Modeling heterogeneous dynamic interactions among energy investment, SO2 emissions and economic performance in regional China

The impact of renewable and non-renewable energy consumption on aggregate output in Pakistan: robust evidence from the RALS cointegration test

Over the past three decades, Pakistan's energy consumption has surged due to industrialization, population growth, and development activities. To meet the escalating energy demands, the country has primarily relied on thermal power projects, which are financially burdensome and environmentally detrimental, compared to hydropower projects. This reliance exposes Pakistan to global oil price shocks and environmental degradation. To address this dilemma, this empirical research investigates the impact of both non-energy factors (labour and capital) and energy-specific factors (renewable and non-renewable) on Pakistan's aggregate output, using annual time-series data from 1980 to 2021. The analysis employs the newly established Residual Augmented Least Square (RALS) cointegration test and the Autoregressive Distributed Lag (ARDL) methodology to estimate the long-term cointegrating relationship among the examined variables. The empirical findings demonstrate that both non-energy and energy-specific factors positively and significantly influence Pakistan's long-term aggregate output. However, petroleum consumption exerts a positive but insignificant influence on Pakistan's long-term aggregate output. The study recommends diversifying the energy supply mix to include more hydroelectricity, non-hydroelectric renewables (mainly solar and wind), and natural gas. Specifically, transitioning from imported, expensive, and more greenhouse gas (GHG)-generating petroleum products to domestically produced natural gas could potentially reduce Pakistan's trade deficit and its vulnerability to global oil price shocks. Besides the economic benefits, shifting from non-renewable energy sources (specifically oil) to renewable energy would enhance Pakistan's image and increase its geopolitical influence over neighboring countries. Additionally, the study emphasizes the need to encourage private sector participation in renewable energy projects and suggests implementing effective carbon tax policies to mitigate CO2 emissions and foster economic growth.

Assessing eco-label knowledge and sustainable consumption behavior in energy sector of Pakistan: an environmental sustainability paradigm

The energy needs of Pakistan have increased many folds in recent years due to improved lifestyle, ever-increasing population, and economic development. Though the government and private sectors are considering efficient energy resources to overcome energy scarcity in the country, studies focusing on assessing consumers' sustainable consumption behavior in the form of energy-saving home appliances are limited in the country. This study aims to address this research gap and also contribute by augmenting the theoretical mechanism of the theory of planned behavior by including three unique dimensions (eco-label knowledge, attitude toward environment, and customer green trust) to comprehensively analyze sustainable consumption behavior in the Pakistani context. An analysis is performed on survey data of 631 consumers in the four largest cities of Pakistan: Karachi, Lahore, Faisalabad, and Islamabad. For the purpose of evaluating formulated hypotheses, the structural equation modeling approach is employed. Empirical findings suggest that eco-label knowledge positively and significantly influences attitude toward environment and consumer green trust. Similarly, attitude toward environment and consumer green trust has a positive and significant influence on purchase intention. Moreover, a significant positive relationship exists between consumer green trust and purchase intention. The research outcomes further disclose that purchase intention positively and significantly influence paying attention to environmental labels. These findings contribute to the literature on sustainable consumption behavior and provide academics and practitioners with future directions to transform social norms, raise consumers' awareness, and redesign policy frameworks through integrative and consistent efforts.

Do environmental knowledge and green trust matter for purchase intention of eco-friendly home appliances? An application of extended theory of planned behavior

This study aims to identify the determinants of consumers' intentions to buy eco-friendly appliances for their households. This research scrutinizes the linkage between environmental knowledge (EK), consumer attitude (CAT), green trust (GT), and purchase intention (PI) in an emerging economy's context. This study analyzes survey data from 331 Pakistani consumers using energy-efficient household products. SEM is employed to assess the formulated hypotheses. Empirical findings suggest that EK positively and significantly influences CAT and green trust. Similarly, CAT has a negative and insignificant influence on PI. In contrast, green trust is significantly and positively related to PIs. The research outcomes further disclose that perceived consumer effectiveness (PCE) and perceived behavioral control (PBC) positively influence PI. The study extends the B2B sales literature and suggests future directions for academics and practitioners.

