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

Does the transition to low-carbon energy alleviate urban-rural energy inequality? The case of China

This paper aims to investigate whether China can reduce urban-rural energy inequality during its transition to low-carbon energy. Using data from 30 Chinese provinces between 2006 and 2019, we employ the system generalized method of moments (SYS-GMM) to investigate the correlation between low-carbon energy transition (LET) and urban-rural energy inequality. Furthermore, to investigate the mechanism, this study also considers energy service accessibility and industrial structure upgrading. The results of the study show that the degree of LET in China is increasing but with uneven spatial distribution. Moreover, LET is effective in reducing urban-rural energy inequality in China. Specifically, 1 % increase in LET corresponds to 0.045 % reduction in the urban-rural energy inequality index. Additionally, energy service accessibility and industrial structure upgrading are identified as effective channels for LET to mitigate urban-rural energy inequality. Furthermore, our study demonstrates that the alleviating impact of LET on energy inequality is more significant in regions where LET and urban-rural energy inequality levels are high. Drawing on our research results, we suggest policy recommendations to encourage the adoption of low-carbon energy sources and diminish urban-rural energy inequality.

Dynamic linkages between tourism development, renewable energy and high-quality economic development: Evidence from spatial Durbin model

There has been a shift in focus toward environmentally and economically sustainable forms of economic growth known as High-quality economic development (HQED). However, this study analyzes the impact of tourism development (TD) and renewable energy consumption on HQED in 30 provinces of China, while covering the time period from 2007 to 2021. TD and HQED has been measured with help of Global Moran Index. This study has used dynamic spatial Durbin model (SDM) to measure the dynamic impact of TD index and renewable energy consumption on HQED along with green finance, foreign direct investment and investment in education. The findings from empirical analysis shows that TD has negative impact on HQED and in more developed regions, the relationship is positive, while in the less developed western part of China, the U-shape has been reversed. Central and northeastern China have a U-shaped connection, while it has been noticed the interaction term of TD and renewable energy endorses HQED. In addition, renewable energy consumption, green finance and increase in education investment have positive and significant impact on HQED while foreign direct investment has negative impact on HQED in China. Therefore, in the light of this study policymakers should focus on the quality of tourism industry, green finance for renewable energy supply and enhancing education investment in China to attain the goal of HQED.

Household energy poverty and trajectories of emotional and behavioural difficulties in children and adolescents: findings from two prospective cohort studies

PURPOSE

The aim of this study is to examine the association between household energy poverty (EP) and trajectories of emotional and behavioural difficulties during childhood.

METHODS

The Growing up in Ireland study is two nationally representative prospective cohorts of children. The Infant Cohort (n = 11,134) were recruited at age 9 months (9 m) and followed up at 3, 5, 7 and 9 years (y). The Child Cohort (n = 8,538) were recruited at age 9 y and followed up at 13 y and 17/18 y. EP was a composite of two relative measures of EP. Emotional and behavioural difficulties were repeatedly measured using the strengths and difficulties questionnaire (SDQ). Linear spline multilevel models were used, adjusted for confounders to examine the association between (1) EP (9 m or 3 y) and trajectories of emotional and behavioural difficulties from 3 to 9 y in the Infant Cohort and (2) EP at 9 y and the same trajectories from 9 to 18 y in the Child Cohort.

RESULTS

In adjusted analyses, EP at 9 m or 3 y of age was associated with higher total difficulties score at 3 y (0.66, 95% CI 0.41, 0.91) and 5 y (0.77, 95% CI 0.48, 1.05) but not at 7 y or 9 y. EP at 9 y was associated with higher total difficulties score at 9 y (1.73, 95% CI 1.28, 2.18), with this difference reducing over time leading to 0.68 (95% CI 0.19, 1.17) at 17/18 y.

CONCLUSIONS

Our study demonstrates a potential association between early life EP and emotional and behavioural difficulties that may be transient and attenuate over time during childhood. Further studies are required to replicate these findings and to better understand if these associations are causal.

