IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i4p2363-d503873.html
   My bibliography  Save this article

The GHG Emissions Generating Capacity by Productive Sectors in the EU: A SAM Analysis

Author

Listed:
  • María T. Álvarez-Martínez

    (Fiscal Policy Analysis Unit, Joint Research Centre, 41092 Seville, Spain)

  • Alfredo J. Mainar-Causapé

    (Department of Applied Economics III, University of Seville, 41020 Seville, Spain)

Abstract

In this paper, we evaluate the generating capacity of Greenhouse Gases (GHG) emissions that all productive sectors have in the EU-27 of 2010. The analysis is performed using the social accounting matrices (SAMs) of each Member State (MS) and evaluating the interactions among industries, productive factors, and households with respect to the aggregated SAM for the EU-27. The main advantages and contributions of this study with respect to the existing literature are two. First, the availability of the whole income distribution detailed in the SAMs and second, their comparability across countries. The aim of this research is to better understand how productive sectors may damage the environment depending on their productive structure and final demand, particularly in a period of economic recession, which is very relevant in the context of COVID-19 and the near future. The results show that intersectoral connections are very diverse by MS and consequently, there are more differences in the generation capacity of GHG emission by country than by sector. Our results reinforce the idea of involving regional and national governments in the design and implementation of EU abatement strategies, taking into account the peculiarities of each region.

