Analyzing asymmetric impact of economic growth, energy use, FDI inflows, and oil prices on CO2 emissions through NARDL approach

Abstract

Even though numerous studies explore the impact of macroeconomic variables on carbon dioxide (CO2) emissions, only a few existing studies estimate the asymmetric impact and causality. By considering the significance of asymmetries, this study investigates the asymmetric impact of economic growth, energy use, and foreign direct investment inflows on CO2 emissions in India wherein oil prices are included as additional variable. The kinked exponential growth of these variables over the period 1986–2014 is also estimated. To this end, nonlinear autoregressive distributed lag (NARDL) model and asymmetric causality test are used. The results show that increase in economic growth would decrease CO2 emissions, while a reduction in economic growth would increase CO2 emissions which implies an inverted U-shaped link between economic growth and CO2 emissions. The positive and negative shocks in oil prices have a favorable and significant impact on CO2 emissions as well. Furthermore, the energy consumption with positive shock shows a positive and significant impact on CO2 emission. Besides, the findings of foreign direct investment inflows support the pollution heaven hypothesis. In light of these results, this study also suggested some policy implications and future research avenues in the concluding section.

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Data availability

Data used in this study can be found in the cited link.

Notes

  1. 1.

    The literature survey is based on the four renowned scholarly databases; Google scholars, JSTOR, PubMed, and ResearchGate.

  2. 2.

    The beginning point is selected on the basis of crude oil prices which is available only from 1986 and the end point is also selected on the basis of CO2 emissions and energy consumptions’ data, which are available only up to 2014 on WDI-2020.

References

  1. AhAtil A, Bouheni FB, Lahiani A, Shahbaz M (2019) Factors influencing CO2 emission in China: a nonlinear autoregressive distributed lags investigation

    Google Scholar 

  2. Aliyu MA (2005) Foreign direct investment and the environment: pollution haven hypothesis revisited. In Eight Annual Conference on Global Economic Analysis, Lübeck, Germany, pp 9–11

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

    Article  Google Scholar 

  4. Antón A (2020) Taxing crude oil: A financing alternative to mitigate climate change? Energy Policy 136:111031

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

  9. Baloch A, Shah SZ, Habibullah MS, Rasheed B (2020) Towards connecting carbon emissions with asymmetric changes in economic growth: evidence from linear and nonlinear ARDL approaches. Environ Sci Pollut Res:1–19

  10. Baz K, Xu D, Ampofo GMK, Ali I, Khan I, Cheng J, Ali H (2019) Energy consumption and economic growth nexus: new evidence from Pakistan using asymmetric analysis. Energy 189:116254

    Article  Google Scholar 

  11. Boyce JK (1986) PRACTITIONERS’CORNER: Kinked exponential models for growth rate estimation. Oxf Bull Econ Stat 48(4):385–391

    Article  Google Scholar 

  12. Brock WA, Dechert WD, Scheinkman J, LeBaron B (1987) A test for independence based upon the correlation dimension. Department of Economics, University of Wisconsin, University of Houston, and the University of Chicago

  13. Broock WA, Scheinkman JA, Dechert WD, LeBaron B (1996) A test for independence based on the correlation dimension. Econ Rev 15(3):197–235

    Article  Google Scholar 

  14. Brown RL, Durbin J, Evans JM (1975) Techniques for testing the constancy of regression relationships over time. J R Stat Soc Ser B Methodol 37(2):149–163

    Google Scholar 

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

    Article  Google Scholar 

  16. Chen T, Gozgor G, Koo CK, Lau CKM (2020) Does international cooperation affect CO 2 emissions? Evidence from OECD countries. Environ Sci Pollut Res:1–9

  17. Dickey DA, Fuller WA (1979) Distribution of the estimators for autoregressive time series with a unit root. J Am Stat Assoc 74(366a):427–431

    Article  Google Scholar 

  18. Dogan E, Ozturk I (2017) The influence of renewable and non-renewable energy consumption and real income on CO 2 emissions in the USA: evidence from structural break tests. Environ Sci Pollut Res 24(11):10846–10854

