Income inequality, ecological footprint, and carbon dioxide emissions in Asian developing economies: what effects what and how?

Pollution halo impact in context of productive capacities, energy poverty, urbanization, and institutional quality

The Belt and Road Initiative (BRI) represents a substantial development strategy spearheaded by China. Its central aim is to foster connectivity across a vast geographical area that includes countries spanning Asia, Europe, and Africa. This project played a pivotal role to develop the region on the one side and also raised serious environmental concerns on the other side. There is extensive literature explored the various dimensions affecting the environment in BRI partner countries but there is hardly any study examining the impact of productive capacities, energy poverty, FDI, urbanization, and institutional quality on CO2 emission in the BRI region. Moreover, pollution halo impact is also explored so this study used panel data of 52 nations engaged in the BRI covering time span of 2001-2022 by applying OLS, Difference GMM, System GMM, Cross sectional-ARDL techniques. The results suggest that enhancing productive capacities, FDI and institutional quality significantly reduces carbon emissions in the region, while energy poverty, urbanization and economic growth is linked to higher carbon emissions. Moreover, 'pollution halo effect' is proved because of adoption of eco-friendly technologies through foreign corporations lead to reduction in carbon emission. The study advocates for policy measures that emphasize the promotion of productive capacities, the utilization of renewable energy sources, the adoption of practices regarding sustainable urban development, the implementation of efficient institutional structure, and inflow of eco-friendly technology through FDI.

Urbanization, rural energy-poverty, and carbon emission: unveiling the pollution halo effect in 48 BRI countries

The Belt and Road Initiative (BRI) is a significant economic development strategy directed by China. Its primary objective is to establish connectivity across a vast region encompassing over 70 countries in Asia, Europe, and Africa. This endeavor significantly impacts worldwide development, economic advancement, and environmental sustainability. Nevertheless, insufficient pertinent evidence exists when exploring the correlation between urbanization, rural energy poverty (Rural_EP), and carbon emissions (CO2_Em) in the BRI region. The present study examines panel data encompassing 48 countries participating in BRI from 2001 to 2020. This research addresses existing gaps by employing the System-GMM and Driscoll and Kraay Standard Error (DKSE) models to investigate factors influencing CO2_Em. The findings indicate that the presence of energy poverty in rural areas is associated with higher levels of CO2_Em, while urbanization has a mitigating effect on such emissions. Furthermore, adopting production methods and environmentally sustainable technologies by foreign corporations leads to a decrease in CO2_Em, thereby providing evidence of a pollution halo effect in BRI. Moreover, economic growth and industrialization have detrimental environmental consequences, primarily through the amplification of CO2_Em. Based on the empirical evidence, the study proposes policy measures that advocate for promoting renewable energy sources, adopting sustainable urban development practices, implementing energy conservation strategies, and establishing carbon pricing mechanisms.

How Do R&D and Renewable Energy Consumption Lead to Carbon Neutrality? Evidence from G-7 Economies

The discussion about whether research and development and advanced energy structure can efficiently control pollution has gained the consideration of researchers across the globe. However, there is a lack of enough empirical and theoretical evidence to support this phenomenon. To offer support of empirical evidence along with theoretical mechanism, we examine the net Impact of research and development (R&D) and renewable energy consumption (RENG) on CO2E utilizing panel data from G-7 economies for 1990-2020. Moreover, this study investigates the controlling role of economic growth and nonrenewable energy consumption (NRENG) in the R&D-CO2E models. The results obtained from the CS-ARDL panel approach verified a long-run and short-run relationship between R&D, RENG, economic growth, NRENG, and CO2E. Short- and long-run empirical results suggest that R&D and RENG improve environmental stability by decreasing CO2E, while economic growth and NRENG increase CO2E. Particularly, long-run R&D and RENG reduce CO2E with the effect of -0.091 and -0.101, respectively, while in the short run, they reduce CO2E with the effect of -0.084 and -0.094, respectively. Likewise, the 0.650% (long run) and 0.700% (short-run) increase in CO2E is due to economic growth, while the 0.138% (long run) and 0.136% (short run) upsurge in CO2E is due to an increase in NRENG. The findings obtained from the CS-ARDL model were also verified by the AMG model, while D-H non-causality approach was applied to check the pair-wise relationship among variables. The D-H causal relationship revealed that policies to focus on R&D, economic growth, and NRENG explain variation in CO2E but not vice versa. Furthermore, policies considering RENG and human capital can also affect CO2E and vice versa, meaning there is a round effect between the variables. All this indication may guide the concerned authorities to devise comprehensive policies that are helpful to environmental stability and in line with CO2E reduction.

