Moderating role of institutional quality in validation of pollution haven hypothesis in BRICS: a new evidence by using DCCE approach

The impact of environmental regulations on the upgrading of the industrial structure: Evidence from China

China's economy has transitioned into a phase of high-quality development, with enhancing its industrial structure becoming a critical objective. We gathered panel data from 30 major provinces in China from 2010 to 2020 and employed the fixed effects model to assess the actual influence of environmental regulations on industrial structure upgrading. Our empirical findings show that the impacts of various environmental regulations on industrial structure upgrading in China are significantly different. Mandatory environmental regulation demonstrates an inverted U-shaped nonlinear correlation with the upgrading level of the entire industrial structure. When the intensity of this regulation is low, it significantly accelerates industrial structure upgrading. As the intensity of this regulation rises, its effect on industrial structure upgrading is inhibitory. In contrast, induced environmental regulation exhibits a nonlinear U-shaped relationship with industrial structure upgrading and shows a nonlinear change trend of first decreasing and then rising. When the intensity of induced environmental regulation reaches a certain critical point and continues to increase, it will change from a negative influence on the upgrading of the industrial structure to a promoting effect. The further discussion of threshold regression and the robustness test also led to similar conclusions. The above research is conducive to the Chinese government's rational use of environmental regulation tools to promote industrial structure upgrading. It is also beneficial to developing countries, allowing them to learn from China's experience to improve the effectiveness of environmental regulation and boost their industrial development.

Exploring the impact of social capital, institutional quality and political stability on environmental sustainability: New insights from NARDL-PMG

The social aspect of sustainable development is often considered the least strong component, particularly in terms of its analytical and theoretical foundations. Although there has been a recent increase in focus on social sustainability, the relationship between the environmental aspect and social capital is still not well understood. This research seeks to explore initial concepts on frameworks for analyzing the interface between environmental and social capital. However, to demonstrated the core connection of social capital, institutional quality, income and renewable energy consumption with sustainability level (CO2 emissions) in the BRICS economies from 1996 to 2021. Specifically, this study uses advanced techniques such as Non-ARDL, Pooled Mean Group, the Augmented Mean Group and Common Correlated Effect Mean Group. However, under the linear outcomes, social capital, law & order, government stability, political stability and income decline the emissions levels. However, renewable energy consumption shows the positive association with rising emissions in BRICS countries. Interestingly, under the non-linear form, study outcomes describe social capital, and law & order contribute to environmental quality, while government & political stability spur the level of emissions in the long-run. Also, this study provides some core implications to meet the desired sustainability level.

BRICS and the climate challenge: navigating the role of factor productivity and institutional quality in CO2 emissions

The BRICS countries are important contributors to global efforts aimed at preventing a climate catastrophe. These countries account for half of the total emissions generated by the G20 nations. In this context, this paper examines the relationship between total factor productivity (TFP) and CO2 emissions (CE) in BRICS countries from 1996 to 2022, with institutional quality serving as a moderating factor. Moreover, a diverse range of methodologies was employed to address the problem of cross-sectional dependence; i.e., the CS-ARDL technique is used to analyze the relationship between variables in both the long and short-run. The AMG and CCEMG methods are employed for robustness analysis, while the Dumitrescu-Hurlin causality test is used to assess causality. Our empirical analysis demonstrates that TFP is positively associated with CE. Conversely, we find that institutional quality has a negative impact on CE. Furthermore, the study confirms that the interaction between TFP and institutional quality has a negative effect on CE. This implies that an improvement in institutional quality leads to a decrease in CE, as it strengthens the regulatory system governing CE and reduces pollution. Environmental policy must include economic flexibility and policy unpredictability in order to meet CO2 reduction targets. In addition, the study has identified bidirectional causal links between CE and variables such as TFP, institutional quality, and other control variables. According to our study, the BRICS countries should encourage digitalization and renewable energy production while preserving a reasonable standard of institutional quality since they have significant resource advantages in the renewable energy sector.

