scholarly journals Foreign Direct Investment, Regional Innovation, and Green Economic Efficiency: An Empirical Test Based on the Investigation of Intermediary Effect and Threshold Effect

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
You-Qun Wu ◽  
Huai-Xin Lu ◽  
Xin-Lin Liao ◽  
Jia-Bao Liu ◽  
Jia-Ming Zhu
Keyword(s):  
Economic Efficiency ◽  
Empirical Test ◽  
Threshold Model ◽  
Threshold Effect ◽  
Green Economy ◽  
Mediation Effect ◽  
Mechanism Analysis ◽  
Regional Innovation ◽  
Effect Analysis ◽  
The Impact

Based on the theoretical mechanism analysis of FDI, regional innovation, and green economic efficiency, this article uses China’s provincial panel data to calculate the provincial green economic efficiency level based on the three-stage DEA method and uses the system GMM model, intermediary effect model, and threshold model to empirically test the specific effects and transmission paths of FDI on the efficiency of the green economy. Research shows that FDI is one of the important factors that promote the improvement of green economic efficiency. Subregional tests have found that FDI has a significant regional heterogeneity in promoting the efficiency of the green economy. The mediation effect test found that the mediation effect of regional innovation is significant, and FDI can significantly promote the growth of green economic efficiency through regional innovation. The threshold effect analysis found that there are significant and effective double thresholds for regional economic levels, and the impact of FDI on green economic efficiency is heterogeneous within different threshold intervals. The research conclusions provide new inspiration for China to allocate FDI more rationally and efficiently under the new development pattern.

scholarly journals Research on the Nonlinear Impact of Environmental Regulation on the Efficiency of China’s Regional Green Economy: Insights from the PSTR Model

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Shuangliang Yao ◽  
Xiang Su
Keyword(s):  
Environmental Pollution ◽  
Environmental Regulation ◽  
Economic Efficiency ◽  
Environmental Regulations ◽  
Threshold Model ◽  
Resource Depletion ◽  
Green Economy ◽  
Eastern Region ◽  
Regional Production ◽  
The Impact

This paper uses the super-efficiency SBM model to measure the green economic efficiency considering undesired output and analyzes the spatial distribution difference of green economic efficiency; secondly, the nonlinear panel threshold model is used to empirically study the nonlinear relationship between environmental regulations and green economic efficiency, and further analyzed the threshold effect of environmental regulations on the efficiency of green economy and concluded as follows. (1) The green economy efficiency index in the eastern region is mostly more significant than 1, and the green economy efficiency in most provinces in the eastern region has improved. These provinces have higher regional production levels and less environmental pollution. The green economy efficiency of the central region is second only to the eastern region. The green economy efficiency of provinces in the western region except Chongqing is less than 1, indicating that these provinces have insufficient regional production, severe environmental pollution, or extensive resource depletion. (2) The impact of environmental regulations on the efficiency of the green economy presents an inverted “U” shape, with a threshold of 0.5128 for environmental regulations. The impact of the industrial structure on the efficiency of the green economy changes from inhibition to promotion after crossing the threshold of the intensity of environmental regulation, and the degree of opening to the outside world has a complementary effect on the efficiency of the green economy. The impact of urbanization on the efficiency of the green economy changes from promotion to suppression after surpassing the threshold of the intensity of environmental regulations.

scholarly journals Is There Any Difference in the Impact of Digital Transformation on the Quantity and Efficiency of Enterprise Technological Innovation? Taking China’s Agricultural Listed Companies as an Example

2021 ◽  
Vol 13 (23) ◽  
pp. 12972
Author(s):  
Haihua Liu ◽  
Peng Wang ◽  
Zejun Li
Keyword(s):  
Technological Innovation ◽  
Threshold Model ◽  
Threshold Effect ◽  
Listed Companies ◽  
Digital Transformation ◽  
Mechanism Analysis ◽  
Differential Impact ◽  
Agricultural Enterprises ◽  
The Impact