Influencing factors of consumers' buying intention of solar energy: a structural equation modeling approach

Due to China's massive usage of fossil fuels, climate change concerns have become serious challenges to the country's sustainable development. Despite the fact that China has effectively employed solar technology to address these problems, there is a paucity of research examining consumers' intention to adopt solar energy in the rural region of China. This study intends to fill this gap in the literature by studying consumers' buying intentions for solar energy in rural China for household purposes. Additionally, the study added to the theory of planned behavior by adding three new variables, namely, environmental knowledge, environmental concern, and beliefs about the benefits of solar energy. Primary data were collected from 847 respondents in Hebei Province using a comprehensive questionnaire survey. Structural equation modeling was employed to examine the data. Empirical results revealed that attitude, environmental knowledge, subjective norm, perceived behavioral control, and beliefs about the benefits of solar energy positively influence buying intention of solar energy. On the contrary, environmental concern had no significant effect on buying intention for solar energy. Study outcomes emphasize the critical significance of changing societal norms, boosting consumer awareness, redesigning regulatory mechanisms, and stressing the benefits provided by solar power through coherent and persistent efforts while simultaneously enhancing environmental sustainability practices.

How do clean fuels and technology-based energy poverty affect carbon emissions? New evidence from eighteen developing countries

Clean fuels and technology-based energy is an essential source to achieve sustainable economic growth and development. Therefore, the relationship between all types of poverty and other socioeconomic indicators has been studied extensively; nevertheless, clean fuels and technology-based energy poverty, adjusted for carbon emissions, has not been studied. The current study examines the impact of clean fuels and technology-based energy poverty on carbon emissions (Co2e). Using System-Generalized Method of Movement (SGMM) estimators, this study utilized panel data from eighteen developing countries in Asia from 2006 to 2017. The empirical findings obtained from econometric model suggest the presence of clean fuels and technology-based energy poverty and its curse on environment, i.e., energy poverty positively affects Co2e growth in Asian developing countries. Furthermore, economic growth (GDP), trade, and population are also positively associated with Co2e growth and negatively affect environmental quality. Based on the empirical findings of the current study, we recommend robust policy implications that the governments of targeted countries should invest more to increase clean fuels and technologies.

Determining the influencing factors of consumers' attitude toward renewable energy adoption in developing countries: a roadmap toward environmental sustainability and green energy technologies

The energy sector is a crucial pillar of the economic development of every nation. In developing countries, renewable energy deployment is scarce; consequently, the government and private sectors are exploring efficient energy resources. This research aims to scrutinize the linkages among value orientation, utilitarian benefits, collectivism, the reason for adoption, attitude toward renewable energy (RE), and adoption intention in the renewable energy context. The study analyzes survey data from 359 Pakistani consumers using solar panels for households. An approach called structural equation modeling is applied to evaluate hypotheses. Empirical findings suggest that value orientation positively and significantly influences the reason for the adoption of RE and attitude toward RE. Similarly, the utilitarian benefit positively and substantially affects attitude toward RE. Moreover, collectivism and reason for adoption are substantially and favorably related to attitude toward RE. The study's findings also show that customer intentions to use renewable energy are favorably and substantially influenced by RE attitudes. The research has contributed to the enhancement of future avenues for scholars and professionals are provided by the literature on renewable practice.

The effect of GDP, renewable energy and total energy supply on carbon emissions in the EU-27: new evidence from panel GMM

The vast usages of sources of energy that pollute the environment have resulted in major problems of global warming in the world. Global warming and greenhouse effect causes droughts, hunger, and starvation among many other health problems. In this research, the effect of energy use, economic, growth, and renewable energy on carbon emissions, in the European Union region from 1990 to 2019, is examined. The current study differs from previous researches, in that it specifies "effective capital" which is the interaction between energy and capital (a product of energy and capital) in the model. Effective capital is inevitable in the production process because physical capital such as machinery, without power or energy to fuel it, is dysfunctional. The current research employs the Generalized Method of Moments which is strong over endogeneity and overcomes heteroskedasticity, serial, and autocorrelation problems. The findings of this research support past studies that renewable energy reduces carbon emissions and gross domestic product exacerbates carbon emissions. Effective capital and energy use are observed to promote carbon emissions, whereas capital and population size reduces carbon emissions in the European Union.

