Re-Examination of Stochastic Convergence in CO₂ Emission: Evidence from the Top 20 Highest Emitting Countries

Yıl 2025, Sayı: 43, 1 - 17, 26.12.2025

Hoşeng Bülbül

https://doi.org/10.26650/ekoist.2025.42.1454121

https://izlik.org/JA67KK59CT

Öz

Climate change is one of the most important environmental issues. International cooperation and effective policies are needed to combat this problem by reducing CO2 emissions, one of the main causes of climate change. Understanding the changes in the dynamic behaviour of CO2 emissions will contribute significantly to the development of environmental policies. This study tested the stochastic convergence hypothesis for the top 20 countries with the highest CO2 emissions. In determining whether shocks to emissions are temporary or permanent, it is crucial to accurately model dynamic behaviours such as non-linearity and structural breaks in data generation processes for the reliability of the results obtained. Otherwise, a conclusion might be reached in favour of non-stationarity. In this regard, the convergence hypothesis was tested for the period 1960-2021 by applying the KSS (2003), Kruse (2011), Fourier ADF (2010), Fourier KSS (2010), and Fourier Kruse (2019) unit root tests, which are non-linear and Fourier unit root tests. According to the unit root test results, the stochastic convergence hypothesis for per capita relative CO2 emissions is valid in 17 of the 20 countries. The findings indicate that the CO2 emissions of these countries have converged over time. Accordingly, the emission amount of countries is not independent from each other and emissions are moving towards a common environmental performance standard. Future emission behaviour for the 17 countries can be predicted and the information obtained from this can contribute to future policies. For Brazil, Iran, and Poland, the policies to be implemented will have a permanent effect.

Anahtar Kelimeler

CO2 Emission , Convergence , Fourier , Unit Root

CO₂ Emisyonunda Stokastik Yakınsamanın Yeniden İncelenmesi: En Yüksek Emisyon Yayan 20 Ülkeden Kanıtlar

https://izlik.org/JA67KK59CT

Öz

İklim değişikliği en önemli çevre sorunlarından biridir. Bu sorunla mücadele etmek için iklim değişikliğinin en önemli nedenlerinden olan CO₂ emisyonlarının azaltılmasına, uluslararası iş birliğine ve etkin politikalara ihtiyaç duyulmaktadır. CO₂ emisyonlarının dinamik davranışlarındaki değişimin anlaşılması, çevre politikalarının oluşturulmasında önemli katkı sağlayacaktır. Bu çalışmada, en yüksek CO₂ emisyonuna sahip ilk 20 ülke için Carlino ve Mills (1993) tarafından önerilen stokastik yakınsama hipotezi test edilmiştir. Emisyonlara yönelik şokların geçici mi yoksa kalıcı mı olduğunun belirlenmesinde, veri yaratma süreçlerindeki doğrusal olmama ve yapısal kırılma gibi dinamik davranışların doğru bir şekilde modellenmesi, elde edilen sonuçların güvenilirliği bakımından son derece önemlidir. Aksi durumda durağan olmama lehine bir sonuca varılabilir. Bu doğrultuda, 1960-2021 dönemi için doğrusal olmayan ve Fourier birim kök testlerinden KSS (2003), Kruse (2011), Fourier ADF (2010), Fourier KSS (2010) ve Fourier Kruse (2019) birim kök testleri uygulanarak yakınsama hipotezi test edilmiştir. Birim kök testi sonuçlarına göre, kişi başına nispi CO₂ emisyonları için stokastik yakınsama hipotezi 20 ülkeden 17'sinde geçerlidir. Bulgular, bu ülkelerin CO₂ emisyonlarının zaman içinde birbirine yakınsadığını göstermektedir. Buna göre, ülkelerin emisyon miktarı birbirinden bağımsız değildir ve emisyon ortak bir çevresel performans standardına doğru hareket etmektedir. 17 ülke için gelecekteki emisyon davranışları tahmin edilebilir ve buradan elde edilecek bilgiler ileriye dönük politikalara katkı sağlayabilir. Brezilya, İran ve Polonya için ise uygulanacak politikalar kalıcı etkiye sahip olacaktır.

