Does economic complexity help in achieving environmental sustainability? New empirical evidence from N-11 countries.

In view of the SDGs argued by UNO, it is vital to address the pressing issues regarding sustainable development. The aim of current study is to investigate the impact of economic complexity (ECC) on environmental sustainability. To achieve this aim, we sampled the 25 years of data of Next-11 countries over the period 1995 to 2019. The economic complexity was measured by the economic complexity index (ECI) while environmental sustainability was measured by two proxy variables including CO2 and greenhouse gas (GHG) emissions. The empirical analysis was established by utilizing the unit root test, cointegration test, FMOLS (fully modified OLS) and DOLS (dynamic OLS) models. The estimated coefficient values disclosed that ECC has a negative and statistically significant relationship with both CO2 and GHG emissions in the long run, implying that ECC ensured environmental sustainability. In addition, the analysis reveals that financial development has a negative while economic growth and energy imports have a positive and statistically significant association with both CO2 and GHG emissions. The findings of the current study suggested an important policy regarding the focus on ECC for achieving environmental sustainability in underlying economies. This study provides robustness to the existing literature in alternative data settings (N-11 countries) and by the unique objective of focusing on environmental sustainability.

Carbon reduction through renewable energy and digitalization in emerging economies: Moderating role of public debt.

Utilizing renewable energy (RE) and embracing the digital economy (DIG) can significantly contribute to achieving economic, energy, and climate goals by promoting carbon reduction. In this regard, public debt (DEB) is particularly important since it provides the funds required to achieve these goals by investing in renewable energy and digital economy projects. This study examines the impact of public debt on the link between renewable energy and carbon emissions (CE), as well as the association between the digital economy and carbon emissions in emerging economies from 2003 to 2022. The study employed cross-sectional augmented autoregressive distributed lag (CS-ARDL) estimation to check the relationship between the variables. The findings of our study suggest that the integration of renewable energy sources and the growth of the digital economy have a positive impact on reducing carbon emissions. On the other hand, public debt has a positive effect on carbon emissions. In addition, the findings support the notion that interaction terms (RE × DEB) and (DIG × DEB) have a diminishing effect on carbon emissions. It can be concluded that the reduction of carbon emissions is contingent upon the utilization of public debt to promote the growth of renewable energy and the digital economy. Based on our study, it is recommended that emerging economies' needs focus on boosting renewable energy usage and digital economy initiatives. Additionally, it is necessary for these economies to maintain a sustainable level of debt.

Does international trade improve carbon productivity? Evidence from countries along the Belt and Road.

The Belt and Road Initiative proposed by China has significantly increased trade in countries along the Belt and Road (B&R). Since most of these countries are developing and emerging economies, the pressure to reduce carbon emissions poses a leading challenge for them. Carbon productivity has become a key indicator for assessing the degree of low-carbon development, as it can link economic development with CO2 emission reduction. However, few studies have investigated how international trade affects carbon productivity. Based on panel data from 43 countries along the B&R during 2001-2019, this paper uses a system GMM model to explore the impact of international trade on carbon productivity. Then, we divide the 43 countries in the sample into two groups according to their income levels to compare the different effects of international trade on carbon productivity. The results show that, first, the carbon productivity of the examined B&R countries has an overall increasing trend, and there is a significant heterogeneity of carbon productivity among countries with different income levels. Second, the effects of international trade, export, and import on carbon productivity are all significantly positive, and export's effect is higher than import. In the high-income group, carbon productivity is more likely to be improved by trade than in the middle (low)-income group. Third, economic development level, urbanization, and energy productivity are positively associated with carbon productivity, while CO2 per capita and government size inhibit carbon productivity improvement. Insight into the impact of international trade on carbon productivity provides theoretical support for B&R countries to better leverage foreign trade activities to achieve a green economy.

Financial regulations and sustainability: The role of energy price and climate policy uncertainty.

