scholarly journals Influence of the Evolution of Marine Industry Structure on the Green Total Factor Productivity of Marine Economy

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1108
Author(s):  
Xinyi Wei ◽  
Qiuguang Hu ◽  
Weiteng Shen ◽  
Jintao Ma
Keyword(s):  
Total Factor Productivity ◽  
Industrial Structure ◽  
Government Intervention ◽  
Malmquist Index ◽  
Marine Ecology ◽  
Advanced Technology ◽  
Factor Productivity ◽  
Marine Economy ◽  
Low Efficiency ◽  
The Impact

The 14th five-year plan emphasizes the importance of marine ecology and environmental protection, and the green concept is incorporated into the high-quality development system of the marine economy. This research used the data of 11 coastal provinces and cities in China from 2006 to 2016, based on the super-efficiency slack-based measure model and global Malmquist index model. The objective was to calculate the green total factor productivity (GTFP) of the marine economy, to study the impact of the evolution of the marine industrial structure on marine economic GTFP. The study found the following: (1) in general, the upgrade of marine industrial structure promoted the growth of marine economic GTFP and presented an inverted “U” trend of initially promoting and then suppressing. Spatially, only the advancement and rationalization of industrial structure in the Yellow and Bohai Sea regions inhibited the growth of marine economic GTFP. In terms of time, the advanced marine industrial structure promoted the growth of GTFP from 2006 to 2010, whereas that of industrial structure inhibited the growth of GTFP from 2011 to 2016. (2) The GTFP of the marine economy showed an increasing trend, but the conversion rate of production technology is low. Falling into the “efficiency trap” of highly advanced technology input and low-efficiency technology output should be avoided. (3) Affected by the mismatch of regional resources or industrial structure, government intervention showed an “opposite” mechanism in areas with different marine economic strengths. Government intervention in areas with higher marine economic strength was conducive to GTFP growth, whereas government intervention in areas with weaker marine economic strength would hinder GTFP growth.

scholarly journals Construction of Spatiotemporal Difference Image of the Impact of Financial Structure on China’s Total Factor Productivity

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yong Yu
Keyword(s):  
Total Factor Productivity ◽  
Evaluation Method ◽  
Financial Structure ◽  
Model Verification ◽  
Factor Productivity ◽  
Analysis Model ◽  
Dea Model ◽  
Dea Analysis ◽  
Low Efficiency ◽  
The Impact

My country’s current research on the influencing factors of total factor productivity has problems such as single evaluation method, low efficiency, and poor overall level in terms of evaluation methods and evaluation efficiency. Based on this, this study divides the financial structure into three traditional sections, banking, securities, and insurance, and uses the DEA model to study the temporal and spatial differences of the financial structure’s influence on the total factor productivity of the four major political and economic regions of China’s eastern, western, central, and northeastern China. First, establish a DEA model based on data mining algorithms, combine financial data comparisons over the years, to achieve a quantitative analysis of the financial structure’s impact on China’s total factor productivity, calculate financial efficiency, and then combine the DEA analysis data model with the grey correlation method. Analyze its internal influence rules, and design experiments for model verification analysis. The results show that the DEA analysis model can realize 8 iterations of data on the impact of financial structure on China’s total factor productivity, and its evaluation accuracy can reach more than 96.2%.

scholarly journals Cost Efficiency and Total Factor Productivity: An Empirical Analysis of Pakistan’s Insurance Sector

2016 ◽  
Vol 21 (1) ◽  
pp. 123-150
Author(s):  
Uzma Noreen ◽  
Shabbir Ahmad
Keyword(s):  
Total Factor Productivity ◽  
Malmquist Index ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Innovative Technology ◽  
Average Score ◽  
Factor Productivity ◽  
Tobit Regression ◽  
Insurance Sector ◽  
The Impact

This study uses data envelopment analysis and the Malmquist index to examine the impact of financial sector reforms on the efficiency and productivity of Pakistan’s insurance sector over the period 2000–09. Our results indicate that the sector is cost-inefficient, with an average score of 58 percent – an outcome of the inappropriate use of inputs. The Malmquist productivity index performs better, indicating an improvement in total factor productivity of about 3 percent on average. The second-stage Tobit regression analysis shows that large firms are relatively inefficient from an allocative perspective as they are unable to equate the marginal product of inputs with their factor prices. Furthermore, the results demonstrate that private firms are more efficient than public firms in the nonlife insurance sector. The empirical findings suggest that a more competitive environment, diversified products and innovative technology could improve the productivity of insurance firms in Pakistan.

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 Energy Efficiency, Policy and GTFP

2018 ◽  
Vol 53 ◽  
pp. 01033
Author(s):  
Fangqing Yi ◽  
Zenglian Zhang
Keyword(s):  
Economic Growth ◽  
Energy Efficiency ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Industrial Structure ◽  
Provincial Government ◽  
Factor Productivity ◽  
Linkage Mechanism ◽  
The Government ◽  
The Impact

The environmental and resource constraints on economic growth are increasingly evident. China urgently needs to reshape its economic growth momentum. The increase in green total factor productivity is particularly necessary for the growth of the quantity and quality of the economy. This paper selects the provincial panel data of 30 provinces in China from 2001 to 2015, and establishes a panel exchangeable errors model to analyze the impact of eight indicators on green total factor productivity (GTFP) and verifies its effectiveness. Empirical analysis shows that inter-provincial government competition, environmental regulation, energy consumption, and capital stock have a significant impact on green total factor productivity. The influence of foreign direct investment, industrial structure, and industrialization level on the total factor productivity of green is not significant. Therefore, the government should adopt suitable, flexible and diverse environmental regulation policies, promote energy-saving emission reduction and technology innovations through policies such as taxes and subsidies, strengthen the linkage mechanism between industrial structure upgrading and energy efficiency, to increase green total factor productivity.

