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Measuring Energy Efficiency: An Application of LMDI Analysis to Power Sector in Kerala

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  • Pillai N., Vijayamohanan

Abstract

The traditional interest in energy efficiency has centred on a single energy input factor in terms of productivity that has become famous through the index method in terms of activity output per unit of energy use. The enquiry that has proceeded from the problems associated with this method has led to identifying the effect source of variation, in terms of decomposition analysis. A variant of factor decomposition analysis, index decomposition analysis takes energy as a single factor of production, and explores various effects on energy intensity changes, by decomposing these changes into pure intensity changes effect, structure changes effect and activity changes effect. The present paper seeks to measure energy efficiency in Kerala in terms of index decomposition analysis, using the Logarithmic Mean Divisia Index (LMDI) method. For the empirical exercise of decomposition, we consider two energy sectors of Kerala: power sector and petroleum sector. Since the petroleum consumption data is available only for the period from 2007-08 to 2016-17, we take this as our study period for the analysis. As the measure of activity, we have the usual real gross State domestic product (GSDP at 2011-12 prices). First we analyse the two sectors separately, and then the combined sector is analysed for decomposition. The petroleum consumption data relating only to the secondary and tertiary sub-sectors, the less-efficient petroleum sector is found to overweigh the combined energy sector of Kerala to such an extent that the energy-efficiency potential of these two sub-sectors gets clouded. A sufficiently high degree of energy efficiency in the petroleum sector can indeed reverse this anomaly.

Suggested Citation

  • Pillai N., Vijayamohanan, 2019. "Measuring Energy Efficiency: An Application of LMDI Analysis to Power Sector in Kerala," MPRA Paper 101981, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:101981
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    References listed on IDEAS

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    1. G. Boyd & J. F. McDonald & M. Ross & D. A. Hansont, 1987. "Separating the Changing Composition of U.S. Manufacturing Production from Energy Efficiency Improvements: A Divisia Index Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 77-96.
    2. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    3. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    4. Bossanyi, Ervin, 1979. "UK primary energy consumption and the changing structure of final demand," Energy Policy, Elsevier, vol. 7(3), pages 253-258, September.
    5. B. W. Ang & Ki-Hong Choi, 1997. "Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 59-73.
    6. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
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    More about this item

    Keywords

    Energy efficiency; Kerala; Power sector; Index decomposition; Divisia index.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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