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Parametric and non-parametric convergence analysis of electricity intensity in developed and developing countries

  • Sakiru Adebola SolarinEmail author
Research Article
  • 16 Downloads

Abstract

This paper examines the pattern of convergence in electricity intensity in a sample of 79 countries. We apply the residual augmented least squares regression to the convergence of energy intensity. This method has been used in the convergence of per capita energy consumption but not convergence of energy intensity. Furthermore, in contrast to the previous studies which mainly used the conventional beta convergence approach to examine conditional convergence, we use a beta convergence method that is capable of identifying the actual number of countries that contribute to conditional convergence. The sigma and gamma convergences of electricity intensity are also examined. In addition to the full sample of countries, we also examine convergence in African countries, Asian and Oceanic countries, American countries and European countries, separately. Convergences in OECD and non-OECD countries are also examined, separately. In the full sample, the results show convergence exists in 54% of the countries in the total sample. There is convergence in 65% of the African countries, 61% of the American countries, 43% of the Asian and Oceanic countries and 33% of the European countries. In terms of the regional classification, it is also observed that convergence exists for 58% of the non-OECD countries and 31% of the OECD countries. There is evidence for sigma convergence in all the blocs with the exception of European and non-OECD countries. With the exception of African countries, there is evidence for gamma convergence in all the countries and the various blocs. The policy implications of the results are discussed.

Keywords

Electricity intensity Conditional convergence Sigma convergence Gamma convergence Policy implications 

