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Stochastic convergence of per capita greenhouse gas emissions: New unit root tests with breaks and a factor structure

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  • Payne, James E.
  • Lee, Junsoo
  • Islam, Md. Towhidul
  • Nazlioglu, Saban

Abstract

This study examines the convergence of per capita greenhouse gas emissions for a global panel of 183 countries. Unlike previous studies that address the effects of structural breaks and cross-correlations separately, a new testing approach is proposed that jointly incorporates structural breaks and cross-correlations. Specifically, we extend the two break tests of Lee and Strazicich (2003) to allow for cross-correlations in a factor structure by adopting the PANIC procedure of Bai and Ng (2004). When accounting for structural breaks and factors, our results show that the evidence of stochastic convergence in greenhouse gas emissions is quite limited compared to other unit root tests that fail to account for cross-correlations. Policy implications of the findings are also discussed.

Suggested Citation

  • Payne, James E. & Lee, Junsoo & Islam, Md. Towhidul & Nazlioglu, Saban, 2022. "Stochastic convergence of per capita greenhouse gas emissions: New unit root tests with breaks and a factor structure," Energy Economics, Elsevier, vol. 113(C).
  • Handle: RePEc:eee:eneeco:v:113:y:2022:i:c:s0140988322003516
    DOI: 10.1016/j.eneco.2022.106201
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    1. Jiaxiong Yao & Mr. Yunhui Zhao, 2022. "Structural Breaks in Carbon Emissions: A Machine Learning Analysis," IMF Working Papers 2022/009, International Monetary Fund.
    2. Peter C. B. Phillips & Donggyu Sul, 2007. "Transition Modeling and Econometric Convergence Tests," Econometrica, Econometric Society, vol. 75(6), pages 1771-1855, November.
    3. Haoyue Wu & Hanjiao Huang & Jin Tang & Wenkuan Chen & Yanqiu He, 2019. "Net Greenhouse Gas Emissions from Agriculture in China: Estimation, Spatial Correlation and Convergence," Sustainability, MDPI, vol. 11(18), pages 1-19, September.
    4. Jushan Bai & Josep Lluís Carrion-I-Silvestre, 2009. "Structural Changes, Common Stochastic Trends, and Unit Roots in Panel Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(2), pages 471-501.
    5. Marco R. Barassi & Nicola Spagnolo & Yuqian Zhao, 2018. "Fractional Integration Versus Structural Change: Testing the Convergence of $$\hbox {CO}_{2}$$ CO 2 Emissions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(4), pages 923-968, December.
    6. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    7. Quah, Danny, 1993. "Empirical cross-section dynamics in economic growth," European Economic Review, Elsevier, vol. 37(2-3), pages 426-434, April.
    8. Menegaki, Angeliki N. & Ahmad, Nisar & Aghdam, Reza FathollahZadeh & Naz, Amber, 2021. "The convergence in various dimensions of energy-economy-environment linkages: A comprehensive citation-based systematic literature review," Energy Economics, Elsevier, vol. 104(C).
    9. Sevil Acar & Patrik Söderholm & Runar Brännlund, 2018. "Convergence of per capita carbon dioxide emissions: implications and meta-analysis," Climate Policy, Taylor & Francis Journals, vol. 18(4), pages 512-525, April.
    10. Mahamat Hamit-Haggar, 2019. "Regional and sectoral level convergence of greenhouse gas emissions in Canada," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 8(3), pages 268-282, July.
    11. Jushan Bai & Serena Ng, 2004. "A PANIC Attack on Unit Roots and Cointegration," Econometrica, Econometric Society, vol. 72(4), pages 1127-1177, July.
    12. Marrero, Gustavo A., 2010. "Greenhouse gases emissions, growth and the energy mix in Europe," Energy Economics, Elsevier, vol. 32(6), pages 1356-1363, November.
    13. Baltagi, Badi H. & Pirotte, Alain, 2010. "Panel data inference under spatial dependence," Economic Modelling, Elsevier, vol. 27(6), pages 1368-1381, November.
    14. Marco Barassi & Matthew Cole & Robert Elliott, 2011. "The Stochastic Convergence of CO 2 Emissions: A Long Memory Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 49(3), pages 367-385, July.
    15. Ghassen El-Montasser & Roula Inglesi-Lotz & Rangan Gupta, 2015. "Convergence of greenhouse gas emissions among G7 countries," Applied Economics, Taylor & Francis Journals, vol. 47(60), pages 6543-6552, December.
    16. Junsoo Lee & Mark C. Strazicich, 2003. "Minimum Lagrange Multiplier Unit Root Test with Two Structural Breaks," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1082-1089, November.