Health, Education, and Economic Well-Being in China: How Do Human Capital and Social Interaction Influence Economic Returns

In developing countries, it is generally believed that a good health status and education (human capital) bring economic well-being and benefits. Some researchers have found that there are overall financial returns and income premiums correlated with human capital because of its excellent and higher ability. Due to different views and a lack of consensus, the role of human capital is still ambiguous and poorly understood. This study investigates the economic returns of health status, education level, and social interaction, that is, whether and how human capital and social interaction affect employment and income premiums. Using the Chinese General Social Survey (CGSS) for specification bias, we used the instrumental variable (IV) approach to specify the endogeneity and interaction effect in order to identify the impact and economic returns of human capital and social interaction on the values of other control and observed variables. However, we show that an individual with strong and higher human capital positively affects economic returns, but the variability of these estimates differs across estimators. Being more socially interactive is regarded as a type of social interaction but as not human capital in the labor market; thus, the empirical findings of this study reflect social stability and that the economic well-being of socially active individuals is an advantaged situation. Furthermore, men with substantial human capital and social interaction are in a more advantaged position compared to women with similar abilities.

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

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

The effect of political stability, carbon dioxide emission and economic growth on income inequality: evidence from developing, high income and Belt Road initiative countries

The reduction of income inequality and environmental frailty are important factors which can help achieve sustainable development. In this context, it is important to investigate the nexus between income inequality and carbon dioxide emission by considering the role of political stability. This paper examines the effect of political stability, economic growth, financial development, and carbon dioxide on income inequality in developing countries, high-income countries, and the Belt Road initiative (BRI) countries from 2002 to 2019. By employing a two-step generalized method of moments and panel quantile regression, the findings show that carbon dioxide emission, financial development, and political stability rise income inequality while economic growth significantly reduces income inequality in developing countries. In the case of high-income countries, political stability and carbon dioxide negatively affect income inequality while financial development rise income inequality. In the case of BRI countries, political stability, economic growth, and carbon dioxide emission significantly reduce income inequality. Our findings have considerable policy implications regarding reducing income inequality in the sample countries.

Time-varying causality between income inequality and ecological footprint in Turkey

This paper investigates the relationship between income inequality and environmental degradation for the case of Turkey between 1987 and 2017 through the bootstrap causality method that changes over time. The study used the GINI coefficient to denote income inequality and ecological footprint (EFP) to represent environmental degradation. According to the analysis results, a causal relationship has been determined for Turkey from GINI to EFP between 2002 and 2015 and from EFP to GINI between 2002 and 2008. Thanks to the method used in the analysis, it was concluded that GINI-affected EFP positively between 2002 and 2005 and negatively between 2006 and 2015. Between 2002 and 2005, Turkey endured a difficult period of restructuring after two major banking crises in 1999 and 2001. The rapid development, especially in industry and urbanization, caused environmental degradation in this period. Between 2006 and 2015, the central dynamic of Turkey's growth trend was the finance sector, and rapid privatizations were realized. Nevertheless, the income justice improvement in this period negatively impacted the environment due to consumption and production habits. Policymakers should evaluate Turkey in its economic reality and produce policies accordingly. Environmental awareness should be increased in the production and consumption activities of all segments of society, benefiting from the developments in income distribution. The ecological impact of the income redistribution policy, along with its market and social consequences, needs to be evaluated.

