Analyzing inclusive green growth in China: a perspective of relative efficiency.

Inclusive green growth is a sustainable development mode in pursuit of economic growth, social equity, and environmental protection. At present, a large number of articles have discussed the impact of foreign direct investment (FDI) on economic growth, green growth, and inclusive growth. However, the research about inclusive green growth is mainly descriptive. This paper constructs China’s inclusive green growth index and analyzes the impact of FDI on inclusive green growth in China. Specifically, by constructing a super efficiency slacks-based measure model (which has two undesirable outputs: income disparity and environmental pollution) to calculate the Inclusive green growth index, this paper compares and analyses the differences and regional characteristics of China’s total factor productivity, inclusive total factor productivity, green total factor productivity, and inclusive green total factor productivity. We find that total factor productivity is decreasing after considering undesirable output, and the traditional total factor productivity is higher than the inclusive green total factor productivity by 0.112; at the regional level, the trend of the total factor productivity is gradually decreasing from east to west, which indicates that there are regional differences in inclusive green growth of China, and there is room for improvement. Meanwhile, we construct a panel vector autoregressive model (PVAR) and use generalized impulse response function and variance decomposition to analyse the influence of FDI on China’s inclusive green total factor productivity. The results show that FDI is beneficial to the promotion of inclusive green total factor productivity in China, and environmental pollution in the FDI process is an important factor hindering the inclusive green total factor productivity.

Inclusive green growth strategy has become a worldwide consensus on sustainable development for its highlight on the coordination between social equity, economic growth quality, and environmental stability. In-depth understanding of the temporal disparity in inclusive green growth is vital for developing countries with regional imbalances to devise scientific and sustainable development strategies. Motivated by the need for continuously monitoring the time-varying process of inclusive green growth and to overcome the shortfalls of conventional inclusive green growth index in dynamic assessment, we developed a functional inclusive green growth index (IGGI(t)) in the context of continuous curves. The inclusive green growth in China comprises four functional sub-indices and is built upon four pillars, namely the economic development, social opportunity equity, sustainable production and consumption, and eco-environmental protection. All normalized indicators within each pillar are individually smoothed into dynamically evolving curves, and then are objectively aggregated using the functional Shannon's entropy weights. Applying the IGGI(t) to examine disparities in China's provincial inclusive green growth from 2000 to 2019 demonstrates significant disparity in the absolute level of inclusive green growth among the three regions in China, whereas disparities in the velocity and acceleration of regional inclusive green growth are not significant. Furthermore, the overall and structural inequality of China's inclusive green growth was decomposed via the extended functional Dagum index and targeted policies for reducing regional inequality and improving China's overall inclusive green growth are proposed based on discussions of empirical results. Finally, a sensitivity analysis was conducted to verify the robustness of conclusions derived from using the IGGI(t). We contributed to proposing a dynamic framework for evaluating the quality of green growth and providing a reference for developing countries, including China, to coordinate economic development, social inclusiveness, and eco-environmental protection.

In the context of the widely recognized concept of inclusive green growth, it is of great practical significance to study the measurement of inclusive green growth, its temporal characteristics and its spatial heterogeneity. However, it should be noted that most existing studies only consider the situation of China when constructing inclusive green growth indices, and such studies lack international comparators. The index selection dimension is relatively single, and the temporal characteristics and spatial heterogeneity are rarely studied simultaneously. In this study, a spatial correlation analysis method is introduced, and the time series characteristics and spatial heterogeneity of inclusive green growth are deeply analyzed by means of a Moran’ I and LISA agglomeration diagram. The results show that: (1) Economic development, fair opportunity, green production and consumption and ecological environment protection are important factors affecting the level of inclusive green growth, but their development is not balanced; (2) Inclusive green growth has obvious time series characteristics, but there are great differences between provinces and regions; (3) The inclusive green growth has significant spatial heterogeneity. From 2010 to 2019, the inclusive green growth level has a dynamic evolution process. Moran’s I Index Global Spatial Test results show that inclusive green growth has obvious spatial autocorrelation, that is, it has great spatial differences. Local spatial test results also show that the inclusive green growth in China has obvious spatial aggregation characteristics. Therefore, it is important to coordinate the development of inclusive green growth between provinces and regions and improve the overall level of inclusive green growth in the future.

