Financial Globalization, Technological Innovation and Environmental Performance in Developing Countries

China's green growth has shown a trend of fluctuation year by year. Simultaneously, Chinese local governments have pursued simple economic growth driven by the interests of "political competition" for a long time, while the supervision of the ecological environment has been loosened and tightened. In this environment, financial development and technological innovation may easily become the accelerator of this phenomenon, thus exacerbating the fluctuation of green growth. To deeply excavate the key factors to achieve stable and sustained growth of green economy, based on the annual panel data of 30 provinces in China from 2011 to 2018, this paper studies the impact of financial development and technological innovation on the volatility of green growth using dynamic system GMM method. The findings of this paper are shown as follows: First, the expansion of financial institutions' scale will significantly enhance the volatility of green growth. Second, the increase in the scale of the stock market will also significantly cause green growth fluctuations. Third, the interaction between financial development and technological innovation can significantly weaken the volatility of green growth. Fourth, financial development measured by stock market indicators is more efficient than financial development measured by financial institutions indicators to curb the volatility of green growth. Fifth, the fluctuation of green growth in the previous period will reduce the volatility of green growth in the current period. This study provides new evidence for exploring the power source to promote the stability and sustainable growth of the green economy in the special stage of financial and technological integration. Controlling the development scale of financial institutions and removing their state preferences, expanding the development of capital markets, and deepening the integration of financial development and technological innovation are conducive to achieve stable green growth.

Sustainable resource consumption is important for the development of the financial system. Besides, an advanced financial system eases the transfer of revenues from production activities and export to productive investments. The influence of natural resource (NR) abundance on financial development (FD) is still an ongoing debate with conflicting results. However, this study applies a novel proxy for FD, which measures the efficiency, accessibility, and depth of the financial market and institutions. Therefore, the current study is a maiden attempt to explore the nexus between FD and NR abundance amidst globalization, human capital, and economic growth in ASEAN economies. Reliable panel econometric techniques, including second-generation unit root tests, Westerlund (2007) cointegration tests, and the Augmented Mean Group (AMG) estimator are employed on the data for the period 1990-2017. The preliminary tests affirm the existence of cross-sectional dependence, unit root, and cointegrating relationship among the variables. The findings from the study reveal that NR abundance reduces FD, while globalization, human capital and economic growth add to FD. A feedback causality exists between NR abundance and FD. Thus, this study argues that more investment in the manufacturing sector will ease the attainment of efficiency in financial sector accessibility and benefits from NR abundance.

This study explores the impact of AI innovation, financial development, and the digital economy on the Load Capacity Factor (LCF) in BRICS nations from 2000 to 2019. Cross-sectional dependence and slope homogeneity tests reveal that the variables exhibit both dependence and heterogeneity. Panel unit root tests confirm stationarity, and a cointegration analysis establishes long-term relationships among the variables. The Panel ARDL method identifies a U-shaped relationship between income and LCF, supporting the LCC hypothesis. AI innovation and the digital economy positively influence LCF, promoting environmental sustainability. Conversely, financial development significantly reduces the LCF in both the short and long terms. To validate these findings, robustness checks using DKSE (Driscoll Kraay Standard Error), AMG (Augmented Mean Group), and CCEMG (Common Correlated Effects Mean Group) estimation techniques yield consistent results with the Panel ARDL analysis. Furthermore, the D-H causality test reveals unidirectional causal relationships from income, financial development, and the digital economy to LCF. It also identifies a bidirectional causal relationship between LCF and AI innovation. These findings highlight the dual role of AI and the digital economy in enhancing environmental sustainability while addressing the challenges posed by financial development in the BRICS nations.

The purpose of this study is to examine the impact of competition on the financial development of countries. For this purpose, Turkey, and BRICS countries (Brazil, Russia, India, China, South Africa) were selected as sample countries for the study. A 17-year dataset was created with country data from 2005 to 2021 as the time period. The competitiveness factor is included in the analysis as an independent variable, using data from the Global Competitiveness Index published by the World Bank. The indices of the most traded stocks on the stock exchanges, which represent the financial performance of countries, were used as the dependent variable. The methods used in the study were the Westerlund cointegration test, Augmented Mean Group (AMG) estimation and Common Correlated Effects (CCE) estimation. The analyzes conducted showed that competition has a positive and significant impact on the financial performance of the sample countries.