Platform economy development and energy efficiency inequality: evidence from China

Alleviating energy efficiency inequality between regions is critical for achieving green sustainable development and environmental equality. This study constructs platform economy development index and adopts Theil index to measure energy efficiency inequality. By using panel data from 30 regions in China spanning from 2013 to 2020, this study investigates the influence of platform economy development on energy efficiency in inequality through a two-way fixed-effects model. The results show that (1) platform economy development can alleviate energy efficiency inequality between regions. After the robustness tests, the results still support the findings. (2) When the level of industrial agglomeration, marketization and environmental decentralization is high, platform economy development is more effective in alleviating energy efficiency inequality. (3) Platform economy development can optimize energy resources allocation, promote energy utilization technology flow and narrow the green finance development gap, thus alleviating energy efficiency inequality. Governmental departments should promote platform economy development and green finance, and optimize renewable energy allocation.

Spatial differentiation of carbon emissions reduction potential for construction and demolition waste recycling

Identifying the regional differences and drivers for carbon reduction of construction and demolition waste (C&DW) recycling is essential to combat climate change. This study aims to calculate the carbon reduction potential for C&DW recycling from 2006 to 2021 in China and investigates the spatial differences and driving factors of carbon reduction potential for C&DW waste by combining the Theil index, Gini coefficient, and geographic detector methods. The carbon reduction potential for C&DW recycling in China was "high in the east and low in the west" overall level, with an average annual growth rate of 6.27%. The overall differences in carbon reduction potential for C&DW recycling are decreasing, mainly due to intraregional differences and inter-provincial differences in Northeast China. The population size, urbanization rate, and technological effect are the key factors influencing carbon reduction potential for C&DW recycling. There are two types of interactions between influencing factor pairs: nonlinear enhancement and two-factor enhancement. This study's results can guide policymakers to devise relevant, regionally specific policies.

Repercussions of Hydroelectricity use on Carbon Emissions in Bangladesh: Evidence using Novel Fourier-Bootstrapped ARDL and Fourier-Gradual Shift Causality analyses

Bangladesh has recently pledged at the 26th Conference of Parties (COP26) to reduce its carbon dioxide emission figures by 22% at the end of 2030. However, since this South Asian country has always turned to fossil fuels for electricity generation purposes, achieving this emission reduction goal is a challenging task for the Bangladesh government. Nevertheless, considering the negative environmental implications associated with the generation and consumption of unclean energy, particularly electricity, it is critically important for Bangladesh to expedite the process of clean transformation of its traditional pollution-intensive power system. Hence, the objective of this study is to dissect the repercussions of hydroelectricity use on Bangladesh's fossil fuel consumption-related carbon dioxide As opposed to the traditional method of quantifying environmental quality using total carbon dioxide emissions, this study considers Bangladesh's annual carbon dioxide emissions generated from the combustion of gas, oil, and coal. Besides, novel Fourier-based econometric methods that effectively handle structural break problems in data are utilized in this study. Based on the results, it is found that up-scaling hydroelectricity consumption levels exert emission-inhibiting effects while greater economic globalization activities are witnessed to boost the emissions. More importantly, hydroelectricity consumption and economic globalization are observed to jointly curb fossil fuel consumption-based emissions of carbon dioxide. Additionally, the results verify the environmental Kuznets curve hypothesis for Bangladesh. Furthermore, financial sector development is found to be effective in reducing the natural gas consumption-related carbon dioxide emissions while urbanization is held responsible for amplifying emissions generated from all three types of fossil fuels. Therefore, considering these findings, the Bangladesh government needs to particularly emphasize scaling up production and consumption of hydroelectricity to decarbonize its economy.

Multidimensional analysis of the regional inequalities in indirect carbon emissions from China's residential consumption

Residential indirect carbon emissions (RICE) are the major contributor to carbon emissions from the household sector. Regional RICE inequality has gradually become the focus of current issues. This paper has accounted for the RICE level of each province in China from 2010 to 2020 and assessed the RICE inequality at different regional scales employing the Theil index. Additionally, this paper presents a comprehensive analysis of RICE inequality across three dimensions: region, consumption category, and driving factors, illustrating the principal sources and determinants of RICE inequality. The results indicate the following: (1) RICE inequality in China is generally on a downward trend. (2) The gap between eastern China and the other regions is the dominant source of RICE inequality. (3) Residence consumption affects RICE inequality far more than other consumption categories. (4) Disposable income and the urban-rural structure of the population are the predominant factors affecting RICE inequality for most regions. The consumption propensity effect has a relatively pronounced impact on RICE inequality in the central and western regions. Based on the analysis, local governments ought to focus on economic construction, promote urbanization, and regulate the housing market to alleviate the RICE inequality.

