Co2 Emisyonlarını Etkileyen Faktörlerin Zamanla Değişen Katsayılı Parametrik Olmayan Panel Veri Modelleri ile Analizi

Abstract

İklim değişikliğinin, küresel ısınmanın ve çevresel bozulmanın bir nedeni olarak karbondioksit (CO2) emisyonlarından oluşan sera gazları gösterilmektedir. CO2 yeryüzüne insan faaliyetleri nedeniyle yayılarak genellikle çevreye zarar verir ve iklim değişikliğine veya küresel ısınmaya yol açar. Bu sebeple CO2 emisyonlarını etkileyen ekonomik ve ekonomik olmayan birçok sosyal faktör araştırmalara konu olmuştur. Ancak çoğu araştırmada CO2 emisyonları konusunda hem ekonomik büyüme hem de enerji kullanımı gibi ana faktörleri de etkileyen ekonomik belirsizlik dikkate alınmamıştır. Bu çalışmada kişi başına düşen CO2 emisyonları ve başta ekonomik belirsizlik (dünya belirsizlik indeksi ile ölçülen) olmak üzere diğer değişkenler arasındaki ilişki ele alınmıştır. 14 OECD ülkesinin 2000-2021 yılları arasındaki verileri zamanla değişen katsayılı parametrik olmayan panel veri modeliyle incelenmiştir. Trend fonksiyonları ve parametrik olmayan katsayı fonksiyonları tahmin edilerek doğrusal olmayan sonuçlara ulaşılmıştır. Parametrik olmayan katsayı fonksiyonlarının CO2 emisyonları üzerinde etkisi zaman içerisinde değişiklik göstermektedir. Sonuçlarımıza göre ele alınan dönem boyunca ekonomik belirsizlik ile CO2 emisyonları arasında ters yönlü bir ilişki bulunmaktadır ve zaman içerisinde düşüş eğiliminde devam etmektedir. Kişi başına düşen GSYH, nüfus ve yenilenebilir enerjinin parametrik olmayan katsayıları zaman içerisinde negatif ve pozitif olarak değişmektedir. Ticaret 2000’li yıllarında başında anlamsız bir değişken olmasına rağmen 2009-2013 yılları arasında anlamlı bir değişkendir, ancak 2021 yılında etkisi tekrar anlamsızlaşmıştır.

Keywords

• Parametrik olmayan panel veri
• zamanla değişen katsayı fonksiyonları
• CO2 Emisyonları

Analyzing the Factors Affecting CO2 Emissions Using Nonparametric Time Varying Coefficient Panel Data Models

Abstract

Carbon dioxide (CO2) emissions and other greenhouse gases are one of the reasons for climate change, global warming, and environmental degradation. CO2 is distributed throughout the Earth’s surface by human activity and is often harmful to the environment by causing climate change (i.e., global warming). Therefore, the literature has examined many economic and noneconomic social factors that affect CO2 emissions. However, most studies, have ignored the economic uncertainty regarding CO2 emissions effects on main factors such as economic growth and energy use. This study, discusses the relationships per capita CO2 emissions has with other variables, especially economic uncertainty as measured by the World Uncertainty Index. This article examines the relationship by utilizing the data for 14 OECD countries between 2000-2021 using a non-parametric panel data model with time-varying coefficients. By estimating trend functions and nonparametric coefficient functions, the study’s results show nonparametric coefficient functions on CO2 emissions to vary with time. In terms of signs and significance, the nonparametric coefficient function for economic uncertainty had a significant negative effect over the 2000-2021 period. In addition, economic uncertainty sustained a negative impact over time. The signs for nonparametric coefficients regarding GDP per capita, population, and renewable energy were seen to fluctuate, alternating between negative and positive values over time. Although trade was insignificant during the early 2000s, it became a significant variable between 2009-2013, while having no significant sustained effect in 2021.

