scholarly journals Yangtze River Basin Environmental Regulation Efficiency Based on the Empirical Analysis of 97 Cities from 2005 to 2016

2021 ◽  
Vol 18 (11) ◽  
pp. 5697
Author(s):  
Qian Zhang ◽  
Decai Tang ◽  
Brandon J. Bethel
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
River Basin ◽  
Yangtze River ◽  
Technological Progress ◽  
Yangtze River Basin ◽  
Efficiency Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Factor Productivity

The Yangtze River Basin (YRB) is an important area for China’s economic development and environmental governance. The aim of this paper is to analyze the total factor productivity across 97 cities in the YRB from 2005 to 2016. Based on the input and output indicators from 2005 to 2016, this paper selects the SE-SBM model to measure the environmental regulation efficiency (ERE) of 97 cities in the YRB and then uses the DEA–Malmquist index to measure the total factor productivity of the region. Results suggest that the overall ERE in the YRB is weakly ineffective, while ERE in the central and eastern coastal areas is relatively high. ERE matches the economic foundation and development of the city. YRB environmental regulation efficiency was in descending order in the middle stream, upstream, and downstream. The efficiency of regional environmental regulation shows an N-type development trend, with obvious characteristics of phased development. Moreover, the total factor productivity of the YRB has shown a downward trend. The scale efficiency index and the technical efficiency index have positively boosted the total factor productivity, while the technological progress index has dragged down the total factor productivity of the area. The contribution to the total factor productivity index is in order of scale efficiency, technological progress index, and technological efficiency index in the downstream. The overall inputs and outputs of the YRB have great development potential. The inputs have not been fully utilized, the outputs have not been maximized, and the regional differentiation is significantly observable.

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 Environmental Regulation, Trade Comparative Advantage, and the Manufacturing Industry’s Green Transformation and Upgrading

2020 ◽  
Vol 17 (8) ◽  
pp. 2823 ◽  
Author(s):  
Mengqi Gong ◽  
Zhe You ◽  
Linting Wang ◽  
Jinhua Cheng
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Comparative Advantage ◽  
Manufacturing Industry ◽  
Environmental Regulations ◽  
Manufacturing Industries ◽  
Productivity Index ◽  
Chinese Government ◽  
Factor Productivity ◽  
Trade Patterns

This paper is the first to systematically review the theoretical mechanisms of environmental regulation and trade comparative advantage that affect the green transformation and upgrading of the manufacturing industry. On this basis, corresponding hypotheses are put forward. The non-radial and non-angle SBM (slacks-based measure) efficiency measurement model with undesirable outputs was used, combined with the use of the ML (green total factor productivity index) productivity index to measure green total factor productivity. Finally, the theoretical hypothesis was empirically tested using data from 27 manufacturing industries in China from 2005 to 2017. The results show the following: (1) There is a significant inverted U-shaped curve relationship between environmental regulation and the transformation of the manufacturing industry. In other words, as environmental regulation increases, its impact on the transformation and upgrading of the manufacturing industry is first promoted and then suppressed. (2) When there are no environmental regulations, the trade comparative advantage of the manufacturing industry is not conducive to industrial transformation. However, under the constraints of environmental regulations, the comparative advantage of trade will significantly promote the green transformation and upgrading of manufacturing. Therefore, in order to effectively promote transformation and upgrading of the manufacturing, this paper proposes the following policy recommendations: (1) The Chinese government should pay more attention to the impact of environmental regulation intensity on the transformation of manufacturing industries, further increase the intensity of environmental regulation within the reasonable range, and fully exert the positive effects of environmental regulation on the trade patterns and manufacturing industry transformation. (2) We should further optimize the structure of trade, realize the diversification of manufacturing import and export, and promote its transformation into high-end manufacturing. On this basis, green production technology in the manufacturing industry can be improved through the technology spillover effect. (3) Efforts should be made to improve the level of collaborative development between environmental regulation and trade patterns and to explore the transformation path of the manufacturing industry with the integration of environmental regulation and trade patterns.

