scholarly journals Analysis of heterogeneity and convergence of TFP in culture industry

2021 ◽  
Vol 235 ◽  
pp. 02009
Author(s):  
Yun Li ◽  
Weijun Zhao
Keyword(s):  
Panel Data ◽  
Convergence Rate ◽  
Technological Progress ◽  
Malmquist Index ◽  
Culture Industry ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Western Region ◽  
Factor Productivity ◽  
Index Method

Based on the panel data of China’s culture and related industries, this paper constructs an evaluation index system of total factor productivity of culture industry, measures the TFP of culture industry by using the global Malmquist index method, The results show that the TFP index of China’s culture industry decreases by 3.1% every year, which is mainly driven by technological progress, There is an obvious trend of σ convergence among China’s culture industry as a whole, the western region and the subdivided industries. The convergence rate of TFP in the whole culture industry is 2.306%.

scholarly journals Research on the Impact of Logistics Technology Progress on Employment Structure Based on DEA-Malmquist Method

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xiao-qing Lei ◽  
Jia-jia Yang ◽  
Jian-bo Zou ◽  
Mei-er Zhuang
Keyword(s):  
Panel Data ◽  
Technological Progress ◽  
Malmquist Index ◽  
Listed Companies ◽  
Index Method ◽  
Logistics Industry ◽  
Employment Structure ◽  
The Impact

In recent years, with the vigorous development of e-commerce, the logistics industry has also developed rapidly and has gradually become one of China’s important industries. This paper takes 49 listed companies in the logistics industry in China as the research object and uses the DEA-Malmquist index method to measure the technology progress index of the logistics industry based on their panel data for a total of 10 years from 2008 to 2017. In this way, this article explores the impact of technological progress in the logistics industry and provides a reference for solving the contradiction of employment structure in China

scholarly journals Measuring Total Factor Productivity of China Provincial Non-Life Insurance Market: A DEA-Malmquist Index Method

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Fangping Yu ◽  
Hang Chen ◽  
Jiaqi Luo ◽  
Haibo Kuang
Keyword(s):  
Total Factor Productivity ◽  
Life Insurance ◽  
Technological Progress ◽  
Insurance Industry ◽  
Malmquist Index ◽  
Insurance Market ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Index Method ◽  
Life Insurance Industry

The unbalanced economic development results in the difference in operating efficiency of the non-life insurance industry in China’s provinces; based on the DEA-Malmquist index method, this paper investigates the provincial differences, dynamic change characteristics, and causes of non-life insurance productivity in 31 provinces of China from 2004 to 2017. The results show that in the sample period, there are significant differences between provinces and regions in China’s non-life insurance efficiency, which generally shows the echelon spatial characteristics of “strong in the west and weak in the east”. Technological progress in the western region promotes the rapid growth of total factor productivity, while the low efficiency of technological progress in the eastern region restrains the improvement of total factor productivity. The overall total factor productivity of China’s provincial non-life insurance industry is on the rise, mainly due to the improvement of pure technical efficiency and scale efficiency, while technological progress has an inhibiting effect on the contrary. These conclusions are of reference value for relevant stakeholders in China’s provincial non-life insurance market to formulate development strategies and business strategies.

scholarly journals Evaluation of Green Total Factor Productivity of China’s Tobacco Manufacturing Industry Based on DEA-Malmquist Index Method

2021 ◽  
Vol 261 ◽  
pp. 03027
Author(s):  
Xiaoyu Qu ◽  
Ziyue Wang
Keyword(s):  
Energy Consumption ◽  
Panel Data ◽  
Environmental Pollution ◽  
Total Factor Productivity ◽  
Manufacturing Industry ◽  
Malmquist Index ◽  
Technical Level ◽  
Factor Productivity ◽  
Upward Trend ◽  
Index Method

Using panel data from China’s tobacco manufacturing industry from 2014 to 2018, the DEA-Malmquist method is used to measure the green total factor productivity of China’s tobacco manufacturing industry on the basis of comprehensive consideration of environmental pollution and energy consumption. The study found that from 2014 to 2018, the Malmquist index of green total factor productivity of China’s tobacco manufacturing industry basically showed a fluctuating upward trend; the technical level of 2014-2017 needs to be improved, and the technical level of 2017-2018 has begun to improve.

