Skip to main content
SpringerLink
Log in

Greenhouse gas emissions: is there an environmental Kuznets curve in South Asia?

  • Published:
Environment, Development and Sustainability Aims and scope Submit manuscript

Abstract

We examine the environmental Kuznets curve (EKC) relationship in South Asia focusing on the emissions of major greenhouse gases (GHGs) namely CO2 (carbon dioxide), CH4 (methane), and N2O (nitrous oxide). We exploit a balanced annual panel dataset for five South Asian countries covering the period 1971–2018, and use the OLS estimation technique with country- and year-fixed effects, and country-specific time trends to begin with. The OLS results show that the income-CO2 emission relationship is positive while the income-CH4 and income-N2O emission relationships follow the EKC or inverted-U pattern. Analyses with a sub-sample, 4-year average data, and considering the cross-sectional dependence support the findings. The panel threshold regression and the nonparametric and semiparametric estimation techniques also support the monotonic positive effect of income on CO2 emissions but indicate non-linearity in the relationship such that emissions rates are higher at higher income. However, the results from these latter estimation techniques weaken the observed EKC patterns regarding CH4 and N2O emissions. So, according to this study, the existence of the GHG–EKC relationships in South Asia is questionable. We suggest that to reduce GHG emissions, South Asian countries should focus on cleaner technology and take coordinated policy actions that should involve all the stakeholders.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Data availability statement

Data used in this study are publicly available. The sources of the data are mentioned in the “Data and Methodology” section of the paper. Further information about the data is available from the corresponding author upon reasonable request.

Notes

  1. Different sections of people of the society including the development practitioners are concerned about the adverse effects of climate change. In a recent note Bill Gates, the founder of Microsoft, warns that the adverse consequences of climate change, if uncontrolled, can be more serious than the recent pandemic of COVID-19 which has devasted the whole world (Gates, 2020). Similarly, acknowledging the negative consequences of climate change, the Nobel laureate and founder of the Grameen Bank, Professor Yunus has been advocating for zero carbon emissions for quite some time (Yunus & Weber, 2017).

  2. Kuznets (1955) observed an inverted U-shaped relationship between income inequality and economic growth which later became familiar as the Kuznets curve hypothesis. This hypothesis was applied to investigate the effect of level of development on environmental pollution and degradation. The latter hypothesis has been termed as the Environmental Kuznets Curve (EKC) hypothesis (see Dasgupta et al., 2002).

  3. The empirical literature investigating the EKC relationship for different types of emissions and concentrations is quite voluminous. GHGs–EKC relationship can be considered a sub-set of the broad EKC literature.

  4. According to the World Bank, countries of the South Asia region are Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan and Sri Lanka.

  5. All the countries of the region endorsed the Paris Agreement which aims to “limit global warming” by requiring the parties to “reach global peaking of greenhouse gas emissions as soon as possible” (UNFCCC, 2015). Under the agreement, each country has to submit a Nationally Determined Contributions (NDCs) which is a detailed plan of actions the countries will undertake to reduce GHG emissions. In their NDCs, all South Asian countries except Nepal pledged to reduce their GHG emissions by different percentages, mainly through adopting renewable energy, converting waste to energy, moving from the current fossil fuel-based transport system to a more efficient one and increasing forest cover (see Haque et al., 2019).

  6. Shafik (1994) examines EKC for a number of pollutants including CO2 emissions.

  7. Also, see List and Gallet (1999) who use a similar specification to estimate the EKC for nitrogen oxide and sulphur dioxide using US state level panel data.

  8. The Polity2 variable commonly used as a proxy for institutional quality has come under a lot of scrutiny and criticism in recent years. Consequently, alternative measures of democracy proposed by the V-Dem are suggested by Lindberg et al. (2014), among others.

  9. Some authors (e. g., Liobikienė & Butkus, 2017; Sharma, 2011) specify a dynamic panel data model and estimate the model using the system GMM technique. However, this estimation method which requires short time periods and large cross-section units is not appropriate in our settings.

  10. This practice of averaging and using initial values is quite common in the literature (see Brueckner et al., 2015).

  11. These techniques are different from the LOWESS nonparametric technique presented in Sect. 3.2. The LOWESS is a bi-variate analysis that does not consider the panel nature of the data. On the other hand, the panel nonparametric technique accounts for panel FE and effects of other possible covariates.

  12. Since the square term is highly significant in this case, we do not exclude the term to examine the possibility of a monotonic relationship as we did for CO2 emissions.

References

  • ADB (2013). Economics of reducing greenhouse gas emissions in South Asia: Options and Costs, Climate Action South Asia (CASA) information update no. 2, Asian Development Bank.

  • 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.

