scholarly journals Total Factor Energy Efficiency of China’s Industrial Sector: A Stochastic Frontier Analysis

2017 ◽  
Vol 9 (4) ◽  
pp. 646 ◽  
Author(s):  
Xiaobo Shen ◽  
Boqiang Lin
Keyword(s):  
Energy Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Industrial Sector ◽  
Frontier Analysis

scholarly journals Total Factor Energy Efficiency of China’s Industrial Sector: A Stochastic Frontier Analysis

2017 ◽  
Author(s):  
Xiaobo Shen ◽  
Boqiang Lin
Keyword(s):  
Energy Efficiency ◽  
Technical Efficiency ◽  
Technical Change ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Industrial Sector ◽  
Scale Efficiency ◽  
Efficiency Change ◽  
Output Data ◽  
Frontier Analysis

Based on stochastic frontier analysis and translog input distance function, this paper examines the total factor energy efficiency of China’s industry using input-output data of 30 sub-industries from 2002 to 2014, and decomposes the changes in estimated total factor energy efficiency into the effects of technical change, technical efficiency change, scale efficiency change and input-mix effect. The results show that during this period the total factor energy efficiency in China’s industry grows annually at a rate of 3.63%, technical change, technical efficiency change and input-mix effect contribute positively to the change in total factor energy efficiency, while scale efficiency change contributes negatively to it.

scholarly journals Estimating Persistent and Transient Energy Efficiency in Belt and Road Countries: A Stochastic Frontier Analysis

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3837
Author(s):  
Huaping Sun ◽  
Bless Kofi Edziah ◽  
Xiaoqian Song ◽  
Anthony Kwaku Kporsu ◽  
Farhad Taghizadeh-Hesary
Keyword(s):  
Energy Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Industrial Sector ◽  
Policy Implications ◽  
Economic Literature ◽  
Frontier Analysis ◽  
Efficiency Performance ◽  
Belt And Road ◽  
Lower Income Countries

In this paper, we examine the energy efficiency performance of the Belt and Road Initiative (BRI) countries using a newly developed panel data stochastic frontier model that allows for estimation of both persistent and transient efficiency while controlling for random country effects and noise. By this, we contribute to the energy economic literature by providing a complete picture of the level of persistent, transient, and total energy efficiency estimates from a cross country perspective for a panel of 48 BRI countries during the period 1990–2015. Adding that there is little evidence to support energy efficiency convergence in the energy economic literature, we went further to check whether energy efficiency converges in the BRI countries. The results show that (1) persistent efficiencies are much lower than transient efficiencies, suggesting that the energy problem in the BRI countries is more of a structural issue; (2) while energy efficiency varies widely across the countries, high-income countries perform better than the lower-income countries; (3) there is evidence of efficiency convergence and it accelerates when trade increases, but decreases when the industrial sector increases. Based on these findings, we propose some policy implications.

scholarly journals Determining the efficiency of residential electricity consumption

2020 ◽  
Author(s):  
Mark A. Andor ◽  
David H. Bernstein ◽  
Stephan Sommer
Keyword(s):  
Energy Efficiency ◽  
Stochastic Frontier Analysis ◽  
Energy Savings ◽  
Stochastic Frontier ◽  
Electricity Consumption ◽  
Frontier Analysis ◽  
Residential Electricity ◽  
Main Determinants ◽  
Residential Electricity Consumption ◽  
Reduction Of Energy Consumption

AbstractIncreasing energy efficiency is a key global policy goal for climate protection. An important step toward an optimal reduction of energy consumption is the identification of energy saving potentials in different sectors and the best strategies for increasing efficiency. This paper analyzes these potentials in the household sector by estimating the degree of inefficiency in the use of electricity and its determinants. Using stochastic frontier analysis and disaggregated household data, we estimate an input requirement function and inefficiency on a sample of 2000 German households. Our results suggest that the mean inefficiency amounts to around 20%, indicating a notable potential for energy savings. Moreover, we find that household size and income are among the main determinants of individual inefficiency. This information can be used to increase the cost-efficiency of programs aimed to enhance energy efficiency.

scholarly journals Energy Efficiency of the Baltic Sea Countries: An Application of Stochastic Frontier Analysis

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 104 ◽  
Author(s):  
Wen-Ling Hsiao ◽  
Jin-Li Hu ◽  
Chan Hsiao ◽  
Ming-Chung Chang
Keyword(s):  
Energy Efficiency ◽  
Baltic Sea ◽  
Urban Population ◽  
Energy Use ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
The Baltic Sea ◽  
Renewable Energy Consumption ◽  
Frontier Analysis ◽  
The Baltic