Anahtar Kelimeler

CO2 Emisyonu , Yakınsama , Fourier , Birim Kök

Kaynakça

• Abadir, K. M., & Distaso, W. (2007). Testing joint hYpotheses when one of the aLternatives is one-sided. Journal of Econometrics, 140(2), 695-718. https://doi.org/10.1016/j.jeconom.2006.07.022 google scholar
• Ahmed, M., Khan, A. M., Bibi, S., & Zakaria, M. (2017). Convergence of per capita co2 emissions across the gLobe: Insights via waveLet anaLYsis. Renewable and Sustainable Energy Reviews, 75, 86-97. https://doi.org/10.1016/j.rser.2016.10.053 google scholar
• ALdY, J. E. (2006). Per capita carbon dioxide emissions: Convergence or divergence?. Environmental and Resource Economics, 33(4), 533-555. https://doi.org/10.1007/s10640-005-6160-x google scholar
• AL-Mulali, U. (2012). Factors affecting CO2 emission in the MiddLe East: A paneL data anaLYsis. Energy, 44(1), 564-569. https://doi.org/10.1016/j.energy.2012.05.045 google scholar
• AYe, G. C., & Edoja, P. E. (2017). Effect of economic growth on CO2 emission in deveLoping countries: Evidence from a dYnamic paneL threshoLd modeL. Cogent Economics & Finance, 5(1). https://doi.org/10.1080/23322039.2017.1379239 google scholar
• Bahmani-Oskooee, M., Chang, T., ELmi, Z. & Ranjbar, O.J.A.E. (2018). Re-testing prebisch - singer hYpothesis: New evidence using Fourier quantiLe unit root test. Applied Economics, 50(4), 441-454. https://doi.org/10.1080/00036846.2017.1332751 google scholar
• Bai, J., Ng, S. (2004). A PANIC attack on unit roots and cointegration. Econometrica, 72(4),1127-1177. https://doi.org/10.1111/j.1468-0262.2004.00528.xgoogle scholar
• Barassi, M.R., CoLe, M.A., ELLiott, R.J. (2008). Stochastic divergence or convergence of per capita carbon dioxide emissions: Re-Examining the evidence. Environmental and Resource Economics, 40 (1), 121-137. https://doi.org/10.1007/s10640-007-9144-1 google scholar
• Barro, R., & SaLa-i-Martin, X. (1991). Convergence across states and regions. Brookings Papers on Economic Activity, 1, 407-443. google scholar
• Becker, R., Enders, W., & Lee, J. (2006). A stationaritY test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. https://doi.org/10.1111/j.1467-9892.2006.00478.x google scholar
• Cai, Y., & Wu, Y. (2019). On the convergence of per capita carbon dioxide emission: A paneL unit root test with sharp and smooth breaks. Environmental Science and Pollution Research, 26(36), 36658-36679. https://doi.org/10.1007/s11356-019-06786-4 google scholar
• Camarero, M., Mendoza, Y., & Ordonez, J. (2011). Re-examining CO2 emissions. Is the assessment of convergence meaningLess?. Depart-ment of Applied Economics II Universidad De Valencia Working Papers,1104, 1-38.google scholar
• CarLino, G. A., & MiLLs, L. O. (1993). Are US regionaL incomes converging?: A time series anaLYsis. Journal of Monetary Economics, 32(2), 335-346. https://doi.org/10.1016/0304-3932(93)90009-5 google scholar
• Carrion-I-SiLvestre, J. L., DeL Barrio-Castro, T., & Lopez-Bazo, E. (2005). Breaking the paneLs: An appLication to the GDP per capita. The Econometrics Journal, 159-175. https://doi.org/10.1111/j.1368-423x.2005.00158.x google scholar
• Chiang, M. H., Kuan, C. M., & Lo, C. H. (2007). PaneL unit root test under smooth transition. NationaL Cheng Kung University. Taiwan, Working Paper. google scholar
• Choi, I. (2001). Unit root tests for paneL data. Journal of International Money and Finance, 20(2), 249-272. https://doi.org/10.1016/s0261-5606(00)00048-6google scholar
• Chong, T. T. L., Hinich, M. J., Liew, V. K. S., & Lim, K. P. (2008). Time series test of nonLinear convergence and transitionaL dYnamics. Eco-nomics Letters, 100(3), 337-339. https://doi.org/10.1016/j.econLet.2008.02.025 google scholar
