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Asymmetric effects of energy efficiency and renewable energy on carbon emissions of BRICS economies: evidence from nonlinear panel autoregressive distributed lag model

Environmental Science and Pollution Research volume 27, pages 18254–18268 (2020)Cite this article

Abstract

Embracing energy efficiency (EE) and renewable energy (RE) is essential for improving environmental quality. This research investigates the asymmetric impacts of EE, RE, and other factors on CO2 emissions in BRICS (i.e., Brazil, Russia, India, China, and South Africa) countries from 1990 to 2014. In contrast to previous studies, the present study considers EE as a major cause of CO2 emissions in BRICS countries. By using the new hidden panel cointegration and nonlinear panel autoregressive distributive lag model, this study is the first of its kind that unfolds the asymmetric links among EE, RE, and CO2 emissions. Findings clearly explain that the impact of the selected variables on CO2 emissions is asymmetric, and both EE and RE help to lower CO2 emissions in BRICS countries. In the long run, positive shocks in EE and RE can significantly mitigate CO2 emissions in BRICS economies. In particular, a 1% fluctuation in the positive sum of EE reduces CO2 emissions by 0.783% in the long run. On the other hand, a 1% fluctuation in the positive component of RE reduces CO2 emissions by 0.733%. Moreover, individual country estimates suggest the heterogeneous effects among BRICS countries. Based on the empirical findings, policymakers should consider the asymmetric behavior of the EE, RE, and economic growth while formulating, energy, environment, and growth policies of BRICS countries.

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Abbreviations

CO2 :

Carbon dioxide

EE:

Energy efficiency

EC:

Energy consumption

EG:

Economic growth

GHG:

Greenhouse gas

MG:

Mean group

NU:

Nuclear energy

NPARDL:

Nonlinear panel autoregressive distributed lag

NRE:

Nonrenewable energy

PMG:

Pooled mean group

RE:

Renewable energy

R&D:

Research and development

SDG:

Sustainable development goal

TWh:

TeraWatt per hour

References

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

  • Ahmad M, Khan Z, Ur Rahman Z, Khan S (2018) Does financial development asymmetrically affect CO2 emissions in China? An application of the nonlinear autoregressive distributed lag (NARDL) model. Carbon Management 9:631–644

    CAS  Google Scholar 

  • Akram R, Chen F, Khalid F, Ye Z, Majeed MT (2019) Heterogeneous effects of energy efficiency and renewable energy on carbon emissions: evidence from developing countries. J Clean Prod:119122

  • Allard A, Takman J, Uddin GS, Ahmed A (2018) The N-shaped environmental Kuznets curve: an empirical evaluation using a panel quantile regression approach. Environ Sci Pollut Res 25:5848–5861

    CAS  Google Scholar 

  • Anoruo E (2011) Testing for linear and nonlinear causality between crude oil price changes and stock market returns. Int J Econ Sci Appl Res 4:75–92

    Google Scholar 

  • Apergis N, Garćıa C (2019) Environmentalism in the EU-28 context: the impact of governance quality on environmental energy efficiency. Environ Sci Pollut Res:1–14

  • Aydin M (2019) Renewable and non-renewable electricity consumption–economic growth nexus: evidence from OECD countries. Renew Energy 136:599–606

    Google Scholar 

  • Azevedo VG, Sartori S, Campos LM (2018) CO2 emissions: a quantitative analysis among the BRICS nations. Renew Sust Energ Rev 81:107–115

    CAS  Google Scholar 

  • Balsalobre-Lorente D, Driha OM, Bekun FV, Osundina OA (2019a) Do agricultural activities induce carbon emissions? The BRICS experience. Environ Sci Pollut Res 26:25218–25234

    CAS  Google Scholar 

  • Balsalobre-Lorente D, Gokmenoglu KK, Taspinar N, Cantos-Cantos JM (2019b) An approach to the pollution haven and pollution halo hypotheses in MINT countries. Environ Sci Pollut Res:1–17

  • Bangake C, Eggoh JC (2012) Pooled mean group estimation on international capital mobility in African countries. Res Econ 66:7–17

    Google Scholar 

  • Bayar Y, Gavriletea MD (2019) Energy efficiency, renewable energy, economic growth: evidence from emerging market economies. Qual Quant:1–14

  • Camioto D, Flávia MHF, Mariano EB, do Nascimento Rebelatto DA (2016) Energy efficiency analysis of G7 and BRICS considering total-factor structure. J Clean Prod 122:67–77

    Google Scholar 

  • Cheng C, Ren X, Wang Z, Yan C (2019) Heterogeneous impacts of renewable energy and environmental patents on CO2 emission-evidence from the BRIICS. Sci Total Environ 668:1328–1338