The purpose of the research is based on the spatial network correlation to explore the convergence path of inclusive green growth. Inclusive green growth is a sustainable development model that emphasizes the integration of economic, social, and ecological systems. Based on the three subsystems of economic growth, social inclusion, and green sustainability, this study structures the indicator system of China’s inclusive green growth and reveals the characteristics of China’s inclusive green growth network using the social network analysis (SNA) method. Then, from the perspective of system deconstruction, this work tests whether and how China’s inclusive green growth converges by constructing a spatial econometric model with different subsystems of spatial correlation networks as spatial weights. The results show that: (1) China’s inclusive green growth level is on the rise in general, showing a spatial distribution pattern of “high in East and West, low in the Central”. (2) China’s inclusive green growth network relationship is significant, and the network system is stable, but there is still room for improvement in network relevance. The spatial correlation of economic growth is relatively closer than other subsystems. (3) China’s inclusive green growth has a remarkable convergence trend in the spatial correlation scenario, and the spatial correlation of social inclusion has the most significant promoting effect on the convergence of the national inclusive green growth; there is a trend of club convergence in the East, Central, and West regions, and the speed of convergence is the fastest in the central region. The spatial correlation of economic growth has a strong promoting effect on the convergence of inclusive green growth in all regions.

Fostering inclusive green growth in China: Identifying the impact of the regional integration strategy of Yangtze River Economic Belt

As an important way for China to integrate into the international circulation, foreign direct investment (FDI) can not only increase China's capital accumulation but also directly affect inclusive green growth by promoting the diffusion and transfer of green technologies and activating the domestic market. Based on China's provincial panel data from 2007 to 2019, this paper discusses the following issues: first, Global Malmquist-Luenberger (GML) productivity index is used to measure and analyze the current situation of inclusive green growth in 30 provinces of China; second, we set a fixed effect panel model to test the relationship between FDI and inclusive green growth in China. Third, based on PVAR (panel vector autoregressive) model, the dynamic impacts of FDI and new urbanization on inclusive green growth are tested. Finally, a regression model with the new urbanization level as the threshold variable is constructed to test the threshold effect of FDI on China's green inclusive growth. Accordingly, each region needs to formulate FDI introduction policies according to the local new urbanization level, so as to give full play to the positive role of FDI in inclusive green growth.

With the vigorous development of digital economy based on digital technologies such as Internet of things (IoT), big data, and artificial intelligence, new vitality has been injected into China's economic model. Inclusive green growth (IGG) supports the transformation of society towards a better quality of life and well-being, as well as environmental protection. Therefore, it is crucial to identify the main drivers of IGG. However, IGG is subject to a variety of interpretations and lacks definitional clarity. To brigade this gap, this study primarily evaluates the performance of IGG and explores the key drivers on IGG in China. Specifically, the data envelopment analysis (DEA) model is employed to calculate IGG for 281 cities in China during 2005–2020. Subsequently, we take advantage of a nest of machine learning (ML) algorithm to demonstrate the vital drivers of urban IGG, which avoids the defects of endogenous linear hypothesis of traditional econometric methods. The results indicate that digitization represented by the IoT and other digital technology is the core drivers of the urban IGG in the overall sample, accounting for about 50% among all of drivers. This finding provides new evidence supporting the “high-quality development” strategy in China, as well as shedding light on grasping the principal fulcrum to achieve the transformation towards IGG in developing economies similar to China.

How economic policy uncertainty processes impact on inclusive green growth in emerging industrialized countries: A case study of China

Spatio-temporal characteristics and analysis of influencing factors of inclusive green growth in China’s oil and gas resource industry

Labor market distortion is ceaselessly endangering the balance among economic efficiency, social equity, and environmental quality sought by inclusive green growth and sustainable development. This study develops an innovative evaluation system to measure China's inclusive green growth by using provincial panel data from 2004 to 2020. Three dimensions are covered, including economic development, social equity and welfare, and green sustainability. Static and dynamic panel econometric models are employed to investigate the effect of labor market distortion on inclusive green growth and the potential transmission channels. The spatial econometric model is further applied to study the spatial spillover effect of labor market distortion on inclusive green growth. The results indicate that labor market distortion negatively affects inclusive green growth. Technological innovation, industrial structure optimization, and export trade upgrading are transmission channels of the impact of labor market distortion on inclusive green growth. In addition to hindering local inclusive green growth, labor market distortion also decreases neighboring inclusive green growth through the spatial spillover effect. These conclusions suggest that removing distortion in the labor market and emphasizing the role of market mechanisms in labor allocation may provide a new perspective to help move toward inclusive green growth for sustainable development.

