scholarly journals Manufacturing productivity and energy efficiency: a stochastic efficiency frontier analysis

2015 ◽  
pp. n/a-n/a ◽  
Author(s):  
Huanyi Shui ◽  
Xiaoning Jin ◽  
Jun Ni
Keyword(s):  
Energy Efficiency ◽  
Efficiency Frontier ◽  
Frontier Analysis ◽  
Manufacturing Productivity

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 The cost efficiency of Vietnamese banks – the difference between DEA and SFA

2020 ◽  
Vol 22 (2) ◽  
pp. 209-227
Author(s):  
Phong Hoang Nguyen ◽  
Duyen Thi Bich Pham
Keyword(s):  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Random Noise ◽  
Stochastic Frontier ◽  
Time Consistency ◽  
Efficiency Frontier ◽  
Content Type ◽  
Frontier Analysis ◽  
The Difference ◽  
The Cost

PurposeThe paper aims to enrich previous findings for an emerging banking industry such as Vietnam, reporting the difference between the parametric and nonparametric methods when measuring cost efficiency. The purpose of the study is to assess the consistency in issuing policies to improve the cost efficiency of Vietnamese commercial banks.Design/methodology/approachThe cost efficiency of banks is assessed through the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA). Next, five tests are conducted in succession to analyze the differences in cost efficiency measured by these two methods, including the distribution, the rankings, the identification of the best and worst banks, the time consistency and the determinants of efficiency frontier. The data are collected from the annual financial statements of Vietnamese banks during 2005–2017.FindingsThe results show that the cost efficiency obtained under the SFA models is more consistent than under the DEA models. However, the DEA-based efficiency scores are more similar in ranking order and stability over time. The inconsistency in efficiency characteristics under two different methods reminds policy makers and bank administrators to compare and select the appropriate efficiency frontier measure for each stage and specific economic conditions.Originality/valueThis paper shows the need to control for heterogeneity over banking groups and time as well as for random noise and outliers when measuring the cost efficiency.

Service quality in Brazilian mobile telephony: an efficiency frontier analysis

2009 ◽  
Vol 41 (18) ◽  
pp. 2299-2307 ◽  
Author(s):  
Marcelo Resende ◽  
Henrique César Tupper
Keyword(s):  
Service Quality ◽  
Mobile Telephony ◽  
Efficiency Frontier ◽  
Frontier Analysis

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.

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