The effect of digital transformation on enterprise technological innovation is reflected in quantity and quality, which may show heterogeneity. In this regard, this paper uses the data of China’s A-share agricultural listed companies from 2015 to 2020 to compare the differential impact of enterprise digital transformation from the perspective of quantity and quality of technological innovation. Firstly, the Tobit model is used to test whether there are differences in the impact of digital transformation on the quantity and quality of technological innovation of agricultural enterprises, and heterogeneity is tested according to the nature of enterprises. Secondly, this paper explores the reasons digital transformation has different effects on the quantity and quality of technological innovation through mechanism analysis. Finally, according to the threshold model, the conditions for digital transformation to promote the quantity and quality of technological innovation of agricultural enterprises are discussed. The empirical results show that, first, the digital transformation of agricultural enterprises only promotes the number of technological innovations, and there is heterogeneity in the nature of enterprises, but the innovation efficiency is not affected. Second, the period expense rate will lead to digital transformation, having different effects on the quantity and efficiency of technological innovation of agricultural enterprises. Third, the impact of digital transformation on the technological innovation efficiency of agricultural enterprises has a significant single threshold effect, and when the period expense rate is less than the threshold, the digital transformation has a significant role in promotion.

scholarly journals Research on the Impact of Green Technology Innovation on Energy Total Factor Productivity, Based on Provincial Data of China

2021 ◽  
Vol 9 ◽  
Author(s):  
Mengxin Wang ◽  
Yanling Li ◽  
Gaoke Liao
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Technology Innovation ◽  
Threshold Model ◽  
Threshold Effect ◽  
Green Technology ◽  
Mediating Effect ◽  
Factor Productivity ◽  
Influence Mechanism ◽  
The Impact

Against the background of carbon peaking and carbon neutralization, green technology innovation plays an important role in promoting the energy total factor productivity (TFP). This study verifies the impact of green technology innovation on energy TFP in a complete sample and the subsamples by region, by constructing a panel threshold model, and analyzes its influence mechanism on the basis of the mediating effect test based on annual provincial data of mainland China from 2005 to 2018. The empirical results reveal the following: first, with the level of economic development as the threshold variable, there is a threshold effect in the impact of green technology innovation on the energy TFP; second, green technology innovation has an impact on the energy TFP through industrial structure upgrading; that is, industrial structure has a mediating effect in the influence mechanism; and third, there is heterogeneity in the impact of green technology innovation on the energy TFP among different regions in China, and the threshold effect only exists in the western region, since the central and eastern regions have crossed a certain developmental stage.

scholarly journals Do City Size and Population Density Influence Regional Innovation Output Evidence from China?

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Cai Shukai ◽  
Wang Haochen ◽  
Zhou Xiaohong
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Positive Impact ◽  
Threshold Value ◽  
Threshold Effect ◽  
The Other ◽  
City Size ◽  
Regional Innovation ◽  
Innovation Output ◽  
The Impact

This paper proposed a substantial gap to a large-scale population density and city size on regional innovation output. To measure the impact of population density and city size on regional innovation output, this study employs the threshold effect model with panel data of 230 prefectures and cities from 2007 to 2016. Based on the econometric analysis, the results exhibit a positive and significant relationship between population density, city size, and innovation output. This correlation suggests that when one factor increases, the other increases in the parallel direction and vice versa. Moreover, when the city size expands the threshold value of 2.934 percent, the innovation promotes and increases the effects of urban-scale expansion. On the other hand, for medium- and low-density cities, the increase of urban population density has a significant and positive impact on urban innovation output. However, for high-density cities, the increase of population density has no significant impact on innovation output.

scholarly journals Threshold Effect of Financial System on High-Quality Economic Development

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Lu Shen ◽  
Guohua He
Keyword(s):  
Economic Development ◽  
Industrial Structure ◽  
Positive Impact ◽  
Threshold Model ◽  
Financial System ◽  
Threshold Effect ◽  
High Quality ◽  
Optimal Interval ◽  
Development Level ◽  
The Impact