    Article  Google Scholar 

  19. Dogan E, Seker F (2016) Determinants of CO2 emissions in the European Union: the role of renewable and non-renewable energy. Renew Energy 94:429–439

    CAS  Article  Google Scholar 

  20. 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

    Article  Google Scholar 

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

    Article  Google Scholar 

  22. Erdogan S, Okumus I, Guzel AE (2020) Revisiting the Environmental Kuznets Curve hypothesis in OECD countries: the role of renewable, non-renewable energy, and oil prices. Environ Sci Pollut Res:1–9

  23. Esty DC, Porter ME (1998) Industrial ecology and competitiveness: strategic implications for the firm. J Ind Ecol 2(1):35–43

    Article  Google Scholar 

  24. Etokakpan MU, Solarin SA, Yorucu V, Bekun FV, Sarkodie SA (2020) Modeling natural gas consumption, capital formation, globalization, CO2 emissions and economic growth nexus in Malaysia: Fresh evidence from combined cointegration and causality analysis. Energy Strateg Rev 31:100526

    Article  Google Scholar 

  25. Fatima T, Shahzad U, Cui L (2020) Renewable and nonrenewable energy consumption, trade and CO2 emissions in high emitter countries: does the income level matter? J Environ Plan Manag:1–25

  26. 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

    Article  Google Scholar 

  27. 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  Article  Google Scholar 

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

    Article  Google Scholar 

  29. Hatemi-j A (2012) Asymmetric causality tests with an application. Empir Econ 43(1):447–456

    Article  Google Scholar 

  30. Inglesi-Lotz R, Dogan E (2018) The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub-Saharan Africa’s Βig 10 electricity generators. Renew Energy 123:36–43

    Article  Google Scholar 

  31. International Energy Agency (2019) Global Energy Review 2019. http://www.iea.org/reports/global-energy-review-2019 Accessed 17 Sept 2020

  32. International Energy Agency (2020) World Energy Outlook 2020. https://www.iea.org/reports/world-energy-outlook-2020. Accessed 17 Sept 2020

  33. Jaffe AB, Palmer K (1997) Environmental regulation and innovation: a panel data study. Rev Econ Stat 79(4):610–619

    Article  Google Scholar 

  34. Lau LS, Choong CK, Ng CF, Liew FM, Ching SL (2019) Is nuclear energy clean? Revisit of Environmental Kuznets Curve hypothesis in OECD countries. Econ Model 77:12–20

    Article  Google Scholar 

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

    CAS  Article  Google Scholar 

  36. Lin B, Jia Z (2020) Economic, energy and environmental impact of coal-to-electricity policy in China: a dynamic recursive CGE study. Sci Total Environ 698:134241

    CAS  Article  Google Scholar 

  37. Mihci H, Cagatay S, Koska O (2005) The impact of environmental stringency on the foreign direct investments of the OECD countries. J Environ Assess Policy Manag 7(04):679–704

    Article  Google Scholar 

  38. Mujtaba A, Jena PK, Mukhopadhyay D (2020) Determinants of CO2 emissions in upper middle-income group countries: an empirical investigation. Environ Sci Pollut Res 27(30):37745–37759

    CAS  Article  Google Scholar 

  39. Nathaniel S, Nwodo O, Adediran A, Sharma G, Shah M, Adeleye N (2019) Ecological footprint, urbanization, and energy consumption in South Africa: including the excluded. Environ Sci Pollut Res 26(26):27168–27179

    Article  Google Scholar 

  40. Nathaniel SP, Nwulu N, Bekun F (2020a) Natural resource, globalization, urbanization, human capital, and environmental degradation in Latin American and Caribbean countries. Environ Sci Pollut Res:1–15

  41. Nathaniel S, Anyanwu O, Shah M (2020b) Renewable energy, urbanization, and ecological footprint in the Middle East and North Africa region. Environ Sci Pollut Res:1–13

  42. 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

    Article  Google Scholar 

  43. Ozcan B, Tzeremes P, Dogan E (2019) Re-estimating the interconnectedness between the demand of energy consumption, income, and sustainability indices. Environ Sci Pollut Res 26(26):26500–26516