Suggested Citation

  • María T. Álvarez-Martínez & Alfredo J. Mainar-Causapé, 2021. "The GHG Emissions Generating Capacity by Productive Sectors in the EU: A SAM Analysis," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:2363-:d:503873
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/4/2363/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/4/2363/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alfredo J. Mainar Causape & Emanuele Ferrari & Scott McDonald, 2018. "Social accounting matrices: basic aspects and main steps for estimation," JRC Research Reports JRC112075, Joint Research Centre.
    2. Duarte, Rosa & Mainar, Alfredo & Sánchez-Chóliz, Julio, 2013. "The role of consumption patterns, demand and technological factors on the recent evolution of CO2 emissions in a group of advanced economies," Ecological Economics, Elsevier, vol. 96(C), pages 1-13.
    3. Quentin Perrier & Céline Guivarch & Olivier Boucher, 2020. "Diversity of greenhouse gas emission drivers across European countries since the 2008 crisis," Climate Policy, Taylor & Francis Journals, vol. 19(9), pages 1067-1087, July.
    4. Pyatt, F Graham & Round, Jeffery I, 1979. "Accounting and Fixed Price Multipliers in a Social Accounting Matrix Framework," Economic Journal, Royal Economic Society, vol. 89(356), pages 850-873, December.
    5. de Nooij, Michiel & van der Kruk, Rene & van Soest, Daan P., 2003. "International comparisons of domestic energy consumption," Energy Economics, Elsevier, vol. 25(4), pages 359-373, July.
    6. Ang, B.W. & Su, Bin & Wang, H., 2016. "A spatial–temporal decomposition approach to performance assessment in energy and emissions," Energy Economics, Elsevier, vol. 60(C), pages 112-121.
    7. Alcantara, Vicent & Duarte, Rosa, 2004. "Comparison of energy intensities in European Union countries. Results of a structural decomposition analysis," Energy Policy, Elsevier, vol. 32(2), pages 177-189, January.
    8. Ang, B.W. & Xu, X.Y. & Su, Bin, 2015. "Multi-country comparisons of energy performance: The index decomposition analysis approach," Energy Economics, Elsevier, vol. 47(C), pages 68-76.
    9. Brizga, Janis & Feng, Kuishuang & Hubacek, Klaus, 2014. "Drivers of greenhouse gas emissions in the Baltic States: A structural decomposition analysis," Ecological Economics, Elsevier, vol. 98(C), pages 22-28.
    10. Rosa Duarte & Alfredo J. Mainar-Causapé & Julio Sánchez Chóliz, 2017. "Domestic GHG emissions and the responsibility of households in Spain: looking for regional differences," Applied Economics, Taylor & Francis Journals, vol. 49(53), pages 5397-5411, November.
    11. Defourny, Jacques & Thorbecke, Erik, 1984. "Structural Path Analysis and Multiplier Decomposition within a Social Accounting Matrix Framework," Economic Journal, Royal Economic Society, vol. 94(373), pages 111-136, March.
    12. Erik Dietzenbacher & Bart Los, 1998. "Structural Decomposition Techniques: Sense and Sensitivity," Economic Systems Research, Taylor & Francis Journals, vol. 10(4), pages 307-324.
    13. Morilla, Carmen Rodriguez & Diaz-Salazar, Gaspar Llanes & Cardenete, M. Alejandro, 2007. "Economic and environmental efficiency using a social accounting matrix," Ecological Economics, Elsevier, vol. 60(4), pages 774-786, February.
    14. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    15. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    16. Barun Deb Pal & Vijay P. Ojha & Sanjib Pohit & Joyashree Roy, 2015. "Impact of Economic Growth on Greenhouse Gas (GHG) Emissions—Social Accounting Matrix (SAM) Multiplier Analysis," India Studies in Business and Economics, in: GHG Emissions and Economic Growth, edition 127, chapter 4, pages 43-60, Springer.
    17. Pal, Barun Deb & Pohit, Sanjib, 2014. "Environmentally Extended Social Accounting Matrix for Climate Change Policy Analysis for India," Journal of Regional Development and Planning, Rajarshi Majumder, vol. 3(1), pages 61-75.
    18. Clemente Polo & D. Roland-Holst & Ferrán Sancho, 1991. "Descomposición de multiplicadores en un modelo multisectorial: una aplicación al caso español," Investigaciones Economicas, Fundación SEPI, vol. 15(1), pages 53-69, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gui, Shusen & Mu, Hailin & Li, Nan, 2014. "Analysis of impact factors on China's CO2 emissions from the view of supply chain paths," Energy, Elsevier, vol. 74(C), pages 405-416.
    2. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.
    3. Wang, H. & Ang, B.W. & Su, Bin, 2017. "A Multi-region Structural Decomposition Analysis of Global CO2 Emission Intensity," Ecological Economics, Elsevier, vol. 142(C), pages 163-176.
    4. Darío Serrano-Puente, 2021. "Are we moving toward an energy-efficient low-carbon economy? An input–output LMDI decomposition of CO $$_{2}$$ 2 emissions for Spain and the EU28," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(2), pages 151-229, June.
    5. Wu, Feng & Huang, Ningyu & Zhang, Qian & Qiao, Zhi & Zhan, Ni-ni, 2020. "Multi-province comparison and typology of China’s CO2 emission: A spatial–temporal decomposition approach," Energy, Elsevier, vol. 190(C).
    6. Duarte, Rosa & Mainar, Alfredo & Sánchez-Chóliz, Julio, 2013. "The role of consumption patterns, demand and technological factors on the recent evolution of CO2 emissions in a group of advanced economies," Ecological Economics, Elsevier, vol. 96(C), pages 1-13.
    7. Su, Bin & Ang, B.W. & Li, Yingzhu, 2017. "Input-output and structural decomposition analysis of Singapore's carbon emissions," Energy Policy, Elsevier, vol. 105(C), pages 484-492.
    8. Lan, Jun & Malik, Arunima & Lenzen, Manfred & McBain, Darian & Kanemoto, Keiichiro, 2016. "A structural decomposition analysis of global energy footprints," Applied Energy, Elsevier, vol. 163(C), pages 436-451.
    9. Zhong, Sheng, 2018. "Structural decompositions of energy consumption between 1995 and 2009: Evidence from WIOD," Energy Policy, Elsevier, vol. 122(C), pages 655-667.
    10. Su, Bin & Ang, B.W., 2022. "Improved granularity in input-output analysis of embodied energy and emissions: The use of monthly data," Energy Economics, Elsevier, vol. 113(C).
    11. Cansino, José M. & Román, Rocío & Ordóñez, Manuel, 2016. "Main drivers of changes in CO2 emissions in the Spanish economy: A structural decomposition analysis," Energy Policy, Elsevier, vol. 89(C), pages 150-159.
    12. Olga Gavrilova & Raivo Vilu, 2015. "Estonia's Energy-related Greenhouse Gas Emissions in 1995-2011: A Structural Decomposition Analysis," Review of Economics & Finance, Better Advances Press, Canada, vol. 5, pages 67-84, February.
    13. Guevara, Zeus & Henriques, SofiaTeives & Sousa, Tânia, 2021. "Driving factors of differences in primary energy intensities of 14 European countries," Energy Policy, Elsevier, vol. 149(C).
    14. Li, Tianxiang & Baležentis, Tomas & Makutėnienė, Daiva & Streimikiene, Dalia & Kriščiukaitienė, Irena, 2016. "Energy-related CO2 emission in European Union agriculture: Driving forces and possibilities for reduction," Applied Energy, Elsevier, vol. 180(C), pages 682-694.
    15. Laia Pié, 2017. "The Catalan Economy towards the New European Energy Policy: Through Accounting of Greenhouse Emission Multipliers," Sustainability, MDPI, vol. 9(12), pages 1-18, December.
    16. Avelino, André F.T. & Franco-Solís, Alberto & Carrascal-Incera, André, 2021. "Revisiting the Temporal Leontief Inverse: New Insights on the Analysis of Regional Technological Economic Change," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 79-89.
    17. Azam, Muhammad & Younes, Ben Zaied & Hunjra, Ahmed Imran & Hussain, Nazim, 2022. "Integrated Spatial-Temporal decomposition analysis for life cycle assessment of carbon emission intensity change in various regions of China," Resources Policy, Elsevier, vol. 79(C).
    18. Fernando Bermejo & Raúl del Pozo & Pablo Moya, 2021. "Main Factors Determining the Economic Production Sustained by Public Long-Term Care Spending in Spain," IJERPH, MDPI, vol. 18(17), pages 1-18, August.
    19. Su, Bin & Ang, B.W., 2020. "Demand contributors and driving factors of Singapore’s aggregate carbon intensities," Energy Policy, Elsevier, vol. 146(C).
    20. Fernández González, P. & Presno, M.J. & Landajo, M., 2015. "Regional and sectoral attribution to percentage changes in the European Divisia carbonization index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1437-1452.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:2363-:d:503873. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.