    17. Manfred Sargl & Andreas Wolfsteiner & Günter Wittmann, 2017. "The Regensburg Model: reference values for the (I)NDCs based on converging per capita emissions," Climate Policy, Taylor & Francis Journals, vol. 17(5), pages 664-677, July.
    18. Bai, Jushan, 2010. "Common breaks in means and variances for panel data," Journal of Econometrics, Elsevier, vol. 157(1), pages 78-92, July.
    19. Siriwardana, Mahinda & Nong, Duy, 2021. "Nationally Determined Contributions (NDCs) to decarbonise the world: A transitional impact evaluation," Energy Economics, Elsevier, vol. 97(C).
    20. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    21. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    22. Badi H. Baltagi & Chihwa Kao & Long Liu, 2017. "Estimation and identification of change points in panel models with nonstationary or stationary regressors and error term," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 85-102, March.
    23. Quah, D., 1990. "Galton'S Fallacy And The Tests Of The Convergence Hypothesis," Working papers 552, Massachusetts Institute of Technology (MIT), Department of Economics.
    24. Baltagi, Badi H. & Feng, Qu & Kao, Chihwa, 2016. "Estimation of heterogeneous panels with structural breaks," Journal of Econometrics, Elsevier, vol. 191(1), pages 176-195.
    25. Nazlioglu, Saban & Lee, Junsoo, 2020. "Response surface estimates of the LM unit root tests," Economics Letters, Elsevier, vol. 192(C).
    26. Kuriyama, Akihisa & Abe, Naoya, 2018. "Ex-post assessment of the Kyoto Protocol – quantification of CO2 mitigation impact in both Annex B and non-Annex B countries-," Applied Energy, Elsevier, vol. 220(C), pages 286-295.
    27. Pettersson, Fredrik & Maddison, David & Acar, Sevil & Söderholm, Patrik, 2014. "Convergence of Carbon Dioxide Emissions: A Review of the Literature," International Review of Environmental and Resource Economics, now publishers, vol. 7(2), pages 141-178, July.
    28. James E. Payne, 2020. "The convergence of carbon dioxide emissions: a survey of the empirical literature," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 47(7), pages 1757-1785, April.
    29. Meng, Ming & Payne, James E. & Lee, Junsoo, 2013. "Convergence in per capita energy use among OECD countries," Energy Economics, Elsevier, vol. 36(C), pages 536-545.
    30. E. Kuntsi‐Reunanen & J. Luukkanen, 2006. "Greenhouse gas emission reductions in the post‐Kyoto period: Emission intensity changes required under the ‘contraction and convergence’ approach," Natural Resources Forum, Blackwell Publishing, vol. 30(4), pages 272-279, November.
    31. Josep Lluís Carrion-i-Silvestre & Tomás del Barrio-Castro & Enrique López-Bazo, 2005. "Breaking the panels: An application to the GDP per capita," Econometrics Journal, Royal Economic Society, vol. 8(2), pages 159-175, July.
    32. Maamoun, Nada, 2019. "The Kyoto protocol: Empirical evidence of a hidden success," Journal of Environmental Economics and Management, Elsevier, vol. 95(C), pages 227-256.
    33. Baumol, William J, 1986. "Productivity Growth, Convergence, and Welfare: What the Long-run Data Show," American Economic Review, American Economic Association, vol. 76(5), pages 1072-1085, December.
    34. Jushan Bai, 2009. "Panel Data Models With Interactive Fixed Effects," Econometrica, Econometric Society, vol. 77(4), pages 1229-1279, July.
    35. Mariam Camarero & Juana Castillo-Giménez & Andrés Picazo-Tadeo & Cecilio Tamarit, 2014. "Is eco-efficiency in greenhouse gas emissions converging among European Union countries?," Empirical Economics, Springer, vol. 47(1), pages 143-168, August.
    36. Ivanovski, Kris & Awaworyi Churchill, Sefa, 2020. "Convergence and determinants of greenhouse gas emissions in Australia: A regional analysis," Energy Economics, Elsevier, vol. 92(C).
    37. William F. Lamb & Michael Grubb & Francesca Diluiso & Jan C. Minx, 2022. "Countries with sustained greenhouse gas emissions reductions: an analysis of trends and progress by sector," Climate Policy, Taylor & Francis Journals, vol. 22(1), pages 1-17, January.
    38. Kavuncu, Y. Okan & Knabb, Shawn D., 2005. "Stabilizing greenhouse gas emissions: Assessing the intergenerational costs and benefits of the Kyoto Protocol," Energy Economics, Elsevier, vol. 27(3), pages 369-386, May.
    39. Schmidt, Peter & Phillips, C B Peter, 1992. "LM Tests for a Unit Root in the Presence of Deterministic Trends," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 257-287, August.
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    More about this item

    Keywords

    Greenhouse gas emissions; Structural breaks; Cross-correlations; PANIC; Panel; Stochastic convergence;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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