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Improving the knowledge base on material flow analysis for Asian developing countries: A case study of Lao PDR

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  • Vilaysouk, Xaysackda
  • Schandl, Heinz
  • Murakami, Shinsuke

Abstract

National material flow accounts have reached maturity over the past decade. Many countries, including the European Community and Japan, now report material flows as part of their national statistical reporting. Global and country by country data has been prepared by the International Resource Panel of United Nations Environment, filling a reporting gap for many countries of the global South. In this research we establish, for the first time, a national material flow account for a low-income country – Lao People’s Democratic Republic – which is solely based on national statistical data from the Lao PDR and in-depth information on the specifics of a low-income, Southeast Asian economy. We develop accounts for domestic extraction and trade for the period 1988–2015. In contrast to existing accounts based on international data sources, our calculation of material flows in Lao PDR includes detailed information about the mining sector, agriculture (including livestock fodder and subsistence economy), forestry and timber harvest which are not available from the international data. The results indicate that domestic material extraction increased ten-fold from 11.3 million tonnes to 120.1 million tonnes, driven by the extraction of natural resources for infrastructure development and primary resource export-oriented sectors. We also engaged with the Lao PDR National Statistical Office to improve trade accounts and have added sensitivity analysis to our accounts. This allows us to test the robustness and credibility of the international datasets that are filling the gap in the absence of national accounts in many developing countries in Asia and beyond.

Suggested Citation

  • Vilaysouk, Xaysackda & Schandl, Heinz & Murakami, Shinsuke, 2017. "Improving the knowledge base on material flow analysis for Asian developing countries: A case study of Lao PDR," Resources, Conservation & Recycling, Elsevier, vol. 127(C), pages 179-189.
  • Handle: RePEc:eee:recore:v:127:y:2017:i:c:p:179-189
    DOI: 10.1016/j.resconrec.2017.09.006
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    References listed on IDEAS

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    1. Stefan Bringezu & Janez Potočnik & Heinz Schandl & Yonglong Lu & Anu Ramaswami & Mark Swilling & Sangwon Suh, 2016. "Multi-Scale Governance of Sustainable Natural Resource Use—Challenges and Opportunities for Monitoring and Institutional Development at the National and Global Level," Sustainability, MDPI, vol. 8(8), pages 1-25, August.
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    1. Xaysackda Vilaysouk & Savath Saypadith & Seiji Hashimoto, 2022. "Semisupervised machine learning classification framework for material intensity parameters of residential buildings," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 72-87, February.

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