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Energy Efficiency: A Sectoral Analysis for Kerala

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  • Pillai N., Vijayamohanan
  • AM, Narayanan

Abstract

One positive impact of the 1973 oil crises has been the concerted effort across the world to reduce energy consumption through energy use efficiency improvements. Improving energy efficiency ensures the objective of conserving energy and thus promoting sustainable development. Recognition of this fact has now appeared in terms of including the aim of improving efficiency as an important component of electrical energy policy in all the countries across the globe. A large number of studies have demonstrated that the aggregate energy efficiency inherently encompasses a number of factors that affect energy intensity, viz., a structural effect, representing the effect of changes in economic structure, an activity effect, representing the changes in the levels of aggregate activity, a wealth effect, representing changes in GDP, and an underlying energy efficiency effect, including a technical effect and an energy quality effect. This new light has in turn led to the development of the techniques of factorization or decomposition. Energy efficiency research in general has opened up three avenues of enquiry, namely, the measurement of energy productivity, the identification of impact elements (such as the three factors mentioned above) and the energy efficiency assessment. The traditional interest in energy efficiency has centred on a single energy input factor in terms of productivity that has become famous through an index method proposed by Patterson (1996). The enquiry that has proceeded from the problems associated with this method has led to identifying the effect source of variation, in terms of some decomposition analysis. Almost all the earlier studies have in general employed the method of indicators pyramid, based on which energy efficiency changes have been decomposed from other factors at each level of disaggregation using factorization method. The Laspeyres index decomposition approach was in vogue earlier that has now been replaced with methodologically superior Divisia approach, in terms of Logarithmic Mean Divisia index (LMDI). Finally, a new energy efficiency estimation method, criticizing the single factor energy efficiency method, has come up utilizing a multi-variate structure. Here we have a parametric (econometric) approach, in terms of frontier production function analysis, and a non-parametric approach, in terms of data envelopment analysis (DEA).

Suggested Citation

  • Pillai N., Vijayamohanan & AM, Narayanan, 2019. "Energy Efficiency: A Sectoral Analysis for Kerala," MPRA Paper 101424, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:101424
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    References listed on IDEAS

    as
    1. Dale W. Jorgenson, 1984. "The Role of Energy in Productivity Growth," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 11-26.
    2. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-598, October.
    3. 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.
    4. Stern, David I., 2010. "Modeling International Trends in Energy Efficiency and Carbon Emissions," Research Reports 94950, Australian National University, Environmental Economics Research Hub.
    5. Gales, Ben & Kander, Astrid & Malanima, Paolo & Rubio, Mar, 2007. "North versus South: Energy transition and energy intensity in Europe over 200 years," European Review of Economic History, Cambridge University Press, vol. 11(2), pages 219-253, August.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Hoover,Kevin D., 2015. "Applied Intermediate Macroeconomics," Cambridge Books, Cambridge University Press, number 9781107436824, January.
    8. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    9. Ang, B.W., 2006. "Monitoring changes in economy-wide energy efficiency: From energy-GDP ratio to composite efficiency index," Energy Policy, Elsevier, vol. 34(5), pages 574-582, March.
    10. Schmidt, Peter, 1976. "On the Statistical Estimation of Parametric Frontier Production Functions," The Review of Economics and Statistics, MIT Press, vol. 58(2), pages 238-239, May.
    11. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    12. Seiford, Lawrence M. & Thrall, Robert M., 1990. "Recent developments in DEA : The mathematical programming approach to frontier analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 7-38.
    13. Usher, Dan (ed.), 1980. "The Measurement of Capital," National Bureau of Economic Research Books, University of Chicago Press, number 9780226843001, October.
    14. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    15. Patterson, M.G., 1993. "An accounting framework for decomposing the energy-to-GDP ratio into its structural components of change," Energy, Elsevier, vol. 18(7), pages 741-761.
    16. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    17. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, June.
    18. 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.
    19. Avi J. Cohen, 2003. "Retrospectives: Whatever Happened to the Cambridge Capital Theory Controversies?," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 199-214, Winter.
    20. Harcourt,G. C., 2022. "Some Cambridge Controversies in the Theory of Capital," Cambridge Books, Cambridge University Press, number 9781009158152, January.
    21. Bossanyi, Ervin, 1979. "UK primary energy consumption and the changing structure of final demand," Energy Policy, Elsevier, vol. 7(3), pages 253-258, September.
    22. Choonjoo Lee, 2010. "An Efficient Data Envelopment Analysis with Large Data Set in Stata," BOS10 Stata Conference 3, Stata Users Group.
    23. 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.
    24. Ayres, Robert U & Kneese, Allen V, 1969. "Production , Consumption, and Externalities," American Economic Review, American Economic Association, vol. 59(3), pages 282-297, June.
    25. Jesus Felipe & Franklin M. Fisher, 2003. "Aggregation in Production Functions: What Applied Economists should Know," Metroeconomica, Wiley Blackwell, vol. 54(2‐3), pages 208-262, May.
    26. Stern, David I., 1997. "Limits to substitution and irreversibility in production and consumption: A neoclassical interpretation of ecological economics," Ecological Economics, Elsevier, vol. 21(3), pages 197-215, June.
    27. Yong-bae Ji & Choonjoo Lee, 2010. "Data envelopment analysis," Stata Journal, StataCorp LP, vol. 10(2), pages 267-280, June.
    28. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    29. Murray Brown, 1980. "The Measurement of Capital Aggregates: A Postreswitching Problem," NBER Chapters, in: The Measurement of Capital, pages 377-432, National Bureau of Economic Research, Inc.
    30. 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.
    31. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    32. Jesus Felipe & John S.L. McCombie, 2013. "The Aggregate Production Function and the Measurement of Technical Change," Books, Edward Elgar Publishing, number 1975.
    33. Richmond, J, 1974. "Estimating the Efficiency of Production," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(2), pages 515-521, June.
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    More about this item

    Keywords

    Energy Efficiency; Productivity; Kerala; Decomposition; Data Envelopment Analysis; Stochastic Frontier Model;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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