Search

China seems ambitious to achieve a "carbon emissions peak" before 2030 and "carbon neutrality" before 2060. To deal with this emissions mitigation plan, technology innovations are regarded as a crucial factor. However, considering its rebound effect (CO 2 emissions driving effect) through economic growth, technology innovations might not prove a promising contributor to CO 2 reduction. Therefore, there is a need to investigate further the nexus between technology innovations and CO 2 emissions for conclusive debate. Based on the data of 215 cities in China, this paper uses mediating effects model to investigate the direct and indirect impacts (through economic growth and industrial structure transformation) of technology innovations on CO 2 emissions from a microeconomic perspective. The main results suggest that technology innovations generally increase CO 2 emissions in China both directly and indirectly. The impact of technology innovations and economic growth on CO 2 emissions indicated the EKC characteristics. Furthermore, the contributions of technology innovations to CO 2 emissions are distinguished in different regions. Thus, there is an urgent need for China to promote innovations in "clean technology" and to transform industrial structure to the tertiary industry to achieve the targets of carbon neutrality and emissions peaking., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The present study aims to scrutinize the long- and short-run relationship along with the direction of causality among environmental pollution (CO 2 ), renewable, non-renewable energy, income disparity, exchange rate, and poverty alleviation in E-9 countries of continent Asia, using a panel dataset from 1990 to 2018. The current study used pooled mean group autoregressive distributed lag (PMG ARDL) and Dumitrescu-Hurlin (D-H) causality test after affirming a stable long-run association among environmental pollution and all the explanatory variables. However, ECM (error correction mechanism) was specified to explore short-run dynamics. The study's outcomes confirmed strong co-integration among environmental pollution (CO 2 ), renewable, non-renewable energy, income disparity, exchange rate, and poverty alleviation. Moreover, uni (bi) directional causality runs from non-renewable energy, exchange rate, and income disparity (poverty alleviation and renewable energy) to environmental pollution (CO 2 ). Results also revealed that poverty alleviation, exchange rate, and renewable energy usage substantially negatively influence environmental pollution (CO 2 ). Contrarily, income disparities and non-renewable energy usage positively influence long- and short-run environmental pollution. Therefore, from the policy perspective, the current study focused on twofold; first, there is a desire to alleviate poverty, the decline in non-renewable energy use and income disparity among upper and lower-income quintiles. Second, boost exchange rate and renewable energy use to control environmental pollution in the described least developed countries (LDCs)., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study is the first attempt to examine the effects of changing climate and financial development on rice cultivation in the context of agrarian economy like Thailand from 1969 to 2016. The current study also uses other important variables, such as cultivated area, organic fertilizers usage, and rural labor to determine the long-term connection amid variables. In this study, we applied several econometric techniques, for instance the autoregressive distributive lag-error correction model (ARDL-ECM), vector error correction model (VECM), impulse response functions (IMFs), and variance decomposition (VARD) method to estimate the most reliable and robust outcomes. The empirical results showed that in the long- and short-run, there is a reduction in rice cultivation as temperature increase. The carbon dioxide (CO 2 ) positively affects rice cultivation in the long-run, while this association is negative in the short-run. The findings further revealed that in the long- and short-run, domestic credit provided by the financial sector significantly positive improved rice cultivation, while domestic credit to private sector by banks negatively affects rice cultivation. The important input factors, including cultivated area, organic fertilizers usage, and rural labor significantly positive contributed toward rice cultivation in the long- and short-run. The calculated long-run causal connection of all the studied variables with rice cultivation is validated. The estimated short-run causal relationship is unidirectional among temperature, CO 2 emissions, financial development, rural labor, and rice cultivation. In addition, our outcomes are robust and also verified by IMFs and VARD method. The study offers some important policy suggestions to increase rice production with the help of sound and well-developed financial systems and climate controls., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Based on the comparative perspective of environmental regulation performance, this paper uses the threshold effect model to analyze the nonlinear characteristics of the impact of environmental regulation on economic development and environmental pollution and explore the dual performance of environmental regulation on economic and environmental development. The results are fourfold: Firstly, the intensity of fiscal expenditure on energy conservation and environmental protection has a restraining effect on environmental pollution, but it has a crowding-out effect on economic growth. Therefore, it is impossible to achieve a win-win situation between ecological protection and economic development by increasing the intensity of financial expenditure on energy conservation and environmental protection. Secondly, giving more financial rights to local governments in eastern China may help to reverse the non-win-win situation of the economy and the environment. Thirdly, increasing the environmental protection awareness of local governments will help to achieve a win-win situation. It is more effective to achieve a win-win situation of ecology and economy using constraint regulation than incentive regulation. Finally, the economic development level of the last period has different threshold effects on the current environmental pollution in the eastern and western China. Thus, the impact of environmental regulation lags. We conclude that we should give full play to the role of the environmental regulation, stimulate the endogenous power of environmental system, accurately implement the key differentiation strategy, and promote the win-win situation of ecological protection and economic development., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Since the development of the service sector and renewable energy reduce fossil-based energy consumption which mitigates CO 2 emissions and this nexus provides a better understanding of the environmental sustainability. Considering the substantially increasing contribution of service sector and tremendous potential for renewable energy in ASEAN5 countries, leaning forward from ASEAN's energy and growth nexus, this study examines the impact of service sector contribution and renewable energy on the environmental quality of ASEAN5 using annual data from 1990 to 2018. The results of the fully modified ordinary least squared, dynamic ordinary least squared, and canonical co-integrating regressions depicted that the service sectors of Thailand, the Philippines, and Singapore augment CO 2 emissions; however, the service sectors of Malaysia and Indonesia could reduce CO 2 emissions. The increasing share of renewable energy can enhance environmental quality, but its magnitude varies in ASEAN5 economies; non-renewable energy, population, and economic development deteriorate the environment. Our results confirm the existence of environmental Kuznets curve in all the ASEAN5; the Gregory-Hansen test confirmed that results are robust. Finally, the Granger causality designated that economic development and non-renewable energy have a significant causal relationship with CO 2 emission of ASEAN5 countries. These findings suggest that the ASEAN5 economies need to optimize their economic structure for promoting sustainable development in the long run.Graphical abstract., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This research examines the heterogeneous dynamic links among healthcare expenditures, land urbanization, and CO 2 emissions across the development levels of China. To this end, data of 27 Chinese provinces are considered from 1999 to 2018. Theoretically, this research developed a healthcare expenditures-augmented Stochastic Impacts of Regression by Population, Affluence, and Technology (STIRPAT) model to incorporate healthcare expenditures as a determinant of affluence. Empirically, this research established a system of simultaneous equations based on the healthcare expenditures-augmented STIRPAT model to estimate the links among the variables. As a pre-analysis, second-generation Westerlund cointegration is applied and found the long-term equilibrium association among the variables. The long-run estimations and short-run causality are done by employing dynamic common correlated effects mean group method (DCCEMGM) and Dumitrescu-Hurlin causality. A heterogeneous long-run equilibrium linkage is confirmed to exist among the variables of interest. Concerning the long-run estimates, firstly, the healthcare expenditures growth and land urbanization exhibited a bilateral positive link. Secondly, CO 2 emissions and healthcare expenditures growth manifested the existence of a bilateral positive link. And thirdly, a unilateral positive (negative) link is revealed to exist from a linear term (squared term) of land urbanization to CO 2 emissions. Concerning the short-run results, firstly, a bilateral causal bond exists between the land urbanization and healthcare expenditures growth. Secondly, a bilateral causal bond prevails between CO 2 emissions growth and healthcare expenditures growth. Finally, a unilateral causal bond is operational from land urbanization to CO 2 emissions growth. In terms of the nature of the link, the long-run findings are consistent across the data samples. However, considering the degree of influence, heterogeneity is confirmed across the development levels for both long- and short-run. It infers that relatively more (less) developed regions showed relatively strong (weak) influence. Based on empirical findings, relevant policies are recommended., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

