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Disaggregating Input--Output Models With Incomplete Information

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  • Sören Lindner
  • Julien Legault
  • Dabo Guan

Abstract

Disaggregating a sector within the Leontief input--output (IO) framework is not a straightforward task since there is more than one possibility for the unknown technical coefficients of the disaggregated IO table, and more information than what is embodied in the aggregated IO table is thus required. This paper presents a methodology for disaggregating sectors into an arbitrary number of new sectors when the only available information about the newly formed sectors is their output weights. A random walk algorithm is used to explore the polytope containing the admissible combinations for the unknown technical coefficients of the disaggregated IO table. These combinations are then used to construct the probability distribution of the coefficients of the inverse Leontief matrix. The methodology is illustrated by disaggregating the electricity production sector of China's 2007 IO table and by looking at the probability distribution of the CO 2 emission intensity factors of the sectors of the economy.

Suggested Citation

  • Sören Lindner & Julien Legault & Dabo Guan, 2012. "Disaggregating Input--Output Models With Incomplete Information," Economic Systems Research, Taylor & Francis Journals, vol. 24(4), pages 329-347, April.
    • Handle: RePEc:taf:ecsysr:v:24:y:2012:i:4:p:329-347
    DOI: 10.1080/09535314.2012.689954
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    Cited by:

    1. Hawkins, Jacob & Ma, Chunbo & Schilizzi, Steven & Zhang, Fan, 2015. "Promises and pitfalls in environmentally extended input–output analysis for China: A survey of the literature," Energy Economics, Elsevier, vol. 48(C), pages 81-88.
    2. Su, Bin & Thomson, Elspeth, 2016. "China's carbon emissions embodied in (normal and processing) exports and their driving forces, 2006–2012," Energy Economics, Elsevier, vol. 59(C), pages 414-422.
    3. Wan, Liyang & Wang, Can & Cai, Wenjia, 2016. "Impacts on water consumption of power sector in major emitting economies under INDC and longer term mitigation scenarios: An input-output based hybrid approach," Applied Energy, Elsevier, vol. 184(C), pages 26-39.
    4. Wang, Yafei & Liang, Sai, 2013. "Carbon dioxide mitigation target of China in 2020 and key economic sectors," Energy Policy, Elsevier, vol. 58(C), pages 90-96.
    5. Lixiao Zhang & Qiuhong Hu & Fan Zhang, 2014. "Input-Output Modeling for Urban Energy Consumption in Beijing: Dynamics and Comparison," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-11, March.
    6. Qian Zhang & Jun Nakatani & Yuichi Moriguchi, 2015. "Compilation of an Embodied CO 2 Emission Inventory for China Using 135-Sector Input-Output Tables," Sustainability, MDPI, vol. 7(7), pages 1-17, June.
    7. Alexandros Gkatsikos & Konstadinos Mattas & Efstratios Loizou & Dimitrios Psaltopoulos, 2022. "The Neglected Water Rebound Effect of Income and Employment Growth," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(1), pages 379-398, January.
    8. Jordan Hristov & Aleksandra Martinovska-Stojcheska & Yves Surry, 2016. "The Economic Role of Water in FYR Macedonia: An Input–Output Analysis and Implications for the Western Balkan Countries," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 2(04), pages 1-37, December.
    9. Surís-Regueiro, Juan C. & Santiago, Jose L., 2018. "Assessment of Socioeconomic Impacts Through Physical Multipliers: The Case of Fishing Activity in Galicia (Spain)," Ecological Economics, Elsevier, vol. 147(C), pages 276-297.
    10. Daesoo Kim & Ranjan Parajuli & Gregory J. Thoma, 2020. "Life Cycle Assessment of Dietary Patterns in the United States: A Full Food Supply Chain Perspective," Sustainability, MDPI, vol. 12(4), pages 1-22, February.
    11. Meng, Fanxin & Liu, Gengyuan & Chang, Yuan & Su, Meirong & Hu, Yuanchao & Yang, Zhifeng, 2019. "Quantification of urban water-carbon nexus using disaggregated input-output model: A case study in Beijing (China)," Energy, Elsevier, vol. 171(C), pages 403-418.
    12. Duan, Cuncun & Chen, Bin & Feng, Kuishuang & Liu, Zhu & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2018. "Interregional carbon flows of China," Applied Energy, Elsevier, vol. 227(C), pages 342-352.
    13. Liu, Lirong & Huang, Guohe & Baetz, Brian & Huang, Charley Z. & Zhang, Kaiqiang, 2019. "Integrated GHG emissions and emission relationships analysis through a disaggregated ecologically-extended input-output model; A case study for Saskatchewan, Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 97-109.
    14. Chen, Shaoqing & Chen, Bin, 2015. "Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis," Applied Energy, Elsevier, vol. 138(C), pages 99-107.
    15. Yuan, Rong & Rodrigues, João F.D. & Tukker, Arnold & Behrens, Paul, 2018. "The impact of the expansion in non-fossil electricity infrastructure on China’s carbon emissions," Applied Energy, Elsevier, vol. 228(C), pages 1994-2008.
    16. Anke Schaffartzik & Dominik Wiedenhofer & Nina Eisenmenger, 2015. "Raw Material Equivalents: The Challenges of Accounting for Sustainability in a Globalized World," Sustainability, MDPI, vol. 7(5), pages 1-26, April.

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