Robust Analysis of Regression of Turkey's CO2 Emission Dataset
Robust Analysis of Regression of Turkey's CO2 Emission Dataset
Resumen
This study examines how Turkey's industrialization affected CO2 emissions from 1973 and 2021. The CO2 emission dataset is analyzed using least squares (LS), generalized least squares (GLS), and robust regression (RR) techniques. The mean squared error (MSE) is used to compare these regression estimate methods. The paper also looks at important regression assumptions such multicollinearity, autocorrelation, heteroscedasticity, and normality. Model selection techniques are applied in the multicollinearity detection case to remove superfluous variables. To find the best model for the CO2 emission dataset, all regression estimation methods are re-applied after variables have been eliminated. The study also examines and corrects for heteroscedasticity and autocorrelation, if they are found. This study intends to offer important insights into the environmental effects of economic development by thoroughly examining the connection between industrialization and CO2 emissions in Turkey.
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Citas
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Manski, C. F. 1991. Regression. Journal of Economic Literature, 29(1), 34-50.
Myers, R.H., Montgomery, D.C., 2002. Response Surface Methodology-Process and Product Optimization using Designed Experiments. Wiley, New York.
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Ozturk, I., &Acaravci, A. (2010). CO2 emissions, energy consumption and economic growth in Turkey. Renewable and Sustainable Energy Reviews, 14(9), 3220-3225.
Pandey, D., Agrawal, M., & Pandey, J. S. 2011. Carbon footprint: current methods of estimation. Environmental monitoring and assessment, 178, 135-160.
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Plass, G. N. (1956). Carbon dioxide and the climate. American Scientist, 44(3), 302-316.
Plass, G. N. (1955). The carbon dioxide theory of climatic change. Tellus, 8(2), 140-154.
Rousseeuw, P.J. 1984. Least median of squares regression. Journal of the American Statistical Association, 79(388), 871-880.
Rousseeuw, P.J. and Yohai, V. 1984. Robust regression by means of S-estimators. Robust and Nonlinear Time Series Analysis, edited by J. Franke, W. Härdle, and R.D. Martin, 26, 256-274. Lecture Notes in Statistics, Springer, New York.
Schwarz, G. (1978). Estimating the dimension of a model. The annals of statistics, 461-464.
Svante Arrhenius, ‘‘On the influence of carbonic acid in the air upon the temperature of the ground,’’ Philosophical Magazine and Journal of Science, 5th series, 41 (1896): 237–76.
Telatar, O. M., & Birinci, N. (2022). The effects of environmental tax on Ecological Footprint and Carbon dioxide emissions: a nonlinear cointegration analysis on Turkey. Environmental Science and Pollution Research, 29(29), 44335-44347.
Thompson, L. G. (2000). Ice core evidence for climate change in the Tropics: implications for our future. Quaternary Science Reviews, 19(1-5), 19-35.
Wang, L., Wang, L., Li, Y., & Wang, J. (2023). A century-long analysis of global warming and earth temperature using a random walk with drift approach. Decision Analytics Journal, 7, 100237.
Yohai, V.J. 1987. High breakdown-point and high efficiency robust estimates for regression. The Annals of Statistics, 15(2), 642.
Akbostancı, E., Tunç, G. İ., &Türüt-Aşık, S. (2018). Drivers of fuel based carbon dioxide emissions: The case of Turkey. Renewable and Sustainable Energy Reviews, 81, 2599-2608.
Craig, M. T., Jaramillo, P., & Hodge, B. M. 2018. Carbon dioxide emissions effects of grid-scale electricity storage in a decarbonizing power system. Environmental Research Letters, 13(1), 014004.
Callendar, G. S. (1938). The artificial production of carbon dioxide and its influence on temperature. Quarterly Journal of the Royal Meteorological Society, 64(275), 223-240.
Furnival, G. and Wilson, R. (1974). Regression by leaps and bounds. Technometrics, 16, 499–511.
Halicioglu, F. (2009). An econometric study of CO2 emissions, energy consumption, income and foreign trade in Turkey. Energy policy, 37(3), 1156-1164.