Using the stochastic frontier analysis (SFA) model, this research measures total-factor energy efficiency (TFEE) and disaggregate input efficiency for 10 countries across the Baltic Sea from 2004 to 2014. Real capital, labor, energy use, and carbon dioxide (CO2) are input variables, real gross domestic product (GDP) is the output variable, and renewable energy consumption and urban population are the environmental variables. The results provide not only the TFEE scores, in which statistical noise is considered, but also the determinants of inefficiency, which show the following. (i) Norway, Sweden, Finland, and Latvia perform better with respect to energy efficiency than other countries in the Baltic Sea Region. (ii) Interestingly, the average energy use efficiency scores from 2004 to 2014 in the 10 Baltic countries exhibit a gradual upward trend except for 2009. (iii) For the inefficiency estimates, higher renewable energy consumption and urban population correspond to higher TFEE scores.

scholarly journals Technical and Energy Efficiency of Urban Logistics in China: Empirical Analysis of 216 Prefecture-Level Cities

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Dongfang Wang ◽  
Jinfeng Li ◽  
Arthur Tarasov
Keyword(s):  
Energy Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Coastal Region ◽  
Eastern Region ◽  
Road Density ◽  
Logistics Industry ◽  
Frontier Analysis ◽  
Long Term Effect ◽  
The Difference

With the rapid economic development in China, substantial capital and resources are invested in urban logistics industry leading to quick expansion of the urban logistics. In this paper, the efficiency and energy efficiency of the urban logistics industry in China is measured through a stochastic frontier analysis based on a translog production function for a period of 2009–2017 using a sample of 216 prefecture-level cities. The results lead to several conclusions. (1) Average urban logistics efficiency and energy efficiency scores are at low levels and unbalanced between sample cities over the research period. Cities located in the eastern coastal region have the largest average efficiency scores, the central region has lower scores, and the western region has the lowest. (2) The difference in logistics efficiency between sample cities shows a downward trend for the entire country and eastern region. (3) Technical change plays an important role in promoting urban logistics efficiency. Technical inefficiency is the main cause of the nonefficient frontier of urban logistics. (4) Using the regression analysis, we found that digitalization and road density are positively correlated with the efficiency of urban logistics. Education has a long-term effect on the improvement of the urban logistics efficiency. In contrast, government intervention and environmental regulations are negatively correlated with the efficiency of urban logistics. (5) The effect of most factors on urban logistics efficiency across the sample stratified between eastern, central, and western regions is in line with the estimation results for the whole sample.

scholarly journals Examining the technical efficiency of small industries: A case study of the crackers industry in South Sumatera, Indonesia

2020 ◽  
Vol 18 (1) ◽  
pp. 13-20
Author(s):  
Mukhlis Mukhlis
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier Analysis ◽  
Raw Materials ◽  
Stochastic Frontier ◽  
Secondary Data ◽  
Industrial Sector ◽  
Business Climate ◽  
Frontier Analysis ◽  
Small Industry ◽  
Small Industries

Small industries are life-sustaining for communities because of their political and strategic position in terms of creating job opportunities and increasing revenue. One small industrial sector that has the potential to be developed is the food industry. Small food industries are widely scattered in every area, including in the city of Palembang. A small industrial group of food that became one of the culinary icons in Palembang is the cracker industry. This type of industry is a culinary icon that has been famous for foreign countries. Nevertheless, the cracker industry is still experiencing obstacles in terms of capital and marketing. The cost of raw materials is relatively expensive to technically trigger the industry inefficiencies. Therefore, it is necessary to review the technical efficiency of this small industry.  The variables used in this study were capital, labor, and output. The data used is secondary data that is analyzed by using the Stochastic Frontier Analysis (SFA) approach. The results showed that the technical efficiency achievement of small industrial crackers in South Sumatera is still categorized as low. The use of labor input is more effective than capital use as a result of the utilization of technology and local resources. Therefore, the development of small industrial crackers through an efficiency approach cannot be separated from the application of technology, human resource management, marketing, and business climate.

scholarly journals Advancing the multifactor model of Stochastic Frontier Analysis

2021 ◽  
Vol 3 (4 (111)) ◽  
pp. 58-64
Author(s):  
Arthur Mitsel ◽  
Aliya Alimkhanova ◽  
Marina Grigorieva
Keyword(s):  
Production Function ◽  
Financial Stability ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Industrial Sector ◽  
Economic Science ◽  
Financial Indicators ◽  
Analysis Model ◽  
Multifactor Model ◽  
Frontier Analysis

The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficiency of enterprises in the industrial sector over the period of 2017‒2018. Stochastic Frontier Analysis is based on the stochastic model of production function. The classic SFA method is based on the production function of the company, which relates the volume of output to the volume of resources consumed. At the same time, the SFA model uses several inputs (volumes of resources consumed) and only one output parameter ‒ the volume of production. In order to achieve more precise results, a given model has been modified. The model allows several key financial indicators to be taken into consideration as outputs at the same time, based on which the financial activities of the studied economic entities are assessed. The result of the work involving open sources has revealed how the efficiency of different enterprises in the same industry changes over several years. It is shown that the modified Stochastic Frontier Analysis model could be used to assess financial stability and predict bankruptcy.

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