This research investigates the dynamic interactive associations among sustainable investment in the energy sector, air pollution, and sustainable development. To this end, it employs a "one-step" system-generalized method of moments (GMM) and "one-step" differential-GMM estimators, covering the period between 1996 and 2017. In this context, it utilizes the simultaneous equations of the dynamic panel data model for panel data of 27 Chinese provinces and municipalities. We have developed a new model of sustainable development, which incorporates sustainable investment in the energy sector and air pollution to offer a robust theoretical foundation for considering the underlying relations. The system-GMM estimator is used for the full data set; however, differential-GMM is utilized for the subsets of data, in order to tackle the small sample bias problem. The empirical outcomes provide several vital insights in that they yield mixed findings for the aggregated sample and subsets of data. For example, a two-way causal relationship occurs for all the panels, except the central part (medium development regions), between sustainable investment in the energy sector and sustainable development. Contrary to this, causality runs from air pollution to sustainable investment in the energy sector in a full data set and the central part (medium dev.). Nevertheless, the opposite is true in the case of the eastern part (most developed regions) of China. Still, the same relationship runs in either direction in the case of the western part (least developed regions). On the other way around, the feedback hypothesis of causality is confirmed, across all the samples, between air pollution and sustainable development. Hence, sustainable development and air pollution are overwhelmingly interdependent, in the country as well as the province and municipality level of the Chinese economy.

