تاثیر برخی از عوامل مؤثر بر انتشار دی اکسید کربن در کشورهای منتخب منطقه منا: رویکرد رگرسیون چندک پنل
الموضوعات :
نوشین کریمی علویجه
1
,
نرگس صالح نیا
2
,
محمدطاهر احمدی شادمهری
3
1 - دکتری اقتصاد، گروه اقتصاد، دانشکده علوم اداری و اقتصادی، دانشگاه فردوسی مشهد، مشهد، ایران.
2 - استادیار گروه اقتصاد، دانشکده علوم اداری و اقتصادی، دانشگاه فردوسی مشهد، مشهد، ایران. *(مسوول مکاتبات)
3 - دانشیار گروه اقتصاد، دانشکده علوم اداری و اقتصادی، دانشگاه فردوسی مشهد، مشهد، ایران.
تاريخ الإرسال : 13 الأربعاء , جمادى الأولى, 1441
تاريخ التأكيد : 08 الإثنين , ذو القعدة, 1441
تاريخ الإصدار : 17 السبت , ربيع الأول, 1443
الکلمات المفتاحية:
تخریب محیط زیست,
CO2,
رگرسیون چندک پنل,
ملخص المقالة :
زمینه و هدف: طی دهه های اخیر انتشار آلاینده ها و حفاظت از محیط زیست یکی از دغدغه های مهم جوامع در حال توسعه می باشد، چرا که این جوامع برای رسیدن به رشد اقتصادی بالا نیازمند استفاده از انرژی هستند و مصرف انرژی بیشتر آلودگی های زیست محیطی بیشتری را به همراه دارد. بررسی عوامل موثر بر انتشار آلاینده ها و به خصوص گاز دی اکسید کربن می تواند در برنامه ریزی برای کنترل و مدیریت آلاینده ها موثر واقع شود. هدف از این تحقیق تعیین تاثیر اندازه جمعیت، تولید ناخالص داخلی، شدت انرژی و شهرنشینی بر انتشار دی اکسید کربن در کشورهای منتخب منطقه منا طی سال های 2000-2017 است.
روش بررسی: عوامل موثر بر انتشار دی اکسید کربن در کشورهای منتخب منطقه منا با استفاده از مدل رگرسیون چندک پنل بررسی شده است. ویژگی شاخص این مدل تخمین متغیرهای مستقل در چندک‌های گوناگون و تاثیر آن‌ها بر متغیر وابسته است که با این کار دقت تخمین بسیار بالاتر رفته و می‌توان نتیجه تخمین در هر چندک را به صورت جداگانه مشاهده کرد.
یافته‌ها: یافته های تحقیق نشان می دهد که اندازه جمعیت به جز چندک‌های 05/0 و 1/0 اثر مثبت و معناداری بر گسترش دی اکسید کربن دارد. شدت انرژی و تولید ناخالص داخلی در تمامی چندک ها اثر مثبت و معناداری بر انتشار CO2دارند. رابطه شهرنشینی و دی اکسید کربن در تمامی چندک‌ها به جز 95/0 منفی و فقط در چندک های 05/0، 1/0، 7/0 و 8/0معنادار است.
بحث و نتیجه‌گیری: در این مطالعه با توجه به این که تولید ناخالص داخلی بیشترین اثرگذاری را بر میزان انتشار دی اکسید کربن دارد، لذا توصیه می‌شود که با ارتقای تکنولوژی های تولید، تعبیه زیرساخت‌های انرژی‌های تجدیدپذیر و ارائه مجوزهایی برای ورورد صنایع کمتر آلاینده کننده به کشورهای مورد بررسی، شرایطی میسر شود که رشد اقتصادی ناشی از افزایش تولید ناخالص داخلی با کمترین میزان انتشار آلاینده ها همراه باشد.
المصادر:
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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.
_||_
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.
