Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Exploring the impact of innovation, renewable energy consumption, and income on CO2 emissions: new evidence from the BRICS economies

  • 107 Accesses

Abstract

The study’s main purpose is to investigate the complex interaction between innovation, renewable energy consumption, and CO2 emissions (CO2e), under the Kuznets curve framework, for BRICS economies from 1980 to 2016. The empirical estimates drwan from the CCEMG technique highlighted the heterogeneous role of innovation. The results indicated that innovation activities have failed to disrupt CO2e in China, India, Russia, and South Africa, except for Brazil. Second, the data showed that renewable energy consumption has mitigated CO2e in the BRICS panel, Russia, India, and China, excluding South Africa. Third, the existence of the EKC hypothesis was confirmed in all the BRICS economies, excluding India and South Africa. Fourth, the causality estimations reflected a two-way causality between innovation and CO2e; innovation and GDP per capita; innovation and renewable energy consumption; and between CO2e and income, thereby confirming the acceptance of income-led emission hypothesis in for BRICS economies, and vice versa.

This is a preview of subscription content, log in to check access.

Fig. 1

Notes

  1. 1.

    International Outlook for 2018, Indian Business Review: https://www.ibrc.indiana.edu/ibr/2017/outlook/international.html

  2. 2.

    International Outlook for 2018, Indian Business Review: https://www.ibrc.indiana.edu/ibr/2017/outlook/international.html

  3. 3.

    Global emissions: https://www.c2es.org/content/international-emissions/

  4. 4.

    State of Global Air/2018: https://www.stateofglobalair.org/sites/default/files/soga-2018-report.pdf

References

  1. Acheampong AO, Adams S, Boateng E (2019) Do globalization and renewable energy contribute to carbon emissions mitigation in Sub-Saharan Africa? Sci Total Environ 677:436–446. https://doi.org/10.1016/J.SCITOTENV.2019.04.353

  2. Abid M (2017) Does economic , financial and institutional developments matter for environmental quality? A comparative analysis of EU and MEA countries. J Environ Manag 188(2):183–194. https://doi.org/10.1016/j.jenvman.2016.12.007

  3. Ahmad M, Khattak SI (2020) Is aggregate domestic consumption spending (ADCS) per capita determining CO2 emissions in South Africa? A New Perspective. Environ Resour Econ:1–24. https://doi.org/10.1007/s10640-019-00398-9

  4. Ahmad M, Hangyi H, Rahman ZU, Khan ZU, Khan S, Khan Z (2018a) Carbon emissions, energy use, gross domestic product. Ekon I Środowisko 65(2):32–44

  5. Ahmad M, Ur Rahman Z, Hong L et al (2018b) Impact of environmental quality variables and socio-economic factors on human health: empirical evidence from China. Pollution 4:571–579. https://doi.org/10.22059/POLL.2018.252214.391

  6. Ahmad M, Khan Z, Rahman ZU et al (2019a) Can innovation shocks determine CO2 emissions (CO2e) in the OECD economies? A new perspective. Econ Innov New Technol:1–21. https://doi.org/10.1080/10438599.2019.1684643

  7. Ahmad M, Khan Z, Rahman ZU, Khan S (2019b) Does financial development asymmetrically affect CO 2 emissions in China ? An application of the nonlinear autoregressive distributed lag ( NARDL ) model. Carbon Manag 9:631–644. https://doi.org/10.1080/17583004.2018.1529998

  8. Albino V, Ardito L, Dangelico RM, Messeni Petruzzelli A (2014) Understanding the development trends of low-carbon energy technologies: a patent analysis. Appl Energy 135:836–854. https://doi.org/10.1016/j.apenergy.2014.08.012

  9. Aldieri L, Bruno B, Vinci CP (2018) Does environmental innovation make us happy? An empirical investigation. Socioecon Plann Sci. https://doi.org/10.1016/J.SEPS.2018.10.008

