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Decomposition analysis: when to use which method?

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  • Paul de Boer
  • João F. D. Rodrigues

Abstract

Structural and index decomposition analyses allow identifying the main drivers of observed changes over time of energy and environmental impacts. These decomposition analyses have become very popular in recent decades and, many alternative methods to implement them have become available. Several of the most popular methods have been developed earlier in index number theory, a context in which each particular method is defined by adhering to a set of properties. The goal of the present paper is to review the main results of index number theory and discuss its connection to decomposition analyses. By doing so, we can present a decision tree that allows users to choose a decomposition method that meets desired properties. We report as hands-on example an empirical case study of the carbon footprint of the Netherlands in the period 2004–2005.

Suggested Citation

  • Paul de Boer & João F. D. Rodrigues, 2020. "Decomposition analysis: when to use which method?," Economic Systems Research, Taylor & Francis Journals, vol. 32(1), pages 1-28, January.
  • Handle: RePEc:taf:ecsysr:v:32:y:2020:i:1:p:1-28
    DOI: 10.1080/09535314.2019.1652571
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    Cited by:

    1. Fernández-Amador, Octavio & Francois, Joseph F. & Oberdabernig, Doris A. & Tomberger, Patrick, 2023. "Energy footprints and the international trade network: A new dataset. Is the European Union doing it better?," Ecological Economics, Elsevier, vol. 204(PA).
    2. Edwin Bernard F. Lisaba & Neil Stephen A. Lopez, 2021. "Spatiotemporal Comparison of Drivers to CO 2 Emissions in ASEAN: A Decomposition Study," Sustainability, MDPI, vol. 13(11), pages 1-21, May.
    3. Eichfelder, Sebastian & Kluska, Mike & Knaisch, Jonas & Selle, Juliane, 2021. "Senkung der Unternehmenssteuerlast versus Förderung von Investitionen: Was ist die bessere Strategie zur Förderung der Standortattraktivität Deutschlands?," arqus Discussion Papers in Quantitative Tax Research 263, arqus - Arbeitskreis Quantitative Steuerlehre.
    4. Lach, Łukasz, 2022. "Optimization based structural decomposition analysis as a tool for supporting environmental policymaking," Energy Economics, Elsevier, vol. 115(C).
    5. Kristiana Dolge & Dagnija Blumberga, 2023. "Transitioning to Clean Energy: A Comprehensive Analysis of Renewable Electricity Generation in the EU-27," Energies, MDPI, vol. 16(18), pages 1-27, September.
    6. Maamar Traich & Amal Rahmane, 2022. "LMDI decomposition analysis of CO2 emissions in Algeria during 2000-2019 and the role of energy policy in reducing emission," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2022(2), pages 83-106.
    7. Lizhan Cao & Hui Wang, 2022. "The Slowdown in China’s Energy Consumption Growth in the “New Normal” Stage: From Both National and Regional Perspectives," Sustainability, MDPI, vol. 14(7), pages 1-21, April.
    8. Jalile, Ileana Raquel & Moncarz, Pedro E., 2022. "Greenhouse Gas Emissions Associated with Argentina's Exports: A Decomposition Exercise," IDB Publications (Working Papers) 12153, Inter-American Development Bank.
    9. Jiang, Xuemei & Zhao, Changjin & Ouyang, Jin & Shen, Meng, 2023. "Integration in the global value chain, structural change, and the widening gender employment gap in China," China Economic Review, Elsevier, vol. 81(C).
    10. Kirill Muradov, 2021. "Structural decomposition analysis with disaggregate factors within the Leontief inverse," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 10(1), pages 1-17, December.
    11. Polina Ustyuzhanina, 2022. "Decomposition of air pollution emissions from Swedish manufacturing," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(2), pages 195-223, April.
    12. Wang, Keying & Cui, Yongyan & Zhang, Hongwu & Shi, Xunpeng & Xue, Jinjun & Yuan, Zhao, 2022. "Household carbon footprints inequality in China: Drivers, components and dynamics," Energy Economics, Elsevier, vol. 115(C).
    13. Driha, Oana & Cascetta, Furio & Nardini, Sergio & Bianco, Vincenzo, 2023. "Evolution of renewable energy generation in EU27. A decomposition analysis," Renewable Energy, Elsevier, vol. 207(C), pages 348-358.
    14. Eichfelder, Sebastian & Kluska, Mike & Knaisch, Jonas & Selle, Juliane, 2021. "Senkung der Unternehmenssteuerlast versus Förderung von Investitionen: Was ist die bessere Strategie zur Förderung der Standortattraktivität Deutschlands?," arqus Discussion Papers in Quantitative Tax Research 266, arqus - Arbeitskreis Quantitative Steuerlehre.

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