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Empirics of the International Inequality in \(\hbox {CO}_{2}\) Emissions Intensity: Explanatory Factors According to Complementary Decomposition Methodologies

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Abstract

This paper analyses the international inequalities in \(\hbox {CO}_{2}\) emissions intensity for the period 1971–2009 and assesses explanatory factors. Group, additive and multiplicative methodologies of inequality decomposition are employed. The first allows us to understand the role of regional groups; the second allows us to investigate the role of different fossil energy sources (coal, oil and gas); and the third allows us to clarify the separated role of the carbonisation index and the energy intensity in the pattern observed for inequalities in \(\hbox {CO}_{2}\) intensities. The results show that, first, the reduction in global emissions intensity has coincided with a significant reduction in international inequality. Second, the bulk of this inequality and its reduction are attributed to differences between the groups of countries considered. Third, coal is the main energy source explaining these inequalities, although the growth in the relative contribution of gas is also remarkable. Fourth, the bulk of inequalities between countries and its decline are explained by differences in energy intensities, although there are significant differences in the patterns demonstrated by different groups of countries. The policy implications of these results are discussed.

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Notes

  1. They identify various groups of countries that converge to different equilibriums and conclude that these differences are more due for differences in convergence in the carbonisation index than for differences in the dynamics of energy intensity.

  2. The Theil (1) index can be decomposed, but the interaction element does not have a clear interpretation.

  3. In short, as regards global IEA (2011) data, the analysis only excluded Botswana, Cambodia, Eritrea, Mongolia, Namibia and Netherlands Antilles, due to problems with the availability of data.

  4. The estimates are based on Gaussian kernel functions (see Quah 1996) that have also, for example, been used in Ezcurra (2007) and Padilla and Serrano (2006) for the case of \(\hbox {CO}_{2}\) emissions per capita. The smoothing parameter is determined endogenously through the Silverman method (1986). The results did not vary significantly using other functions. Estimates are available upon request.

  5. It must be kept in mind that coal is the most carbon intensive fossil source, whereas gas is the least. If we had two countries with same GDP, the one with higher coal in its energy mix would register, ceteris paribus, a higher \(\hbox {CO}_{2}\) intensity.

  6. In terms of the absolute increase in emissions associated with coal, China is clearly the leading country, with an increase of 5,042 Mt between 1971 and 2009 (a 744 % increase); the increases are much lower in India with 938 Mt (658 % more) and the USA with 753 Mt (a 70 % increase). Among the countries with a greater reduction are Germany (264 Mt), the UK (235 Mt) and the former USSR (207 Mt). The increase in oil as a source of \(\hbox {CO}_{2}\) can be attributed to China (833 Mt), India (344 Mt) and Saudi Arabia (267 Mt), while the main reductions take place in the former USSR (220 Mt) and Germany (115 Mt). With respect to gas, the increase is especially attributable to the former USSR (693 Mt), which has abundant reserves of this resource.

  7. In a study for OECD countries, Duro et al. (2010) showed for a similar period a significant trend towards the convergence of energy efficiency between countries sector by sector, which explained much of the general trend for decreasing differences in energy intensities, but also that sector specialisation was increasingly explaining inequality in the final use of energy. However, these results may not be extendable to our wider and more heterogeneous sample, which includes both developed and developing countries.

  8. More sophisticated indicators have recently been used for analysing the convergence in “eco-efficiency”, such as the ones by Camarero et al. (2013a) for different greenhouse gases in 22 OECD countries, and Camarero et al. (2014) for different atmospheric pollutants, including \(\hbox {CO}_{2}\), in the EU. These studies assess “eco-efficiency” at both country and greenhouse-gas-specific levels using data envelopment analysis techniques and directional distance functions, and find an improvement in “eco-efficiency” and the existence of different clubs of convergence.

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Acknowledgments

We are grateful to two anonymous reviewers and the editor. The authors acknowledge support from projects ECO2013-45380-P and ECO2012-34591 (Spanish Ministry of Economy and Competitiveness), and XREAP (DGR).

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Authors and Affiliations

  1. Departament d’Economia and CREIP, Universitat Rovira i Virgili, Av. de la Universitat, 1, 43204, Reus, Spain

    Juan Antonio Duro & Jordi Teixidó-Figueras

  2. Department of Applied Economics, Univ. Autónoma de Barcelona, Campus de Bellaterra, Edificio B, 08193, Cerdanyola del Vallès, Spain

    Emilio Padilla

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  1. Juan Antonio Duro
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  2. Jordi Teixidó-Figueras
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  3. Emilio Padilla
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Corresponding author

Correspondence to Emilio Padilla.

Appendix

Appendix

1.1 Groups of countries:

  • OECD-Europe: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovak Republic, Spain, Sweden, Switzerland, Turkey, United Kingdom.

  • OECD-North America: Canada, Mexico, United States.

  • OECD-Pacific: Australia, Japan, Korea, New Zealand.

  • Non-OECD Europe countries: Albania, Bulgaria, Cyprus, Gibraltar, Malta, Romania, Former USSR, Former Yugoslavia.

  • Africa: Algeria, Angola, Benin, Cameroon, Congo, Democratic Republic of Congo, Côte d’Ivoire, Egypt, Ethiopia, Gabon, Ghana, Kenya, Libya, Morocco, Mozambique, Nigeria, Senegal, South Africa, Sudan, United Republic of Tanzania, Togo, Tunisia, Zambia, Zimbabwe, Other Africa.

  • Latin America: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Haiti, Honduras, Jamaica, Nicaragua, Panama, Paraguay, Peru, Trinidad and Tobago, Uruguay, Venezuela, Other Latin America.

  • Middle East: Bahrain, Islamic Republic of Iran, Iraq, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, United Arab Emirates, Yemen.

  • Asia: Bangladesh, Brunei Darussalam, Chinese Taipei, India, Indonesia, Dem. People’s Rep. of Korea, Malaysia, Myanmar, Nepal, Pakistan, Philippines, Singapore, Sri Lanka, Thailand, Vietnam, Other Asia.

  • China: People’s Republic of China, Hong Kong.

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Duro, J.A., Teixidó-Figueras, J. & Padilla, E. Empirics of the International Inequality in \(\hbox {CO}_{2}\) Emissions Intensity: Explanatory Factors According to Complementary Decomposition Methodologies. Environ Resource Econ 63, 57–77 (2016). https://doi.org/10.1007/s10640-014-9840-6

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  • DOI: https://doi.org/10.1007/s10640-014-9840-6

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