Data for: A multiplicative environmental DEA approach to measure efficiency changes in the world's major polluters

Main Author: Roshdi, Israfil
Format: Dataset
Terbitan: Mendeley , 2016
Subjects:
Online Access: https:/data.mendeley.com/datasets/fy56j8h78n
ctrlnum 0.17632-fy56j8h78n.1
fullrecord <?xml version="1.0"?> <dc><creator>Roshdi, Israfil</creator><title>Data for: A multiplicative environmental DEA approach to measure efficiency changes in the world's major polluters </title><publisher>Mendeley</publisher><description>Abstract of associated article: We propose a multiplicative environmental data envelopment analysis (ME-DEA) approach to measure the performance of 46 countries that generate most of the world's carbon dioxide (CO2) emissions. In the model, we combine economic (labour and capital), environmental (freshwater) and energy inputs with a desirable output (GDP) and three undesirable outputs (CO2, methane and nitrous oxide emissions). We rank each country according to the optimum use of its resources employing a multiplicative extension of environmental DEA models. By computing partial efficiency scores for each input and output separately, we thus identify major sources of inefficiency for all sample countries. Based on the partial efficiency scores obtained from the model, we define aggregate economic, energy and environmental efficiency indexes for 2002, 2007 and 2011, reflecting points in time before and after the official enactment of the Kyoto Protocol. We find that for most countries efficiency scores increase over this period. In addition, there exists a positive relationship between economic and environmental efficiency, although, at the same time, our results suggest that environmental efficiency cannot be realized without first reaching a certain threshold of economic efficiency. We also find support for the Paradox of Plenty, whereby an abundance of natural and energy resources results in their inefficient use.</description><subject>Economics</subject><subject>Macroeconomics</subject><type>Other:Dataset</type><identifier>10.17632/fy56j8h78n.1</identifier><rights>Attribution-NonCommercial 3.0 Unported</rights><rights>https://creativecommons.org/licenses/by-nc/3.0</rights><relation>https:/data.mendeley.com/datasets/fy56j8h78n</relation><date>2016-12-09T14:44:37Z</date><recordID>0.17632-fy56j8h78n.1</recordID></dc>
format Other:Dataset
Other
author Roshdi, Israfil
title Data for: A multiplicative environmental DEA approach to measure efficiency changes in the world's major polluters
publisher Mendeley
publishDate 2016
topic Economics
Macroeconomics
url https:/data.mendeley.com/datasets/fy56j8h78n
contents Abstract of associated article: We propose a multiplicative environmental data envelopment analysis (ME-DEA) approach to measure the performance of 46 countries that generate most of the world's carbon dioxide (CO2) emissions. In the model, we combine economic (labour and capital), environmental (freshwater) and energy inputs with a desirable output (GDP) and three undesirable outputs (CO2, methane and nitrous oxide emissions). We rank each country according to the optimum use of its resources employing a multiplicative extension of environmental DEA models. By computing partial efficiency scores for each input and output separately, we thus identify major sources of inefficiency for all sample countries. Based on the partial efficiency scores obtained from the model, we define aggregate economic, energy and environmental efficiency indexes for 2002, 2007 and 2011, reflecting points in time before and after the official enactment of the Kyoto Protocol. We find that for most countries efficiency scores increase over this period. In addition, there exists a positive relationship between economic and environmental efficiency, although, at the same time, our results suggest that environmental efficiency cannot be realized without first reaching a certain threshold of economic efficiency. We also find support for the Paradox of Plenty, whereby an abundance of natural and energy resources results in their inefficient use.
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