scholarly journals The Measurement and Influencing Factors of Total Factor Productivity in the Chinese Rural Distribution Industry

2021 ◽  
Vol 13 (15) ◽  
pp. 8581
Author(s):  
Chaoxun Ding ◽  
Ruidan Zhang
Keyword(s):  
Total Factor Productivity ◽  
Influencing Factors ◽  
Data Model ◽  
Industrial Structure ◽  
Positive Impact ◽  
Malmquist Index ◽  
Annual Growth Rate ◽  
Factor Productivity ◽  
The Sustainable Development ◽  
Urbanization Rate

Total factor productivity (TFP) is critical to the sustainable development of the rural distribution industry. Improvements in productivity of the rural distribution industry can promote the high-quality development of the Chinese distribution industry. Studying the characteristics and influencing factors of total factor productivity in regard to the rural distribution industry in China is significant for promoting the transformation and development of the rural distribution industry. This paper uses the DEA–Malmquist Index to measure the total factor productivity (TFP) of the Chinese rural distribution industry and its decomposition index, and uses a panel data model to empirically study its influencing factors. The results show that, from 2008 to 2018, the TFP of the Chinese rural distribution industry showed a trend of rising first and then fluctuating and declining, with an average annual growth rate of 2.93%; the fluctuation direction of the TFP of the rural distribution industry in the eastern and western regions of China is basically the same, which has had a reverse change relationship with the central and northeast regions for many years. The industrial structure, urbanization rate, rural informatization rate, and conditions of the transportation facilities have significant impacts on the TFP of the rural distribution industry, among which the informatization rate has the greatest positive impact.

scholarly journals Impact of Green Total Factor Productivity in Marine Economy Based on Entropy Method

2018 ◽  
Vol 25 (s3) ◽  
pp. 141-146
Author(s):  
Danjie Wu
Keyword(s):  
Total Factor Productivity ◽  
Environmental Governance ◽  
Production Efficiency ◽  
Industrial Structure ◽  
Entropy Method ◽  
Factor Productivity ◽  
Factors Affecting ◽  
Green Production ◽  
Model Coefficient ◽  
Marine Economy

Abstract In order to improve the efficiency of marine economic production and realize the sustainable and healthy development of marine economy, the spatial-temporal and dynamic evolution trend of marine economic green production efficiency in coastal areas of China is analysed by means of SFA basic model, coefficient of variation, coefficient of Gini and entropy method. It mainly includes three aspects: the result analysis of marine economy green production efficiency; the dynamic trend analysis of marine economy green production efficiency; the analysis of factors affecting marine economy green production efficiency. The results show that the factors affecting the total factor productivity of the marine economy are: development level of marine economy, marine material capital, level of opening to the outside world, marine industrial structure, marine human capital and marine environmental governance.

scholarly journals Research on the Impact of Chinese Total Factor Productivity on the Modern Economic System Based on the Spatial Dubin Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Qin Tang ◽  
Zhi-An Ren ◽  
Kang-Feng Zhu ◽  
Nai-Ru Xu
Keyword(s):  
Economic Development ◽  
Economic System ◽  
Total Factor Productivity ◽  
Index System ◽  
Malmquist Index ◽  
Factor Productivity ◽  
Index Method ◽  
Five Dimensions ◽  
Modern Economic ◽  
The Impact

Total factor productivity is not only the core of high-quality economic development but also a core indicator for measuring the quality of economic development. Improving total factor productivity is one of the most critical points in building a modern economic system. Firstly, this paper uses the DEA-Malmquist index method to measure and decompose the total factor productivity of China’s 30 provinces, municipalities, and autonomous regions from 2001 to 2017 and analyzes the characteristics of its temporal and spatial changes. From a spatial perspective, the regional gap is relatively large. Secondly, we construct the index system of five dimensions and use this index system to comprehensively evaluate the improvement degree of China’s modernized economic system. The results show that the overall level of the improvement degree of China’s modernized economic system is relatively low, and the differences between provinces are great. Thirdly, this paper uses static and dynamic spatial econometric models to empirically analyze the effect of total factor productivity on the improvement degree of the modern economic system. The results show that the improvement degree of the modern economic system in China has obvious characteristics of time spillover and space spillover. Finally, we put forward countermeasures and suggestions on how to perfect the modern economic system.

scholarly journals The impact of environmental regulation on green total factor productivity: An empirical analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259356
Author(s):  
Qin He ◽  
Yaowu Han ◽  
Lei Wang
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Empirical Analysis ◽  
Malmquist Index ◽  
Measurement Model ◽  
Western China ◽  
Measure Data ◽  
Factor Productivity ◽  
Extensive Growth ◽  
The Impact

The transformation of China’s economy from extensive growth to high-quality development is essentially an increase in green total factor productivity (GTFP). China currently has a range of environmental regulation tools, and the question of whether environmental regulation can promote improvement in China’s GTFP requires theoretical and empirical analysis. This article first divides environmental regulation into three types: administrative, market-based and information-based. It then builds an empirical model of the effect of environmental regulation on GTFP. Slacks based measure-data envelope analysis (SBM-DEA) and the Malmquist index are used to measure the GTFP of 30 provinces in China from 2005 to 2018, and a measurement model of the impact of environmental regulation on GTFP is established. The results show that: (1) there are significant differences in GTFP in eastern, central and western China; (2) there is a non-linear relationship between environmental regulations and GTFP.

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.

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