Evaluation of Bank Innovation Efficiency with Data Envelopment Analysis: From the Perspective of Uncovering the Black Box between Input and Output

Self Cite

256

The digital economy is an important engine to promote sustainable economic growth. Exploring the mechanism by which the digital economy promotes economic development, industrial upgrading and environmental improvement is an issue worth studying. This paper takes China as an example for study and uses the data of 286 cities from 2011 to 2019. In the empirical analysis, the direction distance function (DDF) and the Global Malmquist-Luenberger (GML) productivity index methods are used to measure the green total factor productivity (GTFP), while Tobit, quantile regression, impulse response function and intermediary effect models are used to study the relationship among digital economy development, industrial structure upgrading and GTFP. The results show that: (1) The digital economy can significantly improve China’s GTFP; however, there are clear regional differences. (2) The higher the GTFP, the greater the promotion effect of the digital economy on the city’s GTFP. (3) From a dynamic long-term perspective, the digital economy has indeed positively promoted China’s GTFP. (4) The upgrading of industrial structures is an intermediary transmission mechanism for the digital economy to promote GTFP. This paper provides a good reference for driving green economic growth and promoting the environment.

Section: Methodsmentioning

confidence: 99%

Digital Economy Development, Industrial Structure Upgrading and Green Total Factor Productivity: Empirical Evidence from China’s Cities

Liu

Yang

Li³

et al. 2022

Self Cite

256

“…Since the quadratic effects of command-based and autonomous environmental regulations on industrial green technology progress are not significant, the only square terms of market-based tools are included. According to the previous practice [ 62 ], the selection of pooled OLS, fixed-effect or random effect models is completed. For model T1, the LR test significantly rejects the null hypothesis, indicating that the fixed-effect model is suitable, and the Hausman test also significantly rejects the null hypothesis, which suggests the fixed-effect model is reasonable for it.…”

Section: Resultsmentioning

confidence: 99%

Does Environmental Regulation Promote Industrial Green Technology Progress? Empirical Evidence from China with a Heterogeneity Analysis

Xue

Zhong

2022

Self Cite

The complex relationship between environmental regulation and green technology progress has always been a hot topic of research, especially in developing countries, where the impact of environmental regulation is important. Current research is mainly concerned with the impact of the single environmental regulation on technological progress and lacks study on the diversity of environmental regulations. The main purpose of this paper is to examine the heterogeneity of the effects of different types of environmental regulation on industrial green technology progress. As China’s scale of economy and pollution emissions are both large, and the government has also made great efforts in environmental regulation, this paper takes China as the example for analyses. We first use the EBM-GML method to measure the industrial green technology progress of 30 provinces in China from 2000 to 2018, and then apply the panel econometric model and threshold model to empirically investigate the influence of 3 types of environmental regulation. The results show that, first, the impacts of environmental regulation on industrial green technology progress are significantly different; specifically, command-based regulation has no direct significant impact, and autonomous regulation has played a positive role, and market-based regulation’s quadratic curve effect is significant, in which the cost-based and investment-based tool presents an inverted U-sharped and U-sharped, respectively. Second, there may be a weak alternative interaction among different types of environmental regulation. Third, a market-based regulatory tool has a threshold effect; with the upgrading of environmental regulation compliance, the effect of a cost-based tool is characterized by “promotion inhibition”, and that of an investment-based tool is “inhibition promotion”. Finally, the results of regional analysis are basically consistent with those of the national analysis. Based on the study, policy enlightenment is put forward to improve regional industrial green technology progress from the perspective of environmental regulation. This paper can provide a useful analytical framework for studying the relationship between environmental regulation and technological progress in a country, especially in developing countries.

“…The economic growth of each city in the Yellow River Basin is not only affected by the region but also by the neighboring prefecture-level cities. The traditional ordinary panel model ignores the influence of variables in the surrounding area, leading to biases in the estimation [ 37 , 38 ]. Therefore, the spatial Durbin model for analysis was introduced.…”

Section: Methodsmentioning

confidence: 99%

Drag Effect of Economic Growth and Its Spatial Differences under the Constraints of Resources and Environment: Empirical Findings from China’s Yellow River Basin

Zhou

Liu

et al. 2022

As the global economic development intensifies the plunder of resources and the environment, the constraints are becoming more and more obvious. Based on the background of the strategy for ecological conservation and high-quality development of the Yellow River Basin, this paper intends to construct a resource-environment-constrained economic growth drag effect model and a spatial Dubin model, and explore the economic growth drag effect and its spatial differences in the Yellow River Basin under the constraints of resources and environment. The study found that the total drag effects of the overall economic growth of the Yellow River Basin that were obtained by the classic panel model without spatial effects is significantly negative. This is consistent with the conclusion that the average total drag effects of 80 prefecture-level cities is negative. The total drag effects of the overall economic growth of the Yellow River Basin changes from unconstrained to medium-constrained after adding spatial constraints, indicating that the spatial correlation of factors will restrict economic growth. From the level of the Yellow River sub-catchment, the total drag effect of the direct effects of the upper, middle, and lower reaches of the Yellow River is consistent with the total drag effect of the total effect. It shows that the upper economic growth is strongly constrained by the local resources and environment, while the downstream is strongly constrained by the adjacent resources and the environment. The research results provide references for resolving the resources and environment constraints in the Yellow River Basin. It provides useful inspiration for promoting ecological protection and high-quality development strategies in the Yellow River Basin.