Towards environmental degradation mitigation: The role of regulatory quality, technological innovation and government effectiveness in the CEMAC countries

The study explores the interaction between regulatory quality, economic growth, technological innovation, energy consumption, government spending on research and development, and environmental degradation (EVD) in the Economic and Monetary Community of Central Africa (CEMAC) region. The study applied the econometric approach CS-ARDL to estimate the short and long-term interaction between the regressors and the explanatory variable. The study period covers from 1990 to 2020. To summarize the findings of this research, (1) the study discovered a positive relationship between energy consumption, government effectiveness, regulatory quality, and environmental degradation. (2) Economic growth, government spending on research and development, and technological innovation, on the other hand, extensively dissipates EVD in the CEMAC economies. (3) The causality analysis espoused a bidirectional connection between energy consumption, technological innovation, and EVD. (4) Lastly, a unidirectional interplay exists between economic growth, government effectiveness, regulatory quality, and EVD. This study also serves as a reference point for policymakers and governmental institutions to invest in cleaner technologies and increase government research and development spending to mitigate environmental degradation in these areas.

Impact of Economic Policy Uncertainty and Pandemic Uncertainty on International Tourism: What do We Learn From COVID-19?

Uncertainty is an overarching aspect of life that is particularly pertinent to the present COVID-19 pandemic crisis; as seen by the pandemic's rapid worldwide spread, the nature and level of uncertainty have possibly increased due to the possible disconnects across national borders. The entire economy, especially the tourism industry, has been dramatically impacted by COVID-19. In the current study, we explore the impact of economic policy uncertainty (EPU) and pandemic uncertainty (PU) on inbound international tourism by using data gathered from Italy, Spain, and the United States for the years 1995-2021. Using the Quantile on Quantile (QQ) approach, the study confirms that EPU and PU negatively affected inbound tourism in all states. Wavelet-based Granger causality further reveals bi-directional causality running from EPU to inbound tourism and unidirectional causality from PU to inbound tourism in the long run. The overall findings show that COVID-19 has had a strong negative effect on tourism. So resilient skills are required to restore a sustainable tourism industry.

How do financial fragility and ICT penetration affect renewable energy consumption and green growth in top-polluting economies?

Green growth is an extension of traditional economic growth. Financial fragility and ICT penetration are important pillars of green growth sustainability. However, very limited studies have explored this association and provided conflicting results. Thus, our study intends to fill this vacuum by exploring the impact of financial fragility and ICT penetration on renewable energy consumption and green growth for the top five polluting economies over the period 1996-2020. In this study, financial fragility is measured by bank costs and bank non-performing loans. Panel ARDL technique is used to find out long-run and short-run results estimates. Financial fragility reduces renewable energy consumption and green growth in the long run. However, internet penetration enhances renewable energy consumption and green growth in the long run. Our findings suggest imperative policy implications for the green economy.

Causation between energy consumption and climate change in the countries with the highest global climate risk

The study aims to examine if there is causation between "energy consumption" and "climate change" through the data of ten countries with the highest Climate Risk Index (CRI) scores. The ten highest CRI score countries include Puerto Rico, Myanmar, Haiti, Philippines, Mozambique, The Bahamas, Bangladesh, Pakistan, Thailand, and Nepal. The annual data for the years 2005-2019 was used because of the data constraints. CRI is selected as the dependent variable. As for the independent variables, the ratios of the energy consumption of the key sectors indicated by the International Energy Agency (IEA) to the total energy consumption are chosen. These key sectors in energy consumption are industry (IND), transportation (TRA), trade and public services (TPS), and housing (HOU). Economic growth (EG), which is one of the main factors affecting climate change in the literature, is included in the model as the control variable. According to the results of the Dumitrescu-Hurlin causality test, there is one-way causality from transportation towards CRI, but not any causality between others. It is evaluated that since the transportation sector is heavily dependent on fossil fuels, it has a strong effect on the amount of CO₂ emissions and a significant determining role on climate change.

