Environmental reverberations of geopolitical risk and economic policy uncertainty resulting from the Russia-Ukraine conflict: A wavelet based approach for sectoral CO2 emissions.

After the COVID-19 pandemic, Russia invaded Ukraine in February 2022, and a natural gas crisis between the European Union (EU) and Russia has begun. These events have negatively affected humanity and resulted in economic and environmental consequences. Against this background, this study examines the impact of geopolitical risk (GPR) and economic policy uncertainty (EPU) caused by the Russia-Ukraine conflict, on sectoral carbon dioxide (CO2) emissions. To this end, the study analyzes data from January 1997 to October 2022 by using wavelet transform coherence (WTC) and time-varying wavelet causality test (TVWCT) approaches. The WTC results show that GPR and EPU reduce CO2 emissions in the residential, commercial, industrial, and electricity sectors, while GPR increases CO2 emissions in the transportation sector during the period from January 2019 to October 2022, which includes Russia-Ukraine conflict. The WTC analysis also indicates that the reduction in CO2 emissions provided by the EPU is higher than that of the GPR for several periods. According to the TVWCT, there are causal impacts of the GPR and the EPU on sectoral CO2 emissions, but the timing of the causal impacts differs between the raw and decomposed data. The results suggest that the EPU has a larger impact on reducing sectoral CO2 emissions during the Ukraine-Russia crisis and that production disruptions due to uncertainty have the greatest impact on reducing CO2 emissions in the electric power and transportation sectors.

Capital flow and environmental quality at crossroads: designing a sustainable policy framework for the newly industrialized countries.

It is extremely difficult for emerging economies to achieve the Sustainable Development Goals (SDGs), and in order to close this policy gap, a comprehensive policy framework is needed. The purpose of this research is to determine the proportional impacts of domestic and foreign capital to environmental degradation in newly industrialized nations (NICs). For this reason, panel data methodology is used to evaluate, for the years 1991 to 2018, how the ecological footprint is affected by stock market capitalization, foreign direct investment, economic growth, urbanization, and energy intensity. Using the squared terms of stock market capitalization and foreign direct investment, respectively, it is also looked at whether domestic and foreign capital may have non-linear effects on the environment. According to the empirical findings, whereas local capital growth worsens the environment, increasing international capital prevents environmental degradation. There is an inverted U-shaped link between domestic capital and environmental degradation in the event of non-linearity, but foreign capital has a monotonically declining effect on environmental degradation. The study outcomes are utilized to design a policy framework to address the objectives of SDG 7, SDG 11, and SDG 13.

Understanding the Role of Technology in Asian Economies: The Environmental Impact of Remittances and Economic Complexity.

In recent years, scholars have determined various determinants of environmental degradation using the panel and time-series studies. However, technological innovations (TI) and remittances, among the financial system's essential components, are relatively ignored. In addition, nations' economic progress and environmental performance also depend upon the nature of their economic structure. This empirical research investigates the effects of TI, remittances and economic complexity (EC) on CO2 controlling economic growth and trade openness (TR) in the selected 15 Asian nations. The study collected panel data of 15 Asian countries from 1990 to 2019 and employed the panel quantile regression and augmented mean group methods to unveil the impacts of variables on CO2 emissions. The empirical findings established that remittances are negatively linked with CO2 emissions. Similarly, EC reduces CO2 emissions in the context of Asian countries. In addition, EC and remittances Granger cause CO2 emissions. These findings indicate that remittances and EC positively contribute to environmental quality in Asian countries. Conversely, TI, economic growth, and TR intensify CO2 emissions in Asian countries. Finally, the study recommended policies to enhance remittances and EC in Asian countries to curb environmental degradation.

Assessing environmental quality through natural resources, energy resources, and tax revenues.