• Christidou, M., Panagiotidis, T., & Sharma, A. (2013). On the stationaritY of per capita carbon dioxide emissions over a centurY. Economic Modelling, 33, 918-925. https://doi.org/10.1016/j.econmod.2013.05.024 google scholar
• ChristopouLos, D. K., & Leon-Ledesma, M. A. (2010). Smooth breaks and non-Linear mean reversion: Post-Bretton woods reaL exchange rates. Journal of International Money and Finance, 29(6), 1076-1093. https://doi.org/10.1016/j.jimonfin.2010.02.003 google scholar
• ChurchiLL, S. A., Inekwe, J., & Ivanovski, K. (2020). Stochastic convergence in per capita CO2 emissions: Evidence from emerging economies, 1921-2014. Energy Economics, 86, 104659. https://doi.org/l0.1016Zj.eneco.2019.104659google scholar
• DickeY, D. A., & FuLLer, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427-431. https://doi.org/10.2307/2286348google scholar
• ELLiott, G. (1999). Efficient tests for a unit root when the initiaL observation is drawn from its unconditionaL distribution. International Economic Review, 40(3), 767-784. https://doi.org/10.1111/1468-2354.00039 google scholar
• Enders, W., & Lee, J. (2004). Testing for a unit root with a nonLinear Fourier function. In Econometric SocietY 2004 Far Eastern Meetings, 457, 1-47.google scholar
• Evans, P., & Karras, G. (1996). Convergence revisited. Journal of Monetary Economics, 37(2), 249-265. google scholar
• Friedman, M. (1992) Do oLd faLLacies ever die?, Journal of Economic Literature, 30, 2129-32. google scholar
• JaLiL, A., & Mahmud, S. F. (2009). Environment Kuznets curve for CO2 emissions: A cointegration anaLYsis for China. Energy Policy, 37(12), 5167-5172. https://doi.org/10.1016/j.enpoL.2009.07.044 google scholar
• GaLeotti, M., Lanza, A., & PauLi, F. (2006). Reassessing the environmentaL Kuznets curve for CO2 emissions: A robustness exercise. Ecolog-ical Economics, 57(1), 152-163. https://doi.org/10.1016/j.ecoLecon.2005.03.031google scholar
• Güriş, B. (2019). A new nonLinear unit root test with Fourier function. Communications in Statistics-Simulation and Computation, 48(10), 3056-3062. https://doi.org/10.1080/03610918.2018.1473591 google scholar
• Hadri, K. (2000). Testing for stationaritY in heterogeneous paneL data. The Econometrics Journal, 3(2), 148-161. https://doi.org/10.1111/ 1368-423x.00043google scholar
• Hadri, K. & Kurozumi, E. (2008). A SimpLe paneL stationaritY test in the presence of cross-sectionaL dependence (No. 7). Center for Research on ContemporarY Economic SYstems, Graduate SchooL of Economics, Hitotsubashi UniversitY. google scholar
• Hansen, B. E. (1995). Rethinking the univariate approach to unit root testing: using covariates to increase power. Econometric Theory, 11(5), 1148-1171. https://doi.org/10.1017/s0266466600009993 google scholar
• Harris, D., LeYbourne, S., & Mccabe, B. (2005). Panel stationaritY tests for purchasing power paritY with cross-sectionaL dependence. Jour-nal of Business & Economic Statistics, 23(4), 395-409. https://doi.org/10.1198/073500105000000090 google scholar
• HarveY, D.I. & LeYbourne, S.J. (2007). Testing for time series LinearitY. Econometrics Journal, 10, 149-165. https://doi.org/10.1111/j.1368-423x.2007.00203.x google scholar
• HarveY, D.I., LeYbourne, S.J. And Xiao, B. (2008). A powerfuL test for LinearitY when the order of integration is unknown. Studies in Nonlinear Dynamics & Econometrics. 12 (3). https://doi.org/10.2202/1558-3708.1582google scholar
