scholarly journals Analysis of Green Total Factor Productivity of Grain and Its Dynamic Distribution: Evidence from Poyang Lake Basin, China

Agriculture ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 8
Author(s):  
Bingfei Bao ◽  
Shengtian Jin ◽  
Lilian Li ◽  
Kaifeng Duan ◽  
Xiaomei Gong
Keyword(s):  
Total Factor Productivity ◽  
Poyang Lake ◽  
Kernel Density ◽  
Productivity Index ◽  
Main Peak ◽  
Lake Basin ◽  
Factor Productivity ◽  
Density Curve ◽  
Poyang Lake Basin ◽  
The Right

Based on the grain production data of the counties (cities, districts) in Poyang Lake Basin, this paper uses the productivity index of Epsilon Based Measure of Malmquist Luenberger (EBM-ML Index) to analyse the green total factor productivity (GTFP) of grain in Poyang Lake Basin. Kernel density function and Markov analysis are used to discuss the dynamic evolution process of the distribution of GTFP of grain. The results show the following: (1) From the time dimension, the GTFP of grain is on the rise and fluctuates more frequently from 2001 to 2017, and its trend of change is determined by the combination of technical efficiency and technological progress. Moreover, from a spatial dimension, the number of counties (cities, districts) with GTFP of grain greater than 1.0 has shown an overall increase, indicating that the overall level of GTFP of grain is increasing. (2) According to the kernel density estimation results, the crest of the main peak of the kernel density curve corresponding to the GTFP of grain in Poyang Lake Basin shifts to the right, and the area formed by the right part of the GTFP of grain corresponding to the crest of the main peak of its kernel density curve gradually increases. The peak of the kernel density curve changes from “multi-peak mode” to “single-peak mode,” and the height of the main peak of the kernel density curve of GTFP of grain shows an overall decrease. Meanwhile, the right tail of the kernel density curve shows an overall extending trend. (3) According to the estimation results of the Markov chain, the GTFP of grain in Poyang Lake Basin is highly mobile from 2001 to 2017, and the counties (cities, districts) have a certain degree of agglomeration in the low, medium-low, medium-high and high levels. In other words, the long-term equilibrium state of growth of GTFP of grain remains dispersed in the state space of four level types, indicating that the divergence state of GTFP of grain in counties (cities, districts) of Poyang Lake Basin will continue for a long time in the future. The study reveals the evolution and dynamic change of GTFP of grain in Poyang Lake Basin, which has important theoretical significance and practical value for optimizing the spatial pattern and realizing the balanced development of GTFP among counties (cities, districts) of Poyang Lake Basin and consolidating China’s food security strategy.

scholarly journals Industry Efficiency and Total Factor Productivity Growth under Resources and Environmental Constraint in China

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Feng Tao ◽  
Ling Li ◽  
X. H. Xia
Keyword(s):  
Energy Consumption ◽  
Total Factor Productivity ◽  
Environmental Efficiency ◽  
Pollutant Emissions ◽  
Productivity Index ◽  
Productivity Change ◽  
Factor Productivity ◽  
Energy And Environment ◽  
Capital Labor Ratio ◽  
Investment Capital

The growth of China's industry has been seriously depending on energy and environment. This paper attempts to apply the directional distance function and the Luenberger productivity index to measure the environmental efficiency, environmental total factor productivity, and its components at the level of subindustry in China over the period from 1999 to 2009 while considering energy consumption and emission of pollutants. This paper also empirically examines the determinants of efficiency and productivity change. The major findings are as follows. Firstly, the main sources of environmental inefficiency of China's industry are the inefficiency of gross industrial output value, the excessive energy consumption, and pollutant emissions. Secondly, the highest growth rate of environmental total factor productivity among the three industrial categories is manufacturing, followed by mining, and production and supply of electricity, gas, and water. Thirdly, foreign direct investment, capital-labor ratio, ownership structure, energy consumption structure, and environmental regulation have varying degrees of effects on the environmental efficiency and environmental total factor productivity.

scholarly journals Past and future changes of streamflow in Poyang Lake Basin, Southeastern China