Inclusive green growth is a style of long-term development that prioritises economic growth, social fairness, human well-being, and energy conservation. This research explores the impact of industrial intellectualisation on regional inclusive green growth using panel data from 30 provinces from 2006 to 2018. The research begins by calculating the level of industrial intellectualisation and inclusive green growth employing the entropy technique in China. Second, the benchmark regression results show that industrial intellectualisation boosts regional inclusive green growth significantly. This is true for a variety of robustness tests, including IV regression. Furthermore, spatial autocorrelation exists in regional inclusive green growth, and industrial intellectualisation has a favourable stimulating influence as well as a considerable spatial repercussions on regional inclusive green growth. Furthermore, the mediating effect model is employed to explore the mechanism of industrial intellectualisation's effects on inclusive green growth. The findings demonstrate that industrial intellectualisation has an effect on regional inclusive green growth via industrial structure upgrades, urbanisation, education, and financial development.

Against the backdrop of global climate governance and China’s dual-carbon goals, low-carbon city construction has emerged as a critical strategy for balancing economic growth and environmental sustainability. This study evaluates the impact of low-carbon city construction on inclusive green growth in China from 2006 to 2021. Empirical results indicate that these policies contribute to an average increase of 0.005 units in inclusive green growth for the treatment group compared to the control group, with robustness assessed through placebo tests and alternative variable substitutions. Further analysis indicates that the policy effects are more pronounced in central cities, resource-based cities, and cities with high carbon abatement potential, driven strongly by urban technological innovation, industrial structure optimization, and enhanced government leadership. However, spatial effect analysis shows that, despite a significant positive spatial correlation between cities, the spillover effects of low-carbon policies are limited, primarily concentrated within the pilot cities. Therefore, it is recommended to strengthen cross-regional governance alliances, establish green technology transfer centers, promote the “R&D-manufacturing-recycling” industrial chain, and deploy tailored regional transformation incentives. Additionally, drawing on international models such as the EU’s carbon border mechanism and Germany’s industry-university-research framework, collaborative “regional green growth partnerships” should be developed to foster inclusive green growth.

Smart cities are the product of the integration of China’s new urbanization and informatization. Inclusive green growth (IGG) is an important strategic idea for economic development and transformation. This study uses CRITIC-entropy weight method to quantitatively measure IGG index from the three dimensions of economic growth, green growth and inclusive growth. Based on the panel data of prefectural cities in China from 2006 to 2022, this study evaluates the impact of smart city construction on IGG using multi-period difference-in-differences and spatial difference-in-differences models. The results show that smart city construction has a significant positive impact on IGG, as well as economic growth, green growth, and inclusive growth. Meanwhile, the impact of smart city construction on IGG has significant regional heterogeneity. Mechanism test shows that smart city construction positively affects IGG through three dimensions of technology, talent, and governance. Furthermore, there is a spatial spillover effect in smart city construction, which significantly promotes economic growth and green growth in neighboring non-pilot areas, as well as economic growth in neighboring pilot areas. This study provides valuable theoretical insights and policy ideas for planning in emerging economies to promote high-quality development and ecological civilization through smart city strategy.

Inclusive green growth is an effective strategy for achieving sustainable development in rural areas. In the digital economy era, it is crucial to examine whether rural digital development and inclusive green growth can be harmoniously integrated. This study investigates the spatial and temporal evolution of the coupled coordination between digital village construction and rural inclusive green growth in China. Utilizing panel data from 30 provinces from 2011 to 2022, we assess development levels using the entropy weighting method and analyze interdependencies with a coupling coordination model. The results indicate an upward trend in coupling coordination, with significant regional disparities, and it is slowly taking on the characteristics of spatial clustering. Economically advanced regions exhibit higher coordination levels, attributed to stronger economic foundations and better fiscal resources, enabling effective investments in digital infrastructure and green growth initiatives. Additionally, factors such as urbanization rate, innovation levels, reduction in natural disasters, increased financial support for agriculture, and improved large-scale operations positively contribute to this coordination. These findings offer insights for targeted regional development strategies, enhancing the synergy between digital transformation and sustainable rural development.

As digital economy flourishes, there have been fundamental changes in the patterns of economic development, social structure, and ecological environment, which are the key elements of inclusive green growth (IGG). However, whether digital economy can effectively contribute to IGG requires further investigation. This paper evaluates the direct and spatial spillover effect of digital economy on IGG of 280 cities in China during 2011-2019 using Spatial Durbin Model (SDM). It further explores how government environmental regulation (GER) moderates this facilitating effect. The empirical results show that digital economy significantly reinforces IGG while GER weakens the benefits of digital economy to IGG. There is a significant spatial spillover effect of digital economy on IGG in neighboring regions; specifically, IGG in peripheral cities is more significantly encouraged by digital economy than in central cities. In addition, digital development demonstrates the most significant impact on IGG in central regions of China, followed by the eastern regions, with western regions lagging behind. This paper contributes theoretically and empirically to promote digital economy selectively for IGG in different regions and provides a guideline for policymakers to achieve IGG through proper GER.