Keywords

• nonparametric panel data
• time-varying coefficient function
• CO2 emissions

References

1. Adams, S., Adedoyin, F., Olaniran, E., Bekun, FV. (2020) Energy consumption, economic policy uncertainty and carbon emissions; causality evidence from resource rich economies. Economic Analysis and Policy, 68, 179-190. google scholar
2. Adedoyin, F., Olaniran, E., & Bekun, F.V. (2020). Energy consumption, economic policy uncertainty and carbon emissions; causality evidence from resource rich economies. Economic Analysis and Policy, 68,79-190. google scholar
3. Adedoyin, F., & Zakari, A. (2020). Energy consumption, economic expansion, and CO2 emission in the UK: The role of economic policy uncertainty. Science of the Total Environment, 738, 140014. google scholar
4. Ahir, H., Bloom, N., & Furceri, D. (2022). The world uncertainty index . [Working paper no. 29763]. National Bureau of Economic Reserach. google scholar
5. Anser, M.K, Apergis, N., & Syed, Q.R. (2021). Impact of economic policy uncertainty on CO2 emissions: evidence from top ten carbon emitter countries. Enviromental Science and Pollution Research, 28, 29369-29378. google scholar
6. Antonakakis, N, Chatziantoniou, I., & Filis, G. (2017). Energy consumption, CO2 emissions, and economic growth: An ethical dilemma. Renewable Sustainable Energy Reviews, 68 808-24. google scholar
7. Azka, A., & Eyup, D., (2021) The role of economic policy uncertainty in the energy-environment nexus for China: evidence from the novel dynamic simulations method. Journal of Environmental Management, 292, 112865. google scholar
8. Baker, S.R., Bloom, N., & Davis, S.J. (2016). Measuring Economic Policy Uncertainty. The Quarterly Journal of Economics, 131, 1593-1636. google scholar

