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Eco-Efficiency Analysis of Swedish Regions: A second-stage DEA approach

Grabo, Lisa LU and Olsson, Josefine LU (2018) NEKN01 20181
Department of Economics
Abstract
This paper uses a two-stage data envelopment analysis (DEA) approach to measure and evaluate the relative eco-efficiency and the influencing factors of 17 out of 21 regions in Sweden during the period of 2008 and 2015. In the first stage of the DEA, a standard CCR model is used to calculate the relative eco-efficiency of the regions given multiple inputs and outputs. The model contains the variables labour, capital and energy consumption as desirable inputs, regional GDP as a desirable output and Co2 emissions as an undesirable output. On average, the results show that four regions are eco-efficiency leaders, eight are eco-efficiency followers and the remaining five are eco-efficiency moderates. The main finding from the first stage of the... (More)
This paper uses a two-stage data envelopment analysis (DEA) approach to measure and evaluate the relative eco-efficiency and the influencing factors of 17 out of 21 regions in Sweden during the period of 2008 and 2015. In the first stage of the DEA, a standard CCR model is used to calculate the relative eco-efficiency of the regions given multiple inputs and outputs. The model contains the variables labour, capital and energy consumption as desirable inputs, regional GDP as a desirable output and Co2 emissions as an undesirable output. On average, the results show that four regions are eco-efficiency leaders, eight are eco-efficiency followers and the remaining five are eco-efficiency moderates. The main finding from the first stage of the DEA is that the regions in general should concentrate on energy consumption and capital stock reduction to improve eco-efficiency. However, the results differ slightly across the regions. The second stage of the DEA constitutes a fractional logit regression model, which is used to analyse the factors influencing differences in eco-efficiency across regions. The results indicate that enterprises’ production value of goods has a significant and negative effect on eco-efficiency, whereas environmental awareness and environmental sector have positive and significant effects on eco-efficiency. Furthermore, net income and population density are insignificant. Thus, there is potential to improve eco-efficiency in regions via a reduction in energy consumption and in capital stock while keeping the output constant. A concluding remark is that guidance of national legislation should be better implemented at the regional level. Alternatively, regional legislation based on the regions’ environmental prerequisites should be implemented to a greater extent. (Less)
Popular Abstract
This paper uses a two-stage data envelopment analysis (DEA) approach to measure and evaluate the relative eco-efficiency and the influencing factors of 17 out of 21 regions in Sweden during the period of 2008 and 2015. In the first stage of the DEA, a standard CCR model is used to calculate the relative eco-efficiency of the regions given multiple inputs and outputs. The model contains the variables labour, capital and energy consumption as desirable inputs, regional GDP as a desirable output and Co2 emissions as an undesirable output. On average, the results show that four regions are eco-efficiency leaders, eight are eco-efficiency followers and the remaining five are eco-efficiency moderates. The main finding from the first stage of the... (More)
This paper uses a two-stage data envelopment analysis (DEA) approach to measure and evaluate the relative eco-efficiency and the influencing factors of 17 out of 21 regions in Sweden during the period of 2008 and 2015. In the first stage of the DEA, a standard CCR model is used to calculate the relative eco-efficiency of the regions given multiple inputs and outputs. The model contains the variables labour, capital and energy consumption as desirable inputs, regional GDP as a desirable output and Co2 emissions as an undesirable output. On average, the results show that four regions are eco-efficiency leaders, eight are eco-efficiency followers and the remaining five are eco-efficiency moderates. The main finding from the first stage of the DEA is that the regions in general should concentrate on energy consumption and capital stock reduction to improve eco-efficiency. However, the results differ slightly across the regions. The second stage of the DEA constitutes a fractional logit regression model, which is used to analyse the factors influencing differences in eco-efficiency across regions. The results indicate that enterprises’ production value of goods has a significant and negative effect on eco-efficiency, whereas environmental awareness and environmental sector have positive and significant effects on eco-efficiency. Furthermore, net income and population density are insignificant. Thus, there is potential to improve eco-efficiency in regions via a reduction in energy consumption and in capital stock while keeping the output constant. A concluding remark is that guidance of national legislation should be better implemented at the regional level. Alternatively, regional legislation based on the regions’ environmental prerequisites should be implemented to a greater extent. (Less)
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author
Grabo, Lisa LU and Olsson, Josefine LU
supervisor
organization
course
NEKN01 20181
year
type
H1 - Master's Degree (One Year)
subject
keywords
eco-efficiency, two-stage DEA model, fractional logit regression model, regional environmental performance, undesirable output
language
English
id
8949752
date added to LUP
2018-07-03 14:20:41
date last changed
2018-07-03 14:20:41
@misc{8949752,
  abstract     = {This paper uses a two-stage data envelopment analysis (DEA) approach to measure and evaluate the relative eco-efficiency and the influencing factors of 17 out of 21 regions in Sweden during the period of 2008 and 2015. In the first stage of the DEA, a standard CCR model is used to calculate the relative eco-efficiency of the regions given multiple inputs and outputs. The model contains the variables labour, capital and energy consumption as desirable inputs, regional GDP as a desirable output and Co2 emissions as an undesirable output. On average, the results show that four regions are eco-efficiency leaders, eight are eco-efficiency followers and the remaining five are eco-efficiency moderates. The main finding from the first stage of the DEA is that the regions in general should concentrate on energy consumption and capital stock reduction to improve eco-efficiency. However, the results differ slightly across the regions. The second stage of the DEA constitutes a fractional logit regression model, which is used to analyse the factors influencing differences in eco-efficiency across regions. The results indicate that enterprises’ production value of goods has a significant and negative effect on eco-efficiency, whereas environmental awareness and environmental sector have positive and significant effects on eco-efficiency. Furthermore, net income and population density are insignificant. Thus, there is potential to improve eco-efficiency in regions via a reduction in energy consumption and in capital stock while keeping the output constant. A concluding remark is that guidance of national legislation should be better implemented at the regional level. Alternatively, regional legislation based on the regions’ environmental prerequisites should be implemented to a greater extent.},
  author       = {Grabo, Lisa and Olsson, Josefine},
  keyword      = {eco-efficiency,two-stage DEA model,fractional logit regression model,regional environmental performance,undesirable output},
  language     = {eng},
  note         = {Student Paper},
  title        = {Eco-Efficiency Analysis of Swedish Regions: A second-stage DEA approach},
  year         = {2018},
}