The relationship between financial system and economic development is not a simple linear relationship. In some cases, the development of finance may not improve the economic development level. This paper studies the influence of the financial system on the high-quality economic development, constructs the comprehensive index of the financial system by the factor analysis method, and calculates the green total factor productivity as the index of high-quality economic development by the CRS multiplier model. Empirically, this paper takes the panel data of 30 provinces, municipalities, and autonomous regions in China from 2005 to 2018 as samples, constructs the panel threshold model, and applies the financial system, economic development level, infrastructure, and industrial structure as threshold variables to study the nonlinear relationship between the financial system and high-quality economic development. The results demonstrate that the impact of the financial system on the high-quality economy presents an inverted U-shaped relationship when the financial system and industrial structure are the threshold variables, indicating that there is an optimal interval, that is, when the financial system threshold is between 0.1355 and 0.1377 and the industrial structure threshold is between 0.1364 and 0.1408, the financial system plays a greater role in the allocation of funds and has the most obvious positive impact on high-quality economic development. Meanwhile, the impact of the financial system on the high-quality shows a marginal decreasing trend when the economic development level and infrastructure are the threshold variables; when the economic development threshold is less than 0.1409 and the basic setting threshold is less than 0.1167, the financial system has the greatest effect on promoting high-quality economic development. Based on the research results, targeted policy suggestions are put forward.

scholarly journals Does Renewable Energy Consumption Successfully Promote the Green Transformation of China’s Industry?

Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 229
Author(s):  
Dongri Han ◽  
Tuochen Li ◽  
Shaosong Feng ◽  
Ziyi Shi
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Threshold Model ◽  
Energy Transition ◽  
Threshold Effect ◽  
Renewable Energy Consumption ◽  
Regional Energy ◽  
Economic Output ◽  
The Impact

The trade-off between economic growth and ecological improvement has always become an important and difficult issue for many countries, especially for developing countries. Due to a long-term extensive economic growth pattern, the regional resource allocation deviates from the optimal, especially the existence of energy misallocation, which hinders the maximization of economic output. Therefore, considering the characteristics and heterogeneity of resource endowments in different regions and increasing renewable energy consumption, that is, promoting energy transition, is it capable of sustainable development under China’s actual conditions? The exploration of the issue is a core step in the research of the impact of renewable energy on industrial green transformation. Based on the panel data of 30 regions in China from 2009 to 2016, this paper constructs a threshold model from the perspective of regional energy misallocation and empirically tests the nonlinear mechanism of renewable energy consumption to promote industrial green transformation. The results show that China’s energy allocation efficiency is low, there is a certain misallocation phenomenon, and the improvement effect in recent years is not satisfactory. Further, the relationship between renewable energy consumption and industrial green transformation is not a simple linear relationship, but a double threshold effect due to regional energy misallocation. In areas with severe energy misallocation, renewable energy consumption does not have a significant boost to industrial green transformation. Finally, this paper proposes the policy enlightenment of promoting industrial green transformation from the aspects of performance evaluation, market reform, and factor flow.

scholarly journals Spatio-Temporal Evolution and Mechanism Analysis of China’s Regional Innovation Efficiency

2021 ◽  
Vol 13 (19) ◽  
pp. 11089
Author(s):  
Zhen Xu ◽  
Xiang Zhu ◽  
Guoen Wei ◽  
Xiao Ouyang
Keyword(s):  
Temporal Evolution ◽  
Spillover Effects ◽  
Essential Elements ◽  
Eastern Region ◽  
Mechanism Analysis ◽  
Regional Innovation ◽  
Evolution Pattern ◽  
Evolution Characteristics ◽  
Spatio Temporal ◽  
The Impact

Improving regional innovation efficiency is the key to developing an innovative country. Exploring the spatio-temporal evolution characteristics of regional innovation efficiency is crucial in the formulation of regional policies and the choice of innovation models. This study used the superdata envelopment analysis method with undesirable outputs in evaluating the innovation efficiency of Chinese provinces. To assess the spatial spillover effects of innovation factors, the spatial autocorrelation and spatial Durbin model were adopted to characterize the spatio-temporal evolution, spatial correlation, and mechanisms of innovation efficiency. The highlights of the results are as follows: (1) The time-series changes in innovation efficiency showed a general trend from declining to increasing. (2) There were pronounced regional differences in innovation efficiency. The innovation efficiencies at the provincial level evolved from being decentralized to concentrated. The innovation efficiency was relatively stable in the eastern region and increased significantly in the central and western regions. The east–center–west evolution pattern gradually weakened. (3) The innovative efficiency exhibited spatial dependence, and the spatial agglomeration continued to increase. The extent of hot spots expanded, while cold spots shrunk slightly. (4) The scientific research environment, entrepreneurial environment, labor quality, and market environment were the essential elements that improved innovation efficiency. The impact of the different factors on innovation efficiency at different periods exhibited significant spatial heterogeneity.

