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Literature Review and Methodology

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The Driving Forces of Change in Environmental Indicators

Part of the book series: Lecture Notes in Energy ((LNEN,volume 25))

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Abstract

In order to analyse the historical changes in economic, environmental, socio-economic and energy indicators, it is useful to identify, separate and evaluate the macroeconomic forces that contribute to those changes. Basically, the literature records four paradigms that may be used in order to decompose the change experienced by an indicator. These are (a) econometric analysis, (b) analysis based on aggregate data, (c) index-based analysis (Index Decomposition Analysis, or IDA), and (d) structural analysis (Structural Decomposition Analysis, or SDA).

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Notes

  1. 1.

    Sun’s original contribution only considers additive decompositions.

  2. 2.

    SDA is the technique most frequently used in decomposition studies based on input–output tables, and therefore it is sometimes known as input–output decomposition analysis.

  3. 3.

    In order to be acceptable, a class of economic indices must preserve all information and be mathematically consistent. Diewert (1980, 1990) derives a number of important developments in economic index number theory.

  4. 4.

    In this regard, a line integral is said to be independent of its path in an open region S in \({\Re^{n} }\) if (for \(\varphi\) continuous on S, with x and y being two points in S):

    $$\int_{{\,\varGamma \left( {x,y} \right)}} {\,\,\,\,\,\varphi \,{\text{d}}\alpha \left( t \right)} = \int_{{\,\varGamma_{1} \left( {x,y} \right)}} {\,\,\,\,\,\,\,\varphi \,} {\text{d}}\beta \left( t \right)$$

    for all paths \({\alpha \left( t \right)}\) and \({\beta \left( t \right)}\) describing curves \(\varGamma\) and \({\varGamma_{ 1} }\) such that \({\varGamma \subset S}\), \({\varGamma_{ 1} \subset S}\), \({\alpha \subset \varGamma }\), and \({\beta \subset \varGamma_{ 1} }.\)

  5. 5.

    The term ‘adaptive’ refers to the fact that the parameters are not fixed in advance. Instead, they are determined by the levels of the magnitudes in periods 0 and T.

  6. 6.

    Törnqvist et al. (1985) argue that the above logarithmic function was originally proposed by Törnqvist in (1935), though it is in their 1985 work where it was eventually specified that:

    1. (a)

      \(x\) and \(y\) should be positive numbers,

    2. (b)

      if \({x \ne y}\) the range of function \({L\left( {x,y} \right)}\) should be \({\left( {\left( {xy} \right)^{ 1/ 2} ,\left( {x + y} \right)/ 2} \right)}\).

References

  • Albrecht J, Francois D, Schoors K (2002) A Shapley decomposition of carbon emissions without residuals. Energy Policy 30(9):727–736

    Article  Google Scholar 

  • Ang BW (1994) Decomposition of industrial energy consumption: the energy intensity approach. Energy Econ 16(3):163–174

    Article  MathSciNet  Google Scholar 

  • Ang BW (1995a) Decomposition methodology in industrial energy demand analysis. Energy 20(11):1081–1095

    Article  Google Scholar 

  • Ang BW (1995b) Multilevel decomposition of industrial energy consumption. Energy Econ 17(1):39–51

    Article  Google Scholar 

  • Ang BW (2005) The LMDI approach to decomposition analysis: a practical guide. Energy Policy 33(7):867–871

    Article  MathSciNet  Google Scholar 

  • Ang BW, Choi KH (1997) Decomposition of aggregate energy and gas emission intensities for industry: a refined Divisia index method. Energy J 18(3):59–73

    Article  Google Scholar 

  • Ang BW, Lee SY (1994) Decomposition of industrial energy consumption: some methodological and application issues. Energy Econ 16(2):83–92

    Article  Google Scholar 

  • Ang BW, Skea JF (1994) Structural change sector, sector disaggregation and electricity consumption in the UK industry. Energy Environ 5(1):1–16

    Google Scholar 

  • Boyd G, Hanson DA, Sterner T (1988) Decomposition of changes in energy intensity: a comparison of the Divisia index and other methods. Energy Econ 10(4):309–312

    Article  Google Scholar 

  • Boyd G, McDonald JF, Ross M, Hanson DA (1987) Separating the changing composition of US manufacturing production from energy efficiency improvements: a Divisia index approach. Energy J 8(2):77–96

