Literature DB >> 35384539

The nonlinearity and nonlinear convergence of CO2 emissions: Evidence from top 20 highest emitting countries.

Ali Sohail1, Jinfeng Du2, Babar Nawaz Abbasi3, Zahoor Ahmed4,5.   

Abstract

Carbon dioxide (CO2) is the most prevalent greenhouse gas that triggers climate change, which in turn leads to catastrophic effects on trade, business, human health, and other areas. Understanding the characteristics and tendency of CO2 emissions will improve policy making and mitigation strategies. Understanding the linearity or nonlinearity and convergence or divergence of CO2 emissions is essential for selecting appropriate modeling techniques and for designing reliable policies. Therefore, this paper investigates the nonlinearity and nonlinear convergence of CO2 emissions among the world's top 20 highest emitting countries, which account for 80% of the world's total emissions. To check the nonlinearity of CO2 emissions, the McLeod-Li nonlinearity test, the Terasvirta nonlinearity test, and the Brock-Dechert-Scheinkman-LeBaron nonlinearity test are employed. The convergence or divergence of CO2 emissions is checked by using the Kilic nonlinear unit root test, the Hu and Chen nonlinear unit root test, and the Park and Shintani nonlinear unit root test. The findings revealed that the CO2 emissions process in all the 20 countries is nonlinear; 17 countries exhibit convergence in CO2 emissions while the other 3 countries diverged from 1960 to 2018. Based on the results, the nonlinear nature of CO2 emissions requires special attention from scholars when selecting estimation techniques for CO2 emissions. For countries with convergence, emissions trends can be used to forecast future values of CO2 emissions. Moreover, strong policy actions are required to achieve convergence in the countries with divergence.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Keywords:  CO2 emissions; Convergence test; Environmental sustainability; Nonlinearity test

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Year:  2022        PMID: 35384539     DOI: 10.1007/s11356-022-19470-x

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   5.190


  1 in total

1.  Spatiotemporal Variations of Carbon Emissions and Their Driving Factors in the Yellow River Basin.

Authors:  Shiqing Wang; Piling Sun; Huiying Sun; Qingguo Liu; Shuo Liu; Da Lu
Journal:  Int J Environ Res Public Health       Date:  2022-10-08       Impact factor: 4.614

  1 in total

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