  10. Al-mulali U, Ozturk I, Adebola S (2016) Investigating the environmental Kuznets curve hypothesis in seven regions : the role of renewable energy. Ecol Indic 67:267–282. https://doi.org/10.1016/j.ecolind.2016.02.059

  11. Apergis N, Ozturk I (2015) Testing environmental Kuznets curve hypothesis in Asian countries. Ecol Indic 52:16–22. https://doi.org/10.1016/j.ecolind.2014.11.026

  12. Apergis N, Christou C, Gupta R (2017) Are there environmental Kuznets curves for US state-level CO2 emissions? Renew Sust Energ Rev 69:551–558. https://doi.org/10.1016/J.RSER.2016.11.219

  13. Arrow K, Bolin B, Costanza R, Dasgupta P, Folke C, Holling CS et al (1995) Economic growth, carrying capacity, and the environment. Ecol Econ 15(2):91–95. https://doi.org/10.1016/0921-8009(95)00059-3

  14. Attiaoui I, Toumi H, Ammouri B, Gargouri I (2017) Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach. Environ Sci Pollut Res 24:13036–13048. https://doi.org/10.1007/s11356-017-8850-7

  15. Awaworyi Churchill S, Inekwe J, Ivanovski K, Smyth R (2018) The environmental Kuznets curve in the OECD: 1870–2014. Energy Econ 75:389–399. https://doi.org/10.1016/J.ENECO.2018.09.004

  16. Azevedo VG, Sartori S, Campos LMS (2018) CO2 emissions: a quantitative analysis among the BRICS nations. Renew Sust Energ Rev 81:107–115. https://doi.org/10.1016/j.rser.2017.07.027

  17. Baek J (2015) Environmental Kuznets curve for CO2 emissions: the case of Arctic countries. Energy Econ 50:13–17. https://doi.org/10.1016/J.ENECO.2015.04.010

  18. Bekhet HA, Othman NS (2018) The role of renewable energy to validate dynamic interaction between CO2 emissions and GDP toward sustainable development in Malaysia. Energy Econ 72:47–61. https://doi.org/10.1016/J.ENECO.2018.03.028

  19. Bekun FV, Alola AA, Sarkodie SA (2019) Toward a sustainable environment: Nexus between CO2 emissions, resource rent, renewable and nonrenewable energy in 16-EU countries. Sci Total Environ 657:1023–1029. https://doi.org/10.1016/j.scitotenv.2018.12.104

  20. Ben Jebli M, Ben Youssef S, Ozturk I (2016) Testing environmental Kuznets curve hypothesis: the role of renewable and non-renewable energy consumption and trade in OECD countries. Ecol Indic 60:824–831. https://doi.org/10.1016/J.ECOLIND.2015.08.031

  21. Boontome P, Therdyothin A, Chontanawat J (2017) Investigating the causal relationship between non-renewable and renewable energy consumption, CO2 emissions and economic growth in Thailand. Energy Procedia 138:925–930. https://doi.org/10.1016/J.EGYPRO.2017.10.141

  22. BP Statistical Review of World Energy (2018) https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2019-full-report.pdf

  23. Brandão Santana N, Rebelatto DADN, Périco AE et al (2015) Technological innovation for sustainable development: an analysis of different types of impacts for countries in the BRICS and G7 groups. Int J Sustain Dev World Ecol:1–12. https://doi.org/10.1080/13504509.2015.1069766

  24. Breitung J (2005) A parametric approach to the estimation of cointegration vectors in panel data. Econom Rev 24:151–173. https://doi.org/10.1081/ETC-200067895

  25. Charfeddine L, Kahia M (2019) Impact of renewable energy consumption and financial development on CO2 emissions and economic growth in the MENA region: a panel vector autoregressive (PVAR) analysis. Renew Energy 139:198–213. https://doi.org/10.1016/J.RENENE.2019.01.010

  26. Chen Y, Wang Z, Zhong Z (2019a) CO2 emissions, economic growth, renewable and non-renewable energy production and foreign trade in China. Renew Energy 131:208–216. https://doi.org/10.1016/J.RENENE.2018.07.047