    Article  Google Scholar 

  • de Bruyn SM, van den Bergh JC, Opschoor JB (1998) Economic growth and emissions: reconsidering the empirical basis of environmental Kuznets curves. Ecol Econ 25(2):161–175

    Article  Google Scholar 

  • Chen CY, Rose A (1989) A structural decomposition analysis of changes in energy demand in Taiwan: 1971–1984. Energy J 11(1):127–146

    Google Scholar 

  • Choi KH, Ang BW (2012) Attribution of changes in Divisia real energy intensity index: an extension to index decomposition analysis. Energy Econ 34(1):171–176

    Article  Google Scholar 

  • Dietzenbacher E, Hoen A, Los B (2000) Labor productivity in Western Europe 1975–1985: an intercountry, interindustry analysis. J Region Sci 40(3):425–452

    Article  Google Scholar 

  • Diewert WE (1980) Recent developments in the economic theory of index numbers: capital and the theory of productivity. Am Econ Rev 70(2):260–267

    Google Scholar 

  • Diewert WE (1990) Price level measurement. North-Holland, Amsterdam

    MATH  Google Scholar 

  • Divisia, F. L. (1925): “Indice monétaire et la théorie de la monnaie,” Revue d´Economie Politique, 39, pp. 980-1008

    Google Scholar 

  • Fernández González P, Landajo M, Presno MJ (2013) The Divisia real energy intensity indices: evolution and attribution of percent changes in 20 European countries from 1995 to 2010. Energy 58(1):340–349

    Google Scholar 

  • Fernández González P, Landajo M, Presno MJ (2014a) Multilevel LMDI decomposition of changes in aggregate energy consumption. A cross country analysis in the EU-27. Energy Policy 68:576–584

    Google Scholar 

  • Fernández Vázquez E (2004) The use of entropy econometrics in decomposing structural change. Universidad de Oviedo (Spain), Thesis

    Google Scholar 

  • Fernández Vázquez E, Fernández González P (2008) An extension to Sun´s decomposition methodology: the path based approach. Energy Econ 30(3):1020–1036

    Article  Google Scholar 

  • Fisher I (1922) The making of index numbers; a study of their varieties, tests, and reliability. Houghton Mifflin, Boston

    Google Scholar 

  • Gardner DT (1993) Industrial energy use in Ontario from 1962 to 1984. Energy Econ 15(1):25–32

    Article  Google Scholar 

  • Gardner DT, Elkhafif MAT (1998) Understanding industrial energy use: structural and energy intensity changes in Ontario industry. Energy Econ 20(1):29–41

    Article  Google Scholar 

  • Greening LA, Davis WB, Schipper L, Khrushch M (1997) Comparison of six decomposition methods: application to aggregate energy intensity for manufacturing in 10 OECD countries. Energy Econ 19(3):375–390

    Article  Google Scholar 

  • Hankinson GA, Rhys MM (1983) Electricity consumption, electrticity intensity and industrial structure. Energy Econ 5(3):146–152

    Google Scholar 

  • Hatzigeorgiou E, Polatidis H, Haralambopoulos D (2008) CO2 emissions in Greece for 1990–2002: a decomposition analysis and comparison of results using the arithmetic mean Divisia index and logarithmic mean Divisia index techniques. Energy 33(3):492–499

    Article  Google Scholar 

  • Hoekstra R, van der Bergh JCJM (2003) Comparing structural and index decomposition analysis. Energy Econ 25(1):39–64

    Article  Google Scholar 

  • Howarth RB, Schipper L, Duerr PA, Strøm S (1991) Manufacturing energy use in eight OECD countries. Energy Econ 13(2):135–142

    Article  Google Scholar 

  • Hulten CR (1973) Divisia index numbers. Econometrica 41(6):1017–1025

    Article  MATH  MathSciNet  Google Scholar 

  • Hulten CR (1987) Divisia index. In: Eatwell J et al. (Eds) The new palgrave dictionary of economics. Palgrave Macmillan. (See online at: http://www.dictionaryofeconomics.com/article?id=pde1987_X000612). DOI:10.1057/9780230226203.2399. Palgrave Macmillan. Accessed 14 Sept 2012

  • Jenne C, Cattell R (1983) Structural change and energy efficiency in industry. Energy Econ 5(2):114–123

    Google Scholar 

  • Kaya Y (1990) Impact of carbondioxide emission control on GDP growth: interpretation and proposed scenarios,” IPCC Energy and Industry Subgroup, Response Strategies Working Group, Paris.