    CAS  Google Scholar 

  • Danish BMA, 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

    CAS  Google Scholar 

  • 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

    Google Scholar 

  • Dong K, Sun R, Dong X (2018a) CO2 emissions, natural gas and renewables, economic growth: assessing the evidence from China. Sci Total Environ 640:293–302

    Google Scholar 

  • 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

    Google Scholar 

  • Dutta A, Bouri E, Roubaud D (2019) Nonlinear relationships amongst the implied volatilities of crude oil and precious metals. Res Policy 61:473–478

    Google Scholar 

  • Energy-Hub (2019) Russia’s energy (in)efficiency

  • Espa I, Holzer K (2018) Negotiating 21st century rules on energy: what is at stake for the European Union, the United States and the BRICS? J World Invest Trade 19:415–443

    Google Scholar 

  • European Commission 2016 The macroeconomic and other benefits of energy efficiency, European Commission

  • Fei L, Dong S, Xue L, Liang Q, Yang W (2011) Energy consumption-economic growth relationship and carbon dioxide emissions in China. Energy Policy 39:568–574

    Google Scholar 

  • Hatemi-J A (2014) ASCOMP: GAUSS module to transform data into cumulative positive and negative components

  • Hatemi-J A (2018) Hidden panel cointegration. Journal of King Saud University-Science

  • Haug AA, Ucal M (2019) The role of trade and FDI for CO2 emissions in Turkey: nonlinear relationships. Energy Econ 81:297–307

    Google Scholar 

  • IEA (2013) Redrawing the energy-climate map: world energy outlook special report. OECD/IEA

  • IEA (2019a) Energy efficiency in emerging economies

  • IEA (2019b) Energy efficiency in Brazil

  • IPEEC (2017) BRICS: a force for energy efficiency cooperation

  • Kahneman D, Tversky A (2013) Prospect theory: an analysis of decision under risk, handbook of the fundamentals of financial decision making: part I. World Scientific:99–127

  • Khan Z, Sisi Z, Siqun Y (2019) Environmental regulations an option: asymmetry effect of environmental regulations on carbon emissions using non-linear ARDL. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 41:137–155

    CAS  Google Scholar 

  • Kouton J (2019) The asymmetric linkage between energy use and economic growth in selected African countries: evidence from a nonlinear panel autoregressive distributed lag model. Energy Econ 83:475–490

    Google Scholar 

  • Kumar S (2017) On the nonlinear relation between crude oil and gold. Res Policy 51:219–224

    Google Scholar 

  • Lau L-S, Choong C-K, Ng C-F, Liew F-M, Ching S-L (2019) Is nuclear energy clean? Revisit of environmental Kuznets curve hypothesis in OECD countries. Econ Model 77:12–20

    Google Scholar 

  • Lin B, Moubarak M (2014) Renewable energy consumption–economic growth nexus for China. Renew Sust Energ Rev 40:111–117

    Google Scholar 

  • Liobikienė G, Butkus M (2017) Environmental Kuznets curve of greenhouse gas emissions including technological progress and substitution effects. Energy 135:237–248

    Google Scholar 

  • Liu X, Zhang S, Bae J (2017) The nexus of renewable energy-agriculture-environment in BRICS. Appl Energy 204:489–496

    Google Scholar 

  • Mahmood H, Maalel N, Zarrad O (2019) Trade openness and CO2 emissions: evidence from Tunisia. Sustainability 11:3295

    Google Scholar 

  • Ndoricimpa A (2017) Analysis of asymmetries in the nexus among energy use, pollution emissions and real output in South Africa. Energy 125:543–551

    Google Scholar 

  • Özbuğday FC, Erbas BC (2015) How effective are energy efficiency and renewable energy in curbing CO2 emissions in the long run? A heterogeneous panel data analysis. Energy 82:734–745

    Google Scholar 

  • Özcan KM, Özkan AU (2018) The relationship between energy efficiency and economic performance in G20 countries

  • Ozturk I (2017) Measuring the impact of alternative and nuclear energy consumption, carbon dioxide emissions and oil rents on specific growth factors in the panel of Latin American countries. Prog Nucl Energy 100:71–81

    CAS  Google Scholar 

  • Pao H-T, Tsai C-M (2010) CO2 emissions, energy consumption and economic growth in BRIC countries. Energy Policy 38:7850–7860

    Google Scholar 

  • Pao H-T, Tsai C-M (2011a) Modeling and forecasting the CO2 emissions, energy consumption, and economic growth in Brazil. Energy 36:2450–2458