Developing countries have depleted their natural resources in economic interest to achieve high economic growth. Current urbanization patterns and energy consumption and natural resource extraction are largely unsustainable. In this background, this paper investigates the impact of natural resources rent, energy resources consumption, and tax revenue on carbon emissions for developing countries. The study employed data for 48 developing countries from 1990 to 2020. We used second-generation methods for empirical analysis that control heterogeneity and cross-sectional dependence in the data. The advanced panel data estimates of CS-ARDL provide reliable outcomes by addressing these panel data econometric issues. The study results revealed that natural resources or natural resources rent in their exploitation accelerates carbon emission. Similarly, energy resources excessive consumption and economic growth are highly carbon-intensive for these countries and lead to environmental degradation. In contrast, tax revenue and education stabilized the environmental quality of the study interest. Besides this, to analyze the directional association among variables, the study applied DH causality test, which indicates a bidirectional link between tax revenues and emissions, energy resources and emissions, and income and CO2 emissions. Based on the finding, the study suggests some policy implications to limit the extraction of natural resources and abate carbon emissions by establishing appropriate strategies and imposing environmental charges.

A controversy on the three fundamental growth determinants in selected CEE countries.

The present study is a controversy on the three fundamental growth determinants. It contributes to the literature by divulging the effects of foreign direct investment and financial development on energy consumption in Central and Eastern European countries from 1990 to 2016. In doing so, second-generation multi-econometric methodological methods are adopted to conclude this study. The Pooled Means Group (PMG) estimation approach confirms that foreign direct investment is adversely associated with energy consumption. A one-point rise in FDI in the CEE region reduces energy consumption by 0.0172 points in the long run. Congruently, the globalization index also mitigates energy consumption. Conversely, financial development and economic growth stimulate energy consumption in the CEE region. Energy consumption boosts by 0.0626 points when a one-point escalation in financial development occurs. The U-shaped link between energy consumption and economic growth is revealed. The country-wise results show that energy consumption rises due to financial development and FDI in nine countries and one country. However, reduction in energy consumption occurs due to an upsurge of financial development in seven and FDI in six countries. Moreover, the causality results suggest that energy consumption causes financial development, and FDI. The policy suggestions are included to mitigate unsustainable energy consumption and renovate the energy policy in this region.

Analyzing global inequality in access to energy: Developing policy framework by inequality decomposition.

Energy poverty is a critical policymaking problem in the world, while the outlined solutions in academic and policy literature talks about the solutions, without addressing the possible cause of the problem. The interaction between labor and energy market might pave a way to address the issue. Within the context of energy poverty, this interaction might turn out to be a major roadblock in the way to attain the objectives of Sustainable Development Goals (SDGs). From this perspective, this study aims at analyzing the constituents of inequality in access to energy, and in that pursuit, it has employed Kaya-Theil Decomposition method. The study is carried out at the global level over the period of 1990-2019. The study outcomes demonstrate all the inequality components to be rising during the study period. Presence of a possible feedback loop in the association might create the Vicious Circle of Energy Poverty around the globe. This study contributes to the literature by addressing the demand-side dimension of the energy poverty issue, while using the Kaya-Theil Decomposition method as an estimator of demand-side factors. Based on the study outcomes, a policy framework has been recommended, and it is aimed at helping the nations to achieve the objectives of SDG 7, SDG 8, and SDG 10.

Analyzing the determinants of clean energy consumption in a sustainability strategy: evidence from EU-28 countries.

The current global spirit for sustainable development has led to increased attention to reducing the use of conventional energy sources and managing the issue of climate change. Renewable (or clean) energy consumption is a key element of any country's environmental quality and sustainable economic growth. This study provides a comprehensive analysis of the impacts on clean energy consumption of common factors in pursuing a sustainability strategy, including environmental degradation (measured as carbon dioxide (CO2) emissions), clean energy technology, gross domestic product (GDP) growth, institutional quality, and globalization for a panel of European Union (EU) 28 countries in the period from 1995 to 2017. We employ two estimation techniques, continuous updating-fully modifying (CUP-FM) and continuous updating-bias correcting (CUP-BC). In addition, the study incorporates Driscoll-Kraay regression for a panel model to investigate the validity and reliability of long-term elasticities' results. The findings of long-run analyses indicate that CO2 emissions, clean energy technology, GDP growth, and globalization positively impact clean energy consumption and institutional quality negatively impacts it. Finally, the results of causality testing indicate a unidirectional causal relationship between clean energy technology and clean energy consumption and a bidirectional association between institutional quality and clean energy consumption. The study's outcomes have policy implications, especially regarding designing strategic choices to promote investment in clean energy technology to increase the use of clean energy sources and to overcome the issues of institutional quality in supporting clean energy consumption in the EU-28 countries.