Russia ranks among the top five countries worldwide in terms of carbon emissions, with the energy, transportation, and manufacturing sectors as the major contributors. This poses a significant threat to both current and future generations. Russia faces challenges in achieving Sustainable Development Goal 13, necessitating the implementation of more innovative policies to promote environmental sustainability. Considering this alarming situation, this study investigates the role of financial regulations, energy price uncertainty, and climate policy uncertainty in reshaping sectoral CO2 emissions in Russia. This study utilizes a time-varying bootstrap rolling-window causality (BRW) approach using quarterly data from 1990 to 2021. The stability test for parameters indicates instability, suggesting that the full sample causality test may yield incorrect inferences. Thus, the BRW approach is employed for valid inferences. Our findings confirm the time-varying negative impact of financial regulations on CO2 emissions from energy, manufacturing, and transportation sectors. Additionally, findings confirm time-varying positive impact of energy prices and climate policy uncertainty on CO2 emissions from the energy, manufacturing, and transportation sectors. Strong financial regulations and stable energy and climate policies are crucial for achieving sustainability, highlighting significant policy implications for policymakers and stakeholders.

Unleashing sustainability in uncertain times: Can we leverage economic complexity, uncertainty, and remittances to combat environmental degradation?

Rapid economic growth and human activities have seriously damaged the environment and hindered the achievement of Sustainable Development Goals (SDGs). Hence, this study aims to explore the impact of economic complexity, uncertainty, and remittance on environmental degradation in 134 countries from 2000 to 2022. In addition, it examines whether uncertainty moderates the relationship between remittance and environmental degradation. Two proxies (ecological footprint and CO2) were used to measure environmental degradation. The analysis was conducted using a cross-sectional dependency test, second-generation unit root test, and panel quantile regression. The results revealed that economic complexity significantly and positively impacted environmental degradation, while uncertainty and remittance significantly and negatively impacted environmental degradation. Furthermore, uncertainty weakened the negative relationship between remittance and environmental degradation. Accordingly, this paper discusses various recommendations and policy implications regarding economic complexity, uncertainty, remittance, and environmental degradation.

The role of environmental tax on the environmental quality in EU counties: evidence from panel vector autoregression approach.

This study intends to analyze the influence of environmental taxes on pollution in EU-27 nations. Furthermore, energy from renewable sources consumption and urbanization are employed to clarify CO2 emissions in this study that tests the EKC hypothesis. According to the findings, an increase in environmental taxes reduces CO2 emissions by 0.14%. Also, the data supported the validity of the EKC concept. The findings of the causality test demonstrated that there is a bidirectional causal link between CO2 emissions and environmental taxes. These results reflect that environmental tax revenues contribute to sustainability as an effective policy tool in EU countries. Policies regarding environmental tax enforcement come to the fore in terms of both keeping the balance in economic activities and serving sustainability.

From black to green: Quantifying the impact of economic growth, resource management, and green technologies on CO2 emissions.

In an exploration of environmental concerns, this groundbreaking research delves into the relationship between GDP per capita, coal rents, forest rents, mineral rents, oil rents, natural gas rents, fossil fuels, renewables, environmental tax and environment-related technologies on CO2 emissions in 30 highly emitting countries from 1995 to 2021 using instrumental-variables regression Two-Stage least squares (IV-2SLS) regression and two-step system generalized method of moments (GMM) estimates. Our results indicate a significant positive relationship between economic growth and CO2 emissions across all quantiles, showcasing an EKC with diminishing marginal effects. Coal rents exhibit a statistically significant negative relationship with emissions, particularly in higher quantiles, and mineral rents show a negative association with CO2 emissions in lower and middle quantiles, reinforcing the idea of resource management in emissions reduction. Fossil fuels exert a considerable adverse impact on emissions, with a rising effect in progressive quantiles. Conversely, renewable energy significantly curtails CO2 emissions, with higher impacts in lower quantiles. Environmental tax also mitigates CO2 emissions. Environment-related technologies play a pivotal role in emission reduction, particularly in lower and middle quantiles, emphasizing the need for innovative solutions. These findings provide valuable insights for policymakers, highlighting the importance of tailoring interventions to different emission levels and leveraging diverse strategies for sustainable development.

Examining the dynamic impact of carbon emissions, renewable energy and economic growth on healthcare expenditure in Asian countries.