    Article  CAS  Google Scholar 

  • Ahmed, K., Rehman, M., & Ozturk, I. (2017). What drives carbon dioxide emissions in the long-run? Evidence from selected South Asian Countries. Renewable and Sustainable Energy Reviews, 70, 1142–1153.

    Article  CAS  Google Scholar 

  • Al-mulali, U., Tang, C. F., & Qzturk, I. (2015). Estimating the environment Kuznets curve hypothesis: Evidence from Latin America and the Caribbean countries. Renewable Sustainable Energy Review, 50, 918–924.

    Article  CAS  Google Scholar 

  • Al-Mulali, U., Ozturk, I., & Solarin, S. (2016). Investigating the environmental Kuznets curve hypothesis in seven regions: The role of renewable energy. Ecological Indicators, 67, 267–282.

    Article  Google Scholar 

  • Antonakakis, N., Chatziantoniou, I., & Filis, G. (2017). Energy consumption, CO2 emissions, and economic growth: An ethical dilemma. Renewable and Sustainable Energy Reviews, 68(1), 808–824.

    Article  Google Scholar 

  • Apergis, N. (2016). Environmental Kuznets curves: New evidence on both panel and country-level CO2 emissions. Energy Economics, 54, 263–271.

    Article  Google Scholar 

  • Apergis, N., & Ozturk, I. (2015). Testing environmental Kuznets Hypothesis in Asian Countries. Ecological Indicators, 52, 16–22.

    Article  Google Scholar 

  • Apergis, N., Christou, C., & Gupta, R. (2017). Are there Environmental Kuznets Curves for US state-level CO2 emissions? Renewable and Sustainable Energy Reviews, 69, 551–558.

    Article  CAS  Google Scholar 

  • Baltagi, B. H., & Li, D. (2002). Series estimation of partially linear panel data models with fixed effects. Annals of Economics and Finance, 3, 103–116.

    Google Scholar 

  • Barra, C., & Zotti, R. (2018). Investigating the non-linearity between national income and environmental pollution: International evidence of Kuznets curve. Environmental Economics and Policy Studies, 20, 179–210.

    Article  Google Scholar 

  • Bibi, F., & Jamil, M. (2021). Testing environment Kuznets curve (EKC) hypothesis in different regions. Environmental Science and Pollution Research, 28, 13581–13594.

    Article  CAS  Google Scholar 

  • Brock, W., & Taylor, M. (2005). Economic growth and the environment: a review of theory and empirics. In P. Aghion & S. Durlauf (eds.), Handbook of Economic Growth, Volume 1B (pp. 1749–1821).

  • Brueckner, M., Norris, E., & Gradstein, M. (2015). National income and its distribution. Journal of Economic Growth, 20, 149–175.

    Article  Google Scholar 

  • Caporin, M., Cooray, A., Kuziboev, B., & Yusubov, I. (2023). New insights on the environmental Kuznets curve (EKC) for Central Asia. Empirical Economics. https://doi.org/10.1007/s00181-023-02520-9

    Article  Google Scholar 

  • Carleton, T. A., & Hsiang, S. M. (2016). Social and economic impacts of climate Science. Science, 353(6304), 1112–1128.

    Article  CAS  Google Scholar 

  • Dasgupta, S., Laplante, B., Wang, H., & Wheeler, D. (2002). Confronting the environmental Kuznets curve. Journal of Economic Perspective, 16, 147–168.

    Article  Google Scholar 

  • Dietz, T., & Rosa, E. (1997). Effects of population and affluence on CO2 emissions. Proceedings of the National Academy of Sciences, 94, 175–179.

    Article  CAS  Google Scholar 

  • Dijkgraaf, E., & Vollebergh, H. (2005). A test for parameter homogeneity in CO2 panel EKC estimations. Environmental & Resource Economics, 32, 229–239.

    Article  Google Scholar 

  • Dinda, S. (2004). Environmental Kuznets curve hypothesis: A survey. Ecological Economics, 49, 431–455.

    Article  Google Scholar 

  • Driscoll, J. C., & Kraay, A. C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. Review of Economics and Statistics, 80, 549–560.

    Article  Google Scholar 

  • Galeotti, M., & Lanza, A. (1999). Richer and cleaner? A study on carbon dioxide emissions in developing countries. Energy Policy, 27(10), 565–573.

    Article  Google Scholar 

  • Gates, B. (2020). COVID-19 is awful, Climate change could be worse. Gates Notes—The Blog of Bill Gates. Available at https://www.gatesnotes.com/Energy/Climate-and-COVID-19.

  • Greene, W. (2000). Econometric Analysis. Prentice-Hall.

  • Hansen, B. E. (1999). Threshold effects in non-dynamic panels: Estimation, testing, and inference. Journal of Econometrics, 93, 345–368.