Sulfur dioxide emissions curbing effects and influencing mechanisms of China’s emission trading system

The emissions trading system, a crucial and fundamental system reform in the environmental resources field of China, was established to promote the continuous and effective reduction of total emissions of major pollutants. In this context, based on the panel data of 285 Chinese cities (except Tibet) from 2004 to 2018, this paper uses the quasi-experimental method of Difference in Difference to assess the effect of the emissions trading system introduced on sulfur dioxide emissions of China and the transmission mechanism. The article generates several intriguing findings. (1) The emissions trading system has a significant suppressive effect on sulfur dioxide emissions. (2) Mechanistic tests show that the emissions trading system can effectively suppress sulfur dioxide emissions by reducing government intervention, stimulating green patent innovation, and improving resource use efficiency, in which green utility patents have a masking effect. (3) From the east, central and west divisions, the emissions trading system has a significant suppression effect on sulfur dioxide emission in the eastern and central regions, and the eastern region is better than the central region. (4) In terms of factor endowment, the emissions trading system has a significant suppression effect on sulfur dioxide emissions in both resource-based and non-resource-based cities, with non-resource-based cities outperforming resource-based cities; while within resource-based effect exists only in regenerative cities. (5) The emissions trading system has a significant suppression effect on sulfur dioxide emissions in old and non-old industrial base cities in industrial base zoning. The suppression effect in non-old industrial base cities is better than that in old industrial base cities. This paper provides empirical evidence for evaluating the emissions trading system at the provincial level in China and suggests policy recommendations for selecting government tools to effectively curb sulfur dioxide emissions. Although the emissions trading system has made an outstanding contribution to sulfur dioxide emissions reduction, there is still much space for further development of potential emission reductions.

Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China

Economic development is responsible for excessive sulfur dioxide (SO₂) emissions, environmental pressure increases, and human and environmental risks. This study used spatial autocorrelation, the Environmental Kuznets Curve (EKC), and the Logarithmic Mean Divisia Index model to study the spatiotemporal variation characteristics and influencing factors of SO₂ emissions in the Yangtze River Economic Belt (YREB) from 1997 to 2017. Our results show that the total SO₂ emissions in the YREB rose from 513.14 × 10⁴ t to 974.00 × 10⁴ t before dropping to 321.97 × 10⁴ t. The SO₂ emissions from 11 provinces first increased and then decreased, each with different turning points. For example, the emission trends changed in Yunnan in 2011 and in Anhui in 2015, while the other nine provinces saw their emission trends change during 2005-2006. Furthermore, the SO₂ emissions in the YREB showed a significant agglomeration phenomenon, with a Moran index of approximately 0.233-0.987. Moreover, the EKC of SO₂ emissions and per capita GDP in the YREB was N-shaped. The EKCs of eight of the 11 provinces were N-shaped (Shanghai, Zhejiang, Anhui, Jiangxi, Sichuan, Guizhou, Hunan, and Chongqing) and those of the other three were inverted U-shaped (Jiangsu, Yunnan, and Hubei). Thus, economic development can both promote and inhibit the emission of SO₂. Finally, during the study period, the technical effect (approximately -1387.97 × 10⁴-130.24 × 10⁴ t) contributed the most, followed by the economic (approximately 27.81 × 10⁴-1255.59 × 10⁴ t), structural (approximately -56.45 × 10⁴-343.90 × 10⁴ t), and population effects (approximately 4.25 × 10⁴-39.70 × 10⁴ t). Technology was the dominant factor in SO₂ emissions reduction, while economic growth played a major role in promoting SO₂ emissions. Therefore, to promote SO₂ emission reduction, technological innovations and advances should be the primary point of focus.

Striving towards sustainable development: how environmental degradation and energy efficiency interact with health expenditures in SAARC countries

The previous studies focused on environmental issues, identifying their root causes, urging prompt action to reduce environmental degradation. In this context, the current article extends the literature by incorporating the ecological impacts on the health sector and the role of sustainable development. The present study adds to the body of knowledge by examining the relationship between CO₂ emissions, sustainable development, energy efficiency, energy intensity, and health expenditures for SAARC countries from 2000 to 2020. Fully modified OLS (FMOLS) and dynamic OLS (DOLS) are used and diagnostic tests to check the association between the variables. The empirical analysis validated the long-run impact of the examined factors on health expenditures. The results show that energy efficiency and sustainable development have a statistically significant negative effect on health expenditures, vice-versa for CO₂ emission. Energy efficiency, energy intensity, and CO₂ emissions have been shown to have a one-way causative relationship with health expenditures, but sustainable development and economic growth have a two-way causation relationship. The better health status of the SAARC economies necessitates the establishment of long-term development strategies, environmental sustainability, and an examination of the energy sector. This work's conceptual and empirical advances have significant policy ramifications for this part of the globe and its efforts to improve sustainability.