    Article  Google Scholar 

  44. 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

    Article  Google Scholar 

  45. Phillips PC, Perron P (1988) Testing for a unit root in time series regression. Biometrika 75(2):335–346

    Article  Google Scholar 

  46. Porter ME (1991) America’s green strategy," Scientific American, April p 96

  47. Porter ME, Van der Linde C (1995) Toward a new conception of the environment-competitiveness relationship. J Econ Perspect 9(4):97–118

    Article  Google Scholar 

  48. Raggad B (2020) Economic development, energy consumption, financial development, and carbon dioxide emissions in Saudi Arabia: new evidence from a nonlinear and asymmetric analysis. Environ Sci Pollut Res:1–20

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

    Article  Google Scholar 

  50. 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

    Article  Google Scholar 

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

    Article  Google Scholar 

  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

    Article  Google Scholar 

  53. 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

    Article  Google Scholar 

  54. Shahbaz, M., Van Hoang, T. H., Mahalik, M. K., & Roubaud, D. (2017). Energy consumption, financial development and economic growth in India: new evidence from a nonlinear and asymmetric analysis. Energy Econ, 63, 199-212.

  55. Shahbaz M, Sharma R, Sinha A, Jiao Z (2020) Analyzing nonlinear impact of economic growth drivers on CO2 emissions: designing an SDG framework for India. Energy Policy 148:111965

    Article  CAS  Google Scholar 

  56. Sharif A, Raza SA, Ozturk I, Afshan S (2019) The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: a global study with the application of heterogeneous panel estimations. Renew Energy 133:685–691

    Article  Google Scholar 

  57. Shin Y, Yu B, Greenwood-Nimmo M (2014) Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In: Festschrift in honor of Peter Schmidt. Springer, New York, NY, pp 281–314

    Google Scholar 

  58. Stern N, Stern NH (2007) The economics of climate change: the stern review. Cambridge University press

  59. Toda HY, Yamamoto T (1995) Statistical inference in vector autoregressions with possibly integrated processes. J Econ 66(1-2):225–250

    Article  Google Scholar 

  60. Toumi S, Toumi H (2019) Asymmetric causality among renewable energy consumption, CO 2 emissions, and economic growth in KSA: evidence from a non-linear ARDL model. Environ Sci Pollut Res 26(16):16145–16156

    CAS  Article  Google Scholar 

  61. 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  Article  Google Scholar 

  62. Usmani M, Kondal A, Wang J, Jutla A (2020) Environmental association of burning agricultural biomass in the Indus River basin. GeoHealth 4(11):e2020GH000281

    Article  Google Scholar 

  63. World Bank (2020) World Development Indicator. https://www.worldbank.org/en/publication/wdr2019. Accessed 22 March 2020

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

    Article  Google Scholar 

  65. Zivot E, Andrews DWK (2002) Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. J Bus Econ Stat 20(1):25–44

    Article  Google Scholar 

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

    CAS  Article  Google Scholar 

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Acknowledgements

We would like to express our gratitude to the editor Inglesi-Lotz and two anonymous referees for their valuable comments, which significantly improved the paper. The authors also thankful to Nusrat Akber (Shri Mata Vaishno Devi University) for her  constructive comments on the earlier draft of this paper. A previous version of this article was also presented at the Rajagiri Business School Kerala, India. The author would like to thank the conference participants for their comments, especially Dr. Aviral Kumar Tiwar and Dr. Anoop Sasikumar. However, the usual disclaimer applies.

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Both authors discussed the results and contributed to the final manuscript. More specifically, Aqib Mujtaba has contributed to the conception, drafting, data collection, data analysis, and interpretation, whereas the proofreading and manuscript editing have been contributed by Pabitra Kumar Jena.

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Correspondence to Aqib Mujtaba.

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Mujtaba, A., Jena, P.K. Analyzing asymmetric impact of economic growth, energy use, FDI inflows, and oil prices on CO2 emissions through NARDL approach. Environ Sci Pollut Res (2021). https://doi.org/10.1007/s11356-021-12660-z

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Keywords

  • CO2 emissions
  • Economic growth
  • Oil prices
  • Asymmetries
  • NARDL

JEL classification

  • C50
  • Q56