    Article  Google Scholar 

  • Haque, A., Lohano, H., Mukhopadhyay, P., Nepal, M., Shafeeqa, F., & Vidanage, S. (2019). NDC pledges of South Asia: Are the stakeholders onboard? Climate Change, 155, 237–244.

    Article  Google Scholar 

  • Henderson, D., Carroll, R., & Li, Q. (2008). Nonparametric estimation and testing of fixed effects panel data models. Journal of Econometrics, 144(1), 257–275.

  • Holtz-Eakin, D., & Selden, T. M. (1995). Stoking the fires? CO2 emissions and economic growth. Journal of Public Economics, 57(1), 85–101.

    Article  Google Scholar 

  • De Hoyos, R. E., & Sarafidis, V. (2006). Testing for cross-sectional dependence in panel-data models, the Stata Journal, 6(4), 482–496.

  • Hsiang, S., Burke, M., & Miguel, E. (2013). Quantifying the influence of climate on human conflict. Science. https://doi.org/10.1126/science.1235367

    Article  Google Scholar 

  • Hussain, A., & Dey, S. (2021). Revisiting environmental Kuznets curve with HDI: New evidence from cross-country panel data. Journal of Environmental Economics and Policy, 10(3), 324–342.

    Article  Google Scholar 

  • IPCC (2014). “Climate change 2014: Mitigation of climate change”, Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change”, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Available at https://www.ipcc.ch/site/assets/uploads/2018/05/SYR_AR5_FINAL_full_wcover.pdf.

  • Irfan, M., Saha, S., & Singh, S. (2021). Investigating the existence of environmental Kuznets curve hypothesis for the South Asian region. in T. Chakraborty, D. Mukherjee & S. Saha (editors) Contemporary Issues in Sustainable Development—the case of India, Routledge.

  • Islam, F., Shahbaz, M., & Butt, S. (2013). Is there an environmental Kuznets curve for Bangladesh? Evidence from ARDL bounds testing approach. Bangladesh Development Studies, 36(4), 1–23.

    Google Scholar 

  • Juodis, A., Karavias, Y., & Sarafidis, V. (2021). A homogeneous approach to testing for Granger non-causality in heterogeneous panels. Empirical Economics, 60, 93–112.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Kaya Kanlı, N., & Küçükefe, B. (2022). Is the environmental Kuznets curve hypothesis valid? A global analysis for carbon dioxide emissions. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-022-02138-4.

  • Kostakis, I., Armaos, S., Abeliotis, K., & Theodoropoulou, E. (2023). The investigation of EKC within CO2 emissions framework: Empirical evidence from selected cross-correlated countries. Sustainability Analytics and Modeling, 3, 100015. https://doi.org/10.1016/j.samod.2023.100015

    Article  Google Scholar 

  • Kuznets, S. (1955). Economic growth and income inequality. American Economic Review, 45(1), 1–28.

    Google Scholar 

  • Lee, T., & Nguyen, C. (2020). Determinants of greenhouse gas emissions revisited: A global perspective. The Singapore Economic Review. https://doi.org/10.1142/S0217590820500514

    Article  Google Scholar 

  • Lee, T., & Quah, E. (2018). Income level and the emissions, energy, and growth nexus: Evidence from Asia and the Pacific. International Economics, 156, 193–205.

    Article  Google Scholar 

  • Li, D., Chen, J., & Gao, J. (2011). Non-parametric time-varying coefficient panel data models with fixed effects. The Econometrics Journal, 14, 387–408.

    Article  Google Scholar 

  • Lindberg, S., Coppedge, M., Gerring, J., & Teorell, J. (2014). V-Dem: A new way to measure democracy. Journal of Democracy, 5(3), 159–169.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • List, J., & Galet, C. (1999). The environmental Kuznets curve: Does one size fit all? Ecological Economics, 31, 409–423.

    Article  Google Scholar 

  • Nahid, S., Rahman, M., & Khanam, R. (2022). Environmental Kuznets curve and causal links between environmental degradation and selected socioeconomic indicators in Bangladesh. Environment, Development and Sustainability, 24, 5426–5450.

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  • Nasreen, S., Anwar, S., & Oztark, I. (2017). Financial stability, energy consumption and environmental quality: Evidence from South Asian economies. Renewable and Sustainable Energy Reviews, 67, 1105–1122.

    Article  CAS  Google Scholar 

  • Ozcan, B. (2013). The nexus between carbon emissions, energy consumption and economic growth in Middle East countries: A panel data analysis. Energy Policy, 62, 1138–1147.

    Article  Google Scholar 

  • Panayotou, T. (1993). Empirical tests and policy analysis of environmental degradation at different stages of economic development. Working Paper (WEP 2–22/WP. 238), World Employment Programme Research, ILO, Geneva.

