scholarly journals Carbon Sequestration Total Factor Productivity Growth and Decomposition: A Case of the Yangtze River Economic Belt of China

2019 ◽  
Vol 11 (23) ◽  
pp. 6809
Author(s):  
Guangming Rao ◽  
Bin Su ◽  
Jinlian Li ◽  
Yong Wang ◽  
Yanhua Zhou ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Total Factor Productivity ◽  
Yangtze River ◽  
Stochastic Frontier ◽  
Scale Efficiency ◽  
The Yangtze River ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Natural Ecosystems ◽  
Estimation Model

To find out whether carbon sequestration is both effective at mitigating climate change and promoting economic growth, in this paper, by adopting a stochastic frontier panel model with translog production function, carbon sequestration is incorporated into endogenous variables to establish estimation model of carbon sequestration total factor productivity (CSTFP) and examine CSTFP growth and its drivers decomposition of the Yangtze River Economic Belt (YREB) of China in three estimations. The result shows that, (1) compared to traditional TFP growth, CSTFP growth in YREB is improved by 26.74 percentages (from −26.55% to 0.20%), contributed by three positive drivers of technical efficiency change (28.59%), technological progress change (18.55%), and scale efficiency change (3.99%); (2) different CSTFP growth exists in three watershed segments of YREB, which firstly is the upper reaches (0.62%), then the lower reaches (0.11%) and the middle reaches (−0.14%). Improved CSTFP growth owes to carbon sequestration’s harmonious symbiosis where natural ecosystems and human activities are naturally blended while insufficient synergies are bottleneck for promotion of CSTFP growth in YREB. Related policy suggestions are provided in the end. The proposed analysis framework is efficient to disclose CSTFP growth in YREB, and can also be applied to similar analysis on CSTFP in regions and extended to multi-country/region analysis.

scholarly journals Research on Green Total Factor Productivity of Yangtze River Economic Belt Based on Environmental Regulation

2021 ◽  
Vol 18 (22) ◽  
pp. 12242
Author(s):  
Junxia He ◽  
Luxia Wang ◽  
Decai Tang
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Yangtze River ◽  
Environmental Governance ◽  
Efficiency Index ◽  
Scale Efficiency ◽  
The Yangtze River ◽  
Factor Productivity ◽  
Input Output ◽  
Treatment Rate

With the acceleration of industrialization and urbanization, the Yangtze River Economic Belt (YREB) is facing many environmental problems that need to be solved in the process of development. This paper aims to analyze the environmental governance effects of nine provinces and two municipalities in the Yangtze River Economic Belt from 2009 to 2018. Firstly, based on the input-output index, the slacks-based measure (SBM) undesirable model and Malmquist (ML) index were used to measure the green total factor productivity (GTFP) of the YREB from 2009 to 2018. The results showed that the technological progress index contributed the most to the GTFP of the YREB, followed by the pure technical efficiency index and the scale efficiency index. Environmental regulation has no significant impact on the GTFP of the YREB. Secondly, by analyzing the effect of environmental governance in the YREB, the results show that the main reasons for the ineffective environmental governance in the YREB are the redundant input of environmental resources, excessive unwanted output, and low harmless treatment rate of municipal solid waste, rather than the low level of urban environmental management. Finally, this paper provides recommendations for the ineffective provinces and municipalities of the YREB to further optimize the input-output factors of environmental governance.

scholarly journals Distinction between Informal and Unorganized Sector: A Study of Total Factor Productivity Growth for Manufacturing Sector in India

2011 ◽  
Vol 3 (5) ◽  
pp. 296-310
Author(s):  
Indrajit Bairagya
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Informal Sector ◽  
Productivity Growth ◽  
Manufacturing Sector ◽  
Total Factor Productivity Growth ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Unorganized Sector

Since its very onset, the concept and definition of the informal sector has been a subject of debate both at the national and international levels. Existing literature uses the terms ‘informal sector’ and ‘unorganized sector’ interchangeably. However, in India, the characteristics of enterprises in the informal and non-informal unorganized manufacturing sectors are different and, thus, it is not justifiable to consider the informal and unorganized sector interchangeably for the manufacturing sector. Thus, the objective of this paper is to test the hypothesis on whether or not the total factor productivity growth (TFPG) of the informal manufacturing sector is different from the non-informal unorganized manufacturing sector. TFPG is decomposed into technical efficiency change and technological change. Later, technical efficiency change is further decomposed by pure efficiency change and scale efficiency change. Results show that the average TFPG of the non-informal sector is higher than the informal sector. The informal sector heavily concentrates in own account small enterprises, whereas the non-informal unorganized sector concentrates only in directory manufacturing enterprises (DME). Due to large in size, DME avails the advantages of economies of scale, which, in turn, helps the units for more growth in terms of total factor productivity growth. The main reason for productivity decrease of the enterprises, besides technology regress and the lack of adequate investments, is the limitation of activities and scale along with the optimal allocation of resources. This study provides a basis on how policies can be designed for enhancing the total factor productivity growth of the informal sector.

