Dynamic causality among urban agglomeration, electricity consumption, construction industry, and economic performance: generalized method of moments approach

Exploring the impact of climate technology, financial inclusion and renewable energy on ecological footprint: Evidence from top polluted economies

Most South Asian countries' economies have grown dramatically during the past few decades. However, in light of their environmental sustainability goals, the quality of such growth performances by South Asian nations is called into doubt by the concurrent degradation in environmental quality. Consequently, reducing the environmental challenges these nations encounter is prioritized on the agendas of the relevant authorities. This study aimed to analyze the effect of the top 11 most polluted countries' levels of financial inclusion, technological innovation, consumption of renewable energy, and adoption of climate technology on environmental deterioration from 2000 to 2022. Therefore, this research aims to use cutting-edge panel data econometric techniques to investigate the factors contributing to high carbon footprints in the world's most polluted nations. The results support an inverted U-shaped relationship between economic growth and carbon footprints, crediting the environmental Kuznets curve concept. In addition, it has been shown that TECH, REC, and CT can reduce carbon footprints in both the short and long term, while GDP and financial inclusion only affect carbon footprints in the long term. The results further endorsed the pollution haven hypothesis by showing that GDP positively affects carbon footprint. As a result, leading polluting economies need to strengthen their financial sectors, create green technology, migrate to renewable energy, and limit financial inclusion to improve environmental quality.

Unveiling dynamics of urbanization, rural logistics, and carbon emissions: A study based on China's empirical data

In an era where global focus intensifies on sustainable development, in this study, I investigate the interplay between rapid urbanization, rural logistics evolution, and carbon dynamics in China. We aim to bridge the gap in existing literature by examining the tripartite relationship between these areas and their collective impact on sustainable development. I explore the dynamic interaction mechanisms between urban construction, rural logistics development, and carbon emissions, assessing their joint influence on sustainable development. A detailed analysis of demand dynamics and market mechanisms supporting urbanization, rural logistics development, and carbon emissions has been initiated, leading to the establishment of a theoretical framework. This framework adeptly captures the interdependencies and constraints among these variables, offering a mathematical and bioscientific perspective to understand their complex interactions. Furthermore, a sophisticated nonlinear model based on key quantitative indicators like urbanization level, rural logistics development, and carbon emissions has been incorporated. Considering the multivariate nature, uncertainty, and dynamism presented by the nonlinear model, genetic algorithms have been employed for the estimation of model parameters. Through rigorous empirical testing using data from China spanning the years 1991-2021, I not only validate the effectiveness of the model but also accurately the interactions between urbanization processes, rural logistics progression, and carbon emissions. The findings demonstrate that urban construction significantly drives rural logistics development and uncover a pronounced nonlinear relationship among urbanization, rural logistics development (with a significant pull effect of 4.2), and carbon emissions growth. This research highlights the subtle balance between rural-urban development and environmental management, providing theoretical backing for the creation of sustainable policy frameworks in rural contexts and setting a foundation for future research in this domain.

Coordinated development and driving factor heterogeneity of different types of urban agglomeration carbon emissions in China

Carbon emission (CE) reduction has become the primary task of China's urban agglomerations (UAs) in achieving sustainable development goals. This paper uses a decoupling model and coupling coordination model to measure the relationship between the development levels of different types of UAs and CEs in China from 2004 to 2016. Concurrently, the geographically and temporally weighted regression model is used to explore the spatial heterogeneity of the impact of different driving factors on the CEs of UAs. The results show the following: Most UAs have the potential to further decouple CEs and economic growth. Most UAs are still in coordinated development (> 0.5). Among the service innovation UAs, the Yangtze River Delta UA has a coupling coordination of less than 0.3, while the Pearl River Delta UA has a coupling coordination of more than 0.8, showing polarization. Manufacturing and resource-based UAs are still in the grinding adaptation stage (0.5-0.8). There are apparent spatiotemporal differences in the impacts of various driving factors on the CE of UAs. The level of land urbanization and investment in fixed assets promote CEs. However, the level of population urbanization and industrial structure restrain CEs. Therefore, reducing land development and industrial transformation can be an effective means to reduce CEs in UAs. These findings will provide extensive insights for different UAs to achieve differentiated low-carbon development.