An empirical study on correlation among poverty, inclusive finance, and CO2 emissions in China

This paper explores the nonlinear relationship between poverty and CO₂ emissions based on the panel data of 30 provinces in China from 2005 to 2019. In this study, the autoregressive distributed lag (ARDL) model is first used. Findings confirm that poverty has a negative impact on CO₂ emissions in the short run and a positive impact in the long run, while both effects of inclusive finance on CO₂ emissions are negative. In order to explore the reasons for the change in the coefficient of poverty, we introduce a moderating effect (ME) model and a dynamic panel threshold (DPT) model. The result shows that the negative effect of poverty on CO₂ emissions diminishes with the moderation of inclusive finance. When inclusive finance crosses the threshold value (IFI = 0.2696), the impact of poverty on CO₂ emissions will change from negative to positive gradually, which verifies the applicability of the "Poverty-CO₂ Paradox" in China and provides an empirical basis for breaking the "Poverty-CO₂ Paradox." Consequently, deepening poverty reduction and pushing the region's inclusive finance to the threshold level are proposed as effective ways to promote CO₂ emission reduction.

Digital Economy and Environmental Sustainability: Do Information Communication and Technology (ICT) and Economic Complexity Matter?

In the current era of digital economy, the role of information communication and technology (ICT) and economic complexity are important for controlling environmental unsustainability and formulating policies to deal with ecological concerns. However, the relationship between digital economy and environment has been studied widely; nevertheless, the relationship between ICT-based digital economy, economic complexity, and ecological footprint has not been studied extensively. Therefore, the aim of current study is to fill the existing gap by investigating the relationship between ICT, economic complexity, and ecological footprint in the case of G-seven (digital) economies. Furthermore, the past research studies were usually based on carbon emissions to measure environmental sustainability, while this study fills the gap using ecological footprint as a proxy for environmental degradation. By using the panel data over the period of 2001-2018 for G-seven economies, this study performs first-generation as well as second-generation unit root testing methods. Findings of both Pesaran's and B&P's cross-sectional dependence testing approaches confirm the presence of cross-sectional dependence across all G-seven economies. The empirical findings of cointegration (Pedroni and Kao) tests verify a stable long-run association between ecological footprint, ICT import, ICT export, economic complexity, economic growth, and other control grouped variables. The empirical evidence obtained from the fully modified OLS model suggests that ICT export, economic complexity, and economic growth enhance the intensity of ecological footprint, while ICT import, research and development (RD), and trade are helpful in reducing ecological footprint in G-seven economies. These empirical findings obtained are verified by pooled mean group-ARDL (PMG-ARDL) methodologies and confirm that there is no inconsistency in the results. On the basis of these results, some policy implications for ecological footprint, ICT, and economic complexity are discussed.

How does economic complexity affect ecological footprint in G-7 economies: the role of renewable and non-renewable energy consumptions and testing EKC hypothesis

The discussion concerning whether and how economic complexity (ECI) affects ecological footprint (EFP) has gained researchers' consideration, while there are slight empirical evidence to support the subject matter. In the support of theoretical argument, this study provides empirical evidence by investigating the impact of ECI on EFP along with the role of disaggregated energy consumptions by using a panel dataset of G-7 economies between 1996 and 2019. To this end, we applied panel techniques of Fully-Modify OLS and Dynamic-OLS models for cointegration analysis. The results obtained from Fully-Modify OLS and Dynamic-OLS models reveal that ECI deteriorates environmental quality by increasing EFP, while renewable energy reduces ecological pollution by decreasing EFP. In addition, the increasing demand for non-renewable energy and economic growth both degrades environmental quality in G-7 countries. More interestingly, the non-linear (ECI²) relationship between ECI and EFP confirms a U-shaped association (EKC hypothesis), which suggests that after achieving a certain threshold level, economic complexity mitigates environmental degradation in G-7 economies. The empirical results also suggest that other control variables such as population growth, inflation rate, foreign direct investment, and total trade intensity lead to environmental degradation by increasing ecological footprint. Based on empirical results, the following important policy implications are drawn; first, G-7 economies should speed up the level of economic complexity along with renewable energy consumption to protect environmental quality and maintain sustainable growth and development. Secondly, the governments of G-7 countries should introduce greener technologies and promote production that are environmental friendly for drastic reduction in environmental unsustainability.