scholarly journals An Empirical Study on Scientific Research Performance of Universities in Different Regions of China Based on PCA and Malmquist Index Method

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Cun-Yang Xia ◽  
Ze-Hui Yuan ◽  
Wen-Yu He ◽  
Ju-Hui Zhao
Keyword(s):  
Research Performance ◽  
Malmquist Index ◽  
Scientific Research ◽  
Principal Component ◽  
Development Trend ◽  
Entropy Method ◽  
Evaluation Index System ◽  
Eastern Region ◽  
Index Method ◽  
Output Efficiency

This paper uses principal component analysis (PCA) and entropy method to construct the evaluation index system of the scientific research performance of universities in 31 provinces and cities in China. Based on the traditional DEA model, the development trend of the scientific research performance of the research objects from 2015 to 2019 is dynamically evaluated by the Malmquist index method. The results show that the scientific research performance of universities in various regions of China is not ideal, and the level of scientific research performance is declining. The total factor productivity of scientific research in the central and western regions is much higher than that in the eastern region. The main factor that hinders the improvement of scientific research performance is the efficiency of technological progress. Finally, aiming at the existing problems, some feasible suggestions are put forward to further improve the input-output efficiency of scientific research in universities.

scholarly journals Environmental efficiency measurement based on DEA Malmquist model: a case study of Henan Province

2021 ◽  
Vol 248 ◽  
pp. 01030
Author(s):  
Zijing Zhang
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Technological Progress ◽  
Dynamic Change ◽  
Malmquist Index ◽  
Henan Province ◽  
Environmental Efficiency ◽  
Index Model ◽  
High Level

Based on the panel data of different cities in Henan Province from 2010 to 2016, DEA model with variable scale compensation and Malmquist index model are used to measure environmental efficiency from static and dynamic perspectives. The results show that the overall environmental efficiency of Henan Province is at a high level, the technical efficiency is slightly improved, the allocation of input factors tends to be reasonable; the environmental efficiency is rising in dynamic change, among which the influence of technological progress on the environmental efficiency of Henan Province is more critical.

Explaining International Productivity Differences / Erklärung internationaler Produktivitätsunterschiede

2003 ◽  
Vol 223 (6) ◽  
Author(s):  
Jens J. Krüger ◽  
Uwe Cantner ◽  
Horst Hanusch
Keyword(s):  
Technological Progress ◽  
Malmquist Index ◽  
Efficiency Analysis ◽  
Growth Accounting ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Nonparametric Approach ◽  
Catching Up ◽  
Relative Productivity

SummaryIn this paper we add new results to the investigation of productivity levels rather than productivity changes, as proposed by Hall/Jones (1996, 1997, 1999). To obtain measures of relative productivity levels we depart from traditional growth accounting and calculate the Malmquist index of total factor productivity change using a nonparametric approach to efficiency analysis for a broad sample of 87 countries. This index can be decomposed into measures of technological progress and efficiency change that are cumulated to level measures. The so obtained heterogeneity in productivity levels is then related to several determinants of technology driven growth by regression estimates. Doing this (a) we are able to provide confirmation of the validity of the decomposition of the Malmquist index and (b) we find innovation-related explanations for international technological frontier shifts and imitative catching up and falling behind.

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 A research on the efficiency of regional green innovation in China—Based on DEA-SBM model and Malmquist index method

2021 ◽  
Vol 236 ◽  
pp. 04012
Author(s):  
Li Yang ◽  
You Zhiwei ◽  
Wang Jiaqi ◽  
Lan Fei
Keyword(s):  
Technological Progress ◽  
Mainland China ◽  
Malmquist Index ◽  
Eastern Region ◽  
Green Innovation ◽  
Dynamic Changes ◽  
Index Method ◽  
Sbm Model ◽  
Key Factor ◽  
East West

This paper selects panel data of 29 provinces in mainland China from 2010-2017 and combines a DEA-SBM model that takes into account non-desired outputs and the Malmquis index method to study the static and dynamic changes of regional green innovation efficiency. It is found that the overall level of green innovation efficiency in China is low, but the overall trend is on the rise and there is more room for improvement. The differences in green innovation efficiency values among the three regions of East, West and Central Asia are obvious, with the eastern region developing at a higher level than the central and western regions, and the gap is gradually narrowing. Technological progress is a key factor affecting total factor productivity.

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