This study examines the interaction between energy poverty, employment, education, per capita income, inflation, and economic development using panel data for seven South Asian countries. The present study uses panel data spanning the period from 1995 to 2017, panel cointegration, autoregressive distributed lag (ARDL), and penalized quantile regression (PQR) estimators to test for cointegration in the long-run. The estimated results reveal that both panel cointegration approaches (Pedroni and Johansen-Fisher) demonstrate the existence of the long-term relationship between energy poverty, employment, education, per capita income, inflation, and economic development. The ARDL estimates show that energy poverty has a negative influence on economic development in both the long-run and the short-run. The results provide support for economic, social, and environmental policymakers in their decision-making. This study suggests that, in relation to financing the green and low-carbon economy concept, both the public sector and private industries need to make further efforts to use modern, energy-efficient, and green technologies, which are beneficial both for economic progress as well as managing the ecological degradation process.

This study aims to explore the dynamic association among crop production, livestock production, power consumption in agriculture, forest area, and carbon dioxide (CO 2 ) emissions. Based on the annual data of China, spanning the period 1990 to 2016, the study applied the auto-regressive distributed lag (ARDL) bounds testing approach. In addition, the fully modified ordinary least squares (FMOLS) canonical cointegration regression (CCR) and the Granger causality tests are employed to check the robustness of the ARDL estimations. The ARDL-bounds testing approach indicated that all variables share a long-run connection. The long- and short-run ARDL estimations confirmed that crop production, as well as livestock production, has a significant positive effect on CO 2 emissions in both cases. However, power consumption in agriculture and forest area has a negative effect on it, indicating that both variables reduce CO 2 emissions in the long and short run. These results stood robust under various regression estimators and confirmed the findings of the ARDL method. Additionally, the results of the causality approach specified that a unidirectional causality is running from crop production, power consumption in agriculture, and forest area to CO 2 emissions. The causality between livestock production and CO 2 emissions is bidirectional. Therefore, the directions of this connection also validate the outcomes under various techniques used for robustness. These findings suggest that the government must reconsider its policies related to agricultural and livestock production and adopt environment-friendly practices in the agriculture sector that may reduce the carbon footprints in the long run.

Energy acts as a catalyst to boost the human development index (HDI) in a country. However, the overuse of energy leads to environmental deterioration, which is a byproduct of economic development. Due to the utilization of non-renewable energy sources for a long time, worldwide environmental conditions have become alarming. This study investigates the relationship between renewable and non-renewable energy consumption, economic growth, environmental sustainability, and the human development index (HDI) in Pakistan. The investigation incorporates population growth and technology variables to form a multivariate framework. We use a fully modified ordinary least squares (FMOLS) approach to time-series data from 1990-2017. To check the robustness of estimations, we apply the Gregory-Hansen test with a causality test under the VECM to confirm this association's directions. Our findings confirm that non-renewable energy sources have a positive association with economic growth and CO 2 emissions. However, human development, technology, and renewable energy boost economic development and reduce environmental pollution in Pakistan. The co-integration results confirmed the long run connectivity among all variables. The causality outcomes support the bidirectional causality between renewable and non-renewable energy consumption, economic growth, and CO 2 emissions, both in the short and long run. These outcomes suggest that Pakistan should focus on energy shifts and gradually increase the share of renewables in its energy mix under the China Pakistan Economic Corridor (CPEC). Additionally, the government should increase human and technological development to enhance economic and environmental sustainability.

