Advertisement

Environmental Science and Pollution Research

, Volume 25, Issue 35, pp 35637–35645 | Cite as

Revisiting the growth-carbon dioxide emissions nexus in Pakistan

  • Amine LahianiEmail author
Research Article

Abstract

Pakistan is the most polluted country according to the concentration of air pollution criterion and it has experienced a significant rise in economic growth during the recent years. This paper analyzes the nexus of CO2 emissions and economic growth using quarterly data over the period of 1960Q1–2014Q4. To provide conclusive policy recommendations, this study applied different econometric methodologies such as the quantile causality approach, the linear ARDL (autoregressive distribution lag) model and the quantile ARDL (QARDL) model. The results indicate evidence of causality running from economic growth to CO2 emissions at medium quantiles at the 5% level and at low and medium quantiles at the 10% significance level. Findings of linear and nonlinear ARDL models also support the transmission of growth to CO2 emissions in the long and short run. The Wald test for symmetry sustains the nonlinear ARDL model. Useful policy implications can be learned from the empirical findings.

Keywords

Economic growth CO2 emissions Environmental quality ARDL QARDL 

JEL classification

C32 C5 G1 

References

  1. Ahmed K, Shahbaz M, Qasim A, Long W (2015) The linkages between deforestation, energy and growth for environmental degradation in Pakistan. Ecol Indic 49:95–103CrossRefGoogle Scholar
  2. Arellano M, Bond SR (1991) Some tests of specification for panel data: monte carlo evidence and an application to employment equations. Rev Econ Stud 58:277–297CrossRefGoogle Scholar
  3. Benkraiem R, Lahiani A, Miloudi A, Shahbaz M (2018) New insights into the US stock market reactions to energy price shocks. J Int Financ Mark Inst Money 56:169–187CrossRefGoogle Scholar
  4. Cai Y, Sam CY, Chang T (2018) Nexus between clean energy consumption, economic growth and CO2 emissions. J Clean Prod 182:1001–1011CrossRefGoogle Scholar
  5. Cherni A, Jouini SE (2017) An ARDL approach to the CO2 emissions, renewable energy and economic nexus: Tunisian evidence. Int J Hydrog Energy 42:29056–29066CrossRefGoogle Scholar
  6. Cho JS, Kim T-H, Shin Y (2015) Quantile cointegration in the autoregressive distributed-lag modeling framework. J Econ 188:281–300CrossRefGoogle Scholar
  7. Danish, Zhang B, Wang B, Wang Z (2017) Role of renewable energy and non-renewable energy consumption in EKC: evidence from Pakistan. J Clean Prod 156:855–864CrossRefGoogle Scholar
  8. Esso LJ, Keho Y (2016) Energy consumption, economic growth and carbon emissions: cointegration and causality evidence from selected African countries. Energy 114:492–497CrossRefGoogle Scholar
  9. Ghafoor A, Munir A (2015) Design and economics analysis of an off-grid PV system for household electrification. Renew Sust Energ Rev 42:496–502CrossRefGoogle Scholar
  10. Ghafoor A, Rehman U-T, Munir A, Ahmad M, Iqbal M (2016) Current status and overview of renewable energy potential in Pakistan for continuous energy sustainability. Renew Sust Energ Rev 60:1332–1342CrossRefGoogle Scholar
  11. International Energy Agency (2015) World energy outlook, https://www.iea.org/publications/freepublications/publication/WEO2015.pdf
  12. Ito K (2017) CO2 emissions, renewable and non-renewable energy consumption, and economic growth: evidence form panel data for developing countries. Int Econ 151:1–6CrossRefGoogle Scholar
  13. Kahouli B (2018) The causality link between energy electricity consumption, CO2 emissions, R&D stocks and economic growth in Medeterranean countries. Energy 145:388–399CrossRefGoogle Scholar
  14. Kamran M (2018) “Current status and future success of renewable energy in Pakistan”, renewable and sustainable energy in Pakistan. Renew Sust Energ Rev 82:609–617CrossRefGoogle Scholar
  15. Kim T, White H (2003) Estimation, inference, and specification testing for possibly misspecified quantile regression. In: Fomby T, Hill R (eds) Maximum likelihood estimation of misspecified models: twenty years later, vol 17. Elsevier, New York, p 107–132Google Scholar
  16. Kuznets S (1955) Economic growth and income inequality. Am Econ Rev 1:1–28Google Scholar
  17. Lahiani A, Miloudi A, Benkraiem R, Shahbaz M (2017) Another look on the relationship between oil prices and energy prices. Energy Policy 102:318–331CrossRefGoogle Scholar
  18. Mirza FM, Kanwal A (2017) Energy consumption, carbon emissions and economic growth in Pakistan: dynamic causality analysis. Renew Sust Energ Rev 72:1233–1240CrossRefGoogle Scholar
  19. Riti JS, Song D, Shu Y, Kamah M (2017) Decoupling CO2 emission and economic growth in China: is there consistency in estimation results in analyzing environmental Kuznets curve? J Clean Prod 166:1448–1461CrossRefGoogle Scholar
  20. Sbia R, Shahbaz M, Hamdi H (2014) A contribution of foreign direct investment, clean energy, trade openness, carbon emissions and economic growth to energy demand in UAE. Econ Model 36:191–197CrossRefGoogle Scholar
  21. Shahbaz M, Lean H-H, Shabbir M-S (2012) Environmental Kuznets curve hypothesis in Pakistan: cointegration and Granger causality. Renew Sust Energ Rev 16:2947–2953CrossRefGoogle Scholar
  22. Shahbaz M, Tiwari AK, Nasir M (2013) The effects of financial development, economic growth, coal consumption and trade openness on CO2 emissions in South Africa. Energy Policy 61:1452–1459CrossRefGoogle Scholar
  23. Shahbaz M, Sbia R, Hamdi H, Ozturk I (2014) Economic growth, electricity consumption, urbanization and environmental degradation relationship in United Arab Emirates. Ecol Indic 45:622–631CrossRefGoogle Scholar
  24. 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 50:215–224CrossRefGoogle Scholar
  25. Shahbaz M, Lahiani A, Abosedra S, Hammoudeh S (2018) The role of globalization in energy consumption: a quantile cointegrating regression approach. Energy Econ 71:161–170CrossRefGoogle Scholar
  26. Shin Y, Yu B, Greenwood-Nimmo M (2011) Modelling asymmetric cointegration and dynamic multipliers in an ARDL framework. In: Horrace W, Sickles C, Robin C (eds) Festschrift in honor of Peter Schmidt. Springer Science and Business Media, New YorkGoogle Scholar
  27. Troster V (2018) Teesting for Granger-causality in quantiles. Econ Rev 37:850–866CrossRefGoogle Scholar
  28. Troster V, Shahbaz M, Slah Uddin G (2018) Renewable energy, oil prices, and economic activity: a Granger-causality in quantiles analysis. Energy Econ 70:440–452CrossRefGoogle Scholar
  29. Wang K-M (2012) Modelling the nonlinear relationship between CO2 emissions from oil and economic growth. Econ Model 29:1537–1547CrossRefGoogle Scholar
  30. World Bank Indicators (2016) https://data.worldbank.org

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department for Management of Science and Technology DevelopmentTon Duc Thang UniversityHo Chi Minh CityVietnam
  2. 2.Faculty of Business AdministrationTon Duc Thang UniversityHo Chi Minh CityVietnam

Personalised recommendations