Analyzing the linkage between military spending, economic growth, and ecological footprint in Pakistan: evidence from cointegration and bootstrap causality.

The ecological consequences of military spending is a hugely neglected area, and a veil of mystery surrounds this topic. The environmental threats posed by militaries remain insufficiently investigated in the name of national security. Prompted by the internal and external conflicts and prolonged military dictatorships, the Pakistani military assumes a role that goes beyond that of a traditional army. The current study addresses this significant gap in the literature by investigating the impacts of military spending on economic growth and the ecological footprint in Pakistan from 1971 to 2016 using the combined cointegration test and the bootstrap causality test. The findings of the study unveil a positive impact of military spending on the ecological footprint, while a negative impact on economic growth. The outcomes of the bootstrap causality test of Hacker and Hatemi-J (2012) highlight that economic growth Granger causes military spending, while causality runs from military spending to the ecological footprint. Energy consumption contributes to the ecological footprint and economic growth, whereas education expenditures do not influence economic growth and the environment in the long run. Further, the findings suggest a U-shaped link between GDP and footprint in Pakistan. The authorities should focus on resolving external and internal conflicts, on a priority basis, and reduce military spending to improve economic growth and the environment.

Foreign direct investment and education as determinants of environmental quality: The importance of post Paris Agreement (COP21).

This study investigates the effect of foreign direct investment and education on environmental quality for Asian countries by controlling income, energy consumption, and urbanization for the period of 1990-2018. We have applied panel cointegration techniques to probe for long-run associations among the variables. The empirical results indicate the existence of cointegration between the variables. Dynamic ordinary least square and fully modified least square methods are applied to estimate long-run elasticities. The empirical results confirm that environmental quality is sensitive to foreign direct investment, education, and urbanization. Income and energy consumption deteriorate environmental quality by increasing CO2 emissions. In the long-run, bidirectional causal associations are found for emissions- foreign direct investment, emissions-energy use, income- emissions, foreign direct investment -income, and energy-income nexus. Furthermore, there is a unidirectional causality running from education and urbanization to emissions, foreign direct investment, income, and energy use. Policymakers in Asian economies are encouraged to establish policies that increase the education budget, promote the use of green energy, attract foreign direct investment with green technology, and expand cities to limit the urbanization effects on environmental quality.

Determinants of the ecological footprint in Thailand: the influences of tourism, trade openness, and population density.

This paper investigates the impact of economic growth, energy consumption, tourism, trade openness, and population density on the ecological footprints in Thailand over the period from 1974 to 2016. We applied the augmented Dickey-Fuller and Zivot-Andrews unit root tests to check the stationary properties of the data. The ARDL bounding test approach and VECM Granger causality were used to investigate (i) the long-run and short-run effects and (ii) directions of such effects respectively. The long-run results showed that economic growth, energy consumption, and trade openness have positive relationships with the ecological footprint, while tourism and population density are negatively associated with the ecological footprint in Thailand. The results of VECM Granger causality confirmed that the bidirectional causality (i) between tourism and population density in the long run and (ii) between trade openness and population density in the short run. Furthermore, the unidirectional causality runs from the ecological footprint, economic growth, energy consumption, and trade openness to tourism and population density in the long run. The country policy combined with economic growth, energy consumption, tourism, international trade, and population density perspectives need to be revisited towards sustainable development by mitigating the effects of these variables on environmental depletion especially the ecological footprint. Graphical abstract.