JEL Classification

C32 Q49 

Notes

References

  1. Abid M, Alimi M (2018) Stochastic convergence in US disaggregated gas consumption at the sector level. Journal of Natural Gas Science and Engineering 60:1–37CrossRefGoogle Scholar
  2. Aldy JE (2007) Divergence in state-level per capita carbon dioxide emissions. Land Econ 83(3):353–369CrossRefGoogle Scholar
  3. Armey LE, Hosman L (2016) The centrality of electricity to ICT use in low-income countries. Telecommun Policy 40(7):617–627CrossRefGoogle Scholar
  4. Barro RJ, Sala-i-Martin X, Blanchard OJ, Hall RE (1991) Convergence across states and regions. Brook Pap Econ Act 1991:107–182CrossRefGoogle Scholar
  5. Boyle GE, McCarthy TG (1997) A simple measure of b-convergence. Oxf Bull Econ Stat 59(2):0305–9049CrossRefGoogle Scholar
  6. Burnett JW, Madariaga J (2017) The convergence of US state-level energy intensity. Energy Econ 62:357–370CrossRefGoogle Scholar
  7. Carlino GA, Mills LO (1993) Are US regional incomes converging? A time series analysis. J Monet Econ 32(2):335–346CrossRefGoogle Scholar
  8. Csereklyei Z, Stern DI (2015) Global energy use: decoupling or convergence? Energy Econ 51:633–641CrossRefGoogle Scholar
  9. Dawson JW, Strazicich MC (2010) Time-series tests of income convergence with two structural breaks: evidence from 29 countries. Appl Econ Lett 17(9):909–912CrossRefGoogle Scholar
  10. Ezcurra R (2007) Distribution dynamics of energy intensities: a cross-country analysis. Energy Policy 35(10):5254–5259CrossRefGoogle Scholar
  11. Fallahi F, Voia MC (2015) Convergence and persistence in per capita energy use among OECD countries: Revisited using confidence intervals. Energy Econ 52: 246–253Google Scholar
  12. Friedman M (1992) Do old fallacies ever die? J Econ Lit 30:2129–2132Google Scholar
  13. Galvao AF, Reis Gomes FA (2007) Convergence or divergence in Latin America? A time series analysis. Appl Econ 39(11):1353–1360CrossRefGoogle Scholar
  14. Hajko V (2014) The energy intensity convergence in the transport sector. Procedia Economics and Finance 12:199–205CrossRefGoogle Scholar
  15. Henry M, Kneller R, Milner C (2009) Trade, technology transfer and national efficiency in developing countries. Eur Econ Rev 53(2):237–254CrossRefGoogle Scholar
  16. Herrerias MJ, Liu G (2013) Electricity intensity across Chinese provinces: new evidence on convergence and threshold effects. Energy Econ 36:268–276CrossRefGoogle Scholar
  17. Le Pen Y, Sévi B (2010) On the non-convergence of energy intensities: evidence from a pair-wise econometric approach. Ecol Econ 69(3):641–650CrossRefGoogle Scholar
  18. Le TH, Chang Y, Park D (2017) Energy demand convergence in APEC: An empirical analysis. Energy Econ 65:32–41CrossRefGoogle Scholar
  19. Lee J, Strazicich MC (2003) Minimum Lagrange multiplier unit root test with two structural breaks. Rev Econ Stat 85(4):1082–1089CrossRefGoogle Scholar
  20. Lee J, Strazicich MC, Meng M (2012) Two-step LM unit root tests with trend-breaks. J Stat Econ Methods 1(2):81–107Google Scholar
  21. Liddle B (2009) Electricity intensity convergence in IEA/OECD countries: aggregate and sectoral analysis. Energy Policy 37(4):1470–1478CrossRefGoogle Scholar
  22. Liddle B (2010) Revisiting world energy intensity convergence for regional differences. Appl Energy 87(10):3218–3225CrossRefGoogle Scholar
  23. Markandya A, Pedroso-Galinato S, Streimikiene D (2006) Energy intensity in transition economies: is there convergence towards the EU average? Energy Econ 28(1):121–145CrossRefGoogle Scholar
  24. Meng M, Payne JE, Lee J (2013) Convergence in per capita energy use among OECD countries. Energy Econ 36:536–545CrossRefGoogle Scholar
  25. Meng M, Im KS, Lee J, Tieslau MA (2014) More powerful LM unit root tests with non-normal errors. In: Sickles RC, Horrace WC (eds) Festschrift in Honor of Peter Schmidt. Springer, New York, pp 343–357CrossRefGoogle Scholar
  26. Mishra V, Smyth R (2017) Conditional convergence in Australia’s energy consumption at the sector level. Energy Econ 62:396–403CrossRefGoogle Scholar
  27. Mulder P, de Groot HL (2012) Structural change and convergence of energy intensity across OECD countries, 1970–2005. Energy Econ 34(6):1910–1921CrossRefGoogle Scholar
  28. Nieswiadomy ML, Strazicich MC (2004) Are political freedoms converging? Econ Inq 42(2):323–340CrossRefGoogle Scholar
  29. Ozcan B, Ulucak R, Dogan E (2019) Analyzing long lasting effects of environmental policies: evidence from low, middle and high income economies. Sustainable Cities and Society 44:130–143CrossRefGoogle Scholar
  30. Payne JE, Vizek M, Lee J (2017) Stochastic convergence in per capita fossil fuel consumption in US states. Energy Econ 62:382–395CrossRefGoogle Scholar
  31. Pesaran MH (2007) A pair-wise approach to testing for output and growth convergence. J Econ 138(1):312–355CrossRefGoogle Scholar
  32. Quah D (1993) Galton’s fallacy and tests of the convergence hypothesis. Scand J Econ 95:427–443CrossRefGoogle Scholar
  33. Solarin SA, Lean HH (2016) Are fluctuations in oil consumption permanent or transitory? Evidence from linear and nonlinear unit root tests. Energy Policy 88:262–270CrossRefGoogle Scholar
  34. Solarin SA, Lean HH (2018) Conditional convergence in energy consumption per capita of OPEC member countries: evidence from non-linearity tests. OPEC Energy Review 42(3):199–211CrossRefGoogle Scholar
  35. Ulucak R, Apergis N (2018) Does convergence really matter for the environment? An application based on club convergence and on the ecological footprint concept for the EU countries. Environ Sci Pol 80:21–27CrossRefGoogle Scholar
  36. World Bank (2017). World Development Indicators. (2016) Retrieved from: www.data.worldbank.org. Accessed 26 Dec 2017
  37. Xin-gang Z, Yuan-feng Z, Yan-bin L (2019) The spillovers of foreign direct investment and the convergence of energy intensity. J Clean Prod 206(1):611–621CrossRefGoogle Scholar
  38. Zhang W, Pan X, Yan Y, Pan X (2017a) Convergence analysis of regional energy efficiency in china based on large-dimensional panel data model. J Clean Prod 142:801–808CrossRefGoogle Scholar
  39. Zhang C, Zhou K, Yang S, Shao Z (2017b) On electricity consumption and economic growth in China. Renew Sust Energ Rev 76:353–368CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of BusinessMultimedia UniversityMelakaMalaysia

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