The asymmetric nexus between air pollution and COVID-19: Evidence from a non-linear panel autoregressive distributed lag model

The emergence of a new coronavirus (COVID-19) has become a major global concern that has damaged human health and disturbing environmental quality. Some researchers have identified a positive relationship between air pollution (fine particulate matter PM2.5) and COVID-19. Nonetheless, no inclusive investigation has comprehensively examined this relationship for a tropical climate such as India. This study aims to address this knowledge gap by investigating the nexus between air pollution and COVID-19 in the ten most affected Indian states using daily observations from 9th March to September 20, 2020. The study has used the newly developed Hidden Panel Cointegration test and Nonlinear Panel Autoregressive Distributed Lag (NPARDL) model for asymmetric analysis. Empirical results illustrate an asymmetric relationship between PM2.5 and COVID-19 cases. More precisely, a 1% change in the positive shocks of PM2.5 increases the COVID-19 cases by 0.439%. Besides, the estimates of individual states expose the heterogeneous effects of PM2.5 on COVID-19. The asymmetric causality test of Hatemi-J's (2011) also suggests that the positive shocks on PM2.5 Granger-cause positive shocks on COVID19 cases. Research findings indicate that air pollution is the root cause of this outbreak; thus, the government should recognize this channel and implement robust policy guidelines to control the spread of environmental pollution.

The role of innovation investment and institutional quality on green total factor productivity: evidence from 46 countries along the "Belt and Road"

Based on the panel data of 46 countries in "Belt and Road" (B&R) from 2004 to 2016, this paper studies the impact of innovation investment and institutional quality on green total factor productivity (GTFP). Firstly, the ICRG database, World Bank WDI database, Traditional Foundation database, and Wind database are matched to obtain the balanced panel data of 46 countries along the B&R from 2004 to 2016. Secondly, the Malmquist-Luenberger index, which can be included in the unexpected output, is used to calculate the GTFP of countries along B&R. Thirdly, the evaluation system of national institutional quality of B&R is constructed from three dimensions (political institutional quality, economic institutional quality, and legal institutional quality), and the overall system quality of different countries is measured by entropy method. Finally, an empirical study is made on the relationship among innovation investment, institutional quality, and green total factor productivity. The results show that innovation investment has significantly promoted the GTFP of the B&R countries. It is worth noting that there is a non-linear relationship between innovation investment and GTFP in the B&R countries. With the improvement of overall system quality, political system quality, economic system quality, and legal system quality, the promotion effect of innovation investment on GTFP is further enhanced. In addition, the heterogeneity regression results show that the impact of innovation investment on GTFP is significantly heterogeneous in different regions of the B&R countries. Specifically, innovation investment has the greatest impact on GTFP in South Asia, followed by East Asia and Pacific, Europe and Central Asia, Middle East, and North Africa.

Towards long-term sustainable environment: does agriculture and renewable energy consumption matter?

This work analyzed the long-run (LR) and short-run (SR) effects of renewable and non-renewable energy (RE and NRE) usage, economic development (ED), agricultural value-added (AVA), and forestry area (FA) on the environmental quality (EQ) in China spanning from 1990 to 2015. The autoregressive distributed lags (ARDL) bounds testing method and the Johansen cointegration approach are applied to produce empirical estimates. The empirical results of the ARDL and the fully modified ordinary least square (FMOLS) estimators established that renewable energy usage and forest area reduce CO₂ emissions and improve the environmental quality, while non-renewable energy consumption, economic development, and agricultural output increase the level of CO₂ emissions in China. The robustness of outcomes is checked through the Granger causality test, impulse response function (IRF), and variance decomposition method (VDM) suggesting that fossil fuel usage in the agriculture production process is mainly accountable for China's CO₂ emissions. These findings have inherent policy implications for the central and local Chinese government, which are exhibited in the "Conclusions" section.

Do economic openness and electricity consumption matter for environmental deterioration: silver bullet or a stake?