Effects of ICT diffusion on environmental pollution: analysis of industrial reallocation effects in China

The development of information and communication technology (ICT) has brought about fundamental changes in social progress worldwide. Using panel data from 288 Chinese cities for the period from 1999 to 2019, this study evaluates the effect of the pilot Broadband China Strategy (BCS) program on environmental pollution. We find that BCS significantly reduces environmental pollution, and that this effect is stronger in eastern China and in Chinese cities with higher financial progress or broadband development. Interestingly, the negative effect of BCS on environmental pollution decreases with the improvement of human capital in the cities. We further discuss industrial efficiency and reallocation mechanisms and ascertain that BCS affects environmental pollution in pilot cities not only through the efficiency mechanism as established in the existing literature but also through the industrial scale change and labor transfer between different industries, which we refer to as the industrial reallocation mechanism in this study. Specifically, via the industrial efficiency and reallocation mechanisms, the implementation of the BCS increases the scale and efficiency of the primary and tertiary industries but decreases the scale and efficiency of the secondary industry. This reduction in the secondary industry results in a decline in environmental pollution. It indicates that promoting the balanced development of a country's ICT infrastructure and pushing forward ICT diffusion can help alleviate environmental pollution by industrial reallocation and efficiency improvement, especially in nations with significant regional economic and technological differences.

The spillover of tourism development on CO2 emissions: a spatial econometric analysis

Climate change and tourism's interaction and vulnerability have been among the most hotly debated topics recently. In this context, the study focuses on how CO2 emissions, the primary cause of global warming and climate change, respond to changes in tourism development. In order to do so, the impact of tourism development on CO2 emissions in the most visited countries is investigated. A panel data from 2000 to 2017 for top 70 tourist countries are analysed using a spatial econometric method to investigate the spatial effect of tourism on environmental pollution. The direct, indirect, and overall impact of tourism on CO2 emissions are estimated using the most appropriate generalized nested spatial econometric (GNS) method. The findings reveal that tourism has a positive direct effect and a negative indirect effect; both are significant at the 1% level. The negative indirect effect of tourism is greater than its direct positive effect, implying an overall significantly negative impact. Further, the outcome of financial development and CO2 emissions have an inverted U-shaped and U-shaped relationship in direct and indirect impacts. Population density, trade openness, and economic growth significantly influence environmental pollution. In addition, education expenditure and infrastructure play a significant moderating role among tourism and environmental pollution. The results have important policy implications as they establish an inverted-U-shaped relationship among tourism and CO2 emissions and indicate that while a country's emissions initially rise with the tourism industry's growth, it begins declining after a limit.

Combined role of industrialization and urbanization in determining carbon neutrality: empirical story of Pakistan

A rapid process of industrialization, on the one hand, transformed the economies from agrarian to industrial societies to improve the living standards and welfare of people. On the other hand, the urbanized and industrialized economies have posed challenging threats to environmental sustainability. The query at hand is whether the growing environmental emissions are driven by industrialization and urbanization or not. This research aims to empirically examine the combined role of industrialization and urbanization in achieving carbon neutrality in Pakistan by considering foreign direct investment and economic growth as control variables in the model. The core empirical results are the following: firstly, industrialization and economic growth exhibit negative but statistically insignificant impacts on CO₂ emissions, imparting a neutral role in determining the environmental degradation in Pakistan. Secondly, urbanization and foreign direct investment disclose positive and statistically significant (at 1% level of significance) impacts on CO₂ emissions, manifesting an environmental degradation driving impact in the country. Thirdly, given the slope coefficients of urbanization and foreign direct investment (0.058 and 0.035), urbanization proved to be a stronger driver than foreign direct investment. Finally, foreign direct investment is revealed to make the Pakistani economy a "Pollution Haven" for the foreign enterprises in the country. Based on empirical results, none of the variables predicted the support for carbon neutrality in Pakistan.

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.