Hansen, J., & Lebedeff, S. (1988). Global surface air temperatures: Update through 1987. Geophysical Research Letters, 15(4), 323-326.
Hampel, F.R. 1978. Optimally bounding the gross-error-sensitivity and the influence of position in factor space. Proceedings of the ASA Statistical Computing Section, ASA, Washington, D.C., 59-64.
Hampel, F.R., Ronchetti, E.M., Rousseeuw, P.J. and Stahel, W.A. 1986. Robust Statistics: The Approach Based on Influence Functions, Wiley, 502 p., New York.
Huber, P.J. 1973. Robust regression: Asymptotics, conjectures and Monte Carlo. The Annals of Statistics, 1(5), 799-821.
Krasker, W.S. 1980. Estimation in linear regression models with disparate data points. Econometrica, 48(6), 1333-1346.
Krasker, W.S. and Welsch, R.E. 1982. Efficient bounded-influence regression.
Landsberg, H. E. (1970). Man-made climatic changes: man's activities have altered the climate of urbanized areas and may affect global climate in the future. Science, 170(3964), 1265-1274.
Mallows, C.L. 1975. On some topics in robustness. Technical memorandum, Bell Telephone Laboratories, Murray Hill, N.J.
Mangır, N., & Şahin, Ü. A. (2022). An environmentally extended global multi-regional input–output analysis of consumption-based and embodied import-based carbon emissions of Turkey. Environmental Science and Pollution Research, 29(36), 54813-54826.
Manski, C. F. 1991. Regression. Journal of Economic Literature, 29(1), 34-50.
Myers, R.H., Montgomery, D.C., 2002. Response Surface Methodology-Process and Product Optimization using Designed Experiments. Wiley, New York.
Ekholm, ,N. ‘‘On the variations of the climate of the geological and historical past and their causes,’’ Quarterly Journal of the Royal Meteorological Society 27, no. 117 (1901): 1–62.
Ozturk, I., &Acaravci, A. (2010). CO2 emissions, energy consumption and economic growth in Turkey. Renewable and Sustainable Energy Reviews, 14(9), 3220-3225.
Pandey, D., Agrawal, M., & Pandey, J. S. 2011. Carbon footprint: current methods of estimation. Environmental monitoring and assessment, 178, 135-160.
Paris Agreement (2015), Unıted Natıonsiçinde. https://unfccc.int/sites/default/files/english_paris_agreement. pdf adresindenerişilmiştir.
Plass, G. N. (1956). Carbon dioxide and the climate. American Scientist, 44(3), 302-316.
Plass, G. N. (1955). The carbon dioxide theory of climatic change. Tellus, 8(2), 140-154.
Rousseeuw, P.J. 1984. Least median of squares regression. Journal of the American Statistical Association, 79(388), 871-880.
Rousseeuw, P.J. and Yohai, V. 1984. Robust regression by means of S-estimators. Robust and Nonlinear Time Series Analysis, edited by J. Franke, W. Härdle, and R.D. Martin, 26, 256-274. Lecture Notes in Statistics, Springer, New York.
Schwarz, G. (1978). Estimating the dimension of a model. The annals of statistics, 461-464.
Svante Arrhenius, ‘‘On the influence of carbonic acid in the air upon the temperature of the ground,’’ Philosophical Magazine and Journal of Science, 5th series, 41 (1896): 237–76.
Telatar, O. M., & Birinci, N. (2022). The effects of environmental tax on Ecological Footprint and Carbon dioxide emissions: a nonlinear cointegration analysis on Turkey. Environmental Science and Pollution Research, 29(29), 44335-44347.
Thompson, L. G. (2000). Ice core evidence for climate change in the Tropics: implications for our future. Quaternary Science Reviews, 19(1-5), 19-35.
Wang, L., Wang, L., Li, Y., & Wang, J. (2023). A century-long analysis of global warming and earth temperature using a random walk with drift approach. Decision Analytics Journal, 7, 100237.
Yohai, V.J. 1987. High breakdown-point and high efficiency robust estimates for regression. The Annals of Statistics, 15(2), 642.
Publicado
2025-09-22
Número
Sección
Research Articles
Derechos de autor 2025 Boletim da Sociedade Paranaense de Matemática
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