Determinants of CO2 emissions in upper middle-income group countries: an empirical investigation

Abstract

This study investigates the kinked exponential growth, degree of association, and causation between economic growth, energy consumption, population, trade openness, and carbon dioxide (CO2) emissions in 25 upper middle-income group countries spanning data from 1985 to 2014. The study employed first-generation and second-generation unit root tests; prior to that, the cross-sectional dependence test is also applied and panel cointegration techniques, panel FMOLS and DOLS, and panel causality techniques are employed to test the degree of association and causation among the variables. The study reveals a long-run cointegration among the variables. Results of FMOLS declare that there are negative associations between economic growth and CO2 emissions, trade openness, and carbon dioxide emissions respectively, whereas it was found that there are positive relations between energy consumption and CO2 emissions, population, and CO2 emissions. While analyzing the association through DOLS, we find that all the selected determinants of carbon dioxide emissions are directly proportional to CO2 emissions in these countries. The panel Granger causality test indicates that there is bi-directional causality between population and economic growth and between trade openness and economic growth. Finally, the study ends with some policy suggestions and new avenues for future research.

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Notes

  1. 1.

    International Energy Agency report 2011, entitled, “Deploying Renewables 2011: Best and Future Policy Practice.”

  2. 2.

    Kuznets (1955) defined a reversed U-shaped relation between income inequality and economic growth. Grossman and Krueger (1991) later reestablished the Kuznets curve relationship with economic growth and environmental quality deprivation. Environmental Kuznets curve is an inverse U-shaped curve which shows the connection between environmental quality and economic growth.

  3. 3.

    “Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates” (World Bank WDI, 2019).

  4. 4.

    The literacy rate may be an appropriate proxy of environment awareness only and only if the environmental science is a compulsory discipline at all the levels of formal education in these countries.

References

  1. Ahmad A, Zhao Y, Shahbaz M, Bano S, Zhang Z, Wang S, Liu Y (2016) Carbon emissions, energy consumption and economic growth: an aggregate and disaggregate analysis of the Indian economy. Energy Policy 96:131–143

    CAS  Google Scholar 

  2. Ahmad N, Du L, Lu J, Wang J, Li HZ, Hashmi MZ (2017) Modelling the CO2 emissions and economic growth in Croatia: is there any environmental Kuznets curve? Energy 123:164–172

    Google Scholar 

  3. Ang JB (2007) CO2 emissions, energy consumption, and output in France. Energy Policy 35(10):4772–4778

    Google Scholar 

  4. Antweiler W, Copeland BR, Taylor MS (2001) Is free trade good for the environment? Am Econ Rev 91(4):877–908

    Google Scholar 

  5. Apergis N (2016) Environmental Kuznets curves: new evidence on both panel and country-level CO2 emissions. Energy Econ 54:263–271

    Google Scholar 

  6. Apergis N, Ozturk I (2015) Testing environmental Kuznets curve hypothesis in Asian countries. Ecol Indic 52:16–22

    Google Scholar 

  7. Apergis N, Payne JE (2009) CO2 emissions, energy usage, and output in Central America. Energy Policy 37(8):3282–3286

    Google Scholar 

  8. Baek J, Kim HS (2013) Is economic growth good or bad for the environment? Empirical evidence from Korea. Energy Econ 36:744–749

    Google Scholar 

  9. Bai J, Perron P (1998) Estimating and testing linear models with multiple structural changes. Econometrica 66(1):47–78

    Google Scholar 

  10. Boyce JK (1986) Practitioners’ corner: kinked exponential models for growth rate estimation. Oxf Bull Econ Stat 48(4):385–391

    Google Scholar 

  11. Breusch TS, Pagan AR (1980) The Lagrange multiplier test and its applications to model specification in econometrics. Rev Econ Stud 47(1):239–253

    Google Scholar 

  12. Can M, Gozgor G (2017) The impact of economic complexity on carbon emissions: evidence from France. Environ Sci Pollut Res 24(19):16364–16370

    Google Scholar 

  13. Chakravarty D, Mandal SK (2016) Estimating the relationship between economic growth and environmental quality for the BRICS economies-a dynamic panel data approach. J Dev Areas 50(5):119–130

    Google Scholar 

  14. Chen T, Gozgor G, Koo CK, Lau CKM (2020) Does international cooperation affect CO2 emissions? Evidence from OECD countries. Environ Sci Pollut Res 27(8):8548–8556

    CAS  Google Scholar 

  15. Cole MA, Rayner AJ (2000) The Uruguay round and air pollution: estimating the composition, scale and technique effects of trade liberalization. J Int Trade Econ Dev 9(3):339–354

