The Impact of Some Effective Factors on Emission of CO2 in Selected Countries of the MENA Region: Panel Quantile Regression Approach
Subject Areas :
Environmental Economics
Nooshin Karimi Alavijeh
1
,
Narges Salehnia
2
,
Mohammad Taher Ahmadi Shadmehri
3
1 - PhD of Economics, Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.
2 - Assistant Professor of Economic, Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran. *(Corresponding Author)
3 - Associate Professor of Economic, Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.
Received: 2020-01-08
Accepted : 2020-06-29
Published : 2021-10-23
Keywords:
Environment Destruction,
CO2 Gas,
Panel Quantile Regression,
Abstract :
Background and Objective: Over the past decades, emissions of pollution and environmental protection have become one of the major concerns of developing countries, because these communities need to use energy to achieve high economic growth and more energy consumption brings more environmental pollution. Investigating influencing factors on the emission of pollutants, and in particular carbon dioxide gas, can be effective in planning for the control and management of pollutants. The purpose of this study is to investigate the effect of population size, GDP, energy intensity and urbanization on carbon dioxide emissions in selected countries of the Mena region during the years 2000-2017.
Material and Methodology: Factors affecting the emission of CO2 in selected countries of the MENA region have been investigated using Panel Quantile Regression model. Important feature of this model is the estimation of independent variables in different quantiles and their effect on the dependent variable, which greatly increases the accuracy of the estimate and the result of the estimate in each quantile can be seen separately.
Findings: Research findings show that population size except for quantiles of 0.05 and 0.1 has a positive and significant effect on carbon dioxide emissions. The energy intensity and GDP at all quantiles have a positive and significant effect on CO2 emissions. The relationship between urbanization and carbon dioxide is negative at all quantiles except 0.95 and only in 0.05, 0.1, 0.7 and 0.8 quantiles is significant.
Discussion and Conclusion: In this study, given that GDP has the greatest impact on carbon dioxide emissions, it is recommended that by upgrading production technologies, preparation renewable energy infrastructure and issuing permits to enter less polluting industries into the countries studied, create the conditions that economic growth due to the increase in GDP to be accompanied by the lowest emissions of pollutants.
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Aşıcı AA. Economic growth and its impact on environment: A panel data analysis. Ecological indicators. 2013;24:324-33.
Behbudi D, Fallahi F, Barghi E. The Economical and Social Factors Effecting on CO2 Emission in Iran. journal of Economic Research. 2010;45(1):1-17. (In Persian(
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Dincer I. Environmental impacts of energy. Energy policy. 1999;27(14):845-54.
Poor Ebadolahan Kovich M, Bargi Oskoee MM, Sadeghi SK, Ghasemy i. Decomposing the Influencing Factors of CO2 Emissions of Iranian Manufacturing Industries. Journal of Applied Economics Studies in Iran. 2013;3(9):115-31. (In Persian)
Ebrahimi M, Babaey M, Kafili V. The Role of Money Market Development in the Environmental Pollution: Comparison between High and Lower Middle Income Countries Among OECD Member. Quarterly Journal of Fiscal and Economic Policies. 2017;5(19):213-36. (In Persian(
Alishiri H, Mohamadkhanli S, Mohammadbagheri A. Study of factors affecting carbon dioxide emission in the country (With refined Laspeyres decomposition analytic method). Journal of Environmental Science and Technology. 2017;19(2):51-62. (In Persian(
Arouri MEH, Youssef AB, M'henni H, Rault C. Energy consumption, economic growth and CO2 emissions in Middle East and North African countries. Energy policy. 2012;45:342-9.
jafari Samimi A, Mohammadi Khyareh M. Short run and Long run Relationship among CO2 Emissions, Energy Consumption and Economic Growth: New Evidence from Iran. Journal of Economic Research. 2014;14(2):1-20. (In Persian(
Tamizi A. Determinants of CO2 Emissions in Developing Countries using Bayesian Econometric Approach. Applied Theories of Economics. 2015;2(4):145-68. (In Persian(
Çetin M, Ecevit E. Urbanization, energy consumption and CO 2 emissions in Sub Saharan countries: a panel cointegration and causality Journal of Economics and Development Studies. 2015;3(2):66-76.
Xu B, Lin B. A quantile regression analysis of China's provincial CO2 emissions: Where does the difference lie? Energy Policy. 2016;98:328-42.