    Google Scholar 

  • Pao H-T, Tsai C-M (2011b) Multivariate granger causality between CO2 emissions, energy consumption, FDI (foreign direct investment) and GDP (gross domestic product): evidence from a panel of BRIC (Brazil, Russian Federation, India, and China) countries. Energy 36:685–693

    Google Scholar 

  • Pata UK (2018a) Renewable energy consumption, urbanization, financial development, income and CO2 emissions in Turkey: testing EKC hypothesis with structural breaks. J Clean Prod 187:770–779

    Google Scholar 

  • Pata UK (2018b) The Feldstein Horioka puzzle in E7 countries: evidence from panel cointegration and asymmetric causality analysis. J Int Trade Econ Dev 27:968–984

    Google Scholar 

  • Pathak L, Shah K (2019) Renewable energy resources, policies and gaps in BRICS countries and the global impact. Front Energy 13:506–521

    Google Scholar 

  • Pesaran MH (2004) General diagnostic tests for cross section dependence in panels

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

    Google Scholar 

  • Po W-C, Huang B-N (2008) Tourism development and economic growth–a nonlinear approach. Physica A: Statistical mechanics and its applications 387:5535–5542

    Google Scholar 

  • 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 10:227–239

    Google Scholar 

  • Reilly J (2015) Energy and development in emerging countries. Revue d’economie du developpement 23:19–38

    Google Scholar 

  • Salisu AA, Isah KO (2017) Revisiting the oil price and stock market nexus: a nonlinear panel ARDL approach. Econ Model 66:258–271

    Google Scholar 

  • Salman M, Long X, Dauda L, Mensah CN, Muhammad S (2019) Different impacts of export and import on carbon emissions across 7 ASEAN countries: a panel quantile regression approach. Sci Total Environ 686:1019–1029

    CAS  Google Scholar 

  • Shahbaz M, Shahzad SJH, Ahmad N, Alam S (2016) Financial development and environmental quality: the way forward. Energy Policy 98:353–364

    Google Scholar 

  • Shahbaz M, Balsalobre-Lorente D, Sinha A (2019) Foreign direct investment–CO2 emissions nexus in Middle East and North African countries: importance of biomass energy consumption. J Clean Prod 217:603–614

    Google Scholar 

  • Shao Q, Wang X, Zhou Q, Balogh L (2019) Pollution haven hypothesis revisited: a comparison of the BRICS and MINT countries based on VECM approach. J Clean Prod 227:724–738

    Google Scholar 

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

  • 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 26:16145–16156

    CAS  Google Scholar 

  • Wang S, Zhou D, Zhou P, Wang Q (2011) CO2 emissions, energy consumption and economic growth in China: a panel data analysis. Energy Policy 39:4870–4875

    Google Scholar 

  • Westerlund J (2007) Testing for error correction in panel data. Oxf Bull Econ Stat 69:709–748

    Google Scholar 

  • World Bank (2018) World Development Indicators

  • Zhang B, Wang B, Wang Z (2017) Role of renewable energy and non-renewable energy consumption on EKC: evidence from Pakistan. J Clean Prod 156:855–864

    Google Scholar 

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Author information

Affiliations

  1. School of International Trade and Economics, University of International Business and Economics, Beijing, China

    Rabia Akram

  2. School of Economics, Quaid-i-Azam University, Islamabad, Pakistan

    Muhammad Tariq Majeed

  3. School of Business, Huzhou University, Huzhou, Zhejiang, China

    Zeeshan Fareed

  4. Business school, University of International Business and Economics, Beijing, China

    Fahad Khalid & Chengang Ye

Authors
  1. Rabia Akram
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  2. Muhammad Tariq Majeed
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  3. Zeeshan Fareed
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  4. Fahad Khalid
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  5. Chengang Ye
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Correspondence to Rabia Akram.

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Highlights

• Nonlinear/asymmetric effects are examined in energy efficiency, renewable energy, and CO2 emissions nexus of BRICS countries.

• Energy efficiency helps to reduce CO2 emissions in BRICS economies.

• Energy efficiency and renewable energy have an asymmetric effect on CO2 emissions.

Responsible editor: Nicholas Apergis

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Akram, R., Majeed, M.T., Fareed, Z. et al. Asymmetric effects of energy efficiency and renewable energy on carbon emissions of BRICS economies: evidence from nonlinear panel autoregressive distributed lag model. Environ Sci Pollut Res 27, 18254–18268 (2020). https://doi.org/10.1007/s11356-020-08353-8

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  • DOI: https://doi.org/10.1007/s11356-020-08353-8

Keywords

  • Energy efficiency
  • Asymmetric effects
  • Hidden panel cointegration
  • Nonlinear panel ARDL