Developing countries are enthusiastically on the road to economic progress and economic openness, which is proved to be a silver bullet for them. However, it has put their environmental quality at stake. This study examines whether economic openness and electricity consumption matter for environmental deterioration by controlling for the influence of economic progress. For this, we have used time series frequency data of Pakistan from 1971 to 2016 and employed the state-of-the-art dynamic autoregressive distributed lag (ARDL) simulation model. The model has the advantage over traditional ARDL in determining the positive and negative environmental deterioration variations induced by economic openness, electricity consumption, and economic progress. The main findings are as follows: Firstly, electricity consumption in both long and short run positively and significantly influenced CO₂ emissions, while long-run influence exceeded that of short run. Secondly, economic progress validated an environmental Kuznets curve hypothesis and thus limited the environmental degradation. Thirdly, economic openness showed an insignificant influence on CO₂ emissions both in the long and short run. Based on research findings, it is suggested that economic progress and economic openness are not the direct culprits to deteriorate a developing country's environmental condition like Pakistan; rather, electricity consumption remained the key role player. Therefore, the transition from fossil-based electricity consumption to renewable energy consumption would provide a sustainable pathway towards achieving sustainable economic openness in the future.

Impacts of Energy Efficiency and Economic Growth on Air Pollutant Emissions: Evidence from Angara–Yenisey Siberia

Environmental problems of urban and rural areas are now high on the agenda of industrialized countries, becoming a key challenge for regional-level policymaking. The mutual influence of population growth, economic and technological development, and the anthropogenic pressure on the environment is still insufficiently studied in many countries, including Russia. In this paper, this relationship is studied for the municipalities of Angara–Yenisey Siberia using an ensemble of the STIRPAT-like regression models, adapted according to the available data. We found that population size and gross municipal product were positively associated with pollutant emissions (p < 0.01), while energy efficiency had no significant impact on air pollution. In addition to the poor national data quality and completeness issues, which can distort statistical conclusions, the cause of the observed lack of spatial correlation between energy efficiency and air pollutant emissions may be path dependence and an insufficient pace of transition to a greener economy. This leaves room for institutional transformations aimed at intensifying energy efficiency to reduce the environmental burden.

Comparison between Historical and Real-Time Techniques for Estimating Marginal Emissions Attributed to Electricity Generation

Electricity generation is tied to various environmental and social consequences. In prior studies, the environmental emissions associated with electricity generation were calculated using average emission factors (AEFs) whose use is different from the method of marginal emission factors (MEFs) in regard to the geographical redefinition and new policies applied to the US electricity grid in 2013. Moreover, the amount of emissions being released at a generation site depends on the technology of the generating units; it is important to take into account this factor as well. Thus, this paper provides comparisons between different historical and real-time approaches of estimating MEFs (i.e., CO2, SO2, and NOx) for the Midcontinent Independent System Operator (MISO) electricity region. The region under study is the same for all the scenarios, although the comparative time frames are different. The study is focused on the similarities observed in the data trends and system behaviors. We carry out different temporal comparisons whose results show the value of real-time approaches for estimating the MEFs for each location and at any time. These approaches can be extended to other regions to assist with proper investment and policy making, thereby increasing the grid efficiency, mitigating the environmental emissions, and clarifying the byproducts of energy consumption.

Do Perceived Risk, Perception of Self-Efficacy, and Openness to Technology Matter for Solar PV Adoption? An Application of the Extended Theory of Planned Behavior

Solar PV (photovoltaic) technology has gained considerable attention worldwide, as it can help reduce the adverse effects of CO2 emissions. Though the government of Pakistan is adopting solar PV technology due to its environmental friendliness nature, studies focusing on consumer’s acceptance of solar PV are limited in the country. This research aims to close this knowledge gap by looking into the various considerations that may influence consumers’ willingness to adopt (WTA) solar PV for household purposes. The study further contributes by expanding the conceptual framework of the theory of planned behavior by including three novel factors (perceived risk, perception of self-efficacy, and openness to technology). The analysis is based on questionnaire data collected from 683 households in Pakistan’s provincial capitals, including Lahore, Peshawar, Quetta, Gilgit, and Karachi. The proposed hypotheses are investigated using the state-of-the-art structural equation modeling approach. The empirical results reveal that social norms, perception of self-efficacy, and belief about solar PV benefits positively influence consumers’ WTA solar PV. On the contrary, the perceived risk and solar PV cost have negative effects. Notably, the openness to technology has an insignificant effect. This study can help government officials and policymakers explore cost-effective, risk-free technologies to lessen the environmental burden and make the country more sustainable. Based on research results, study limitations, as well as prospective research directions, are also addressed.