Environmental impact of foreign direct investment in Turkey: does the quality of institutions matter? Evidence from time series analysis using the Fourier extension

Since the 1980s, Turkey has experienced a significant increase in both foreign direct investment (FDI) and its ecological footprint (EFP). While FDI is widely acknowledged as a pivotal driver of economic growth, its impact on environmental degradation is multifaceted and debated. Moreover, a country's institutional framework plays a key role in shaping this relationship. Yet, the influence of institutional structures on the FDI-environment nexus is often neglected in current literature. In this study, we investigate the environmental implications of FDI in Turkey from 1984 to 2018, employing time series analysis with a Fourier extension and accounting for institutional quality. Fourier function models give more effective results in modeling structural breaks. We first use Fourier techniques to assess the unit root and cointegration relationship. Upon establishing cointegration, we employ the DOLS estimator, extended with Fourier terms, to determine the long-term coefficients. We then assess the causal relationship between the variables using the Fourier causality test. Our findings indicate that while FDI exacerbates environmental degradation (supporting the pollution haven hypothesis), the interaction term of FDI-institutional quality mitigates this degradation (supporting the pollution halo hypothesis). Given these empirical findings, this study suggests that strengthening Turkey's institutional quality has the potential to amplify the environmental advantages of FDI, alongside its economic benefits.

Impact of technological innovation and renewable energy on ecological footprint in G20 countries: The moderating role of institutional quality

The connection between ecological footprint and economic complexity has significant implications for environmental sustainability regarding the policy. Additionally, institutional quality is crucial in ensuring environmental sustainability and moderating the link between economic complexity and ecological footprint. The task of achieving sustainable environmental development and preventing further degradation of the environment poses a formidable challenge to policymakers. This study delves into the significance of technology innovation and renewable energy in creating a more sustainable environment. Recognizing the need for a more critical review, this research establishes the dynamic linkage between ecological footprint, renewable energy consumption, and technological innovation, especially in conjunction with a moderating component, particularly institutional quality, in G20 countries from 1990 to 2021. We employ advanced panel approaches to address panel data analysis concerns, such as cross-sectional dependence, slope heterogeneity, unit root, cointegration test and CS-ARDL. The long-term estimator indicates that renewable energy and technological innovation negatively but significantly impact the ecological footprint. Whilst economic growth, FDI, and urbanization have shown a positive and significant impact on ecological footprint; institutional quality negatively moderates the relationship between ecological footprint, renewable energy, and technological innovation in the G20 countries. Further evidence from the Dumitrescu-Hurlin Granger causality test shows that efforts to expand access to renewable energy, technological advancements, and economic growth will significantly affect environmental impacts. Based on our results, it is imperative to introduce more favorable legislation and encourage technological advancements in the field of renewable energy if we want to achieve our sustainable development objectives.

Sectoral foreign direct investment and environmental degradation: new insights from diversification of energy mix containing fossil fuels and renewable energy

The objective of the study is to extend the existing literature by investigating the effects of foreign direct investment, gross domestic products and per capita and energy diversification on the nitrogen oxide emissions in Brazil, Russia, India, China and South Africa (BRICS) by using annual data during the period 1992-2019. As per our knowledge, the present study is a first of its kind to examine the impact of a new energy diversification index, based on Herfindahl-Hirschman framework on pollution. This study has adopted a new quantile regression augmented method of moments, which is capable of producing the total impacts of the independent variables across the entire distribution of nitrogen oxides emissions. The findings suggest that an increase in foreign direct investment leads to a decrease in nitrogen oxides emissions at the aggregate level and in both manufacturing and service sectors. We observe that foreign direct investment leads to an increase in nitrogen oxides emissions in the agricultural sector in most of the quantiles. Diversification towards renewable energy causes a decrease in nitrogen oxides emissions in most quantiles at aggregate level, agricultural and manufacturing sectors, whilst diversification leads to an increase in nitrogen oxides emissions in the service sector. The findings also suggest that GDP per capita leads to an increase in NOx emissions in all the quantiles. The study suggests the policy to use and attract more clean energy through foreign direct investment for towards the achievement of sustainable development.