As reported at the 26th UN Climate Change Conference (COP26), worsening climate situation has led to frequent extreme weather events around the world. The main cause of climate change is carbon emissions from human activities. While realizing rapid economic development, China has become the world's largest energy consumer and carbon emitter. To achieve the goal of carbon neutrality by 2060, it should reasonably use natural resources (NR) and promote energy transition (ET). In this study based on panel data on 30 Chinese provinces from 2004 to 2020, second generation panel unit root tests were performed after validating slope heterogeneity and cross-sectional dependency. Mean group (MG) estimation and error correction model were used to empirically test the impact of natural resources and energy transition on CO2 intensity (CI). The results show that natural resources exerted adverse effects on CI, whereas ET, economic growth and technological innovation were beneficial to CI. Analysis of heterogeneity indicates that natural resources exerted the greatest impact on CI in central China, followed by west China. Its impact in east China was positive but did not pass significance test. West China achieved the best result in carbon reduction through ET, followed by central China and east China. The robustness of the results was checked with augmented mean group (AMG) estimation. Our policy suggestions are to urge reasonable development and utilization of natural resources, accelerate ET to replace fossil fuels with renewable energy, and implement differentiated policies on natural resources and ET based on regional characteristics.

Based on provincial panel data from 2008 to 2017 as the research sample in China, this study examines the impact of financial development on carbon emissions. Regression models are employed to estimate the influence of financial development on carbon emissions in different regions. The research reveals that the level of carbon emissions is influenced by differentiation and heterogeneity, with different regions showing varying sensitivities to factors such as financial development, technological innovation, and industrial structure. Financial efficiency has a negative impact on carbon emissions, being positive in regions with low carbon emissions. In areas with higher carbon emissions, the impact of financial efficiency on carbon emissions is greater. Industrial structure has a negative impact on carbon emissions, and in regions with lower carbon emissions, the upgrading of industrial structure has a greater impact on carbon reduction. Technological innovation has a negative impact on carbon emissions in regions with medium to high levels of emissions, while its impact in low-emission areas is positive but not significant. Per capita GDP, energy structure, and urbanization level overall have a positive impact, while foreign investment has a negative impact. The introduction of technological innovation as a moderating variable significantly enhances the significance level of financial efficiency.

The main aim of the study is to analyze the link between technological innovation and income inequality for Turkey in terms of financial Kuznets curve (FKC) hypothesis. The study uses time-series data from 1987 to 2018. We employ the Hatemi-J cointegration, ARDL bounds test and VECM Granger causality techniques to investigate the relations between the variables. We also employ the DOLS, FMOLS and CCR approaches to estimate the long-run parameters. The results reveal that the series are cointegrated under the structural breaks. The results also reveal that the FKC is valid for Turkish economy in the long run. Technological innovation positively affects income inequality while economic growth is negatively linked with income inequality. There exists a bi-directional causal linkage between financial development and income inequality. Technological innovation and income inequality cause each other. In addition, economic growth causes income inequality. Empirical results suggest a twofold policy implication: i) improvement of the financial system and ii) to eliminate the adverse effects of technological innovations on income distribution.

Analysis of environmental sustainability and economic development from electricity consumption based on the modified spatial Durbin model

Green technology innovation corporates can effectively coordinate the relationship between the environment and the economy, which has been an area of interest among academia and governments. To stimulate the sustainable green technology innovation of corporates, it is necessary to clarify the internal correlation among green technology innovation, environmental performance, and economic performance. Based on the information of 642 industrial corporates obtained from a field investigation in China, this article systematically examines the relationships between corporate green technology innovation and environmental performance, economic performance, and the moderating effect of different governmental market‐based regulations on these relationships. The results show the following. (1) Green technology innovation can significantly improve corporate environmental performance and economic performance. (2) Corporate environmental performance can be transformed into economic performance, and an improvement in environmental performance leads to an increase in the economic performance produced by unit environmental performance, which shows a nonlinear relationship. (3) Government supply‐based market regulation negatively moderates the relationship between end‐of‐pipe technology innovation and environmental performance while positively moderating the relationship between green process innovation and environmental performance and the relationship between green product innovation and economic performance; government demand‐based market regulation positively moderates the relationship between green process innovation and environmental performance and the relationship between green process innovation and economic performance; government competitive‐based market regulation only has a positive effect on the relationship between green product innovation and economic performance. (4) Government market‐based regulations can positively promote the transformation from environmental performance to economic performance. The stronger the market‐based regulations, the greater the economic performance that corporate environmental performance can bring.

This research assesses the impact of remittances and financial development on the size of shadow economy in Africa. Furthermore, the study examines the moderating effect of financial development on the linkages between remittances and the shadow economy. The data set for the study comprises 29 African countries between 2000 and 2020, while Driscoll and Kraay’s non-parametric standard error, fully modified ordinary least squares, augmented mean group, and method of moment quantile regression are used as estimation techniques. The study documents that remittances and financial development lessen the size of shadow economy in Africa. Additionally, the study found no substitute or complementary role of financial development and remittances in influencing the size of the shadow economy. This suggests that financial development and remittances can have separate effects on the size of the shadow economy. The results of other control variables also indicate that economic growth and foreign direct investment reduce the size of the shadow economy while population and institutional quality increase its size. The results of this study are robust to different estimation techniques.