Achieving pro-poor growth and environmental sustainability agenda through information technologies: as right as rain

The pro-poor growth and environmental sustainability are the twin agendas widely discussed in environmental science literature. The technology-embodied growth helps to attain both agendas through knowledge sharing and technology transfer, which trickle down to the poor income group and improve their living standards. Hence, the role of information and communication technologies (ICTs) is deemed crucial in boosting economic growth and is under deep consideration to establish its role in reducing poverty and environmental pollution. The current study examines the long-run relationship between ICTs, poverty reduction, and ecological degradation in Pakistan using time series data from 1975-2018. The short- and long-run parameter estimates were obtained through the Autoregressive Distributed Lag (ARDL) model for robust inferences. The results substantiate the inverted U-shaped Environmental Kuznets Curve relationship between income and emissions with a turning point at US$1000 in the short-run and US$800 in the long-run. The results confirmed the decisive intervention of ICTs factors in the poverty reduction, i.e., computer communications and mobile-telephone-broadband subscriptions support to reduce poverty incidence with the mediation of inbound FDI in a country. As far as income inequality is concerned, it shows that computer services support minimizing income inequality via a channel of high-technology exports in a country. The technology embodied emissions verified in the long-run, where mobile-telephone-broadband subscriptions increase carbon emissions. Finally, mobile-telephone-broadband subscriptions and inbound FDI both are significant contributors to amplify the country's economic growth. The results conclude that poverty reduction and environmental sustainability agenda are achieved by developing green ICT infrastructure in a country.

Regional difference decomposition and its spatiotemporal dynamic evolution of Chinese agricultural carbon emission: considering carbon sink effect

The current study aims to analyze the regional differences and spatiotemporal dynamic evolution of carbon emission intensity (CEI) and carbon emission per capita (CEPC) of planting industry with consideration of carbon sink effect. The results indicate that: (i) The CEI and CEPC of China's planting industry present significant non-equilibrium distribution characteristic during the investigate period, provinces with high CEI are mainly distributed in major agricultural provinces, while high CEPC provinces are mainly located in northeast and individual central provinces with large planting industry. (ii) Inter-regional difference is the principal course of the total differences, the CEI Theil index demonstrates gradient decreasing pattern of "western > central > eastern > northeast," the contribution rate of CEI Theil index shows "northeast > eastern > central > western," the CEPC Theil index shows the spatial pattern of "northeast > central > western > eastern," and the contribution rate of CEPC Theil index presents the spatial pattern of "eastern > central > western > northeast." (iii) The dynamic evolution of CEI and CEPC curve presents polarization or multipolar differential phenomenon accompanies with distinct gradient characteristics, the regional difference of agglomeration level in CEI is gradually narrowing, while the CEPC gradually expanding and the dispersion level is increasing, which implies the "intra-regional convergence and inter-regional divergence." Consequently, differential carbon reduction policies have been put forward according to the study findings.

Do Financial Development and Economic Openness Matter for Economic Progress in an Emerging Country? Seeking a Sustainable Development Path

While emerging economies face the challenge of competing with developed nations, they are capable of catching up to the developed world. In this context, financial development and the degree of economic openness may provide better living conditions for the current generation without giving up future generations’ prosperity. Therefore, this research’s prime intention is to investigate the impact of economic openness and financial development on economic progress, employing Pakistan’s time-series data from 1975–2018. To examine the long-term association between economic openness, financial development, and economic progress, Autoregressive Distributed Lag (ARDL) cointegration tests were performed and the results present a long-term association between these variables. Findings from ARDL estimates indicate that the relationship between financial development and economic progress is significantly positive in the long term. Contrastingly, the relationship between economic openness and economic progress is significantly positive in the short term. A fully modified ordinary least square technique was applied to check the robustness of the long-term links. The Granger causality test revealed that economic progress is motivated by both economic openness and financial development in an emerging economy such as Pakistan. Thus, policies boosting financial development and economic openness are proposed to put the emerging economies on a path of sustainable economic development.