2012 ◽  
Vol 16 (7) ◽  
pp. 2005-2020 ◽  
Author(s):  
S. L. Sun ◽  
H. S. Chen ◽  
W. M. Ju ◽  
J. Song ◽  
J. J. Li ◽  
...  
Keyword(s):  
Poyang Lake ◽  
Water Cycle ◽  
Coupled Model ◽  
Soil Water Storage ◽  
Future Climate Change ◽  
Lake Basin ◽  
Poyang Lake Basin ◽  
The Future ◽  
Intercomparison Project ◽  
Meteorological Observations

Abstract. To understand the causes of the past water cycle variations and the influence of climate variability on the streamflow, lake storage, and flood potential, we analyze the changes in streamflow and the underlying drivers in four typical watersheds (Gaosha, Meigang, Saitang, and Xiashan) within the Poyang Lake Basin, based on the meteorological observations at 79 weather stations, and datasets of streamflow and river level at four hydrological stations for the period of 1961-2000. The contribution of different climate factors to the change in streamflow in each watershed is estimated quantitatively using the water balance equations. Results show that in each watershed, the annual streamflow exhibits an increasing trend from 1961–2000. The increases in streamflow by 4.80 m3 s−1 yr−1 and 1.29 m3 s−1 yr−1 at Meigang and Gaosha, respectively, are statistically significant at the 5% level. The increase in precipitation is the biggest contributor to the streamflow increment in Meigang (3.79 m3 s−1 yr−1), Gaosha (1.12 m3 s−1 yr−1), and Xiashan (1.34 m3 s−1 yr−1), while the decrease in evapotranspiration is the major factor controlling the streamflow increment in Saitang (0.19 m3 s−1 yr−1). In addition, radiation and wind contribute more than actual vapor pressure and mean temperature to the changes in evapotranspiration and streamflow for the four watersheds. For revealing the possible change of streamflow due to the future climate change, we also investigate the projected precipitation and evapotranspiration from of the Coupled Model Intercomparison Project phase 3 (CMIP3) under three greenhouse gases emission scenarios (SRESA1B, SRESA2 and SRESB1) for the period of 2061–2100. When the future changes in the soil water storage changes are assumed ignorable, the streamflow shows an uptrend with the projected increases in both precipitation and evapotranspiration (except for the SRESB1 scenario in Xiashan watershed) relative to the observed mean during 1961–2000. Furthermore, the largest increase in the streamflow is found at Meigang (+4.31%) and Xiashan (+3.84%) under the SRESA1B scenario, while the increases will occur at Saitang (+6.87%) and Gaosha (+5.15%) under the SRESB1 scenario.

scholarly journals Productivity Change of Microfinance Institutions in Bosnia and Herzegovina

2019 ◽  
Vol 14 (2) ◽  
pp. 23-33
Author(s):  
Velid Efendić ◽  
Nejra Hadžiahmetović
Keyword(s):  
Total Factor Productivity ◽  
Bosnia And Herzegovina ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Productivity Change ◽  
Microfinance Institutions ◽  
Factor Productivity ◽  
Strategic Objectives ◽  
Average Decrease ◽  
Recent Financial Crisis

Abstract The main aim of this paper is to investigate the productivity changes of microfinance institutions (MFIs) in Bosnia and Herzegovina (BiH) during and after the recent financial crisis. The study covers the period starting from 2008 until 2015. Using the Malmquist Productivity Index (MPI) over the sample of 10 MFIs and a balanced panel dataset of 80 observations, this study explores technical and technological change as well as total factor productivity (TFP) change. The empirical findings indicate a decline in TFP in most of the analyzed periods with an average decrease of 2.5%. The study reveals an average technological decline in the industry of 1.7%, while technical efficiency change is recorded at the level of -0.8%. Overall, crisis efficiency recovery occurred during the period between 2009 and 2013. However, due to technological inefficiencies, average total factor productivity change remains negative. Hence, policy makers need to enhance the technological progress in order to meet their strategic objectives in BiH MFIs.

scholarly journals Towards the measurement of total factor productivity index

2009 ◽  
Vol 57 (4) ◽  
pp. 544-554 ◽  
Author(s):  
Jakub Fischer ◽  
Jaroslav Sixta
Keyword(s):  
Total Factor Productivity ◽  
Productivity Index ◽  
Factor Productivity
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