Revisiting the environmental Kuznetz curve and pollution haven hypothesis in N-11 economies: Fresh evidence from panel quantile regression

Human activities in recent decades have severely affected environmental quality, and CO₂ emissions have irreparable consequences on human health and the survival of the earth. Moreover, achieving sustainable development goals requires the expansion of environmental literature to accelerate the performing of critical actions. With this in mind, this study evaluates the impact of foreign direct investment, economic complexity, and the utilization of renewable energy on CO₂ emission in N-11 countries from 1995 to 2019 by Panel Quantile Regression. As a novelty, the interaction between economic complexity and foreign direct investment is considered to get a better comprehension. Given the results, Environmental Kuznetz Curve is validated in N-11 countries through economic complexity. Notably, the impact of economic complexity is more substantial and robust in the incipient stages of industrialization. Furthermore, foreign direct investment is a destructive factor for environmental quality, and Pollution Haven Hypothesis is not rejected. Interestingly, the interaction of economic complexity and foreign direct investment mitigates the trend of CO₂ emissions. Eventually, the utilization of renewable energy reduces CO₂ emissions. Thereby, applying more strict environmental regulations and standards, developing green energy infrastructure and technologies, improving institutional quality, and supporting knowledge-based and technology-intensive exports are the main policy recommendations of this study.

Do trade openness and institutional quality contribute to carbon emission reduction? Evidence from BRICS countries

The quest for rapid economic development by modern nations has led to an unprecedented increase in carbon emissions. Knowledge spillovers from increasing trade activities and effective environmental regulations have been suggested as viable means of controlling these rising emissions. To that end, this study aims to examine the impact 'trade openness' and 'institutional quality' had on CO2 emissions in BRICS countries from 1991 to 2019. Three indices, namely, institutional quality, political stability, and political efficiency, are constructed to measure the overall institutional impact on emissions. A single indicator analysis is conducted for a deeper investigation of each index component. Given the existence of cross-sectional dependence among variables, the study uses the modern dynamic common correlated effects (DCCE) method to estimate their long-run relationships. Confirming the pollution haven hypothesis, the findings reveal that 'trade openness' indeed is a cause of environmental degradation in the BRICS nations. Through reduced corruption, improved political stability, bureaucratic accountability, and better law and order, 'institutional quality' is found to be contributing positively to environmental sustainability. It is also confirmed that renewable energy sources do have a positive environmental impact; however, it is found to be insufficient to offset the adverse effects caused by non-renewable sources. Based on the results, it is advised that BRICS countries should strengthen their cooperation with developed countries so that positive spillovers of green technologies may occur. Moreover, renewable resources should be aligned with firms' profits so that sustainable production practices can become the new norm.

Can fiscal decentralization be the route to the race to zero emissions in South Africa? Fresh policy insights from novel dynamic autoregressive distributed lag simulations approach

There has been a plethora of debate on the link between fiscal decentralization and a drop in carbon dioxide (CO2) emissions, even though the evidence supporting this assertion is relatively sparse. Although the precise nature of this relationship is still up for discussion, economic hypothesis postulates that fiscal decentralization has an impact on environmental sustainability. Some researchers claim that fiscal decentralization could potentially result in a race to the top, while some believe it would lead to a race to the bottom. This analysis intends to shed light on the precise processes by which this connection may work in South Africa between 1960 and 2020 in light of current discussions in environmental and development economics. In contrary to previous studies, this paper employs a cutting-edge dynamic autoregressive distributed lag simulations methodology to evaluate the positive and negative variations in fiscal decentralization on CO2 emissions. Our findings demonstrate the prevalence of the race to the top strategy by illustrating how fiscal decentralization has a bearing on CO2 emissions reduction in the short and long terms. In accordance with the findings, greater fiscal decentralization should be implemented through the transfer of more powers to regional authorities, especially in the realm of environmental legislation considerations, in a bid to preserve South Africa's environmental integrity. By establishing a lower tier of government and defining roles at the federal and provincial divisions, South Africa could adopt strategies to improve green environment in an effort to fulfill the energy-saving tasks of fiscal expenditures.