• Hu, J., & Chen, Z. (2016). A unit root test against gLobaLLY stationarY ESTAR modeLs when LocaL condition is non-stationarY. Economics Letters, 146, 89-94. https://doi.org/10.1016/j.econLet.2016.07.002 google scholar
• Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous paneLs. Journal of Econometrics, 115(1), 53-74. https:// doi.org/10.1016/s0304-4076(03)00092-7 google scholar
• IntergovernmentaL PaneL On CLimate Change. (2001). CLimate change 2001, SYnthesis Report, IPCC report. google scholar
• InternationaL EnergY AgencY. (2022). CO2 emissions in 2022. Erişim adresi: https://iea.bLob.core.windows.net/assets/3c8fa115-35c4-4474-b2371b00424c8844/CO2Emissionsin2022.pdf google scholar
• IsLam, N. (2003). What have we Learnt from the convergence debate?, Journal of Economic Surveys, 17(3), 309-362. google scholar
• Kapetanios, G., Shin, Y., & SneLL, A. (2003). Testing for a unit root in the nonLinear STAR framework. Journal of Econometrics, 112(2), 359-379. https://doi.org/10.1016/s0304-4076(02)00202-6 google scholar
• KıLıç, R. (2011). Testing for a unit root in a stationarY ESTAR process. Econometric Reviews, 30(3), 274-302. https://doi.org/10.1080/07474938.2011.553511 google scholar
• Kruse, R. (2011). A new unit root test against ESTAR based on a cLass of modified statistics. Statistical Papers, 52, 71-85. https://doi.org/10.1007/s00362-009-0204-1 google scholar
• Kwiatkowski, D., PhiLLips, P. C., Schmidt, P., & Shin, Y. (1992). Testing the nuLL hYpothesis of stationaritY against the aLternative of a unit root: How sure are we that economic time series have a unit root?. Journal of Econometrics, 54(1-3), 159-178. https://doi.org/10. 1016/0304-4076(92)90104-Y google scholar
• Lee, C. C., Chang, C. P. (2008). New evidence on the convergence of per capita carbon dioxide emissions from panel seemingly unrelated regressions augmented DickeY-FuLLer tests. EnergY, 33(9), 1468-1475. https://doi.Org/10.1016/j.energY.2008.05.002 google scholar
• Lee, C. C., Chang, C. P., & Chen, P. F. (2008). Do CO2 emission LeveLs converge among 21 OECD countries? New evidence from unit root structuraL break tests. Applied Economics Letters, 15(7), 551-556. https://doi.org/10.1080/13504850500426236 google scholar
• Lee, J., YuceL, A. G., & İslam, M. T. (2023). Convergence of CO2 emissions in OECD countries. Sustainable TechnologY and Entrepreneur-ship, 2(1), 100029. https://doi.org/10.1016/j.stae.2022.100029 google scholar
• Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: AsYmptotic and finite-sampLe properties. Journal of Economet-rics, 108(1), 1-24. https://doi.org/10.1016/s0304-4076(01)00098-7 google scholar
• LeYbourne, S., NewboLd, P., & Vougas, D. (1998). Unit roots and smooth transitions. Journal of Time Series AnalYsis, 19(1), 83-97. https:// doi.org/10.1111/1467-9892.00078 google scholar
• Li, X. L., Tang, D. P., & Chang, T. (2014). CO2 emissions converge in the 50 US states—SequentiaL PaneL SeLection Method. Economic Modelling, 40, 320-333. https://doi.org/10.1016/j.econmod.2014.04.003 google scholar
• Lumsdaine, R. L., & PapeLL, D. H. (1997). MuLtipLe trend breaks and the unit-root hYpothesis. Review of Economics and Statistics, 79(2), 212-218. https://doi.org/10.1162/003465397556791 google scholar
• Mackinnon, J. G. (1991). CriticaL vaLue for cointegration tests. Rob EngLe and C. W. J. Granger, eds., Long-Run Economic ReLationships: Readings in Cointegration, Oxford UniversitY Press, 267-287. google scholar
• MaddaLa, G. S., & Wu, S. (1999). A comparative studY of unit root tests with paneL data and a new simpLe test. Oxford Bulletin of Economics and Statistics, 61(S1), 631-652. https://doi.org/10.1111/1468-0084.0610s1631 google scholar