scholarly journals The Impact of Innovative Industrial Cluster Policy on Regional Innovation: Evidence from a Quasi-Natural Experiment in China

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Huan Wang ◽  
Jinhua Guo
Keyword(s):  
Natural Experiment ◽  
Industrial Cluster ◽  
Industrial Clusters ◽  
Government Support ◽  
Mediation Effect ◽  
Eastern Region ◽  
Cluster Policy ◽  
Regional Innovation ◽  
Promoting Effect ◽  
The Impact

As important carriers of local innovation activities, innovative industrial clusters are attracting increasing attention. Therefore, several countries have started promotion policies for innovative industrial clusters. However, there are few empirical studies on relevant policies. This paper investigates the impact of China’s “innovative industrial cluster pilot” (IICP) policy on regional innovation. Taking the implementation of IICP policy as a quasi-natural experiment and using the panel data of 266 prefecture-level cities in China in 2008-2019, this paper provides strong evidence that IICP policy promotes regional innovation. The conclusion still holds after a battery of robustness checks. The heterogeneity test shows that the promoting effect of IICP policy on innovation is more significant in central and western region than in eastern region. Moreover, the lower the city administrative level and the lower the dependence on natural resource, the more prominent the innovation effect of IICP policy. Further, the mechanism test shows that the IICP policy can promote regional innovation indirectly by strengthening government support for innovation and attracting the agglomeration of science and technological talents, but the mediation effect of industrial structure has not been verified.

scholarly journals Does the Construction of National Eco-Industrial Demonstration Parks Improve Green Total Factor Productivity? Evidence from Prefecture-Level Cities in China

2021 ◽  
Vol 14 (1) ◽  
pp. 26
Author(s):  
Lu Liu ◽  
Xiaodong Yang ◽  
Yuxin Meng ◽  
Qiying Ran ◽  
Zilian Liu
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Mediation Effect ◽  
Eastern Region ◽  
Mechanism Analysis ◽  
Natural Experiments ◽  
Factor Productivity ◽  
The Difference ◽  
The Impact ◽  
Industrial Demonstration

This study conducted quasi-natural experiments based on the panel data of 239 prefecture-level cities in China from 2005 to 2017. The difference-in-difference (DID) and mediation effect model are used to test the impact and mechanism of the construction of national eco-industrial demonstration parks (NEDP) on green total factor productivity (GTFP). The results show that: (1) The construction of NEDP has significantly improved the urban GTFP, and the conclusion is still valid after running the robustness test. (2) Mechanism analysis shows that the construction of NEDP has improved GTFP through technological innovation and industrial structure upgrading. (3) The heterogeneity results reveal that NEDP has a significant positive effect on GTFP in the central and western regions, while the effect was insignificant in the eastern region. Moreover, NEDP significantly contributes to GTFP in resource-based and non-resource-based cities, while the contribution of resource-based cities is greater than that of non-resource-based cities. This study provides a reference for China to further promote the construction quality of NEDP and green development.

scholarly journals Improvement of Different Types of Environmental Regulations on Total Factor Productivity: A Threshold Effect Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Xubin Lei ◽  
Shusheng Wu
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Environmental Regulations ◽  
Threshold Model ◽  
Threshold Effect ◽  
Impact Behavior ◽  
Factor Productivity ◽  
Data Set ◽  
Different Types ◽  
The Impact

Based on the distinction of different types of environmental regulations, this paper attempts to test the threshold effect of environmental regulation on the total factor productivity (TFP) by employing a panel threshold model and a province-level panel data set during 2006–2016. Research results show that the influence of command-and-control and market incentive environmental regulation on the total factor productivity has a single threshold conversion characteristic of foreign direct investment (FDI) and financial scale, but the impact behavior and influence degree around the threshold are inconsistent. The effect of voluntary conscious environmental regulation on the total factor productivity has a single threshold conversion feature of human capital, and moderately enhanced intensity of environmental regulation is conducive to promoting the total factor productivity after crossing the threshold. Finally, in order to enhance the regional total factor productivity, relevant policy recommendations are proposed.

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