  27. Chen Y, Zhao J, Lai Z et al (2019b) Exploring the effects of economic growth, and renewable and non-renewable energy consumption on China’s CO2 emissions: evidence from a regional panel analysis. Renew Energy 140:341–353. https://doi.org/10.1016/J.RENENE.2019.03.058

  28. Cheng C, Ren X, Wang Z (2019) The impact of renewable energy and innovation on carbon emission: an empirical analysis for OECD countries. Energy Procedia 158:3506–3512. https://doi.org/10.1016/j.egypro.2019.01.919

  29. Cherni A, Essaber Jouini S (2017) An ARDL approach to the CO2 emissions, renewable energy and economic growth nexus: Tunisian evidence. Int J Hydrog Energy 42:29056–29066. https://doi.org/10.1016/J.IJHYDENE.2017.08.072

  30. Danish, Baloch MA, Mahmood N, Zhang JW (2019) Effect of natural resources, renewable energy and economic development on CO2 emissions in BRICS countries. Sci Total Environ 678:632–638. https://doi.org/10.1016/J.SCITOTENV.2019.05.028

  31. Dauda L, Long X, Mensah CN, Salman M (2019) The effects of economic growth and innovation on CO2 emissions in different regions. Environ Sci Pollut Res 26:1–11. https://doi.org/10.1007/s11356-019-04891-y

  32. Dinda S (2004) Environmental Kuznets curve hypothesis: a survey. Ecol Econ 49(4):431–455. https://doi.org/10.1016/j.ecolecon.2004.02.011

  33. Dong K, Sun R, Hochman G (2017) Do natural gas and renewable energy consumption lead to less CO2 emission? Empirical evidence from a panel of BRICS countries. Energy 141:1466–1478. https://doi.org/10.1016/J.ENERGY.2017.11.092

  34. Dong K, Hochman G, Zhang Y et al (2018a) CO2 emissions, economic and population growth, and renewable energy: empirical evidence across regions. Energy Econ 75:180–192. https://doi.org/10.1016/J.ENECO.2018.08.017

  35. Dong K, Sun R, Jiang H, Zeng X (2018b) CO2 emissions, economic growth, and the environmental Kuznets curve in China: what roles can nuclear energy and renewable energy play? J Clean Prod 196:51–63. https://doi.org/10.1016/J.JCLEPRO.2018.05.271

  36. Dong K, Sun R, Li H, Liao H (2018c) Does natural gas consumption mitigate CO2 emissions: testing the environmental Kuznets curve hypothesis for 14 Asia-Pacific countries. Renew Sust Energ Rev 94:419–429. https://doi.org/10.1016/j.rser.2018.06.026

  37. Dumitrescu E-I, Hurlin C (2012) Testing for Granger non-causality in heterogeneous panels. Econ Model 29:1450–1460. https://doi.org/10.1016/J.ECONMOD.2012.02.014

  38. Ergun SJ, Owusu PA, Rivas MF (2019) Determinants of renewable energy consumption in Africa. Environ Sci Pollut Res 26:1–16. https://doi.org/10.1007/s11356-019-04567-7

  39. Fodha M, Zaghdoud O (2010) Economic growth and pollutant emissions in Tunisia : an empirical analysis of the environmental Kuznets curve. Energy Policy 38:1150–1156. https://doi.org/10.1016/j.enpol.2009.11.002

  40. Gorus MS, Aslan M (2019) Impacts of economic indicators on environmental degradation: evidence from MENA countries. Renew Sust Energ Rev 103:259–268. https://doi.org/10.1016/J.RSER.2018.12.042

  41. Granger CWJ (1969) Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37:424. https://doi.org/10.2307/1912791

  42. Grossman G, Krueger A (1991) Environmental impacts of a North American free trade agreement. https://doi.org/10.3386/w3914

  43. Grossman GM, Krueger AB (1995) Economic growth and the environment. Q J Econ 110:353–377. https://doi.org/10.2307/2118443