Analysis of the mechanism of the impact of internet development on green economic growth: evidence from 269 prefecture cities in China

As the digital economy develops rapidly and the network information technology advances, new development models represented by the network economy have emerged, which have a crucial impact on green economic growth. However, the relevant previous studies lacked the role of analyzing the direct and indirect effects of internet development on green economic growth at the prefecture-level city level. For this purpose, this paper aims to examine the intrinsic mechanism of the impact of internet development on green economic growth and provide empirical support for cities and regions in China to increase internet construction. Furthermore, the mixed model (EBM), which includes both radial and non-radial distance functions, is applied to calculate the green economic growth index. Fixed effect model and mediation effect model are also employed to test influence mechanisms of the internet development on green economic growth using panel data of 269 prefecture-level cities in China from 2004 to 2019. The statistical results reveal that internet development has contributed significantly to green economic growth. When the internet development level increases by 1 unit, the green economic growth level increases by an average of 5.0372 units. However, regional heterogeneity is evident between internet development and green economic growth, that is, the promoting effect of internet development on green economic growth is gradually enhanced from the eastern region to the western region. We also find that internet development guides industrial structure upgrading improves environmental quality and accelerates enterprise innovation, which indirectly contributes to green economic growth. And internet development mainly achieves green economic growth through enterprise innovation. Based on the above findings, we concluded that policymakers should not only strengthen the guiding role of social actors to promote the stable development of the internet industry, but also foster the construction of the three models of "internet+industry integration," "internet+environmental governance," and "internet+enterprise innovation" to promote green economic growth.

The Energy Mix Dilemma and Environmental Sustainability: Interaction among Greenhouse Gas Emissions, Nuclear Energy, Urban Agglomeration, and Economic Growth

In this paper we examined the interaction between greenhouse gas emissions, nuclear energy, coal energy, urban agglomeration, and economic growth in Pakistan by utilizing time series data during 1972–2019. The stationarity of the variables was tested through unit root tests, while the ARDL (autoregressive distributed lag) method with long and short-run estimations was applied to reveal the linkages between variables. A unidirectional association between all variables was revealed by performing a Granger causality test under the vector error correction model (VECM) that was extracted during the short-run estimate. Furthermore, the stepwise least squares technique was also utilized to check the robustness of the variables. The findings of long-run estimations showed that GHG emissions, coal energy, and urban agglomeration have an adversative association with economic growth in Pakistan, while nuclear energy showed a dynamic association with the economic growth. The outcomes of short-run estimations also show that nuclear energy has a constructive association with economic growth, while the remaining variables exposed an adversative linkage to economic growth in Pakistan. Similarly, the Granger causality test under the vector error correction model (VECM) outcomes exposes that all variables have unidirectional association. Furthermore, the outcomes of the stepwise least squares technique reveals that GHG emissions and coal energy have an adverse association with economic growth, and variables nuclear energy and urban agglomeration have a productive linkage to the economic growth in Pakistan. GHG emissions are no doubt an emerging issue globally; therefore, conservative policies and financial support are needed to tackle this issue. Despite the fact that Pakistan contributes less to greenhouse gas emissions than industrialized countries, the government must implement new policies to address this problem in order to contribute to environmental sustainability while also enhancing economic development.

Role of trade openness, export diversification, and renewable electricity output in realizing carbon neutrality dream of China

Since climate change mitigation is the central debate of modern literature, the realization of carbon neutrality in response to diversified macroeconomic variables is the most crucial concern of international economies. However, the critical role of trade and renewable electricity output in export diversification-environmental nexus is missing. Therefore, this study investigates the combined influence of trade openness, exports diversification, and renewable electricity output on carbon dioxide emissions (CO₂) in China from 1989 through 2019. Applying novel time series econometric techniques robust to structural breaks, following new outcomes are obtained. Firstly, long-run equilibrium cointegration existed among the under-analysis variables. Secondly, export diversification and renewable electricity output are predicted to decelerate CO₂, supporting carbon neutrality in the long run. Thirdly, trade openness and gross domestic product accelerated the CO₂, delaying carbon neutrality accomplishment. Most importantly, significant structural break dummy interacting with trade openness implicated that during the post-2001 era, China's trade openness extensively deteriorated the environmental quality in the face of trade liberalization obtained after joining the World Trade Organization (WTO). Based on empirical results, export diversification and renewable electricity production policies should be mutually non-exclusive and closely coordinated. Further, to counter the carbon emission acceleration impact of trade openness, increasing the share of green tradable products is suggested. Finally, bilateral trade restructuring is recommended to realize the long-term dream of economic sustainability and carbon neutrality.