The United Nations Climate Change Conference (COP26) recommended that the member nations enhance their technological progression and structural transformation to mitigate the problems of climate change. The BRICS-T countries consisting of Brazil, Russia, India, China, South Africa, and Turkey agreed to implement COP26's policy suggestions. These countries accounted for 40% of global greenhouse gas emissions in 2017, thus posing severe threats to the global environment. The current study explores the role of renewable energy, forest depletion, eco-innovations, and export diversification in impacting the ecological footprint for those BRICS-T countries. We further examine the moderating effect of eco-innovations on agriculture on the BRICS-T nations. The study contributes to the existing literature by providing newer empirical insights on how eco-innovations and export diversification, along with renewable energy, forest cover, and agriculture, affecting the ecological footprint in the BRICS-T nations. It utilizes novel empirical methods like parametric and non-parametric techniques to derive the short-run and long-run empirical results. The empirical findings based on the augmented mean group and the kernel regularized least square methods document that economic growth, agriculture value added, and forest depletion increase the ecological footprint. In contrast, renewable energy and eco-innovations decrease the level of ecological footprint. In the long run, a 1% rise in GDP leads to a rise in the ecological footprint by 0.64% using the augmented mean group (AMG) estimation. The mean marginal effects are - 0.27%, 0.29%, and 0.17% for renewable energy; agriculture and forest cover, respectively, using the kernel-based regularized least square methods. The study suggests that policies designed for controlling the ecological footprints focus on the use of energy efficient technologies, particularly in the agricultural sector.

Is knowledge spillover from human capital investment a catalyst for technological innovation? The curious case of fourth industrial revolution in BRICS economies

With the ongoing advancements in the modern industrial economy, the global ecological environment is encountering a multitude of challenges, prompting the increasing dissemination and global acknowledgment of the concept of sustainable development. Governments have formulated green development strategies aimed at incentivizing enterprises to enhance their environmental performance and mitigate environmental risks. This study utilizes a research sample comprising 3313 firm-level environmental performance scores and primary business data for 276 Chinese enterprises from 2007 to 2017. Based on the empirical evidence from the fixed-effects model, it is evident that technological innovation overall enhances the environmental performance and reduces the environmental risks of Chinese enterprises. Heterogeneity analysis reveals that internal innovation within Chinese enterprises exhibits heterogeneous impacts on environmental performance. The study shows that, compared to enterprises in the primary and tertiary industries, technological innovation in the enterprises of China’s secondary industry has a greater impact on enhancing environmental performance. Furthermore, within the secondary industry, the positive impact of technological innovation on environmental performance is more pronounced for the traditional sectors. Based on these findings, government authorities should actively encourage technological innovation among enterprises and formulate differentiated environmental policies tailored to different enterprises and industries. This research holds significant implications for the implementation of green strategies, enhancement of enterprise competitiveness, achievement of long-term sustainability, and improvement of global ecological environmental quality.

ABSTRACTSustainable income growth in emerging nations requires productive populations to adopt and innovate technology to boost marginal productivity per worker. To this end, the present study examines how technological adoption, productive population and sustainability affect income growth in selected Asian economies between 1990 and 2022. Thus, to achieve the study objective, a panel analysis circumvents cross‐sectional dependence with estimators such as Augmented Mean Group (AMG) heterogeneous panel regression. Similar robustness estimators like Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS) and Driscoll–Kraay Standard Errors (DKSE) were employed. Key empirical findings include that, with all things being equal, productive population size decreases income growth by 5.6%. This means that productive activity considerably reduces Asian income growth. However, technical advancement boosts revenue. Technological innovation enhances Asian income growth by 1.1% when all model variables are constant. In contrast, using 1% sustainable energy to increase sustainability reduces the region's income growth by 2.9%. This means sustainable energy consumption in Asia reduces economic productivity and income per capita. Based on the study's findings, Asian countries should encourage technology innovation and skill development for productive populations. A productive workforce can build creative skills through ongoing training and manpower incubation via an innovation ecosystem. In the conclusion, more policy directions are appended.

Addressing carbon emissions is an urgent priority for nations leading global economic and industrial activities. This study focuses on the P5 Plus 1 countries China, the United States, Russia, the United Kingdom, France, and Germany due to their dominant role in global carbon output and economic influence. The research investigates how four critical factors economic growth, development of the financial sector, technological innovation, and economic complexity affect efforts to reduce carbon emissions and achieve carbon neutrality. Using data spanning from 1995 to 2021, the study employs both advanced non-parametric and parametric statistical models to capture long-term patterns and causal relationships. The findings highlight that increasing economic complexity generally supports carbon reduction goals, though results differ by model. Technological innovation and financial development display both positive and negative impacts, suggesting context-specific effects, while economic growth continues to pose challenges to emission control. Based on these insights, the study recommends policies promoting clean technology development, green financial instruments, energy transition incentives, and sustainable industrial restructuring. These targeted strategies can help high-emission economies align their growth objectives with environmental sustainability goals.