This study aims to examine the impact of renewable energy, carbon emissions, and economic growth on healthcare spending in 36 Asian countries during 2000-2019. Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) models have been applied to the panel data for 36 Asian countries. The study's findings show that CO2 emissions in Asia increased due to public and private health spending, with the commercial health sector having a larger negative influence on CO2 emissions than the public sector. According to FMOLS and DOLS findings, carbon emissions and GDP are positively related to health spending, indicating that high economic growth through energy-intensive production processes leads to increased carbon emissions, but on the contrary, renewable energy consumption has decreased healthcare expenditure. This study advocates new policies to reduce carbon emissions and hospitalisation without jeopardising national economic growth. In order to achieve sustainable health services and an environmentally friendly future in Asia, health administrators must raise state and private healthcare spending while implementing an effective cost-service and energy-efficient management plan.

Understanding China's CO2 emission drivers: Insights from random forest analysis and remote sensing data.

China has become the world's largest emitter of carbon dioxide, putting significant pressure on the government to reduce emissions. This study analyzes the driving factors of carbon emissions in 281 prefecture-level cities in China from 2003 to 2019, based on carbon emission data matched with the locations of thermal power stations and nighttime light data. Firstly, we compare the accuracy of multivariate linear regression and random forest models, finding that the random forest regression yields superior results. Then, we rank the impact of various factors using the random forest method, revealing that population, economic development, and industrialization are the top three influencing factors. The interaction between population and economic development explains 68.5% of carbon emissions, with regional variations in the ranking of influencing factors. The main policy implications of this study are as follows: firstly, there is no need to overly concern about the impact of population growth on carbon emissions, and policies regarding fertility can be adjusted flexibly; secondly, controlling urbanization to a certain extent is conducive to achieving efficient low-carbon cities; thirdly, during the process of industrialization, carbon emissions inevitably increase, and it is advisable to accelerate industrialization to reach a turning point as soon as possible.

Inequality characteristics and influencing factors of CO2 emissions per capita in Jiangsu Province, China.

Analyzing the inequality characteristics and influencing factors of CO2 emissions per capita (CEPC) is conducive to balancing regional development and CO2 emissions reduction. This study applied the Gini coefficient and Theil index to investigate the CEPC inequalities during 2005-2017 at the county level in Jiangsu Province, China. Considering the spatial spillover and interaction effects, the factors influencing CEPC were analyzed by a hierarchical spatial autoregressive model. The results showed that the inequalities in CEPC first increased and then decreased at the inter-regional, and inter-county levels. The spatial pattern of CEPC was stable, and there was a significantly positive spatial autocorrelation of CEPC at the county level. The High-High type counties were mainly located in Sunan (southern Jiangsu). The spatial interaction effects of the CEPC between the prefecture and county levels indicated that governments at the prefecture level should integrate their county governments to reduce the CEPC. Moreover, carbon intensity, GDP per capita, land urbanization, and industrial structure play an important role in reducing CEPC. Our findings provide a scientific basis for formulating reasonable and effective carbon emission reduction policies.

Combining the role of urbanization and renewable energy in sustainable development: testing the EKC hypothesis for Africa.

The pressing necessity to curb greenhouse gas emissions due to climate change has sparked significant scientific interest in comprehending the factors behind CO2 emissions, particularly concerning environmental sustainability challenges. Nonetheless, there exists a notable gap in our understanding of how the process of urbanization interacts with the utilization of renewable energy to impact CO2 emissions. This research endeavor seeks to evaluate the complex interplay among urbanization, renewable energy, and CO2 emissions across 46 African nations spanning from 1990 to 2019. To accomplish this objective, a variety of econometric methodologies are employed, including Driscoll-Kraay standard errors, IV-GMM, and method of moments quantile regression (MMQR) panel estimations to address issues like cross-sectional dependencies, endogeneity, heterogeneity, and panel Granger causality examination. The empirical results suggest that urbanization leads to an increase in CO2 emissions, whereas the consumption of renewable energy plays a role in enhancing environmental quality by reducing CO2 emissions. A significant outcome of the study is the revelation that a combination of urbanization and renewable energy leads to a decrease in carbon emissions. Moreover, the Environmental Kuznets Curve (EKC) hypothesis is validated. Lastly, through the Dumitrescu-Hurlin panel causality test, it is uncovered that urbanization and renewable energy consumption exhibit a bidirectional relationship with CO2 emissions. To reduce dependence on fossil fuels and curb CO2 emissions, policymakers should promote renewable energy usage in urban areas.