  44. Hafeez M, Chunhui Y, Strohmaier D, Ahmed M, Jie L (2018) Does finance affect environmental degradation: evidence from one belt and one road initiative region? Environ Sci Pollut Res 25:9579–9592. https://doi.org/10.1007/s11356-018-1317-7

  45. Harbaugh WT, Levinson A, Wilson DM (2002, August) Reexamining the empirical evidence for an environmental Kuznets curve. Rev Econ Stat 84:541–551. https://doi.org/10.1162/003465302320259538

  46. Huaman NER, Xiu JT (2014) Energy related CO2 emissions and the progress on CCS projects: a review. Renew Sust Energ Rev 31:368–385. https://doi.org/10.1016/j.rser.2013.12.002

  47. Im KS, Pesaran M, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econom 115:53–74

  48. Ito K (2017) CO2 emissions, renewable and non-renewable energy consumption, and economic growth: evidence from panel data for developing countries. Int Econ 151:1–6. https://doi.org/10.1016/J.INTECO.2017.02.001

  49. Kaika D, Zervas E (2013) The environmental Kuznets curve (EKC) theory—part a: concept, causes and the CO2 emissions case. Energy Policy 62:1392–1402. https://doi.org/10.1016/J.ENPOL.2013.07.131

  50. Kao C (1999) Spurious regression and residual-based tests for cointegration in panel data. J Econom 90:1–44. https://doi.org/10.1016/S0304-4076(98)00023-2

  51. Kapetanios G, Pesaran MH, Yamagata T (2011) Panels with non-stationary multifactor error structures. J Econom 160:326–348. https://doi.org/10.1016/j.jeconom.2010.10.001

  52. Khan A, Chenggang Y, Hussain J, Bano S (2019a) Does energy consumption, financial development, and investment contribute to ecological footprints in BRI regions? Environ Sci Pollut Res 26:36952–36966. https://doi.org/10.1007/s11356-019-06772-w

  53. Khan A, Hussain J, Bano S, Chenggang Y (2019b) The repercussions of foreign direct investment, renewable energy and health expenditure on environmental decay? An econometric analysis of B&RI countries. J Environ Plan Manag:1–22. https://doi.org/10.1080/09640568.2019.1692796

  54. Kraft J, Kraft A (1978) The journal of energy and development Vol. 3, no. 2. Spring, pp 401–403

  55. Kuznets, S. (1955) Economic growth and income inequality. Am Econ Rev, 45(1), 1–28. Retrieved January 31, 2020, from https://www.jstor.org/stable/1811581

  56. Levin A, Lin C-F, James Chu C-S (2002) Unit root tests in panel data: asymptotic and finite-sample properties. J Econom 108:1–24

  57. Lin B, Wesseh PK (2014) Energy consumption and economic growth in South Africa reexamined: a nonparametric testing apporach. Renew Sust Energ Rev 40:840–850. https://doi.org/10.1016/j.rser.2014.08.005

  58. Lin B, Raza MY (2019) Analysis of energy related CO2 emissions in Pakistan. J Clean Prod 219:981–993. https://doi.org/10.1016/J.JCLEPRO.2019.02.112

  59. Lin B, Xu M (2018) Regional differences on CO 2 emission efficiency in metallurgical industry of China. Energy Policy 120:302–311. https://doi.org/10.1016/j.enpol.2018.05.050

  60. Maddala GS, Wu S (1999) A comparative study of unit root tests with panel data and a new simple test. Oxf Bull Econ Stat 61:631–652. https://doi.org/10.1111/1468-0084.0610s1631

  61. Maranville S (1992) Entrepreneurship in the business curriculum. J Educ Bus 68:27–31. https://doi.org/10.1080/08832323.1992.10117582

  62. Mensah CN, Long X, Boamah KB, Bediako IA, Dauda L, Salman M (2018) The effect of innovation on CO2 emissions of OCED countries from 1990 to 2014. Environ Sci Pollut Res 25:29678–29698. https://doi.org/10.1007/s11356-018-2968-0