Research on TFP of Enterprises in China’s Manufacturing Industry Based on Malmquist Index Approach

2011 ◽  
Vol 201-203 ◽  
pp. 2793-2796 ◽  
Author(s):  
Shuang Chen Li ◽  
Shu Gai ◽  
Di Yuan
Keyword(s):  
Manufacturing Industry ◽  
Malmquist Index ◽  
Efficiency Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Technology Advancement ◽  
Index Approach ◽  
Exponential Method ◽  
Object Of Study

This template takes the 30 completely state-owned and the scale above the manufacturing industry professions as the object of study, has surveyed the manufacturing industry entire essential factor productivity index, the technology advancement index and the technology efficiency index with the Malmquist productivity exponential method. The conclusion believed that Manufacturing industry showed continued growth in total factor productivity trends, mainly due to the raising level of technological progress, while the scale efficiency and pure technical efficiency was manifested as decreased.

Evaluation analysis on industrial green total factor productivity and energy transition policy in resource-based region

2021 ◽  
pp. 0958305X2110054
Author(s):  
Yaozu Xue
Keyword(s):  
Environmental Pollution ◽  
Total Factor Productivity ◽  
Pollution Control ◽  
Energy Transition ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Shanxi Province ◽  
Scale Efficiency ◽  
Factor Productivity ◽  
Positive Effect

Based on the input-output panel data of industrial sectors of Shanxi Province, which is the only province-wide resource-based region in China, this paper uses the non-parametric DEA model and the Malmquist productivity index to construct the DEA-Malmquist model for evaluation analysis of the green total factor productivity (GTFP) and its decomposition value of the sub-sector, and then through fixed effect panel regression model studies the ways of energy transition of the SDG’s. The results show that the technological progress index has the greatest contribution to the growth of GTFP, while the scale efficiency index has the lowest contribution. And the amount of investment in environmental pollution control has a significant positive relationship with the GTFP of the three major polluting industries in Shanxi. Among them, investment in environmental pollution control has the greatest positive effect on the GTFP of light polluting industries characterized by high technology, high added value and low emissions; investment in environmental pollution control has the largest positive effect on the GTFP of heavy polluting industries with heavy chemical industry and pollution-intensive industries; investment in environmental pollution control has the weakest positive effect on the GTFP of the medium polluting industries that manufacture life service products and some heavy industrial products. Based on these results, the paper puts forward effective policy for the energy transition of resource-based regions.

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 Research on Environmental Regulation and Green Total Factor Productivity in Yangtze River Delta: From the Perspective of Financial Development

2021 ◽  
Vol 18 (23) ◽  
pp. 12453
Author(s):  
Jia Li ◽  
Decai Tang ◽  
Acheampong Paul Tenkorang ◽  
Zhuoran Shi
Keyword(s):  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Financial Development ◽  
Yangtze River ◽  
Foreign Capital ◽  
Yangtze River Delta ◽  
Factor Productivity ◽  
Control Variables ◽  
Financial Cooperation ◽  
The Yrd

This paper employs the global Malmquist Luenberger (GML) index and the System Generalized method of moments (GMM) estimation method to investigate the influence of both environmental regulation and financial development on green total factor productivity in 41 cities of the Yangtze River Delta (YRD) in China from 2003–2019. We select the relevant input-output data to measure the green total factor productivity (GTFP) and its decomposition index including undesirable output. The results show that the GTFP and its decomposition index in the YRD have a slow fluctuating upward trend. The YRD mainly depends on improving the level of technological progress and environmental governance to promote the improvement of regional economic green development level. The empirical research results show that there is an inverted U relationship between environmental regulation and GTFP in the YRD, too strict environmental regulation will inhibit the growth of green total factor productivity. By adding control variables, the inflection point of environmental regulation is 0.5034, which is lower than that without control variables. There is a strong interaction and superposition effect between financial development and environmental regulation, which is closely related to the established financial cooperation mechanism, perfect financial system arrangement and cross-regional financial cooperation platform in the YRD. Government intervention should be reduced, the introduction of foreign capital should be controlled appropriately, foreign capital should be guided to green industries, and the use efficiency of foreign capital should be improved. This paper holds that we should pay attention to the strength of environmental regulation, prevent overcorrection, increase the guidance of credit funds, deepen the reform of the financial system, appropriately intervene in the market by the government, strengthen the guidance of foreign capital, and promote the development and transformation of the green economy in the YRD region with the help of several policies.