    Google Scholar 

  • Lee K, Oh W (2006) Analysis of CO2 emissions in APEC countries: a time-series and a cross-sectional decomposition using the log mean Divisia method. Energy Policy 34(17):2779–2787

    Article  Google Scholar 

  • Li JW, Shrestha RM, Foell WK (1990) Structural change and energy use: the case of the manufacturing sector in Taiwan. Energy Econ 12(2):109–115

    Google Scholar 

  • Liu XQ, Ang BW, Ong HL (1992) The application of the Divisia index to the decomposition of changes in industrial energy consumption. Energy J 13(4):161–177

    Article  Google Scholar 

  • Ma C, Stern DI (2008) China’s changing energy intensity trend: a decomposition analysis. Energy Econ 30(3):1037–1053

    Article  Google Scholar 

  • Morović T, Gerritse G, Jaeckel G, Jochem E, Mannsbart W, Poppke H, Witt B (1989) Energy conservation indicators II. Springer, Berlin

    Book  Google Scholar 

  • Nag B, Parikh J (2000) Indicators of carbon emission intensity from commercial energy use in India. Energy Econ 22(4):441–461

    Article  Google Scholar 

  • Panayotou T (1997) Demystifying the environmental Kuznets curve misleading us? The case of CO2 emissions. Environ Dev Econ 2(4):465–484

    Article  Google Scholar 

  • Park SH (1992) Decomposition of industrial energy consumption—an alternative method. Energy Econ 14(4):265–270

    Article  Google Scholar 

  • Park SH, Dissmann B, Nam KY (1991) A cross-country decomposition analysis of manufacturing energy consumption. Energy 18(2):93–100

    Google Scholar 

  • Reitler W, Rudolph M, Schaefer M (1987) Analysis of the factors influencing energy consumption in industry: a revised method. Energy Econ 9(3):145–148

    Article  Google Scholar 

  • Richter MK (1966) Invariance axioms and economic indexes. Econometrica 34(4):739–755

    Article  MATH  Google Scholar 

  • Sahu SK, Narayanan K (2010) Decomposition of industrial energy consumption in Indian manufacturing: the energy intensity approach. J Environ Manag Tour Assoc Sustain Educ, Res Sci 1:22–38

    Google Scholar 

  • Sato K (1976) The ideal log-change index number. Rev Econ Stat 58(2):223–228

    Article  Google Scholar 

  • Shahiduzzaman Md, Alam K (2013) Changes in energy efficiency in Australia: a decomposition of aggregate energy intensity using Logarithmic Mean Divisia approach. Energy Policy 56:341–351

    Article  Google Scholar 

  • Sun JW (1998) Changes in energy consumption and energy intensity: a complete decomposition model. Energy Econ 20(19):85–100

    Article  Google Scholar 

  • Sun JW, Ang BW (2000) Some properties of an exact decomposition model. Energy 25(12):1177–1188

    Article  Google Scholar 

  • Törnqvist L (1935) A memorandum concerning the calculation of Bank of Finland consumption price index. Bank of Finland, Helsinki

    Google Scholar 

  • Törnqvist L, Vartia P, Varita Y (1985) How should relative changes be measured? Am Stat 39(1):43–46

    Google Scholar 

  • Wood R (2009) Structural decomposition analysis of Australia’s greenhouse gas emissions. Energy Policy 37(11):4943–4948

    Article  Google Scholar 

  • Zhang Z (2003) Why did the energy intensity fall in China’s industrial sector in the 1990s? The relative importance of structural change and intensity change. Energy Econ 25(6):625–638

    Article  Google Scholar 

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Authors and Affiliations

  1. University of Oviedo, Oviedo, Spain

    Paula Fernández González, Manuel Landajo & MªJosé Presno

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  1. Paula Fernández González
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  2. Manuel Landajo
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  3. MªJosé Presno
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Correspondence to Paula Fernández González .

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Fernández González, P., Landajo, M., Presno, M. (2014). Literature Review and Methodology. In: The Driving Forces of Change in Environmental Indicators. Lecture Notes in Energy, vol 25. Springer, Cham. https://doi.org/10.1007/978-3-319-07506-8_1

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  • DOI: https://doi.org/10.1007/978-3-319-07506-8_1

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