Evaluation of Countries Environmental Efficiency Using Data Envelopment Analysis
محورهای موضوعی : Data Envelopment AnalysisMina Moshfegh 1 , Mohsen Rostami Malkhalifeh 2
1 - Islamic Azad University, Science and Research Branch, Tehran, Iran
2 - Islamic Azad University, Science and Research Branch
کلید واژه: Data envelopment analysis, Environmental efficiency, Anderson Peterson model,
چکیده مقاله :
Over the last few decades, there has been a dramatic increase in public attention to environmental issues. As a consequence of the growing concerns about environmental quality, climate change, and pollutant emission, which are key elements of sustainable development, one of the main challenges is measuring environmental efficiency. The main purpose of this study is to evaluate the ecological efficiency of countries and rank countries based on data envelopment analysis (DEA) method, considering the favorable and unfavorable outputs (7 inputs and 7 outputs) affecting climate change in 2020 in 176 countries. The units were evaluated by CCR model and Also AP model in order to ranking both efficient units and inefficient units. The results show that the environmental efficiency of the selected countries is 80.60% on average, of which Iran ranks 140th with an efficiency of 0.58 and Iceland, Singapore and Lesotho have the highest environmental efficiency, respectively, as well as Sierra Leon, the Philippines, and Pakistan have the lowest environmental performance, respectively.
Over the last few decades, there has been a dramatic increase in public attention to environmental issues. As a consequence of the growing concerns about environmental quality, climate change, and pollutant emission, which are key elements of sustainable development, one of the main challenges is measuring environmental efficiency. The main purpose of this study is to evaluate the ecological efficiency of countries and rank countries based on data envelopment analysis (DEA) method, considering the favorable and unfavorable outputs (7 inputs and 7 outputs) affecting climate change in 2020 in 176 countries. The units were evaluated by CCR model and Also AP model in order to ranking both efficient units and inefficient units. The results show that the environmental efficiency of the selected countries is 80.60% on average, of which Iran ranks 140th with an efficiency of 0.58 and Iceland, Singapore and Lesotho have the highest environmental efficiency, respectively, as well as Sierra Leon, the Philippines, and Pakistan have the lowest environmental performance, respectively.
Barzegarinegad, A., Jahanshahloo, G., & Rostamy-Malkhalifeh, M. (2014). A full ranking for decision making units using ideal and anti-ideal points in DEA. The Scientific World Journal, 2014.
Data envelopment analysis with R, volume 386 of studies in fuzziness and soft computing. F Hosseinzadeh Lotfi, A Ebrahimnejad, M Vaez-Ghasemi, Z Moghaddas. 2020. Springer, Cham Bottom of Form.
Farrell, M. J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society, 120, 253-281.
Fathi, B., Ashena, M., & Bahari, A. R. (2021). Energy, environmental, and economic efficiency in fossil fuel exporting countries: A modified data envelopment analysis approach. Sustainable Production and Consumption, 26, 588-596.
Hermoso-Orzáez, M. J., García-Alguacil, M., Terrados-Cepeda, J., & Brito, P. (2020). Measurement of environmental efficiency in the countries of the European Union with the enhanced data envelopment analysis method (DEA) during the period 2005–2012. In Multidisciplinary Digital Publishing Institute Proceedings , (38)1, 20
Hosseinzadeh Lotfi, F., Jahanshahloo, G. R., Khodabakhshi, M., RostamyMalkhlifeh, M., Moghaddas, Z., & Vaez-Ghasemi, M. (2013). A review of ranking models in data envelopment analysis. Journal of Applied Mathematics, 2013.
Houshangi Maryam, Emami Meibodi Ali, (2019), Measuring Technical Efficiency, Environmental Efficiency and Energy Efficiency in Desalination Plant by Data Envelopment Analysis, Journal of Environmental and Natural Resource Economics,(6)3, 131-157
Jahanshahloo, G., Lotfi, F. H., Rostamy-Malkhalifeh, M., Maddahi, R., & Ebrahimnejad, A. (2013). Ranking non-extreme efficient units based on super efficiency method in the presence of undesirable outputs: a DEA approach. International Journal of Applied Decision Sciences, 6(1), 83-95.
James D. Ward, Paul C. Sutton, Adrian D. Werner, Robert Costanza, Steve H. Mohr, Craig T. Simmons PLoS One. 2016; 11(10): e0164733.
Javidnia, Kiumars ,(2011). International environmental cooperation from Stockholm to Johannesburg (1972-2002), analyzes and reports. Foreign Policy Quarterly, (62), 572-559.
Lotfi, F. H., Navabakhs, M., Tehranian, A., Rostamy-Malkhalifeh, M., & Shahverdi,
Mamipour Siab, Najafzadeh Behnam, (2018), Three Stage Envronmental Efficiency Evaluation of Iran’s Power Industry: Network Data Envelopment Analysis Approach, Journal of Tahghighat-E-Eghtesadi, (53)2, 437-463
Mohsen Vaez-Ghasemi, Zohreh Moghaddas, Reza Farzipoor Saen. (2021), Cost efficiency evaluation in sustainable supply chains with marginal surcharge values for harmful environmental factors: a case study in a food industry, Operational Research (Springer Berlin Heidelberg),1-16
Ohadi, N., Shahraki, J., Pahlavani, M., & Mardani Najafabadi, M. (2020), Measuring Carbon-Environmental Efficiency with Imprecise Data by Using Fuzzy Data Envelopment Analysis (Case Study: Iran and Oil-Rich Countries), Journal of Sustainable Growth and Development (The Economic Research), (19)4, 111-130
Ohadi, N., Shahraki, J., Pahlavani, M., & Mardani najafabadi, M. (2019). Evaluating and Ranking of Environmental Efficiency of Oil-Rich Countries. Iranian Economic Development Analyses, 6(2), 124-146
Peykani, P., Mohammadi, E., Saen, R. F., Sadjadi, S. J., & Rostamy-Malkhalifeh,
Rasekhi Saeed, Shahrazi Milad, Sheidaee Zahra, Jafari Maryam, Dehghan Zahra, (2016), A Nexus Between Environmental and Economical Efficiency: New Evidence to Developing and Developed Countries, Journal of Economic Research and Politics, (24)78, 31-56
Sang-Heui Lee, Monica Thiel (2017). Relations between GDP growth and environmental performance using latent growth curve model applied for environmental Kuznets curve. International Journal of Sustainable Economy, 87-104.
Shahiki Tash, M., Khajeh Hasani, M., Jafari, S., (2015). Assessment of the Environmental Performance in Energy Intensive Industries of Iran by Using Directional Distance Function Approach. Quarterly Journal of Applied Theories of Economics, 2(1), 99-120.
Wang, Ke; Yu, Shiwei & Zhang, Wei. (2013). China’s Regional Energy and Environmental Efficiency: a DEA Window Analysis Based Dynamic Evaluation. Mathematical and Computer Modelling, 58(5-6), 1117-1127.
Wang, Y., Wen, Z., Cao, X., Zheng, Z., & Xu, J. (2020). Environmental efficiency evaluation of China's iron and steel industry: A process-level data envelopment analysis. Science of the Total Environment, 707, 135903.
WCED (1987) Our Common Future. World Commission on Environment and Development, Oxford University Press, Oxford/New York
Zohreh Moghaddas, Mohsen Vaez-Ghasemi, Farhad Hosseinzadehlotfi(2021), A NOVEL DEA APPROACH FOR EVALUATING SUSTAINABLE SUPPLY CHAINS WITH UNDESIRABLE FACTORS., Economic Computation & Economic Cybernetics Studies & Research, 55