  63. Mert M, Bölük G (2016) Do foreign direct investment and renewable energy consumption affect the CO2 emissions? New evidence from a panel ARDL approach to Kyoto Annex countries. Environ Sci Pollut Res 23:21669–21681. https://doi.org/10.1007/s11356-016-7413-7

  64. Mert M, Bölük G, Çağlar AE (2019) Interrelationships among foreign direct investments, renewable energy, and CO2 emissions for different European country groups: a panel ARDL approach. Environ Sci Pollut Res 26:21495–21510. https://doi.org/10.1007/s11356-019-05415-4

  65. Nathaniel SP, Iheonu CO (2019) Carbon dioxide abatement in Africa: the role of renewable and non-renewable energy consumption. Sci Total Environ 679:337–345. https://doi.org/10.1016/J.SCITOTENV.2019.05.011

  66. New Development Bank (2018) Developing Solutions For A Sustainable Future Annual Report 2017. https://www.ndb.int/wpcontent/uploads/2018/07/NDB_AR2017.pdf

  67. Özokcu S, Özdemir Ö (2017) Economic growth, energy, and environmental Kuznets curve. Renew Sust Energ Rev 72:639–647. https://doi.org/10.1016/j.rser.2017.01.059

  68. Pao H-T, Tsai C-M (2010) CO2 emissions, energy consumption and economic growth in BRIC countries. Energy Policy 38(12):7850–7860. https://doi.org/10.1016/J.ENPOL.2010.08.045

  69. Pedroni, P. (1995) Panel cointegration; asymptotic and finite sample properties of pooled time series tests with an application to the ppp hypothesis. https://web.williams.edu/Economics/pedroni/WP-95-13.pdf

  70. Pesaran M (2004) ‘General diagnostic tests for cross section dependence in panels.’ Cambridge Work Pap Econ

  71. Pesaran M (2006) Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica 74:967–1012. https://doi.org/10.1111/j.1468-0262.2006.00692.x

  72. Pesaran MH (2007) A simple panel unit root test in the presence of cross-section dependence. J Appl Econ 22:265–312. https://doi.org/10.1002/jae.951

  73. Pesaran M, Yamagata T (2008) Testing slope homogeneity in large panels. J Econom 142:50–93. https://doi.org/10.1016/J.JECONOM.2007.05.010

  74. Rahman ZU, Ahmad M (2019) Modeling the relationship between gross capital formation and CO2 (a)symmetrically in the case of Pakistan: an empirical analysis through NARDL approach. Environ Sci Pollut Res 26:8111–8124. https://doi.org/10.1007/s11356-019-04254-7

  75. Rahman Z, Chongbo W, Ahmad M (2019) An (a)symmetric analysis of the pollution haven hypothesis in the context of Pakistan: a non-linear approach. Carbon Management 10(3):227–239. https://doi.org/10.1080/17583004.2019.1577179

  76. Raiser K, Naims H, Bruhn T (2017) Corporatization of the climate? Innovation, intellectual property rights, and patents for climate change mitigation. Energy Res Soc Sci 27:1–8. https://doi.org/10.1016/J.ERSS.2017.01.020

  77. Rauf A, Liu X, Amin W, Ozturk I, Rehman OU, Hafeez M (2018) Testing EKC hypothesis with energy and sustainable development challenges: a fresh evidence from belt and road initiative economies. Environ Sci Pollut Res 25:32066–32080. https://doi.org/10.1007/s11356-018-3052-5

  78. Sadorsky P (2009) Renewable energy consumption and income in emerging economies. Energy Policy 37(10):4021–4028. https://doi.org/10.1016/j.enpol.2009.05.003

  79. Salim RA, Hassan K, Shafiei S (2014) Renewable and non-renewable energy consumption and economic activities: further evidence from OECD countries. Energy Econ 44:350–360. https://doi.org/10.1016/j.eneco.2014.05.001

  80. 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. https://doi.org/10.1016/J.ENECO.2017.04.001