Revisiting the nexus between fiscal decentralization and CO2 emissions in South Africa: fresh policy insights

The argument over fiscal decentralization and carbon dioxide emission (CO₂) reduction has received much attention. However, evidence to back this claim is limited. Economic theory predicts that fiscal decentralization affects environmental quality, but the specifics of this relationship are still up for debate. Some scholars noted that fiscal decentralization might lead to a race to the top, whereas others contended that it would result in a race to the bottom. In light of the current debates in environmental and development economics, this study aims to provide insight into how this relationship may function in South Africa from 1960 to 2020. In contrast to the existing research, the present study uses a novel dynamic autoregressive distributed lag simulation approach to assess the positive and negative changes in fiscal decentralization, scale effect, technique effect, technological innovation, foreign direct investment, energy consumption, industrial growth, and trade openness on CO₂ emissions. The following are the main findings: (i) Fiscal decentralization had a CO₂ emission reduction impact in the short and long run, highlighting the presence of the race to the top approach. (ii) Economic growth (as represented by the scale effect) eroded ecological integrity. However, its square (as expressed by technique effect) aided in strengthening ecological protection, validating the environmental Kuznets curve hypothesis. (iii) CO₂ emissions were driven by energy utilization, trade openness, industrial value-added, and foreign direct investment, whereas technological innovation boosted ecological integrity. Findings suggest that further fiscal decentralization should be undertaken through further devolution of power to local entities, particularly regarding environmental policy issues, to maintain South Africa's ecological sustainability. South Africa should also establish policies to improve environmental sustainability by strengthening a lower layer of government and clarifying responsibilities at the national and local levels to fulfill the energy-saving functions of fiscal expenditures.

How do foreign direct investment flows affect carbon emissions in BRICS countries? Revisiting the pollution haven hypothesis using bilateral FDI flows from OECD to BRICS countries

Foreign direct investment (FDI) flows from developed to developing countries may increase carbon emissions in developing countries as developing countries are seen as pollution havens due to their lenient environmental regulations. On the other hand, FDI flows from the developed world may improve management practices and advanced technologies in developing countries, and an increase in FDI flows reduces carbon emissions. Most of the existing studies examine the relationship between FDI flows and carbon emissions by using aggregate FDI flows; however, this paper contributes to the literature by analyzing the impact of FDI flows on carbon emissions in Brazil, Russia, India, China, and South Africa (BRICS) between 1993 and 2012 using bilateral FDI flows from eleven OECD countries. According to our empirical results, from which OECD country FDI flows to BRICS countries matters for carbon emissions in BRICS countries. Our results confirm that FDI flows to BRICS countries from Denmark and the UK increase carbon emissions in BRICS countries, confirming the pollution haven hypothesis. On the other hand, FDI that flows from France, Germany, and Italy reduced carbon emissions in the BRICS countries, confirming the pollution halo effect. FDI flows from Austria, Finland, Japan, Netherlands, Portugal, and Switzerland have no significant impact on carbon emissions in BRICS countries. The BRICS countries should promote clean FDI flows by reducing environmental damages, and investing countries should be rated based on their environmental damage in the host countries.

Pollution heaven or pollution halo? Assessing the role of heterogeneous environmental regulation in the impact of foreign direct investment on green economic efficiency

As the main engine of the global economy, China has been attracting increasing foreign direct investment (FDI) since the 1980s. The frequent occurrence of pollution incidents by multinational companies and the continuous deterioration of the environment have prompted China to attach importance to environmental regulations and attempt to avoid the potential pollution heaven effect of FDI on green development. To assess the effectiveness of these environmental regulations, this paper investigates the moderating effect of environmental regulation, in particular, the heterogeneous environmental regulatory tools, on the relationship between FDI and green economic efficiency. In addition, the spatial performance of these moderating effects is examined through the spatial Durbin model (SDM), using China's provincial panel data from 2004 to 2018. The results show that environmental regulation has an overall positive moderating effect, exacerbating the pollution heaven effect of FDI on green economic efficiency. In the meantime, the moderating effects of heterogeneous environmental regulations are obviously different; i.e., command-and-control and public-participation-based environmental regulations have positive moderating effects, while market-based environmental regulation has a negative moderating effect. In addition, in terms of spatial performance, the market-based environmental regulation has a positive spillover effect, thereby promoting green economic efficiency in surrounding regions, which is contrary to command-and-control and public-participation-based environmental regulations. Based on the above findings, this paper makes some recommendations for policymakers.

The paradigms of transport energy consumption and technological innovation as a panacea for sustainable environment: is there any asymmetric association?