  • Pesaran, M. H. (2015a). Time series and panel data econometrics. Oxford University Press.

    Book  Google Scholar 

  • Pesaran, M. H. (2015b). Testing weak cross-sectional dependence in large panels. Econometrics Review, 34, 1089–1117.

    Article  Google Scholar 

  • Pesaran, M. H. (2003). A Simple Panel Unit Root Test in the Presence of Cross Section Dependence. Cambridge Working Papers in Economics 0346, Faculty of Economics (DAE), University of Cambridge.

  • Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels, CESifo Working Paper No. 1229.

  • Polemis, M. (2023). Revisiting the environmental Kuznets curve: A semi-parametric analysis on the role of market structure on environmental pollution. Letters in Spatial and Resource Sciences, 11, 27–35.

    Article  Google Scholar 

  • Purcel, A. (2020). New insights into the environmental Kuznets curve hypothesis in developing and transition economies: A literature survey. Environmental Economics and Policy Studies, 22, 585–631.

    Article  Google Scholar 

  • Ronaghi, M., Reed, M., & Saghaian, S. (2020). The impact of economic factors and governance on greenhouse gas emission. Environmental Economics and Policy Studies, 22, 153–172.

    Article  Google Scholar 

  • Rosa, E., & Dietz, T. (2012). Human drivers of national greenhouse gas emissions. Nature Climate Change, 2(8), 581–586.

    Article  CAS  Google Scholar 

  • Schmalensee, R., Stoker, T., & Judson, R. (1998). World carbon dioxide emissions: 1950–2050. The Review of Economics and Statistics, 80(1), 15–27.

    Article  Google Scholar 

  • Shafiei, S., & Salim, R. A. (2014). Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: A comparative analysis. Energy Policy, 66, 547–556.

    Article  CAS  Google Scholar 

  • Shafik, N. (1994). Economic development and environmental quality: An econometric analysis. Oxford Economic Papers, 46, 757–773.

    Article  Google Scholar 

  • Shahbaz, M., & Sinha, A. (2019). Environmental Kuznets curve for CO2 emissions: A literature survey. Journal of Economic Studies, 46(1), 106–168.

    Article  Google Scholar 

  • Shahbaz, M., Solarin, S. A., Sbia, R., & Bibi, S. (2015). Does energy intensity contribute to CO2 emissions? A trivariate analysis in selected African countries. Ecological Indicators, 50, 215–224.

    Article  Google Scholar 

  • Sharma, S. (2011). Determinants of carbon dioxide emissions: Empirical evidence from 69 countries. Applied Energy, 88, 376–382.

    Article  CAS  Google Scholar 

  • Sirag, A., Matemilola, B., Law, S., & Bany-Ariffin, A. (2018). Does environmental Kuznets curve hypothesis exist? Evidence from dynamic panel threshold. Journal of Environmental Economics and Policy, 7(2), 145–165.

    Article  Google Scholar 

  • Stern, D. (2004). The rise and fall of the environmental Kuznets curve. World Development, 32(8), 1419–1439.

    Article  Google Scholar 

  • Stern, D. (2017). The environmental Kuznets curve after 25 years. Journal of Bioeconomics, 19, 7–28.

    Article  Google Scholar 

  • UNFCCC (2015). The Paris agreement”, the United Nations. Available at https://unfccc.int/sites/default/files/english_paris_agreement.pdf.

  • Wang, Q. (2015). Fixed-effect panel threshold model using Stata. The Stata Journal, 15(1), 121–134.

    Article  Google Scholar 

  • WDI (2021). The World Development Indicators Database. The World Bank.

  • Westerlund, J. (2007). Testing for error correction in panel data. Oxford Bulletin of Economics and Statistics., 69(6), 709–748.

    Article  Google Scholar 

  • Yunus, M., & Weber, K. (2017). A world of three zeros: The new economics of zero poverty, zero unemployment, and zero net carbon emissions. PublicAffairs.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Research Department, Bangladesh Bank, Head Office, Dhaka, 1000, Bangladesh

    Puja Bhattacharjee

  2. Department of Economics, University of Chittagong, Chittagong, 4331, Bangladesh

    Mohammad Tarequl Hasan Chowdhury

Authors
  1. Puja Bhattacharjee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohammad Tarequl Hasan Chowdhury
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammad Tarequl Hasan Chowdhury.

Ethics declarations

Conflict of interest

The authors have no competing interests.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bhattacharjee, P., Chowdhury, M.T.H. Greenhouse gas emissions: is there an environmental Kuznets curve in South Asia?. Environ Dev Sustain (2024). https://doi.org/10.1007/s10668-024-04722-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10668-024-04722-2

Keywords

JEL Classification

Search

Navigation