9. Baker, S.R., Bloom, N., Davis, S.J., & Terry S.J. (2020). National Bureau of Economic Research; 2020. Covid-induced economic uncertainty. google scholar
10. Breusch, T., & Pagan, A. (1980) The Lagrange multiplier test and its application to model specifications in econometrics. The Review of Economic Studies, 47, 239-253. google scholar
11. Cowan, W.N., Chang, T., Inglesi-Lotz, R., & Gupta, R. (2014). The nexus of electricity 600 consumption, economic growth and CO2 emissions in the BRICS countries. Energy Policy, 601(66),359-368. google scholar
12. Danish, Ulucak, R., & Khan,S.U.D. (2020). Relationship between energy intensity and CO2 emissions: does economic policy matter? Sustainable Development, 28 (5), 1457-1464. google scholar
13. De, H., Rafael, E., & Sarafidis, V. (2006). Testing for Cross-Sectional Dependence in Panel Data Models. The Stata Journal: Promoting Communications on Statistics and Stata 6(4), 482-96. google scholar
14. Dong, K., Hochman, G., Zhang, Y., Sun, R., Li, H., & Liao, H. (2018). CO2 emissions, economic and population growth, and renewable energy: Empirical evidence across regions. Energy Economics,75, 180-192. google scholar
15. EPU Economic Policy Uncertainty Index. https://www.policyuncertainty.com. google scholar
16. Gulen, H., & Ion, M. (2016). Policy uncertainty and corporate investment. The Review of Financial Studies, 29(3), 523-564. google scholar
17. Güriş, B., (2015). Panel Kırılmalı Birim Kök Testleri ve Eşbütünleşme, S. Güriş (Ed.) içinde Stata ile Panel Veri Modelleri (s.281-287), İstanbul, Der Yayınları. google scholar
18. Grossman, G.M., & Krueger, A.B. (1991). Environmental impacts ofa North American free trade agreement.Working Paper No. 3914. National Bureau of Economic Research, Cambridge. google scholar
19. Huang, Y., Chen, F., Wei, H., Xiang, J., Xu, Z., & Akram, R. (2022). The Impacts of FDI Inflows on Carbon Emissions: Economic Development and Regulatory Quality as Moderators. Frontiers in Energy Research, 9, 938. google scholar
20. Im, K.S., Pesaran,M.H., & Shin,Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics,115 (1), 53-74. google scholar
21. Jiang, Y., Zhou, Z., & Liu, C. (2019). Does economic policy uncertainty matter for carbon emission? Evidence from US sector level data. Environmental Science and Pollution Research, 26(24),24380-24394. google scholar
22. Jebli, M.B., & Youssef, S.B. (2017). The role of renewable energy and agriculture in reducing CO2 emissions: evidence for North Africa countries. Ecological Indicators, 74, 295-301. google scholar
23. Kendall, M.G., 1975. Rank Correlation Methods. Griffin, London. google scholar
24. Li, D., Chen, J., & Gao, J. (2011). Nonparametric time varying coefficient panel data models with fixed effects”. The Econometrics Journal, 14(3):387-408. google scholar
25. Mann, H.B. (1945). Nonparametric tests against trend. Econometrica 13(3):245. google scholar
26. Mammen, E. (1993). Bootstrap and wild bootstrap for high dimensional linear models. Ann. Stat. 21 (1), 255-285. google scholar
27. Pesaran, M.H. (2004). General diagnostic tests for cross section dependence in panels. CESifo Working Paper Series No. 1229. google scholar
28. Pesaran, M.H. (2007). A simple panel unit root test in the presence of cross-section dependence, Journal of Applied Econometrics, 22 (2), 265-312. google scholar
29. Pirgaip, B., & Dincergok, B. (2020). Economic policy uncertainty, energy consumption and carbon emissions in G7 countries: evidence from a panel Granger causality analysis. Environmental Science and Pollution Research, 27, 30050-30066. google scholar
30. Silvapulle, P., Smyth, R., Zhang, X., & Fenech, J.P., 2017. Nonparametric panel data model for crude oil and stock market prices in net oil importing countries. Energy Economics, 67, 255-267. google scholar
31. Syed, Q.R., & Bouri, E. (2022). Impact of economic policy uncertainty on CO2 emissions in the US: Evidence from bootstrap ARDL approach. Journal of Public Affairs, 2, e2595. google scholar
32. Şak, N. (2015). Panel Birim Kök Testleri,S, Güriş (Ed.) içinde Stata ile Panel Veri Modelleri, (203-264), İstanbul, Der Yayınları. google scholar
33. Ulucak, R., & Khan S. (2020) Relationship between energy intensity and CO2 emissions: does economic policy matter? Sustainable Development, 28,1457-1464. google scholar
34. Uddin, M., Vinod Mishra, V., & Smyth, R. (2020). Income inequality and CO2 emissions in the G7, 1870-2014: Evidence from non-parametric modelling. Energy Economics, 88, 104780. google scholar
35. Wang, Q., Jiang, X.T., Ge, S., & Jiang, R. (2019). Is Economic Growth Compatible with a Reduction in CO2 Emissions? Empirical Analysis of the United States. Resources Conservation and Recycling, 151, 104443. google scholar
36. Wang, Q., Xiao, K., & Lu, Z. (2020). Does Economic Policy Uncertainty Affect CO2 Emissions? Empirical Evidence from the United States. Sustainability, 12, 9108. google scholar
37. Wu, C.F.J., (1986). Jackknife, bootstrap and other resampling methods in regression analysis. The Annals of Statistics, 14 (4), 1261-1295. google scholar
38. Yang, L. (2019) Connectedness of economic policy uncertainty and oil price shocks in a time domain perspective. Energy Economics, 80, 219-233. google scholar
39. Zakarya, G.Y., Mostefa, B., Abbes, S.M. & Seghir, G.M. (2015). Factors Affecting CO2 Emissions in the BRICS Countries: A Panel Data Analysis. Procedia Economics and Finance, 26, 114-125. google scholar