The impact of urbanization and economic growth on carbon dioxide emission in sub-Saharan African countries: a perspective from the spatial-temporal approach.

Sub-Saharan Africa (SSA) is seeing exceptional urbanization and economic expansion rates. Therefore, the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) parameters and the spatial econometric framework are used in this work to examine the influence of economic growth and urbanization on SSA's CO2 emissions. Likewise, to determine the spatial effect and understand how factors influence the spatial dependence of carbon emissions, the study builds a spatial Durbin model (SDM). In line with the findings, the spatial correlation test revealed the spatial correlations across various countries. This indicates that the changes in sub-Saharan African country's CO2 emissions impacted nearby countries and the countries themselves. Additionally, the findings reveal that, in the SSA's countries, urbanization, economic growth, industrial structure, trade, and population, excluding energy intensity, which failed the significant test, all positively influence CO2 outflows, in line with the spatial econometric model's findings. Thus, energy intensity shares an adverse impact on carbon emissions. As an outcome, energy intensity reduces carbon dioxide emissions in nearby nations and the entire region. Thus, the study recommends that policymakers account for the effects of spatial spillover when establishing low-carbon policies, encouraging a low-carbon lifestyle, promoting environmentally friendly technologies, and improving regional collaboration.

Empirical evidence of emissions discourse related to food, beverage, and tobacco production in leading manufacturing nations.

The proliferation of carbon dioxide (CO2) emissions has resulted in significant environmental challenges worldwide, particularly within industrialized nations. The present paper tries to investigate the role of food, beverages, and tobacco in mitigating CO2 emissions in the top industrial countries. Economic growth and renewable and non-renewable energy consumption are integrated as control variable in the empirical model. The study applied the pooled mean group-autoregressive distributed lag (PMG-ARDL) model proposed by (J Appl Econ, 16:289-326, 2001) and Granger causality test for causalities directions. The empirical outcomes suggest the presence of cross-sectional dependence, and variables are integrated of order one and cointegrated. Long-run estimates revealed the presence of inversed U curve proving the validity of the environmental Kuznets curve. Also, the results show that renewable energy (RE) consumption contribute in reducing emissions, while non-renewable energy (NRE) and food, beverages, and tobacco (FBT) led to increase emissions level in the long run. Granger shows bidirectional long-run relationship between CO2 emissions, non-renewable energy, and economic growth. Moreover, Granger recorded no causality between food, beverages, and tobacco and any other variable. We recommend that firms engaged in the production of food, beverages, and tobacco products are increasingly urged to make investments in clean technologies powered by renewable energy sources for their manufacturing processes. This is considered a necessary step to achieve a significant reduction in CO2 emissions over an extended period.

Renewable energy consumption and CO2 emissions nexus in the USA: the role of technical innovation.

Using the QARDL approach and data from January of 2010 to May of 2022, we explore how renewable energy consumption affects CO2 emissions in the USA. Long-term analysis reveals a negative link between these variables, while only lower quantile levels show short-term statistical significance. Integrating technical innovation (measured by patents) in our QARDL model shows substantial reduction in CO2 emissions, with varying effects over time. Interestingly, only renewable energy consumption, not technical innovation, significantly impacts CO2 emissions at lower quantile levels. These findings emphasize the crucial role of renewable energy in reducing both short-term and long-term CO2 emissions and offer policymakers valuable insights for shaping effective energy strategies to combat emissions and promote sustainability in the USA.

Decomposition of the site-level energy consumption and carbon dioxide emissions of the iron and steel industry.

Identifying the key factors influencing energy consumption and CO2 emissions is necessary for developing effective energy conservation and emission mitigation policies. Previous studies have focused mainly on decomposing changes in energy consumption and CO2 emissions at the national, regional, or sectoral levels, while the perspective of site-level decomposition has been neglected. To narrow this gap in research, a site-level decomposition of energy- and carbon-intensive iron and steel sites is discussed. In this work, the logarithmic mean Divisia index (LMDI) method is used to decompose the changes in the energy consumption and CO2 emissions of iron and steel sites. The results show that the production scale significantly contributes to the increase in both energy consumption and CO2 emissions, with cumulative contributions of 229.63 and 255.36%, respectively. Energy recovery and credit emissions are two key factors decreasing site-level energy consumption and CO2 emissions, with cumulative contributions to the changes in energy consumption and CO2 emissions of -158.30 and -160.45%, respectively. A decrease in energy, flux, and carbon-containing material consumption per ton of steel promotes direct emission reduction, and purchased electricity savings greatly contribute to indirect emission reduction. In addition, site products and byproducts promote an increase in credit emissions and ultimately inhibit an increase in the total CO2 emissions of iron and steel sites.