  81. Sarkodie SA, Adams S (2018) Renewable energy, nuclear energy, and environmental pollution: accounting for political institutional quality in South Africa. Sci Total Environ 643:1590–1601. https://doi.org/10.1016/j.scitotenv.2018.06.320

  82. 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. https://doi.org/10.1016/J.RSER.2014.07.033

  83. Shahbaz M, Ali M, Roubaud D (2018) Environmental degradation in France: the effects of FDI , fi nancial development , and energy innovations. Energy Econ 74:843–857. https://doi.org/10.1016/j.eneco.2018.07.020

  84. Stojkoski V, Popova K (2016) Financial development and growth: panel cointegration evidence from south-eastern and central Europeel cointegration evidence from south-eastern and Central Europe

  85. Su H-N, Moaniba IM (2017) Does innovation respond to climate change? Empirical evidence from patents and greenhouse gas emissions. Technol Forecast Soc Change 122:49–62. https://doi.org/10.1016/J.TECHFORE.2017.04.017

  86. United Nations (2005) The millennium ecosystem assessment. https://matagalatlante.org/nobre/down/MAgeneralSynthesisFinalDraft.pdf

  87. Waheed R, Chang D, Sarwar S, Chen W (2018) Forest, agriculture, renewable energy, and CO2 emission. J Clean Prod 172:4231–4238. https://doi.org/10.1016/J.JCLEPRO.2017.10.287

  88. Xu R, Chou L-C, Zhang W-H (2019) The effect of CO2 emissions and economic performance on hydrogen-based renewable production in 35 European countries. Int J Hydrog Energy. https://doi.org/10.1016/J.IJHYDENE.2019.02.167

  89. Yang Y, Zhang H, Xiong W et al (2018) Regional power system modeling for evaluating renewable energy development and CO2 emissions reduction in China. Environ Impact Assess Rev 73:142–151. https://doi.org/10.1016/J.EIAR.2018.08.006

  90. Yii K, Geetha C (2017) The nexus between technology innovation and CO 2 emissions in Malaysia : evidence from granger causality test. Energy Procedia 105:3118–3124. https://doi.org/10.1016/j.egypro.2017.03.654

  91. Yu Y, Du Y (2019) Impact of technological innovation on CO2 emissions and emissions trend prediction on ‘New Normal’ economy in China. Atmos Pollut Res 10:152–161. https://doi.org/10.1016/J.APR.2018.07.005

  92. Zhang S, Liu X, Bae J (2017a) Does trade openness affect CO2 emissions: evidence from ten newly industrialized countries? Environ Sci Pollut Res 24:17616–17625. https://doi.org/10.1007/s11356-017-9392-8

  93. Zhang Y-J, Peng Y-L, Ma C-Q, Shen B (2017b) Can environmental innovation facilitate carbon emissions reduction? Evidence from China. Energy Policy 100:18–28. https://doi.org/10.1016/J.ENPOL.2016.10.005

  94. Zhou H, Sandner PG, Martinelli SL, Block JH (2016) Patents, trademarks, and their complementarity in venture capital funding. Technovation 47:14–22. https://doi.org/10.1016/j.technovation.2015.11.005

  95. Zoundi Z (2017) CO2 emissions , renewable energy and the Environmental Kuznets Curve, a panel cointegration approach. Renew Sust Energ Rev 72:1067–1075. https://doi.org/10.1016/j.rser.2016.10.018

Download references

Author information

Correspondence to Manzoor Ahmad.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Responsible editor: Muhammad Shahbaz

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Khattak, S.I., Ahmad, M., Khan, Z.U. et al. Exploring the impact of innovation, renewable energy consumption, and income on CO2 emissions: new evidence from the BRICS economies. Environ Sci Pollut Res (2020). https://doi.org/10.1007/s11356-020-07876-4

Download citation

Keywords

  • Innovation
  • renewable energy consumption
  • income
  • GDP
  • CO2
  • CCEMG
  • BRICS