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Energy-GDP decoupling in a second best world—a case study on India

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Abstract

Reference emission scenarios in the literature have been the target of criticisms that suggest they convey too optimistic views on spontaneous energy-GDP decoupling of emerging countries economies. This article focuses on the case of India. It explores the role of current suboptimalities of the Indian power sector (structural under-investment in the sector leading to capacity shortage, power cuts and low efficiency) on future energy-GDP decoupling. To do so, it uses a hybrid general equilibrium framework, in which these suboptimalities are explicitly introduced. The results highlight that whether the constraints on investments in the power sector persist or not leads to contrasted trends in energy-GDP decoupling and GHG emissions. Over the short-term, capital scarcity in the power sector constrains the development of energy-intensive activities and therefore leads to higher energy-GDP decoupling. But on the longer-term, constrains on the power sector capacity limits substitution from fossil fuels to electricity, which entails both a low energy-GDP decoupling and a constraint on GDP growth when oil prices are high. The alleviation of suboptimalities appears thus as an insurance policy towards future oil price increase.

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Notes

  1. These revisions upwards of future growth rates for emerging countries date from before the financial crisis. More recent studies either keep assuming high growth rates for emerging countries in the coming years (see for instance IEO 2009 in Table 1), or take into account a relative slowdown of economic growth (see for instance WEO 2009 in Table 1).

  2. Following the Copenhagen Accord, India pledged to reduce the emission intensity of its GDP by 20–25% in 2020 compared to 2005 level, and China to lower its carbon dioxide emissions per unit of GDP by 40–45% in 2020 compared to 2005 level.

  3. In IEO, energy demand growth drivers for India are not detailed.

  4. In this subsection, we often refer to WEO 2007, as this edition was dedicated to India and China.

  5. This number however corresponds to a relatively low equipment rate: around 200 vehicles for 1000 persons. It is around 800 vehicles for 1000 persons today in USA.

  6. Over the projection period, the efficiency of coal fired power generation is projected to improve considerably, as the new plants will be larger and more efficient, and more supercritical units will be built.

  7. These measures are not considered in the IEP reference scenario.

  8. The level of T&D losses is in fact uncertain. For instance, the value stated by the Indian Planning Commission was 22% in 1998 while the World Bank (1998) pointed out that it could actually be twice this official level. Moreover, as there is no metering of the electricity consumption it is difficult to distinguish technical from commercial losses.

  9. For further description of suboptimalities and of the institutional aspects of the Indian power sector, refer to Mathy and Guivarch (2010).

  10. Details concerning calibration and disaggregation are given in SOM.

  11. See SOM for details on these assumptions.

  12. Guivarch et al. (2011) analyze the impact of the real wages rigidities on the model results.

  13. Following (Corrado and Mattey 1997), we assume that this is generally caused by higher labour costs due to extra hours with lower productivity, costly night work and more maintenance works.

  14. See SOM for further details on the representation of the evolution of energy supply and demand, energy efficiency and induced technical change.

  15. Mean generation costs increase when capacity is overused due to the existence of static decreasing returns due to higher labour costs and because less efficient units are switched on last at the aggregate level. By default, following Corrado and Mattey (1997), in our model the increasing factor is attached to wages.

  16. There are alternative representation of shortages, in particular explicit restriction of demand growth in some sectors, which could have different economic effects.

  17. Oil prices in imaclim-r result from the endogenous interplay between the strategic behaviour of oil producers, constraints on supply (temporal constraints on capacity development and total reserves available) and demand dynamics. Assumptions concerning oil reserves amount to 2.200 Gbl of conventional oil and 1.200Gbl of non conventional oil (including extra-oil in Venezuela and tar sands in Canada). This is in line with estimates from the US Geological Survey.

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Correspondence to Céline Guivarch.

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Guivarch, C., Mathy, S. Energy-GDP decoupling in a second best world—a case study on India. Climatic Change 113, 339–356 (2012). https://doi.org/10.1007/s10584-011-0354-8

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