Analyzing the determinants of sustainability of China Pakistan Economic Corridor (CPEC) projects: an interpretive structural modelling (ISM) approach

China Pakistan Economic Corridor (CPEC) is a game changer initiative of South Asian Pacific Rim. It has great importance for almost all Asian countries. Its success is expected to dictate the economic development of the stakeholders. The aim of this study is to evaluate the essential determinants deriving the sustainability of CPEC projects. The design of the study comprises of the review of literature, data collection, and analysis. Population under study is the folk of stakeholders of CPEC. Sampling envisages on purposive sampling design, i.e., 14 experts from within the stakeholders. Primary data is collected in the field setting through a survey questionnaire appropriate for the study. ISM is used for modelling and MICMAC for analysis and classification using inductive approach. The findings of the literature survey show that there are 23 prime determinants of sustainability of CPEC projects. The results of ISM show that 13 determinants are at Level-I, nine at Level-II, and one determinant namely "economic globalization" is at Level-III being the most critical and driving determinant. The findings of MICMAC show that only one determinant is classified in independent quadrant, and all the remaining determinants are in linkage quadrant, whereas, no determinant is shown in autonomous and/or dependence quadrant. But most of the determinants have potential to be classified in dependent and independent quadrants. It is intimately evident that the results of MICMAC corroborate the results of ISM. It is useful for folk of the stakeholders by way of developing an understanding about the multitude of determinants, intra-determinant relations, prioritizing the determinants for policy decisions, and/or for building future studies. This study has some limitations, e.g., the study uses qualitative approach and answers what and how questions that do not quantify the relations or tell the cause of indicated relations.

The impact of space development structure on the level of ecological footprint - Shift share analysis for European Union countries

The impact of the space development structure on the level of the ecological footprint is an important element of the sustainable development policy, determining not only its directions, but also indicating the manner of respecting environmental principles. The aim of the research is to assess the impact of the spatial development structure on the ecological footprint level. The considerations are based on the assumption that the spatial development structure is a determinant of the ecological footprint level. The study used the shift share analysis method. Selected European countries were the subject of the research. The research period covered the years 2009-2019. The spatial differentiation of the GDP level and the ecological footprint were compared. For each country, the components of structural changes were determined and their changes over time were assessed. The study positively verified the main hypothesis and the auxiliary hypothesis. The ecological footprint decreased in the analyzed period. This phenomenon was not evenly distributed in European countries. Regions with a higher level of changes in the phenomenon than the EU average can be distinguished. The greatest changes in the demand for biosphere' natural resources in hectares of land and sea were recorded in Latvia and Lithuania. In contrast, the largest decrease in the size of the ecological footprint was observed in Cyprus. Differentiation of changes was visible within the individual components making up the ecological footprint in the analyzed period. The biggest changes took place within the fishing grounds. The smallest changes were recorded for cropland. This paper is expected to provide policy makers with a set of policy proposals to achieve sustainable environmental and economic development.

Spatial Differentiation of Digital Rural Development and Influencing Factors in the Yellow River Basin, China

The new development mode represented by the digital economy has provided new ideas for sustainable rural development. To comprehensively understand the status of digital rural development and propose scientific measures of rural revitalization in the Yellow River Basin (YRB), this study used counties as the research unit and data from 2020 to analyze the spatial differentiation characteristics and influencing factors by employing the Theil index, spatial autocorrelation analysis, and a geodetector model. The results showed that the digital rural development index in the YRB is slightly higher than it is in China overall, but the sub-index for the digital economy is lagging. The levels of digital rural development in the different reaches were lower reaches > middle reaches > upper reaches. Additionally, municipal districts and county-level cities have higher statuses than t general counties. Moreover, the decomposition of the Theil index shows that the intra-group differences in the upper reaches and general counties are the most important cause of the total differences. Moreover, the levels of digital rural development demonstrate spatial differences, with high and low levels in the east and west, respectively. An obvious reliable spatial correlation exists, and the spatial agglomeration featured with a similar level is significant. Finally, the influencing factors of spatial heterogeneity of digital rural development in the YRB and different reaches were different, with government expenditure being the main leading factor in the YRB and its upper reaches, while educational attainment and industrial structure are the leading factors in the middle reaches and lower reaches, respectively. The explanatory power of the interactions between the factors far exceeds that of a single factor, as shown through double-factor and nonlinear enhancement. This study provides a scientific reference for facilitating more targeted policy measures to achieving the goal of digital China and rural revitalization.