Asymmetric investigation to track the effect of urbanization, energy utilization, fossil fuel energy and CO2 emission on economic efficiency in China: another outlook

The accelerated urbanization in China was already coupled with a steadily increasing demand for energy usage. The present study major aim was to determine the asymmetric influence of urbanization, energy utilization, fossil fuel energy and CO₂ emission on economic progress in China by using an annual time series data varies from 1975 to 2017. Stationarity amid variables was verified by applying the unit root tests, while non-linear autoregressive distributed lag (NARDL) bounds testing model was used to examine the asymmetric impacts on variables with short- and long-run dynamics. Outcomes revealed that via short-run estimates, the negative shocks of energy usage cause significantly to increase the economic efficiency, but positive shocks of energy utilization display the adverse linkage with the economic progress. Similarly, the negative shocks of GDP per capita growth demonstrate a substantial upsurge in the economic progress, and the positive shocks establish the adverse influence towards economic growth. Further, the outcomes of short-run dynamics also exposed the negative shocks of urbanization significantly affected the economic growth, but positive shocks exposed the adversative influence on economic growth. The outcomes display that fossil fuel energy consumption showed a constructive impact to economic progress, and additionally, the variable CO₂ emission also uncovered a positive shocks having significant impact on economic progress. Furthermore, the outcomes of long-run analysis express that energy utilization has negative and positive shocks that expose the adverse influence on economic progress of China. GDP per capita growth exposed the constructive influence on the economic growth in both shocks. The negative and positive shocks of urbanization demonstrate a noteworthy influence on economic growth. The variable fossil fuel energy consumption also exposed an optimistic influence on economic progress, and finally the influence of CO₂ emission on economic growth is insignificant as the results exposed. The reducing carbon alteration target aims to be reached for China, and in the next several decades, it will encourage the green energy options in order to decrease carbon dioxide emission to avoid environmental pollution by raising its energy intensity.

New insights into an old issue: exploring the nexus between economic growth and CO2 emissions in China

It is globally acceptable that carbon dioxide (CO₂) emissions are one of the greenhouse gases are considered the main factor influencing global warming and environmental degradation. The present study focuses on China, the world's largest carbon emitter. The study aims to capture the time-frequency dependency of economic growth and CO₂ emissions in China for the time period 1950-2016 using a wavelet coherence approach, which allows us to investigate both the long-run and short-run causal links of the estimated variables. In order to capture the long-run and causal linkage between economic growth and CO₂ emissions, the study employs Maki cointegration, wavelet coherence, Toda-Yamamoto causality, Fourier Toda-Yamamoto causality, and nonparametric Granger causality tests. The findings of this study reveal that (i) there is a significant vulnerability between economic growth and CO₂ emissions throughout the 2000s both the short-term and medium-term; (ii) there is long-run cointegration linkage between economic growth and CO₂ emissions in China; (iii) economic growth in China has an important power for predicting CO₂ emissions over the selected study period, especially in the short-term and medium-term; and (iv) it was observed that there is positive correlation between economic growth during the 1980s and 1990s in the short-term only. The outcome of the Toda-Yamamoto causality, Fourier Toda-Yamamoto causality, and nonparametric Granger causality tests underlines that economic growth is a robust policy variable for predicting CO₂ emissions in China.

The effect of environmental regulation intensity deviation on China's inclusive growth

This is the first attempt to explore the impact of environmental regulation intensity deviation on inclusive growth. An analysis framework in which the deviation between actual intensity and optimal intensity affects inclusive growth is constructed. Based on this analytical framework, this study uses panel data from 281 prefecture-level cities in China during the period 2004-2016 to investigate environmental regulation intensity deviation, as well as the feature, heterogeneity, and mechanisms of environmental regulation intensity deviation affecting inclusive growth. The empirical findings show that (i) environmental regulation has an inverted U-shaped effect on inclusive growth, but the actual intensity of environmental regulation in China is lower than the optimal intensity, which makes it difficult to give full play to its incentive role on inclusive growth; (ii) further grouping tests show that environmental regulation intensity deviation will inhibit inclusive growth within regions but promote inclusive growth between regions due to the difference in deviation; (iii) technological innovation, industrial transformation, and foreign investment have a partial mediating effect, which may be important mechanisms for environmental regulation intensity deviation to restrain inclusive growth; and (iv) the robustness test of informal environmental regulation supports the findings of formal environmental regulation and finds that the deviation of informal environmental regulation is more severe than that of formal environmental regulation. The empirical findings therefore suggest that policymakers should scientifically improve the environmental regulation intensity and optimize the environmental regulatory structure.