scholarly journals TOTAL FACTOR PRODUCTIVITY GROWTH IN CHINA’S CORN FARMING: AN APPLICATION OF GENERALIZED PRODUCTIVITY INDICATOR

2021 ◽  
Vol 22 (5) ◽  
pp. 1189-1208
Author(s):  
Zhiyong Niu ◽  
Yining Zhang ◽  
Tianxiang Li ◽  
Tomas Baležentis ◽  
Dalia Štreimikienė ◽  
...  
Keyword(s):  
Total Factor Productivity ◽  
Technological Progress ◽  
General Setting ◽  
Scale Efficiency ◽  
Production Data ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Corn Production ◽  
Tfp Growth ◽  
Input And Output

Total factor productivity (TFP) growth measures usually focus on a certain direction of optimization and ignore the general setting encompassing the input and output orientations simultaneously. This paper uses the generalized Luenberger-Hicks-Moorsteen (LHM) TFP indicator which is additively complete and can be decomposed by three mutually exclusive elements. The input- and output-oriented analysis is undertaken in order to derive the generalized TFP measured. The paper uses the corn production data from 19 Chinese provinces over the period of 2004–2017. This research is important as China is the second largest corn producer in the world. The TFP growth was observed for Chinese corn farming the rate of 0.56% per year. The technological progress (0.48%) was the major source of the TFP growth, whereas the importance of the technical efficiency change (0.09%) and scale efficiency change (–0.01%) was negligible.

scholarly journals Impact of collaborative innovation on green total factor productivity in Yangtze River Economic Belt: Analysis based on endogenous spatial-temporal weight matrix

2021 ◽  
Author(s):  
lei Wu ◽  
Xiaoyan Jia ◽  
Jie Lv ◽  
Li Gao
Keyword(s):  
Total Factor Productivity ◽  
Yangtze River ◽  
Negative Impact ◽  
Positive Impact ◽  
Spatial Interaction ◽  
Evaluation Index System ◽  
Weight Matrix ◽  
The Yangtze River ◽  
Factor Productivity ◽  
Collaborative Innovation

Abstract Technological innovation can promote high-quality economic growth. This paper discusses the promotion of green total factor productivity from the perspective of collaborative innovation in the Yangtze River Economic Belt. Firstly, the evaluation index system of collaborative innovation level is constructed from two aspects of collaborative innovation elements and collaborative innovation environment. Then the entropy method is used to measure its development level. The results show that the collaborative innovation level of provinces in the Yangtze River Economic Belt presents an increasing trend year by year. Meanwhile, there are regional differences, which is characterized by 'high in the middle reaches, middle in the downstream and low in the upstream' Secondly, the SDM model based on endogenous spatio-temporal weight matrix is constructed to analyze the influencing factors of green total factor productivity. The results show that collaborative innovation in the Yangtze River Economic Belt has significant negative impact on green total factor productivity in terms of spatial interaction and fiscal expenditure also has a negative impact. The spatial interaction between environmental protection and opening up has a significant positive impact on green total factor productivity. However, the spatial interaction between industrial structure and human capital on green total factor productivity is not obvious. Finally, this paper puts forward some policy suggestions to improve green total factor productivity.

Productivity Analysis of Coal-fired Thermal Power Plants in India Using Malmquist Index Approach

2019 ◽  
Vol 21 (6) ◽  
pp. 1338-1353
Author(s):  
Amritpal Singh Dhillon ◽  
Hardik Vachharajani
Keyword(s):  
Total Factor Productivity ◽  
Power Plants ◽  
Thermal Power ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Tfp Growth

The sustainable socio-economic growth of any country depends on the availability of adequate and reliable power at reasonable rates. This is even true in case of a rapidly developing country like India where coal-based power plants account for the majority of electricity generation. Making use of data envelopment analysis (DEA) and Malmquist productivity index (MPI), this study analyses the productivity change of coal-fired power plants during 2002–2012. Productivity change is further decomposed into technical efficiency change (EFFCH), technological change (TECHCH), scale efficiency change (SECH), pure technical change (PECH) and total factor productivity change (TFPCH). The study revealed that 0.70 per cent of average annual total factor productivity (TFP) growth was witnessed from 2002–2003 to 2011–2012 indicating overall progress. The contribution of TECHCH in TFP growth is positive, that is, 1.3 per cent per annum. It demonstrates that expansion of the efficient frontier. However, there was a decrease in technical EFFCH of −0.6 per cent per year, indicating the adverse sign of progress. Plants in the central sector achieved maximum growth of 4.6 per cent annually. A total of 54.05 per cent of plants have recorded negative TFP growth. Power plants between 500 and 999 MW achieved the highest operational performances in all indices except SECH.

