Convergence in Sulphur Dioxide (SO2) Emissions Since 1850 in OECD Countries: Evidence from a New Panel Unit Root Test

Abstract

The convergence of air pollution is a key assumption in several environmental impact assessment models and one of the major ingredients for multilateral climate agreements and allocation of emission rights. In this paper, the sulphur dioxide (SO2) emissions’ convergence among 32 OECD countries is examined using the panel stationarity test of Nazlioglu and Karul [1] that provides for smooth breaks, cross-sectional dependency and heterogeneity across the cross-sectional units. For robustness sake, we have also used a panel stationarity test that accounts for sharp breaks. Overall, the findings reveal that there is convergence of SO2 emissions among the OECD countries. The results imply that adjusting the mean value of the relative SO2 emissions trend path should be a key concern of the OECD nations. Moreover, the findings signify that instead of following independent paths in pollution control, the OECD countries are gravitating towards a similar standard of environmental performance. Moreover, the forecast of future relative SO2 emission figures can be based on its past values.

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Fig. 1

Notes

  1. 1.

    Usually the existing literature will only test the cross-sectional dependency of the original series. We have also tested cross-sectional dependency of the relative series since the unit root testing has been conducted on the relative series in the process of testing for convergence.

References

  1. 1.

    Nazlioglu, S., & Karul, C. (2017). A panel stationarity test with gradual structural shifts: re-investigate the international commodity price shocks. Economic Modelling, 61, 181–192.

    Google Scholar 

  2. 2.

    Brännlund, R., Karimu, A., & Söderholm, P. (2017). Convergence in carbon dioxide emissions and the role of growth and institutions: a parametric and non-parametric analysis. Environmental Economics and Policy Studies, 19(2), 359–390.

    Google Scholar 

  3. 3.

    Rios, V., & Gianmoena, L. (2018). Convergence in CO2 emissions: a spatial economic analysis with cross-country interactions. Energy Economics, 75, 222–238.

    Google Scholar 

  4. 4.

    Solarin, S. A., & Bello, M. O. (2018). Persistence of policy shocks to an environmental degradation index: the case of ecological footprint in 128 developed and developing countries. Ecological Indicators, 89, 35–44.

    Google Scholar 

  5. 5.

    Fan, S., Burstyn, I., & Senthilselvan, A. (2010). Spatiotemporal modeling of ambient sulfur dioxide concentrations in rural Western Canada. Environmental Modeling & Assessment, 15(2), 137–146.

    Google Scholar 

  6. 6.

    Lee, D. S., Kingdon, R. D., Jenkin, M. E., & Webster, A. (2000). Modelling the contribution of different sources of sulphur to atmospheric deposition in the United Kingdom. Environmental Modeling & Assessment, 5(2), 105–118.

    Google Scholar 

  7. 7.

    Raheem, A. A., Adekola, F. A., & Obioh, I. O. (2009). The seasonal variation of the concentrations of ozone, sulfur dioxide, and nitrogen oxides in two Nigerian cities. Environmental Modeling & Assessment, 14(4), 497–509.

    Google Scholar 

  8. 8.

    Cai, Y., Chang, T., & Inglesi-Lotz, R. (2018). Asymmetric persistence in convergence for carbon dioxide emissions based on quantile unit root test with Fourier function. Energy, 161, 470–481.

    Google Scholar 

  9. 9.

    Pettersson, F., Maddison, D., Acar, S., & Söderholm, P. (2014). Convergence of carbon dioxide emissions: a review of the literature. International Review of Environmental and Resource Economics, 7(2), 141–178.

    Google Scholar 

  10. 10.

    Presno, M. J., Landajo, M., & González, P. F. (2018). Stochastic convergence in per capita CO2 emissions. An approach from nonlinear stationarity analysis. Energy Economics, 70, 563–581.

    Google Scholar 

  11. 11.

    Solarin, S. A. (2014). Convergence of CO2 emission levels: evidence from African countries. Journal of Economic Research, 19(1), 65–92.

    Google Scholar 

  12. 12.

    Alvarez, F., Marrero, G. A., & Puch, L. A. (2005). Air pollution and the macroeconomy across European countries. Documento de trabajo, 10, 1–40.

    Google Scholar 

  13. 13.

    Liu, C., Hong, T., Li, H., & Wang, L. (2018). From club convergence of per capita industrial pollutant emissions to industrial transfer effects: an empirical study across 285 cities in China. Energy Policy, 121, 300–313.

    CAS  Google Scholar 

  14. 14.

    Nourry, M. (2009). Re-examining the empirical evidence for stochastic convergence of two air pollutants with a pair-wise approach. Environmental and Resource Economics, 44(4), 555.

    Google Scholar 

  15. 15.

    Payne, J. E., Miller, S., Lee, J., & Cho, M. H. (2014). Convergence of per capita sulphur dioxide emissions across US states. Applied Economics, 46(11), 1202–1211.

    Google Scholar 

  16. 16.