• Matsuki, T. (2019). Per capita output convergence across Asian countries: Evidence from covariate unit root test with an endogenous structuraL break. Economic Modelling, 82, 99-118. https://doi.org/10.1016/j.econmod.2019.03.005 google scholar
• Matsuki, T., & Pan, L. (2021). Per capita carbon emissions convergence in DeveLoping Asia: A centurY of evidence from covariate unit root test with endogenous structuraL breaks. EnergY Economics, 99, 105326. https://doi.org/10.1016/j.eneco.2021.105326 google scholar
• Moon, H. R., & Perron, B. (2004). Testing for a unit root in paneLs with dYnamic factors. Journal of Econometrics, 122(1), 81-126. https:// doi.org/10.1016/j.jeconom.2003.10.020 google scholar
• Mott, G., Razo, C., & HamweY, R. (2021). Carbon emissions anYwhere threaten deveLopment everYwhere. İn United Nations Conference on Trade and DeveLopment (UNTAD). Erişim adresi: https://unctad. org/news/carbon-emissions-anYwhere-threaten-deveLopment-everYwhere google scholar
• Park, J. Y., & Shintani, M. (2016). Testing for a unit root against transitionaL autoregressive modeLs. International Economic Review, 57(2), 635-664. https://doi.org/10.1111/iere.12171 google scholar
• PaYne, J. E., & Apergis, N. (2021). Convergence of Per capita carbon dioxide emissions among deveLoping countries: Evidence from stochastic and cLub convergence tests. Environmental Science and Pollution Research, 28, 33751-33763. https://doi.org/10.1007/s 11356-020-09506-5 google scholar
• PaYne, J. E., Lee, J., İsLam, M. T., & NazLiogLu, S. (2022). Stochastic convergence of per capita greenhouse gas emissions: New unit root tests with breaks and a factor structure. EnergY Economics, 113, 106201. https://doi.org/10.1016/j.eneco.2022.106201 google scholar
• Perron, P. (1989). The great crash, the oiL price shock, and the unit root hYpothesis. Econometrica: Journal of the Econometric SocietY, 1361-1401. https://doi.org/10.2307/1913712 google scholar
• Pesaran, M. H. (2004). GeneraL diagonist tests for cross section dependence in paneLs. Mimeo, UniversitY of Cambridge. google scholar
• 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. https://doi.org/10.1002/jae.951 google scholar
• Peter, S. C. (2018). Reduction of CO2 to chemicaLs and fueLs: A soLution to gLobaL warming and energY crisis. ACS EnergY Letters, 3(7), 1557-1561. https://doi.org/10.1021/acsenergYLett.8b00878 google scholar
• PhiLLips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. https://doi.org/10.1093/biomet/75.2.335 google scholar
• Romero-ÂviLa, D. (2008). Convergence in carbon dioxide emissions among IndustriaLised Countries Revisited. EnergY Economics, 30(5), 2265-2282. https://doi.org/10.1016/j.eneco.2007.06.003 google scholar
• SaLa-i-Martin, X. X. (1996). The cLassicaL approach to convergence anaLYsis. The Economic Journal, 106(437), 1019-1036. google scholar
• SaLahuddin, M., ALam, K., & Ozturk, I. (2016). The effects of internet usage and economic growth on CO2 emissions in OECD countries: A paneL investigation. Renewable and Sustainable EnergY Reviews, 62, 1226-1235. https://doi.org/10.1016/j.rser.2016.04.018 google scholar
• SaLiminezhad, A., & Bahramian, P. (2020). Convergence in per capita CO2 emissions: Evidence from nonLinear unit root tests in top four oiL exporter countries. International Journal of EnergY Sector Management, 14(6), 1143-1155. https://doi.org/10.1108/ijesm-10-2019-0023 google scholar
• Schwert G. W. (1989). Tests for unit roots: A Monte CarLo investigation. Journal of Business & Economlc Statistics, 7, 147-159. https://doi. org/10.2307/1391432 google scholar