The nexus among CO2 emission, health expenditure and economic development in the OECD countries: New insights from a cross-sectional ARDL model.

To find a way to realize sustainable development, this paper applied a cross-sectional ARDL (CS-ARDL) method to explore the interaction between carbon emissions, economic development, and health care expenditure for OECD countries. Firstly, we conduct a cross-sectional test to check whether the data is confronted with this issue. Secondly, we conduct a panel unit root test and cointegration test to confirm whether the ARDL-based method is suitable for our data. Thirdly, we analyze the results and provide possible explanations. Lastly, we conduct a short-term causality test to detect the connection between different variables. The main conclusion of our study includes: 1) Health care is a necessity in OECD countries. 2) Environmental deterioration places a heavy burden on health care expenditure in OECD countries. 3) Health care expenditure of last year negatively affects health care expenditure. 4) There is a short-run causality relationship from CO2, economic development, and dependency rate of youth to health care expenditure in OECD countries. Related policy proposals are provided according to our analysis of the results.

Energy, technology, and economic growth in Saudi Arabia: An ARDL and VECM analysis approach.

This paper investigates the effects in short and long run of renewable and non-renewable energy, technological advancement, population, foreign direct investment, energy export, energy price, and carbon dioxide emissions on economic growth in Saudi Arabia as one of the largest oil producing and richest countries in the world and as a leading country in investing in modern technology, during 1990-2022 by using the Autoregressive Distributed Lag(ARDL) approach and the Vector Error Correction Model (VECM) Granger causality technique. In first step, the ADF and DF-GSL tests are used to identify the order of integration of variables. In the second step, the Bounds test and the Wald test are used respectively to verify the existence of long run cointegration relationships and the long run relationships between variables. In the third step, we have applied the ARDL approach to capture the effect of each variable on Saudi economic growth in long term. Finally, the VECM technique was used to detect the direction of causality running from variable to another. It is appearing that all variables are stationary in first difference, and there are a long run cointegration and relationships among variables. The results of ARDL estimation show that non-renewable energy, renewable energy, population, foreign direct investment, energy export, and energy price positively affect the Saudi economic growth. While technological advancement and carbon dioxide emissions have negative effects on the economic increase of Saudi Arabia. These two results appear important and useful because of their consequences. In effect, it could damage its worldwide standing and dishearten foreign investment, stopping economic diversification efforts and increasing the income inequality. Though, the results of VECM technique show four bidirectional causal relationships between economic growth and non-renewable energy, foreign direct investment, energy export, and energy price. The findings of this study have several policy implications for Saudi Arabia. First, Saudi government should continue investing in the energy sector. Second, to attract more FDI, Saudi government should continue its efforts to reduce bureaucracy, simplify regulations, and provide a business-friendly environment. This strategy can help transfer technology and knowledge. Third, the government should monitor and control energy prices, as these can significantly impact economic growth. The government should invest in technological advancement, as this can help reduce carbon dioxide emissions and improve energy efficiency; also, investing in human capital is essential for long-term economic growth. Policies that promote the health, education, and general well-being of the population can lead to a more productive and innovative workforce. However, the article reveals that technological advancements have a negative impact on economic growth in Saudi Arabia. This could be due to a number of factors, such as a lack of skilled workers to implement new technologies or a mismatch between the skills of the workforce and the needs of the economy. As solutions, Saudi government must invest in education and training can help address these challenges by developing a workforce capable of adapting to the changing needs of the economy and effectively using new technologies. Also, it's important to create science and technology parks to foster innovation and collaboration between businesses and universities. By taking these steps, the Saudi government can help create more diverse and knowledge-based economy, making it less dependent on oil and gas exports and more resilient to economic shocks.

Does FDI mitigate CO2 emissions intensity? Not when institutional quality is weak.