    Hadri, K., & Kurozumi, E. (2011). A locally optimal test for no unit root in cross-sectionally dependent panel data. Hitotsubashi Journal of Economics, 165–184.

  17. 17.

    Acar, S., & Yeldan, A. E. (2018). Investigating patterns of carbon convergence in an uneven economy: the case of Turkey. Structural Change and Economic Dynamics., 46, 96–106.

    Google Scholar 

  18. 18.

    Lin, J., Inglesi-Lotz, R., & Chang, T. (2018). Revisiting CO2 emissions convergence in G18 countries. Energy Sources, Part B: Economics, Planning, and Policy, 13(5), 269–280.

    CAS  Google Scholar 

  19. 19.

    Shimamoto, K. (2017). Examining The existence of Co2 emission per capita convergence in East Asia. Regional Science Inquiry, 9(2), 11–28.

    Google Scholar 

  20. 20.

    Churchill, S. A., Inekwe, J., & Ivanovski, K. (2018). Conditional convergence in per capita carbon emissions since 1900. Applied Energy, 228, 916–927.

    Google Scholar 

  21. 21.

    Zang, Z., Zou, X., Song, Q., Wang, T., & Fu, G. (2018). Analysis of the global carbon dioxide emissions from 2003 to 2015: convergence trends and regional contributions. Carbon Management, 9(1), 45–55.

    CAS  Google Scholar 

  22. 22.

    List, J. A. (1999). Have air pollutant emissions converged among US regions? Evidence from unit root tests. Southern Economic Journal, 144-155.

  23. 23.

    Bulte, E., List, J. A., & Strazicich, M. C. (2007). Regulatory federalism and the distribution of air pollutant emissions. Journal of Regional Science, 47(1), 155–178.

    Google Scholar 

  24. 24.

    International Energy Agency (2016). Energy and air pollution. Available at https://www.iea.org/publications/freepublications/publication/WorldEnergyOutlookSpecialReport2016EnergyandAirPollution.pdf

  25. 25.

    Smith, S. J., Aardenne, J. V., Klimont, Z., Andres, R. J., Volke, A., & Delgado Arias, S. (2011). Anthropogenic sulfur dioxide emissions: 1850–2005. Atmospheric Chemistry and Physics, 11(3), 1101–1116.

    CAS  Google Scholar 

  26. 26.

    The Guardian (2014). Carbon emissions: coal reliance puts Australia second on OECD's dirt list. Available at https://www.theguardian.com/environment/2014/jan/10/carbon-emissions-australias-growth-puts-it-near-top-of-oecd-rankings

  27. 27.

    Becker, R., Enders, W., & Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381–409.

    Google Scholar 

  28. 28.

    Hadri, K., & Kurozumi, E. (2012). A simple panel stationarity test in the presence of serial correlation and a common factor. Economics Letters, 115(1), 31–34.

    Google Scholar 

  29. 29.

    Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574–599.

    Google Scholar 

  30. 30.

    Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics, 22(2), 265–312.

    Google Scholar 

  31. 31.

    Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239–253.

    Google Scholar 

  32. 32.

    Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. University of Cambridge Working Papers in Economics.

  33. 33.

    Baltagi, B. H., Feng, Q., & Kao, C. (2012). A Lagrange multiplier test for cross-sectional dependence in a fixed effects panel data model. Journal of Econometrics, 170(1), 164–177.

    Google Scholar 

  34. 34.

    Bahmani-Oskooee, M., & Gelan, A. (2006). Testing the PPP in the non-linear STAR framework: evidence from Africa. Economics Bulletin, 6(17), 1–15.

    Google Scholar 

  35. 35.

    Carrion-i-Silvestre, J., Del Barrio-Castro, T., & López-Bazo, E. (2005). Breaking the panels: an application to the GDP per capita. The Econometrics Journal, 8(2), 159–175.

    Google Scholar 

  36. 36.

    Strazicich, M. C., Lee, J., & Day, E. (2004). Are incomes converging among OECD countries? Time series evidence with two structural breaks. Journal of Macroeconomics, 26(1), 131–145.

    Google Scholar 

  37. 37.

    Romero-Ávila, D. (2009). Are OECD consumption–income ratios stationary after all? Economic Modelling, 26(1), 107–117.

    Google Scholar 

  38. 38.

    El-Montasser, G., Inglesi-Lotz, R., & Gupta, R. (2015). Convergence of greenhouse gas emissions among G7 countries. Applied Economics, 47(60), 6543–6552.

    Google Scholar 

  39. 39.

    OECD. (2007). Climate Change Policies. OECD Policy Briefs, August, 2007, 1–8.

    Google Scholar 

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Correspondence to Sakiru Adebola Solarin.

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Solarin, S.A., Tiwari, A. Convergence in Sulphur Dioxide (SO2) Emissions Since 1850 in OECD Countries: Evidence from a New Panel Unit Root Test. Environ Model Assess 25, 665–675 (2020). https://doi.org/10.1007/s10666-019-09687-5

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Keywords

  • Convergence
  • OECD countries
  • Sulphur dioxide (SO2) emissions
  • Structural breaks