Analyzing the association between innovation, economic growth, and environment: divulging the importance of FDI and trade openness in India.

The objective of this paper is to explore the nexus of innovation-environment and economic growth in the context of the Indian economy. To achieve the study objective, we explored the role of technological innovation, FDI, trade openness, energy use, and economic growth toward carbon emissions. Using the data of 1985-2017, the study employed ARDL bound testing and vector error correction model (VECM) methods to capture the effects of technological innovation, trade openness, FDI, energy use, and economic growth on CO2 emissions. Empirical estimation has confirmed the existence of long-run cointegration. Similarly, in the long run, it is found that trade openness, energy use, and economic growth positively reinforce CO2 emissions. In contrast, technological innovation and FDI negatively reinforce CO2 emissions in the long run. Furthermore, VECM indicates that the relationship among innovation, trade openness, and energy use is bidirectional in the long run. Whereas, unidirectional relation has been found that is coming from GDP to carbon emissions, FDI, innovation, trade, and energy use. In the short run, unidirectional link found which is coming from FDI, innovation, and energy use to carbon emission. However, the association between emissions and trade openness is bidirectional. The conclusions put forward policy implications that innovation is a way to reduce environmental degradation.

Uncovering the driving forces of carbon dioxide emissions in Chinese manufacturing industry: An intersectoral analysis.

As the pillar of national economy, manufacturing industry is the largest primary energy consumer and emitter of carbon dioxide (CO2) in China. Therefore, capturing the determinants of CO2 emissions in manufacturing industry is extremely important for national efforts to mitigate carbon emissions. This paper explores the major driving forces behind CO2 emission changes in China's manufacturing industry during 2000-2015 from perspectives of the whole sector and 28 subsectors, by applying the temporal logarithmic mean Divisia index (LMDI) method. Moreover, an intersectoral LMDI model is built to uncover the intersectoral discrepancies of CO2 emissions among 28 subsectors. The temporal analysis indicates that industrial activity and energy intensity are crucial factors respectively contributing to the increase and mitigation of CO2 emissions. The intersectoral analysis reveals that energy intensity is the dominant factor responsible for the intersectoral discrepancies of CO2 emissions among 28 subsectors. The great mitigation towards CO2 emissions can be achieved if energy efficiency is largely improved in carbon-intensive subsectors. Priority should be given by governments to the industrial technology advancement, such as subsidies for energy-saving technological transformation and promotion of international advanced techniques and equipment, which can greatly improve production efficiency and mitigate emissions in manufacturing industry.

Determinants of carbon emissions in Pakistan's transport sector.

The transport infrastructure plays an imperative role in a country's progress. At the same time, it causes environmental degradation due to extensive use of fossil fuels. The transport system of Pakistan is largely dependent on nonrenewable energy sources (oil, coal, and gas), which are hazardous to environmental quality. This research uses an autoregressive distributive lag model (ARDL) to examine the impact of oil prices, energy intensity of road transport, economic growth, and population density on carbon dioxide (CO2) emissions of Pakistan's transport sector during the 1971-2014 period. The ARDL bounding test examines the cointegration and long-run relationships among the variables, and the directions of causal relationships are found through the Granger causality vector error correction model (VECM). The long-run results indicate that increases in oil prices and economic growth help to reduce the transport sector's CO2 emissions, while rising energy intensity, population concentration, and road infrastructure increase them, with population playing a dominant role. The findings of this study can help authorities in Pakistan to develop suitable energy policies for the transport sector. Among other recommendations, the study recommends investment in renewable energy projects and energy-efficient transport systems (e.g., light train, rapid transport system, and electric busses) and environmental taxes (subsidies) on the vehicles that use fossil fuels (renewable energy).

Identification and analysis of driving factors of CO2 emissions from economic growth in Pakistan.