A Stochastic Frontier Approach to Assessing Total Factor Productivity Change in China’s Star-Rated Hotel Industry

2020 ◽  
Vol 45 (1) ◽  
pp. 109-132
Author(s):  
Hongwei Liu ◽  
Henry Tsai
Keyword(s):  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Stochastic Frontier ◽  
Hotel Industry ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Frontier Analysis ◽  
Scale Change ◽  
Economic Regions

Using a stochastic frontier analysis approach and a flexible translog production function considering neutral technological progress, this study assesses technical efficiency change, technological change, and scale change, and further measures the total factor productivity (TFP) change and its convergence of China’s star-rated hotel industry in 31 provinces, municipalities, and regions from 2001 to 2015. The results show that the TFP change of China’s star-rated hotel industry was generally favorable and boosted by both the technical efficiency change and technical change; nevertheless, the scale change hindered and largely caused fluctuations in the TFP change. From a regional economic perspective, the TFP change of the star-rated hotel industry in most of the eight comprehensive economic regions examined was rather stable. While few comprehensive economic regions existed absolute convergence, all of the regions showed significant conditional convergence except for the Eastern Coastal region.

scholarly journals ANALISIS TINGKAT EFISIENSI SEKTOR PARIWISATA DI JAWA TENGAH TAHUN 2017 DAN 2019

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Yennie Glorya Panjaitan ◽  
Edy Yusuf Agung Gunanto
Keyword(s):  
Data Envelopment Analysis ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Data Envelopment ◽  
Factor Productivity ◽  
Efficiency Change

Sektor pariwisata sebagai salah satu sektor yang diandalkan bagi penerimaan daerah maka pemerintah Provinsi Jawa Tengah dituntut untuk dapat menggali dan mengelola potensi wisata yang dimiliki. Penelitian ini bertujuan untuk menganilisis tingkat efisiensi dan produktivitas pada sektor pariwisata di Jawa Tengah antara tahun 2017 dan 2019 dengan sampel 35 Kabupaten/Kota. Analisis dilakukan dengan menggunakan konsep efisiensi yang didasarkan pada teori produksi, pengukuran nilai efisiensi dan produktivitas diperoleh menggunakan metode analisis Data Envelopment Analysis (DEA) dan Malmquist Productivity Index (MPI). Asumsi yang digunakan adalah variable return to scale (VRTS) dan model orientasi output (output oriented). Dengan variable input objek wisata, restoran dan rumah makan, biro perjalanan wisata dan jumlah hotel bintang serta melati. Variabel output dalam penelitian ini adalah wisatawan dan pendapatan sektor pariwisata. Hasil akhir penelitian menunjukkan bahwa terdapat 16 Kabupaten/Kota (45,8%) di tahun 2017, 18 Kabupaten/Kota (51,4%) di tahun 2019 yang mencapai efisiensi teknis penuh. Total Factor productivity change mengindikasikan bahwa 22 Kabupaten/Kota (62,8%) mendekati frontier baik pada frontier produksi maupun frontier efisiensi dan dari scale efficiency change mengindikasikan bahwa terdapat 17 Kabupaten/Kota (48,57%) mengalami perbaikan efisiensi teknis selama periode 2017 ke 2019.

scholarly journals Measurement of Total Factor Productivity in Commercial Airlines Sector using Malmquist Index and Data Envelopment Model

2020 ◽  
Vol 8 (6) ◽  
pp. 2168-2173
Keyword(s):  
Panel Data ◽  
Technical Efficiency ◽  
Total Factor Productivity ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Factor Productivity ◽  
Efficiency Change ◽  
Year 2013

This study attempts to measure productivity change of Airlines companies in private and public sector in India for a period of four years (2011-2016). In this study the nature and productivity change is probed using the Malmquist Productivity Index. This index has the constituents which are used to measure the performance in terms of change in Scale Efficiency, change in Technical Efficiency, change in Technological Change and Total Factor Productivity. The paper compares efficiencies for the companies in public and private commercial airlines sector in India. Five Airlines companies are included in the study. The research includes Total Annual Income as an output variable and Total Expenditure, Employee Compensation, Sales & Distribution Expenditure and Marketing expenses as Input variables. A panel data with 30 observations has been used for analysis. The panel data is used to arrive to MPI estimates, with a total of five commercial airlines companies in India. The Total Factor Productivity change in the airlines sector depends upon the change in the efficiency and productivity of the companies. From the study it is evident that the Total Factor Productivity change has not changed significantly over the last six years for all the companies under study. The Technical Efficiency was the highest in the year 2013-14 which then dropped in the subsequent year. The Total Factor Productivity change is mainly due to change in scale efficiency of the companies since the pure efficiency has shown no significant change during the period under study. The Total Factor Efficiency dropped by almost 50% in the case of Air India in the year 2015-16. This drop is attributed to the deterioration in the technical efficiency of the company. The overall Total Factor Productivity of Air India is the highest. This can be attributed to positive change in the company’s Technical Efficiency especially in the year 2013-14. It is evident that all the airlines companies under study have not emphasized on improving scale efficiency as well as pure efficiency. These companies can improve their overall productivity by bringing in efficiency in the scale of operations as well as focus on improving efficiency on factors other than scale of operations. The commercial airlines companies in India need to improve their scale efficiency and pure efficiency to improve their total factor productivity.

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