Investigating factors affecting global environmental sustainability: evidence from nonlinear ARDL bounds test

The concept of environmental sustainability formed the basis of the Paris Agreement and the United Nations conference in Rio de Janeiro. Empirically, without environmental sustainability, everything else could fall apart or be aimless. This study investigates factors affecting global environmental sustainability spanning 1966Q1 to 2019Q4. However, there are many micro-/macroeconomic factors engendering the environment, and the absence of robust clarity on whether factors such as economic growth, urbanization, trade openness, and energy consumption matter for global environmental sustainability remains a global academic dilemma in the economics literature. This paper utilized the unrestricted nonlinear autoregressive distributed lag (NARDL) bounds test techniques to model their relationship. Furthermore, the study adopted fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegrating regression (CCR) methods to test the research hypothesis, catering to the problem of endogeneity and serial correlation. Up-to-date of this study, no empirical study has examined the nexus of these variables within the global framework. The outcomes suggested that (i) NARDL bounds test of cointegration confirmed evidence of long-run and short-run relationships among the variables; (ii) long-run asymmetric relationship was affirmed among the variables; and (iii) DOLS, FMOLS, and CCR models demonstrate that economic growth, energy consumption, and trade openness are positively significantly correlated with environmental sustainability except for economic growth which shows negative and insignificant correlation. These findings validate the protracted argument in literature that these estimated variables are significant for global environmental sustainability. This study recommends that environmental policymakers integrate global economic incentives with favorable regulatory changes for achieving the goals of a global sustainable environment in the long-run equilibrium.

Spatiotemporal Evolution and Influencing Factors of Carbon Emission Efficiency in the Yellow River Basin of China: Comparative Analysis of Resource and Non-Resource-Based Cities

Comparing the carbon emission efficiency (CEE) of resource and non-resource-based cities in the Yellow River Basin (YRB) can guide their synergistic development and low-carbon transition. This study used the super-efficiency slacks-based measure (super-SBM) model to measure the CEE of cities in the YRB. Kernel density estimation and Theil index decomposition methods were used to explore the spatiotemporal evolutionary patterns, and a panel regression model was established to analyze the influencing factors of CEE. The research results showed that the CEE of the two types of cities have an overall upward trend in time, with a widening regional gap. Resource-based cities mainly displayed the characteristics of decentralized regional agglomeration, while non-resource-based cities mainly showed the characteristics of convergent regional agglomeration. Panel regression results showed that the levels of economic development, indus-trial structure, and population density are significantly positively correlated with CEE in the YRB, while foreign direct investment and resource endowment are significantly negatively correlated with CEE. Except for economic development and industrial structure, there is some variability in the contribution of the remaining influencing factors to the CEE of the resource and non-resource-based cities. The research results suggest developing classification measures for low-carbon transition in the YRB.

The role of green finance and energy innovation in neutralizing environmental pollution: Empirical evidence from the MINT economies

Pursuing ecological sustainability while mitigating the effects of environmental pollution has become a global pursuit. Moreover, the issue of how emerging economies like Mexico, Indonesia, Turkey, and Nigeria (MINT) economies can significantly reduce environmental pollution (EVP) remains elusive. This study sought to investigate the interplay between economic growth, green finance, renewable energy use, natural resource rent, energy innovation, urbanization and environmental pollution by analyzing panel data from 1990 to 2020. This research employed the novel econometrics approach CS-ARDL to examine the short and long-term relationships among the series. The research outcome disclosed that economic growth, natural resource rent and urbanization increase environmental pollution. In contrast, the empirical findings of this study revealed that environmental pollution could be neutralized through effective mechanisms such as green finance, renewable energy consumption, and the promotion of energy innovation. This research provides a fresh insight from the MINT economies and contributes to the existing literature by examining factors contributing to environmental pollution. This research also provides a benchmark for policy-makers and governments to invest in environmentally-friendly technologies to exploit the natural resources in these countries to mitigate the effect of environmental pollution.