This study applied the logarithmic mean Divisia index (LMDI) model to identify and discuss the main drivers of Pakistan's CO2 emissions over the period 1990-2016. The study examined the effects of five factors based on Pakistan's three main economic sectors while considering the 11 types of fuels consumed in that country. The results showed that the energy structure effect is the greatest driving force of CO2 emissions in this country, followed by scale effect and economic structure effect. Energy intensity is the main contributor to reducing Pakistan's carbon emissions throughout the study period. A comparative review at the sectoral level shows that the industrial sector for which coal is the main source of energy supply is the one that contributes the most to CO2 emissions in Pakistan. Alongside this sector is the tertiary sector, where the transport sub-sector imposes rules of conduct based on a growing Pakistani population. Meanwhile, deforestation would be the main cause of CO2 emissions from the agricultural sector in Pakistan, as energy consumption in this sector remains very low. Improving energy efficiency through the intensification of clean energy is urgently needed if Pakistan's environmental goals are to be achieved.

The impact of globalization and financial development on environmental quality: evidence from selected countries in the Organization for Economic Co-operation and Development (OECD).

This study investigates the impacts of globalization and financial development on environmental quality by incorporating energy consumption in the framework of the Environmental Kuznets Curve (EKC) hypothesis for selected countries in the Organization for Economic Co-operation and Development (OECD) over the 1990-2014 time spans. The cross-sectional dependence is determined by using the cross-sectional dependence and Lagrange Multiplier (LM) methods. This study employs second-generation panel unit root tests to check the unit root properties and the Westerlund panel cointegration test to examine the long-run equilibrium relationship among the variables. The results confirm the presence of cointegration in the long run. The Continuously Updated Fully Modified Ordinary Least Square (CUP-FM) and Continuously Updated Bias-Corrected (CUP-BC) approaches are applied to investigate long-term output elasticities of the variables. The results show the stimulating role of energy consumption on Carbon dioxide (CO2) emissions. This study finds support for the EKC hypothesis as it relates to selected OECD countries. Globalization and financial development increase environmental quality by reducing CO2 emissions. The causal relationship reveals the presence of a bidirectional relationship between energy consumption and CO2 emissions. The feedback causal effect runs between economic growth and CO2 emissions and between globalization and economic growth, while unidirectional causality runs from CO2 emissions to financial development, from economic growth to energy consumption, from energy consumption to financial development, from globalization to energy consumption, and from globalization to financial development. Policies that support green technology transfer among OECD countries, foreign direct investment in the renewable energy sector, financial development to support green infrastructure, and energy generation using renewable energy sources are recommended.

The nexus of renewable and nonrenewable energy consumption, trade openness, and CO2 emissions in the framework of EKC: evidence from emerging economies.

Emerging economies are experiencing considerable economic changes due to change in energy demand and CO2 emissions. To explore the link between energy demand and CO2 emissions, this study disaggregates energy consumption into renewable and nonrenewable, and investigates its impact on carbon (CO2) emissions by incorporating the role of trade openness using the environment Kuznets curve (EKC) framework. Emerging economies from 1990 to 2015 are examined based on Morgan Stanley Capital International's (MSCI's) classification. This empirical study uses cross-sectional dependence (CD) test and second-generation panel unit root test for precise estimation. The Pedroni and Westerlund panel cointegration tests are used to examine the long-run equilibrium. Continuously updated fully modified (CUP-FM) and continuously updated bias-corrected (CUP-BC) approaches are applied to investigate long-run output elasticities while the vector error correction model (VECM) is used to examine the direction of causal relationships among the variables. The results show that renewable energy consumption affects the CO2 emissions negatively while nonrenewable energy consumption positively impacts the CO2 emissions. The study also supports the EKC hypothesis. Trade openness adversely affects the CO2 emissions which are an imperative inclination of these economies towards globalization. Moreover, in the long run, energy consumption from renewable energy and economic growth Granger cause CO2 emission, nonrenewable energy, and trade openness. In the short run, renewable energy Granger causes economic growth, while economic growth Granger causes nonrenewable energy. The study offers some vital policy suggestions for these emerging economies and some interesting lessons for the developing economies.