    Google Scholar 

  16. Dietz T, Rosa EA (1997) Effects of population and affluence on CO2 emissions. Proc Natl Acad Sci 94(1):175–179

    CAS  Google Scholar 

  17. Dogan E, Turkekul B (2016) CO 2 emissions, real output, energy consumption, trade, urbanization and financial development: testing the EKC hypothesis for the USA. Environ Sci Pollut Res 23(2):1203–1213

    Google Scholar 

  18. Dong B, Wang F, Guo Y (2016) The global EKCs. Int Rev Econ Financ 43:210–221

    Google Scholar 

  19. Fang J, Gozgor G, Lu Z, Wu W (2019) Effects of the export product quality on carbon dioxide emissions: evidence from developing economies. Environ Sci Pollut Res 26(12):12181–12193

    CAS  Google Scholar 

  20. Gill AR, Viswanathan KK, Hassan S (2018) The environmental Kuznets curve (EKC) and the environmental problem of the day. Renew Sust Energ Rev 81:1636–1642

    Google Scholar 

  21. Gozgor G (2017) Does trade matter for carbon emissions in OECD countries? Evidence from a new trade openness measure. Environ Sci Pollut Res 24(36):27813–27821

    CAS  Google Scholar 

  22. Gozgor G, Can M (2017) Does export product quality matter for CO2 emissions? Evidence from China. Environ Sci Pollut Res 24(3):2866–2875

    CAS  Google Scholar 

  23. Grether JM, Mathys NA, De Melo J (2007) Is trade bad for the environment? Decomposing world-wide SO emissions 1990-2000. Discussion Paper, University of Genevaa

  24. Grossman GM, Krueger AB (1991) Environmental impacts of a North American free-trade agreement. National Bureau of Economic Research (NBER) Working Paper 3914:1–57

    Google Scholar 

  25. Halicioglu F (2009) An econometric study of CO2 emissions, energy consumption, income and foreign trade in Turkey. Energy Policy 37(3):1156–1164

    Google Scholar 

  26. Hamit-Haggar M (2012) Greenhouse gas emissions, energy consumption and economic growth: a panel cointegration analysis from Canadian industrial sector perspective. Energy Econ 34(1):358–364

    Google Scholar 

  27. Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econ 115(1):53–74

    Google Scholar 

  28. International Energy Agency (2011) Deploying renewables 2011: best and future policy practice https://www.iea.org/newsroom/news/2011/. Accessed 11 Nov 2019

  29. Jaforullah M, King A (2017) The econometric consequences of an energy consumption variable in a model of CO2 emissions. Energy Econ 63:84–91

    Google Scholar 

  30. Jalil A, Mahmud SF (2009) Environment Kuznets curve for CO2 emissions: a cointegration analysis for China. Energy Policy 37(12):5167–5172

    Google Scholar 

  31. Jamel L, Derbali A (2016) Do energy consumption and economic growth lead to environmental degradation? Evidence from Asian economies. Cogent Econ Finance 4(1):1–19

    Google Scholar 

  32. Kao C (1999) Spurious regression and residual-based tests for cointegration in panel data. J Econ 90(1):1–44

    Google Scholar 

  33. Klasra MA (2011) Foreign direct investment, trade openness and economic growth in Pakistan and Turkey: an investigation using bounds test. Qual Quant 45(1):223–231

    Google Scholar 

  34. Knapp T, Mookerjee R (1996) Population growth and global CO2 emissions: a secular perspective. Energy Policy 24(1):31–37

    Google Scholar 

  35. Kuznets S (1955) Economic growth and income inequality. Am Econ Rev 45(1):1–28

    Google Scholar 

  36. Lean HH, Smyth R (2010) CO2 emissions, electricity consumption and output in ASEAN. Appl Energy 87(6):1858–1864

    CAS  Google Scholar 

  37. Levin A, Lin CF, Chu CSJ (2002) Unit root tests in panel data: asymptotic and finite-sample properties. J Econ 108(1):1–24

    Google Scholar 

  38. Lopez R (1994) The environment as a factor of production: the effects of economic growth and trade liberalization. J Environ Econ Manag 27(2):163–184

    Google Scholar 

  39. Nasir M, Rehman FU (2011) Environmental Kuznets curve for carbon emissions in Pakistan: an empirical investigation. Energy Policy 39(3):1857–1864

    CAS  Google Scholar 

  40. Nasreen S, Anwar S, Ozturk I (2017) Financial stability, energy consumption and environmental quality: evidence from South Asian economies. Renew Sust Energ Rev 67:1105–1122