• Shahbaz, M., & Sinha, A. (2019). EnvironmentaL Kuznets curve for CO2 emissions: A Literature surveY. Journal of Economic Studies, 46(1), 106-168. https://doi.org/10.1108/jes-09-2017-0249 google scholar
• Shrestha, R. M., Anandarajah, G., & LiYanage, M. H. (2009). Factors affecting CO2 emission from the power sector of seLected countries in Asia and the Pacific. Energy Policy, 37(6), 2375-2384. https://doi.org/10.1016/j.enpoL.2009.01.032 google scholar
• SohaiL, A., Du, J., Abbasi, B. N., & Ahmed, Z. (2022). The nonLinearitY and nonLinear convergence of CO2 emissions: Evidence from top 20 highest emitting countries. Environmental Science and Pollution Research, 29(39), 59466-59482. https://doi.org/10.1007/s11356-022-19470-x google scholar
• SoLarin, S. A. (2014). Convergence of CO2 emission LeveLs: Evidence from African countries. Journal of Economic Research, 19(1), 65-92. https://doi.org/10.17256/jer.2014.19.1.004 google scholar
• SoLarin, S. A. (2019). Convergence in CO2 emissions, carbon footprint and ecoLogicaL footprint: Evidence from OECD countries. Environ-mental Science and Pollution Research, 26, 6167-6181. https://doi.org/10.1007/s11356-018-3993-8 google scholar
• SoLLis, R. (2009). A simpLe unit root test against asYmmetric STAR nonLinearitY with an appLication to reaL exchange rates in Nordic countries. Economic Modelling, 26(1), 118-125. https://doi.org/10.1016/j.econmod.2008.06.002 google scholar
• SoLow, R. M. (1956). A contribution to the theorY of economic growth. The Quarterly Journal of Economics, 70(1), 65-94. google scholar
• Strazicich, M. C., & List, J. A. (2003). Are CO2 emission LeveLs converging among IndustriaL countries?. Environmental and Resource Economics, 24, 263-271. https://doi.org/10.1023/a:1022910701857 google scholar
• Tiwari, A. K., KYophiLavong, P., & ALbuLescu, C. T. (2016). Testing the stationaritY of co2 emissions series in sub-saharan african countries bY incorporating nonLinearitY and smooth breaks, Research in International Business and Finance, 37, 527-540. google scholar
• Tinbergen, J. (1959-2). The theorY of the optimum regime. in economic modeLs (Eds: L.H. KLaassen, L.M. KoYck and H.J. Witteveen), Jan Tinbergen: SeLected Papers, Amsterdam, 264-304. google scholar
• Tiwari, A. K., KYophiLavong, P., & ALbuLescu, C. T. (2016). Testing the stationaritY of CO2 emissions series in Sub-Saharan African countries bY incorporating nonLinearitY and smooth breaks. Research in International Business and Finance, 37, 527-540. https://doi.org/ 10.1016/j.ribaf.2016.01.005google scholar
• WorLd DeveLopment Indicators Database, WorLd Bank, Erişim adresi: https://databank.worLdbank.org/source/worLd-deveLopment-indicatorsgoogle scholar
• Yavuz, N. C., & YiLanci, V. (2013). Convergence in per capita carbon dioxide emissions among G7 countries: A TAR paneL unit root approach. Environmental and Resource Economics, 54, 283-291. https://doi.org/10.1007/s10640-012-9595-x google scholar
• ZakarYa, G. Y., Mostefa, B. E. L. M. O. K. A. D. D. E. M., 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. https://doi.org/10.1016/s2212-5671(15)00890-4 google scholar
• Zhou, P., & Wang, M. (2016). Carbon dioxide emissions aLLocation: A review. Ecological Economics, 125, 47-59. https://doi.org/10.1016/j. ecoLecon.2016.03.001 google scholar
• Zivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oiL-price shock, and the unit-root hYpothesis. Journal of Business & Economic Statistics, 10(3), 25-44. https://doi.org/10.2307/1391541 google scholar