Energy affects the economic growth and development of a country. Renewable energy has become an important part of the world's energy consumption. The use of fossil fuel energy contributes to global warming and carbon dioxide emissions, and has a detrimental effect on the environment. The long-run and short-run causality relationships between electric power consumption, renewable electricity output, renewable energy consumption, fossil fuel energy consumption, energy use, carbon dioxide emissions, and gross domestic product per capita for Pakistan over the period of 1990-2017 were investigated in this paper using the autoregressive distributed lag bounds testing approach to cointegration. The augmented Dickey-Fuller unit root test and the Phillips-Perron unit root test were used to check the stationarity of the variables, while the Johansen cointegration test was applied to check the robustness of the long-run relationships. The Granger causality test under the vector error correction model extracted during the short-run estimation showed a unidirectional relationship among all variables except for the relationship between gross domestic product per capita and carbon dioxide emission, which was bidirectional (feedback hypothesis). The evidence showed that in the long run, carbon dioxide emissions, electric power consumption, and renewable electricity output had a positive and significant relationship with the gross domestic product per capita, while the relationship of renewable energy consumption, energy use, and fossil fuel energy consumption with the gross domestic product per capita had a negative effect. Overall, the long-run effects of the variables were found to have a stronger effect on the gross domestic product per capita than the short-run dynamics, which indicated that the findings were heterogeneous. The evidence suggests that the government of Pakistan should take steps to enhance the use of renewable energy resources to resolve the energy crisis in the country and introduce new policies to reduce carbon dioxide emissions.

Promoting the green development of resource-based cities is an essential way to achieve sustainable regional economic development. Based on 2009–2019 panel data of the Yellow River Basin cities, this study adopts the super-directional distance function model to measure the green development efficiency of these selected cities. Furthermore, based on the Malmquist-Luenberger index, this paper focuses on the dynamic change trend of green development efficiency and internal driving factors. Furthermore, the Tobit model is used to specifically explore the influencing factors affecting the green development of cities. The findings suggested that the green development efficiency of selected cities falls in the middle to high range and that the efficiency varies among all cities in the Yellow River Basin. Likewise, technical efficiency improvements and technological progress drive development efficiency, and the former contributes more to green development. However, financial development, energy structure adjustments, and environmental regulation can strongly contribute to the green development of cities, and each influencing factor has obvious temporal and regional differences. This paper proposes appropriate policy suggestions to promote the coordinated development of the economic development and environmental protection of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

The present study intends to scrutinize the asymmetrical influence of economic growth, industrial production, CPI (consumer price index) and oil price on the trade deficit for the People's Republic of China's economy. The Toda–Yamamoto causality, non-linear ARDL method, and quarterly data for 1995Q1 to 2021Q4 have been utilized to investigate the results. The estimated results confirm the uni-directional causality and presence of non-linear co-integration among variables under discussion. However, bound test analysis also reveals the long-run asymmetrical association among TD (trade deficit), IP (industrial production), oil price, and GDP growth, but not the CPI (consumer price index). Further, long-run asymmetrical outcomes highlight that a decrease (increase) in industrial production and an increase (decrease) in oil price and GDP growth rate increase (decrease) the trade deficit. Short-run asymmetrical outcomes reveal a similar trend to the long run, but the impact of all variables in the short run is insignificant, which means that linkages between the trade deficit and the explanatory variables are a long-run phenomenon in People's Republic of China. Thus, in terms of policy, to reduce the trade deficit, it is necessary to focus on attaining standardized GDP growth, increasing industrial-sector production using advanced technology, and replacing oil-using energy sources with green technology (solar panels, wind farm energy). [ABSTRACT FROM AUTHOR]

The primary objective of this research was to determine the impact of renewable energy, alternative and nuclear energy, urbanization, energy use, and fossil fuel energy consumption on Romanian economic development. To investigate the relation between variables, we employed the Autoregressive Distributed Lag (ARDL) technique in conjunction with FMOLS (Fully Modified Least Squares) and CCR (Canonical Cointegrating Regression). Long-run and short-run findings suggest that alternative and nuclear energy, as well as fossil fuel consumption, has a positive association with economic growth, but renewable energy, urbanization, and energy usage have an adversative relationship with economic growth. Similarly, FMOLS and CCR statistics indicate that alternative and nuclear energy and fossil fuel consumption have a favorable impact on economic development. Renewable energy consumption, urbanization, and energy use, on the other hand, revealed a negative connection with economic progress. Conservative solutions are necessary to implement appropriate policies to address energy consumption concerns in Romania in order to improve economic development. [ABSTRACT FROM AUTHOR]