    CAS  Google Scholar 

  41. Neve M, Hamaide B (2017) Environmental Kuznets curve with adjusted net savings as a trade-off between environment and development. Aust Econ Pap 56(1):39–58

    Google Scholar 

  42. Pal D, Mitra SK (2017) The environmental Kuznets curve for carbon dioxide in India and China: growth and pollution at crossroad. J Policy Model 39(2):371–385

    Google Scholar 

  43. Pedroni P (1999) Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxf Bull Econ Stat 61(S1):653–670

    Google Scholar 

  44. Pedroni P (2000) Fully modified OLS for heterogeneous cointegrated panels. Adv Econ 15:93–130

    Google Scholar 

  45. Pesaran MH (2007) A simple panel unit root test in the presence of cross-section dependence. J Appl Econ 22(2):265–312

    Google Scholar 

  46. Rehman MU, Rashid M (2017) Energy consumption to environmental degradation, the growth appetite in SAARC nations. Renew Energy 111:284–294

    Google Scholar 

  47. Sapkota P, Bastola U (2017) Foreign direct investment, income, and environmental pollution in developing countries: panel data analysis of Latin America. Energy Econ 64:206–212

    Google Scholar 

  48. Sarker S, Khan A, Mahmood R (2016) FDI, economic growth, energy consumption & environmental nexus in Bangladesh. Econ Appl Inform 1:33–44

    Google Scholar 

  49. Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6(2):461–464

    Google Scholar 

  50. Sebri M, Ben-Salha O (2014) On the causal dynamics between economic growth, renewable energy consumption, CO2 emissions and trade openness: fresh evidence from BRICS countries. Renew Sust Energ Rev 39:14–23

    Google Scholar 

  51. Shafik N, Bandyopadhyay S (1992) Economic growth and environmental quality: time series and cross-country evidence, Policy Research Working Paper Series 904, The World Bank, World Development Report, Washington, DC

  52. Shahbaz M, Lean HH, Shabbir MS (2012) Environmental Kuznets curve hypothesis in Pakistan: cointegration and Granger causality. Renew Sust Energ Rev 16(5):2947–2953

    Google Scholar 

  53. Shahbaz M, Hye QMA, Tiwari AK, Leitão NC (2013) Economic growth, energy consumption, financial development, international trade and CO2 emissions in Indonesia. Renew Sust Energ Rev 25:109–121

    Google Scholar 

  54. Shahbaz M, Solarin SA, Sbia R, Bibi S (2015) Does energy intensity contribute to CO2 emissions? A trivariate analysis in selected African countries. Ecol Indic 50:215–224

    Google Scholar 

  55. Shi A (2003) The impact of population pressure on global carbon dioxide emissions, 1975–1996: evidence from pooled cross-country data. Ecol Econ 44(1):29–42

    Google Scholar 

  56. Sugiawan Y, Managi S (2016) The environmental Kuznets curve in Indonesia: exploring the potential of renewable energy. Energy Policy 98:187–198

    Google Scholar 

  57. Tutulmaz O (2015) Environmental Kuznets curve time series application for Turkey: why controversial results exist for similar models? Renew Sust Energ Rev 50:73–81

    CAS  Google Scholar 

  58. World Bank (2019) World Development Indicator. https://www.worldbank.org/en/publication/wdr2019. Accessed 11 Nov 2019

  59. Zhang XP, Cheng XM (2009) Energy consumption, carbon emissions, and economic growth in China. Ecol Econ 68(10):2706–2712

    Google Scholar 

  60. Zoundi Z (2017) CO2 emissions, renewable energy and the environmental Kuznets curve, a panel cointegration approach. Renew Sust Energ Rev 72:1067–1075

    CAS  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the comments received from the conference participants and paper panellists in the 56th Annual Conference of the Indian Econometric Society (TIES), India, during 8-10 January 2020, held at School of Economics, Madurai Kamaraj University, India. The authors are thankful to Professor Kamaiah Bandi, Emeritus Professor, School of Economics, University of Hyderabad for his insightful and constructive comments on the earlier draft of this paper. We would also like to thank the editor and anonymous referees for their thoughtful and valuable comments. However, the usual disclaimer applies.

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Correspondence to Pabitra Kumar Jena.

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Mujtaba, A., Jena, P.K. & Mukhopadhyay, D. Determinants of CO2 emissions in upper middle-income group countries: an empirical investigation. Environ Sci Pollut Res (2020). https://doi.org/10.1007/s11356-020-09803-z

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Keywords

  • Carbon dioxide emissions
  • Economic growth
  • Energy consumption
  • Population
  • Trade openness
  • FMOLS and DOLS

JEL classification

  • C50
  • O13
  • Q56