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Linking Aid to the Sustainable Development Goals – a machine learning approach

Author

Listed:
  • Arnaud Pincet
  • Shu Okabe
  • Martin Pawelczyk

Abstract

Official Development Assistance amounted USD 146.6 billions in 2017 but do we know how much of this aid contributed to the Sustainable Development Goals (SDGs)? And to what SDG in particular? This paper present a new methodology using machine learning designed to link project-based flows to the Sustainable Development Goals. It provide first estimates of DAC and non-DAC donors’ aid contribution for the goal and show that similar analysis can be done at the recipient level and for other type of textual database such as private sector reports; opening wide array for policy analysis.The methodology presented in this working paper uses semantic analysis of the text description of each project present in the Creditor Reporting System (CRS).

Suggested Citation

  • Arnaud Pincet & Shu Okabe & Martin Pawelczyk, 2019. "Linking Aid to the Sustainable Development Goals – a machine learning approach," OECD Development Co-operation Working Papers 52, OECD Publishing.
    • Handle: RePEc:oec:dcdaaa:52-en
    DOI: 10.1787/4bdaeb8c-en
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    Citations

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    Cited by:

    1. Asadikia, Atie & Rajabifard, Abbas & Kalantari, Mohsen, 2021. "Systematic prioritisation of SDGs: Machine learning approach," World Development, Elsevier, vol. 140(C).
    2. Olivera Kostoska & Ljupco Kocarev, 2019. "A Novel ICT Framework for Sustainable Development Goals," Sustainability, MDPI, vol. 11(7), pages 1-31, April.
    3. Young Song, Annie & Lee, Seunghyeon & Wong, S.C., 2023. "A machine learning approach to analyzing spatiotemporal impacts of mobility restriction policies on infection rates," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    4. von Braun, Joachim & Beyene Chichaibelu, Bezawit & Laborde, David & Torero Cullen, Maximo, 2024. "Cost of Ending Hunger – Consequences of Complacency, and Financial Needs for SDG2 Achievement," Discussion Papers 343159, University of Bonn, Center for Development Research (ZEF).

    More about this item

    Keywords

    Artificial Intelligence; Credit Reporting System; Innovation; Machine Learning; Official Development Finance; Sectors; Sustainable Development Goals; Text Mining;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements
    • F35 - International Economics - - International Finance - - - Foreign Aid
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development

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