Foreign direct investment benefits developing countries. However, concerns have arisen that the influx of FDI potentially exacerbates environmental pollution. While this debate continues, growing attention has recently emerged on the role of institutions in mitigating FDI's potential damages, although the empirical findings remain inconclusive. This paper examines how institutional quality shapes the relationship between FDI and CO2, both at the aggregate level and across different income groupings, using a reduced-form CO2 emissions model, panel data from 2000 to 2018 and the IVGMM techniques. Three key conclusions emerge. First, the findings show that FDI reduces CO2 emissions, but its magnitude depends on the measure used. Second, institutional quality is directly associated with higher emissions across income groups, suggesting current regulations inadequately ameliorate environmental pollution. Third, we find a positive interaction effect between CO2 emissions and institutional quality. We argue that, for FDI to consistently curb CO2 emissions, the quality of institutions must improve to better regulate foreign investors' activities, especially in low and high-income nations. Enhancing the quality of institutions will help translate FDI into improved environmental outcomes across income groups.

Comparative life cycle assessment of light frame timber and reinforced concrete masonry structural systems for single-family houses in Luxembourg.

The building sector's significant greenhouse gas emissions and energy consumption present added challenges to meeting European climate commitments amidst rapid population growth. In Luxembourg, single-family houses dominate the residential buildings, noticeably contributing to construction waste and CO2 emissions. This study compares the environmental impacts of a three-story reinforced concrete masonry single-family house and an identical timber building in Luxembourg, emphasizing greenhouse gas emissions and embodied energy. A cradle-to-grave life cycle assessment was conducted using Building Information Modelling (BIM) models to analyze the global warming potential and primary energy requirements. Environmental product declarations from the producers and the ÖKOBAUDAT German database were used to determine the environmental impacts of the materials. The results show that the timber building outperforms the concrete building with a 43.5% lower global warming potential, while the concrete building demonstrates a 15.6% reduction in primary energy demand. This aligns with the average outcomes of seven similar studies discussed in this paper, at 33.2% and 4.7%, respectively. Moreover, the timber building is 78.6% lighter than the concrete one. When evaluating benefits and loads beyond the system boundary, the timber building provides 3.6 and 4 times greater advantages in terms of global warming potential and primary energy, respectively, compared to the reinforced concrete masonry building. Additionally, the study explores the impact of reusing the floors in the timber building. The cradle-to-grave LCA reveals that reusing the timber slabs improves the building's global warming potential and primary energy by 2.4% and 1.2%, respectively. However, when considering the benefits and loads beyond the system boundary, floor system reuse exhibits a 38.9% surge in global warming advantages while reducing primary energy benefits by 28.1%. The findings advocate for a policy promoting timber construction and reuse in Luxembourg, aiming to achieve the net-zero emission target by 2050.

Exploring asymmetric influence of R&D expenditures on CO2 emissions in China: evidence from nonlinear ARDL model.

R&D spending upsurges technological advancement and innovation which results in lowering energy consumption and environmental degradation. The current study investigates the asymmetrical impact of R&D spending on CO2 emissions in China via employing annual data from 1980 to 2021 and the NARDL model for empirical analysis. The estimated results of the NARDL model confirmed that there are asymmetries in positive and negative coefficients of R&D spending in China. The results depict that the positive shock in R&D spending exerts a negative and statistically significant impact on CO2 emissions in both runs implying that an increase in R&D spending lowers CO2 emissions. However, the negative coefficient of R&D spending yields a positive and statistically significant impact on CO2 emissions revealing the fact that a negative shock in R&D spending results in the upsurge of CO2 emissions in China. According to these findings, the impact of positive and negative shocks in R&D spending on CO2 emissions is asymmetric. The findings also show that the impact of a negative shock in R&D spending is greater than the impact of a positive shock on CO2 emissions. In addition to the negative shock in R&D spending, increases in energy consumption, economic growth, and FDI inflows also contribute to an upsurge in CO2 emissions in China. The robustness of the estimated results is assessed using standard fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models. The FMOLS and DOLS results have been confirmed to be sound and consistent with the results of the NARDL model. The study suggests that the economic strategies should aim at investing in R&D spending to foster environment-friendly technological innovations and to lower environmental degradation in China.