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High-quality economic development focuses on achieving effective qualitative improvement and reasonable quantitative growth in the economy, which is the essential way for China to achieve sustainable development. This paper aims to investigate the role of financial development in the impact of foreign direct investment on high-quality economic development. GDP and green total factor productivity are used to measure the quantity and quality of economic development, respectively. We construct benchmark panel regression models, nonlinear interaction term models, and panel threshold models to examine the threshold effect of FDI on high-quality economic development based on the scale, structure, and efficiency of financial development. A series of tests are conducted to check the robustness of the estimates. Our results show that green total factor productivity in China is primarily driven by green technology progress. Additionally, foreign direct investment has a positive impact on China's high-quality economic development, with a threshold effect and nonlinear characteristics. Specifically, the scale of financial development affects the influence of foreign direct investment on the quantity of economic development, while the efficiency of financial development affects its influence on the quality of economic development. Furthermore, the structure of financial development affects both the quantity and quality of economic development. This study presents novel findings that contribute to understanding the role of financial development in the impact of foreign direct investment on high-quality economic development. Likewise, our research has implications for achieving high-quality development. The introduction of foreign direct investment under the high-quality development of the economy should comprehensively consider financial development. • The impacts on high-quality economic development of financial development and FDI were discussed. • The scale, structure and efficiency of financial development were considered. • Both quantity and quality of economic development were focus on. • The green total factor productivity in China was measured. • Policy implications of introducing FDI in China were proposed. [ABSTRACT FROM AUTHOR]

Transitioning to environmentally friendly economic growth is crucial for achieving sustainable development. Digital inclusive finance (DIF) can promote environmentally friendly economic activities and play a crucial role in fostering green and low-carbon development. In this context, a fundamental research question revolves around the theoretical foundations of how DIF impacts the growth of green total factor productivity (GTFP) and whether this relationship can be empirically verified. This question is particularly relevant for rural areas where financial innovations are necessary for the advancement of businesses and society as a whole. Additionally, expanding DIF can bring benefits to the environment, which is affected by agricultural activities. Therefore, it is important to assess the mechanisms behind the development of DIF and its impact on agricultural productivity growth. This paper presents an analysis of the interaction between DIF and GTFP growth in China's agricultural sector. Panel data from 2012 to 2019 at the province level are used for this analysis. The results reveal that GTFP and DIF demonstrate similar growth patterns, with DIF significantly contributing to GTFP growth. DIF can enhance GTFP by promoting information channels and fostering innovation in green technologies. [ABSTRACT FROM AUTHOR]

Improving forestry green total factor productivity is important for promoting green and high-quality development of the forestry industry. Meanwhile, there are major expectations that the digital economy, which is the new engine driving China's economic development, will help achieve the green transformation and high-quality development of the industry. We systematically examine the impact of the digital economy on forestry green total factor productivity in dynamic and spatial dimensions using a dynamic panel model, mediating effect model and dynamic spatial Durbin model based on the Non-Radial Directional Distance Function-Luenberger Hicks Moorsteen model; furthermore, we measure forestry green total factor productivity in 30 provinces in China from 2013 to 2019. Our results indicate that China's forestry green total factor productivity grew at an average annual rate of 5.03% from 2013 to 2019, maintaining an overall stable growth trend, and the growth rate declined in the order of Central, Eastern, Western, and Northeastern China. At the same time, the positive spatial correlation of green total factor productivity in China's forestry industry increased significantly during this period, and the local spatial correlation showed a trend of gradually shifting to the H–H agglomeration feature, with significant path-dependent characteristics and overall spatial spillover effects. The digital economy can significantly promote an improvement in forestry green total factor productivity, and this conclusion is still valid after robustness tests and endogeneity treatment. The analysis of the mechanism of action shows that industrial structure upgrading and green technology innovation are important mechanisms through which the digital economy can improve forestry green total factor productivity. The heterogeneity analysis shows that the enhancement effect of the digital economy on forestry green total factor productivity is more obvious in the eastern and northeastern regions than in the central and western regions. Finally, according to spatial spillover analysis, the positive effects of the digital economy can have spatial spillover effects on neighboring regions that are geographically close and have similar economies. The research in this paper advances the understanding of the growth drivers of forestry green total factor productivity, the mechanisms, and the regional differences in forestry green total factor productivity as affected by the digital economy. [ABSTRACT FROM AUTHOR]

Infrastructure development and the green transition of manufacturing are two crucial issues concerning the national economy and people's livelihood. However, not many literatures discuss the influencing mechanism connecting the two. This paper starts from a new research perspective of infrastructure development and explores the potential ways to improve manufacturing's ETFP. The empirical results indicate that the infrastructure development has indeed improved the green development level (GDL) of manufacturing. This impact is heterogeneous in terms of different infrastructure types and planning periods. Besides, the completed infrastructure helps the formation of an environmentally friendly development model, while the new infrastructure investment could generate negative environmental externalities. Through mechanism analysis, we found that infrastructure mainly promotes the GDL through the two tracks: scale effect and energy structure adjustment. The technological progress and industrial structure adjustment did not play the expected mediating impact. The dynamic panel threshold model results proved that with the expansion of the scale effect and the optimization of energy consumption structure, the role of infrastructure in promoting the manufacturing's GDL could be stronger. Some policy recommendations are proposed to provide a reference for the infrastructure programming and the green transformation in the manufacturing industry. [Display omitted] • Infrastructure development improved the manufacturing's green development level. • The impact is heterogeneous in different infrastructure types and time dimensions. • Scale and agglomeration effect and energy structure effect are the main tracks. • Industrial marginal effect of infrastructure presents a non-linear feature. [ABSTRACT FROM AUTHOR]

Green technology innovation can greatly decline the environmental effects arising from fossil energy consumption. It is an essential way to improve green total factor productivity (GTFP) and achieve China's goal of sustainable development. In this paper, stochastic frontier analysis and Malmquist index methods are applied to estimate provincial GTFPs of China during 2000–2016. Then, Spatial Durbin model is used to find out their spatial effect of green technology innovation on green total factor productivity from regional perspective. Empirical results are as follows: Firstly, it shows an upward trend on the whole while GTFP of eastern region is the highest and that of western region is the lowest. Moran index of GTFPs varies such dynamic trends as 'upward→downward→upward'. Moreover, it is significantly positive and still at the lower-level range. 'High-High' and 'Low-Low' are the dominant spatial clustering types. This indicates that more attention should be paid to spatial arrangements. Secondly, based on the analysis results of Spatial Durbin model, green technology innovation has significant positive effect on its own GTFP variation but negative effects on that of its neighbors during the research period. Thirdly, based on three subsamples results, green technology innovations of eastern and central regions have negative effects on their GTFPs while having positive effects on that of western provinces. Findings can provide spatial references for central government in the policy regarding accelerating high-quality green development. • Chinese green total factor productivity shows an upward trend during the research period. • Spatial correlation exists in GTFP of 30 provinces in China. • Green technology innovation has heterogeneous spatial effects in different samples. [ABSTRACT FROM AUTHOR]