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.

Does economic prosperity lead to environmental sustainability in developing economies? Environmental Kuznets curve theory

Since developing countries experience economic and environmental sustainability challenges, it is desirable digging into the linkages between economic and environmental parameters. The purpose of this work is to evaluate the existence of the environmental Kuznets curve (EKC) theory (i.e., the inverse U-shape connection between real GDP per capita and per capita carbon dioxide emissions) in the sample of 11 developing countries. By using balanced annual panel data in the period between 1992 and 2014 and two alternative estimation techniques, we explored the potential inverted U-shaped linkage between carbon dioxide emissions and real GDP per capita in the sample of interest. For analysis purposes, Pedroni and Westerlund co-integration techniques are employed. Then, fully modified ordinary least squares, pooled mean group methods are applied for long-run parameter estimations. And, the Dumitrescu-Hurlin causality approach is employed for causal directions. Firstly, this work's findings provide the supportive evidence to the inverse U-shaped linkage in the long-run, indicating that an increase in real GDP per capita and electricity consumption tends to mitigate long-run carbon dioxide emissions in the developing countries, for the whole sample. Secondly, the country-specific findings suggested the presence of EKC theory for Brazil, China, India, Malaysia, the Russian Federation, Thailand, and Turkey. It implicated that these countries are on the path of attaining environmental sustainability in the long-run. However, Mexico, Philippines, Indonesia, and South Africa failed to lend credence to the EKC theory. It manifested that these countries need to design strategies directed to reduce carbon dioxide emissions from economic activity and electricity generation through efficiency improvement or promotion of renewables. Finally, bidirectional causal links are observed among all the variables of interest. The findings suggest that country-specific targeted action plans should be implemented to ensure the environmental sustainability in the developing world.

Heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions across regional development levels

This study examined the long-run and short-run heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions index across the regional development levels of 31 Chinese provinces. By employing the augmented mean group method and Dumitrescu-Hurlin causality, the following results are drawn: Firstly, a bidirectional positive linkage was existent between the economic development and urban concentration in both the long-run and short-run across regional development levels. Secondly, a unidirectional positive linkage emerged from non-renewable energy use intensity to environmental emissions index, with the most influential effect in EER China (highest development level). Thirdly, bidirectional mixed linkages prevailed between economic development and non-renewable energy use intensity. Economic development mitigated the non-renewable energy use intensity (inverted U-shaped curve) in the national data set and EER China (highest development level); nevertheless, the linear linkage was observed in IER China (medium development level) and WER China (lowest development level). Fourthly, unidirectional mixed linkages were found from urban concentration to non-renewable energy use intensity and environmental emissions index. Urban concentration demonstrated a U-shaped linkage with non-renewable energy use intensity and environmental emissions index in the national data set and EER China. But it unveiled a linear linkage with both variables in IER China and WER China. Fifthly, economic development showed an environmental Kuznets curve with environmental emissions index in the national data set and EER China. Conversely, it showed a linear linkage with the environmental emissions index in IER China and WER China. In turn, the environmental emissions index linearly hampered the economic development in the national data set as well as regional samples. Finally, the long-run and short-run effects showed homogeneity of the linkages' nature; yet, the degree of effects in the long-run surpassed those in the short-run for all development levels.

Dynamic interactive links among sustainable energy investment, air pollution, and sustainable development in regional China

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.

Empirics on heterogeneous links among urbanization, the intensity of electric power consumption, water-based emissions, and economic progress in regional China

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. Graphical abstract.