Technological innovations have a great potential to develop the transportation system as more efficient, intelligent, connected, and sustainable. Therefore, transport energy consumption fundamentally transmutes how goods and people are moved with significant effects on transport demand with related energy consumption on a sustainable environment. To this end, our research aimed at investigating the environmental performance (carbon dioxide and ecological footprint) by stochastic impact by regression through a population, affluence, and technology (STIRPAT) model, and econometric approach for estimation of transport energy consumption from 1975 to 2018 for Pakistan. Moreover, our study supports the literature by exploring the association of technological innovations, financial development, carbon damage costs, and economic growth with the environment. The linear relationships of the variables are governed by the autoregressive distributive lag (ARDL) model that interestingly explored that economic growth and energy consumption, and financial development degrade the environment and resource depletion; however, technological innovations are inclined towards cleaner technologies. For asymmetric findings, we employ the non-linear autoregressive distributive lag technique recently introduced by Shin et al. (2014). The findings validate the existence of an asymmetric relationship between transport energy consumption and environmental indicators. The policymakers' prerequisites the alternative energies apart from conventional energies in the transport sector with technological innovations in transport sector energy consumption like the electronic and hybrid vehicles for a cleaner environment.

A novel grey spatial extension relational model and its application to identify the drivers for ambient air quality in Shandong Province, China

The ambient air quality is a complex dynamical system that is shocked by a number of subsystems, such as government policies, industry regulation adjustment and internationalization. To identify the drivers for ambient air quality, a grey spatial extension relational analysis model is proposed. Firstly, a spatial extension method for one-dimensional time series of complex systems is introduced, and the two key parameters are obtained based on the grey similarity and proximity relational analysis models. Secondly, grey relational coefficient is calculated by the difference of the three-dimensional vector, and a grey spatial extension relational analysis model is presented. Furthermore, the properties of the proposed model were investigated. Finally, the model is used to identify the drivers of the ambient air quality in eastern coastal Shandong Province, China. Results suggest that the drivers of the ambient air quality vary among cities, but with some common ones. Therefore, this paper provides an important reference for the improvement of ambient air quality.

Corruption and FDI in Brazil: Contesting the “Sand” or “Grease” Hypotheses

Foreign Direct Investment (FDI) is seen as a significant driver of economic growth and a potential ally in the struggle against poverty and inequality, making emerging countries focus on attracting this type of investment. Thus, understanding factors that impact the concentration of regional FDI is essential to verifying which characteristics encourage or deter foreign investment. Likewise, the literature has explored institutional factors such as corruption as determining factors for the concentration of FDI. Within this framework, this study aims to empirically examine the sensitivity of multinational enterprises (MNEs) to corruption. Few studies have been carried out on this subject, mainly in Latin American economies. We employ a unique Brazilian municipality-level FDI database to investigate whether corruption hinders (i.e., corruption acting as “sand”) or promotes the concentration of foreign investment (i.e., corruption acting like “grease”). Additionally, we believe that analyzing different economic sectors is essential to deepening the knowledge about the impacts of corruption on FDI. Our results show that corruption acts as “grease” for both overall FDI and at the level of individual sectors. Finally, when taking a non-linear approach, our findings show that corruption acts as grease for FDI only in regions with intermediate (medium–low) levels of corruption.

Carbon Emissions and Socioeconomic Drivers of Climate Change: Empirical Evidence from the Logarithmic Mean Divisia Index (LMDI) Base Model for China

The main objective of the present study was to examine the impact of socioeconomic factors on environmental degradation or preservation using the logarithmic mean disivia index (LMDI). The study used the latest data from thirty Chinese provinces from 2012 to 2020. Pooled mean group (PMG) results were estimated to determine the long-term and short-term impact of the aforementioned compound variables on carbon emissions. The study results revealed that population growth, per capita GDP growth, and fossil fuel-led energy consumption, positively impacted environmental degradation in China at the provincial level. However, clean energy intensity and a transition towards renewable energy in China are helping to reduce carbon emissions. Similarly, clean energy intensity is also helping to lower carbon emissions. The study proposed that at the provincial level, joint efforts were required to control environmental degradation in China. The positive impact of renewable energy intensity on carbon emissions encourages the transition from fossil fuels to clean energy sources for environmentally friendly growth.