Behera SR, Dash DP. The effect of urbanization, energy consumption, and foreign direct investment on the carbon dioxide emission in the SSEA (South and Southeast Asian) region. Renewable Sustainable Energy Reviews. 2017;70:96-106.
Bilgili F, Koçak E, Bulut Ü. The dynamic impact of renewable energy consumption on CO2 emissions: a revisited Environmental Kuznets Curve approach. Renewable Sustainable Energy Reviews. 2016;54:838-45.
Stern DI. A multivariate cointegration analysis of the role of energy in the US macroeconomy. Energy Economics. 2000;22(2):267-83.
Shim J. The Reform of Energy Subsidies for the Enhancement of Marine Sustainability. Case Study of South Korea, University of Delaware p3. 2006.
Kuznets S. Economic growth and income inequality. The American Economic 1955;45(1):1-28.
Bargi Oskoee MM. The Impact of Trade Liberalization on the Greenhouse Gases (CO2Emission) in EKC. Journal of Economic Research. 2008;43(1):1-21. (In Persian(
Falahi F, Hekmati Farid S. Determinants of CO2 Emissions in the Iranian Provinces (Panel Data Approach). Journal of Iranian Energy Economics. 2015;2(6):129-50. (In Persian(
Shi A. The impact of population pressure on global carbon dioxide emissions, 1975–1996: evidence from pooled cross-country data. Ecological Economics. 2003;44(1):29-42.
Alam S, Fatima A, Butt MS. Sustainable development in Pakistan in the context of energy consumption demand and environmental degradation. Journal of Asian Economics. 2007;18(5):825-37.
Saadat R, Sadeghi H. Population Growth, Economic Growth, and Environmental Impacts in Iran (A Causal Analysis). Journal of Economic Research. 2004;39(1):163-80. (In Persian(
Koenker R, Bassett Jr G. Regression quantiles. Econometrica: journal of the Econometric Society. 1978:33-50.
Powell JL. Least absolute deviations estimation for the censored regression model. Journal of Econometrics. 1984;25(3):303-25.
Mohammadzadeh Asl N, Seifi Pour R, Mehrabian A. The Impact of the Return of Research and Development on Economic Growth (Using Regression Quintiles Model). Journal of Economics and Business Research. 2017;8(15):1-14.
Bameni Moghadam M, Khoshgooyan Fard A. The Application of the Quantile Regression in Finding the Distribution of Expected Welfare. Journal of Social Welfare. 2005; 56-43:(15)4. (In Persian(
Davino C, Furno M, Vistocco D. Quantile regression: theory and applications: John Wiley & Sons; 2013.
Zhu H, Duan L, Guo Y, Yu K. The effects of FDI, economic growth and energy consumption on carbon emissions in ASEAN-5: evidence from panel quantile regression. Economic Modelling. 2016;58:237-48.
Lancaster T. The incidental parameter problem since 1948. Journal of Econometrics. 2000;95(2):391-413.
Neyman J, Scott EL. Consistent estimates based on partially consistent observations. Econometrica: journal of the Econometric Society. 1948;16(1):1-32.
Canay IA. A simple approach to quantile regression for panel data. The Econometrics Journal. 2011;14(3):368-86.
Alexander M, Harding M, Lamarche C. Quantile regression for time-series-cross-section data. International Journal of Statistics Management System. 2011;6(1-2):47-72.
Lamarche C. Measuring the incentives to learn in Colombia using new quantile regression approaches. Journal of Development Economics. 2011; 96(2):88-278.
Damette O, Delacote P. On the economic factors of deforestation: What can we learn from quantile analysis? Economic Modelling. 2012;29(6):2427-34.
Lin S, Zhao D, Marinova D. Analysis of the environmental impact of China based on STIRPAT model. Environmental Impact Assessment Review. 2009;29(6):341-7.
Aşıcı AA. Economic growth and its impact on environment: A panel data analysis. Ecological indicators. 2013;24:324-33.
Behbudi D, Fallahi F, Barghi E. The Economical and Social Factors Effecting on CO2 Emission in Iran. journal of Economic Research. 2010;45(1):1-17. (In Persian(
Salehnia, N., Karimi Alavijeh, N. & Salehnia, N. Testing Porter and pollution haven hypothesis via economic variables and CO2emissions: a cross-country review with panel quantile regression method. Environ Sci Pollut Res. 2020. https://doi.org/10.1007/s11356-020-09302-1.