scholarly journals Going Green or Going Away? A Spatial Empirical Examination of the Relationship between Environmental Regulations, Biased Technological Progress, and Green Total Factor Productivity

2018 ◽  
Vol 15 (9) ◽  
pp. 1917 ◽  
Author(s):  
Xueli Wang ◽  
Caizhi Sun ◽  
Song Wang ◽  
Zhixiong Zhang ◽  
Wei Zou
Keyword(s):  
Economic Development ◽  
Environmental Regulation ◽  
Total Factor Productivity ◽  
Capital Stock ◽  
Technological Progress ◽  
Environmental Regulations ◽  
Factor Productivity ◽  
Total Capital ◽  
Green Gdp ◽  
The Relationship

China’s economic development has resulted in significant resource consumption and environmental damage. However, technological progress is important for achieving coordinated economic development and environmental protection. Appropriate environmental regulation policies are also important. Although green total factor productivity, environmental regulations, and technological progress vary by location, few studies have been conducted from a spatial perspective. However, spatial spillover effects should be taken into consideration. This study used energy consumption, the sum of physical capital stock and ecological service value as total capital stock, the number of employed people as inputs, sulfur dioxide emissions as undesired outputs, and green GDP as total output to obtain green TFP through a slacks-based measure (SBM) global Malmquist-Luenberger Index. This study also estimated China’s biased technological progress under environmental constraints from 2004 to 2015 based on relevant data (e.g., green GDP, total capital stock, and employment figures). The relationship between green total factor productivity (GTFP), technological progress, and environmental regulation was then examined using a spatial Durbin model. Results were as follows: (1) Based on the complementary elements, although the labor costs gradually increase, the rapid accumulation of capital leads to technological progress that is biased toward capital. However, technological progress in the labor bias can significantly increase GTFP. (2) There is a u-shaped relationship between existing environmental regulations and GTFP. Technological progress can significantly promote GTFP in the surrounding areas through existing environmental regulations. (3) Under spatial weight, the secondary industry coefficient was negative while human capital stock and FDID had positive effects on GTFP. Technological progress is the source of economic growth. It is therefore necessary to promote biased technological development and improve labor-force skills while implementing effective environmental regulation policies.

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.

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.

Measuring total factor productivity change of microfinance institutions in India using Malmquist productivity index

2018 ◽  
Vol 12 (1) ◽  
pp. 105-130 ◽  
Author(s):  
Dilip Ambarkhane ◽  
Ardhendu Shekhar Singh ◽  
Bhama Venkataramani
Keyword(s):  
Total Factor Productivity ◽  
Financial Institutions ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Scale Efficiency ◽  
Productivity Change ◽  
Microfinance Institutions ◽  
Factor Productivity ◽  
Content Type ◽  
The Poor

PurposeMicrofinance institutions (MFIs) provide small loans and other financial services to the poor. These institutions are established for helping the poor to raise income levels and to reduce poverty. Recently, MFIs are required to reduce their dependence on grants and subsidies. Consequently, they face conflicting objectives of improving reach and profitability. These can be achieved by improving productivity. This paper aims to investigate productivity change in 21 major MFIs in India which are rated by Credit Rating and Information Services of India Limited in 2014.Design/methodology/approachThis paper attempts to examine total factor productivity change in 21 major Indian MFIs during the period from 2014 to 2016 using Malmquist productivity index. The inputs and outputs are selected considering objectives of outreach and financial sustainability. The authors have categorized MFIs in three categories, namely, large, medium and small, depending on asset size.FindingsIt is revealed that large MFIs are able to catch up with industry best practices by improving their systems and processes, but they need to improve scale efficiency. The Reserve Bank of India has recently initiated a policy of granting banking licenses to those financial institutions which have good outreach and are financially strong. It can be used for shortlisting MFIs before granting permission to operate as banks. The method can also be used for benchmarking them for productivity. It can also be replicated in other countries.Originality/valueIn India, MFIs are playing important role in economic development by providing microcredit to the poor. However, very few studies have been undertaken regarding productivity of MFIs in India. The present study intends to fill this gap. It will facilitate benchmarking of MFIs as competitive and sustainable financial institutions catering to the requirements of small borrowers.

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