ecological Footprint of India? Empirical Evidence from Augmented ARDL Co-Integration and Dynamic ARDL Simulations

The objective of this study is to investigate the impact of exports, renewable energy, and industrialization on the ecological footprint (EF) of India over the period spanning from 1970–2017 by employing the newly developed augmented ARDL (A-ARDL) co-integration approach and the novel dynamic ARDL (D-ARDL) technique. The empirical results demonstrate that exports and renewable energy consumption reduce the EF, while industrialization intensifies the EF. More precisely, a 1% increase in export (renewable energy consumption) reduces the EF by 0.05% (0.09%). In addition, the short-run elasticity of the GDP is found to be larger than the long-run elasticity indicating the possibility of the existence of the Environmental Kuznets Curve (EKC) of the EF for India. The study indicates that the income effect and increased policy focus on renewable energy usage can be expected to reduce India’s per capita EF in the long run. Moreover, India’s export sector has been traditionally less energy intensive, which reflects in our findings of export growth leading to a reduction in EF. Based on the empirical findings, this study recommends some policy insights that may assist India to effectively reduce its ecological footprint.

Can Energy Efficiency Help in Achieving Carbon-Neutrality Pledges? A Developing Country Perspective Using Dynamic ARDL Simulations

The current research sheds light on the nexus between environmental degradation as proxied by carbon dioxide emissions (CO2), energy efficiency (EE), economic growth, manufacturing value-added (MVA), and the interaction effect of EE and MVA in India. Using yearly data from 1980 to 2019, the current study employs dynamic auto-regressive distribution lag (DARDL) simulations and Fourier Toda and Yamamoto causality techniques. The findings of DARDL reveal that as income and MVA rise, environmental quality decreases, while EE improves environmental conditions in both the long and short run. Surprisingly, the interaction term of EE and MVA has a detrimental influence on environmental quality, meaning that India remains unable to provide energy savings technologies to the manufacturing industry. Furthermore, the environmental Kuznets curve (EKC) hypothesis is well-founded for India, as the long-run income coefficient is smaller than the short-run coefficient, implying that India is in its scale stage of economy, where economic growth is prioritized over environmental quality. The results of the causality technique reveal that CO2 emissions and EE have a bidirectional association. Therefore, policymakers in India should embrace realistic industrialization strategies combined with moderate decarbonization and energy efficiency initiatives under the umbrella of sustainable industrial and economic growth.