This study investigates the heterogeneous causal linkages between urbanization, the intensity of electric power consumption, water-based pollutant emissions, and GRP in regional China by developing an urbanization-augmented "Stochastic Impacts by Regression on Population, Affluence, and Technology" (STIRPAT) model. A whole country panel of 29 provinces as well as region sub-panels of China, for the period 1999 to 2018, are estimated employing common correlated effects mean group approach (CCEMGA), which offers robustness against heterogeneous characteristics and cross-sectionally dependent series. From the theoretic modeling aspect, the intensity of electric power consumption and urbanization have been introduced as the determinants of water-based pollutant emissions in the STIRPAT modeling framework. Based on empirical results, first, GRP growth has shown appealing behavior in the form of its heterogeneous impacts on water-based pollutant emissions growth in the case of different regions. For instance, its impact is noted to be positive and statistically significant for the western region, which turned positive but statistically insignificant for the intermediate region. And it further turned significantly negative in the case of the eastern region. We call this phenomenon as "development level-based emission mitigation effect." Second, in terms of the impact of GRP growth on urbanization, the "development-based urbanization ladder effect" has been found. Based on heterogeneous causal links, firstly, the existence of a positive bilateral causal link between the intensity of electric power consumption and GRP growth and urbanization and GRP growth has been validated. Secondly, a positive unidirectional causal link emerged from urbanization to the intensity of electric power consumption and water-based pollutant emissions growth. Thirdly, the causal connection between GRP growth and water-based pollutant emissions growth remained very interesting and of mixed nature. Based on empirical findings, useful policies are extended. [ABSTRACT FROM AUTHOR]

In this study, we attempt to investigate the relationship between electricity consumption, foreign direct investment (FDI) and economic progress in Pakistan during the period from 1997 to 2017. We applied the unit root tests to cointegration approach with the vector error correction model (VECM) approach. We also authenticated the robustness of the outcomes with the help of the regression methods. The main findings indicated that variables are cointegrated in the long-run and the VECM approach verified long-run causal links among the variables. The short-run causality is running from electricity consumption and economic development to FDI. The results remained uniform under the fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and the autoregressive distributed lag (ARDL) estimations. Correspondingly, these three methods ratified that there is a significant long-run linkage between electricity consumption and the economic development of Pakistan. Additionally, the diagnostic assessments fixed that results are free from correlations and models are stable. Thus, based on these results, electricity generation and consumption, as well as FDI, is crucial for the economic progress of Pakistan. The priority should be given to promote the optimum use of available resources to generate energy, and FDI in the energy sector should be attracted through various incentives to support the economic advancement of Pakistan. Renewable energy resources are recyclable springs that can cut the intensity of carbon emissions and encourage to the promising magnitude of FDI and also certify sustainable and economic progression of Pakistan. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to examine the long-term effects of financial development, economic growth, energy consumption (electricity consumption in the agriculture sector), foreign direct investment (FDI), and population on the environmental quality in Pakistan during the period of 1980 to 2016. We use CO2 emissions from the agriculture sector as a proxy indicator for environmental quality. We employ various unit root tests (e.g., ADF, PP, ERS, KPSS) and structural break unit root tests (Z&A, CMR) to check the stationarity and structural break in the data series. Cointegration tests, i.e., Johansen, Engle-Granger, and ARDL cointegration approaches are used to ensure their robustness. Results showed that significant long-term cointegration exists among the variables. Findings also indicated that an increase in financial development and foreign direct investment (FDI) improves environmental quality, whereas the increase in economic growth and electricity consumption in the agriculture sector degrades environmental quality in Pakistan. Based on the findings, we suggest policymakers should provide a conducive environment for foreign investment. Moreover, it is also suggested that a reliance on fossil fuels be reduced and a transition to renewable energy sources be encouraged to decrease the environmental pollution in the country. [ABSTRACT FROM AUTHOR]

This paper investigates the electricity production from different sources in Pakistan, and the contribution of these sources to economic growth. An ADF (Augmented Dickey-Fuller) unit root test was used to check the variables stationarity, while an ARDL bounds testing approach was used to check the long-term relationship among the study variables. Results illustrate that electricity produced from coal, hydropower, natural gas and nuclear sources has a significant influence on the economic growth of Pakistan. [ABSTRACT FROM AUTHOR]