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Identifying Synergies and Complementarities Between MDGs: Results from Cluster Analysis

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  • Maria Lo Bue
  • Stephan Klasen

Abstract

The MDGs are interlinked: acceleration in one goal is likely to speed up progress in others. Nevertheless, these synergies are not always visible, and may differ across countries. Using bivariate cluster analysis, this paper investigates whether distinct groups of developing countries can be identified, using statistical methods, on the basis of the correlation of changes in main MDG indicators over the 1990–2008 period. Identified groups include: (1) “good performers”, characterized by strong positive synergies in MDGs indicators; (2) “poor performers”, where there are synergies in poor progress towards the MDGs and (3) “partial performers” countries where progress in one MDG went along with regress or stagnation in another. We then study the determinants of cluster membership. While growth in GDP per capita is, unsurprisingly, best able to distinguish between “good” and “poor” performers, a poor institutional framework and deteriorations in the income distribution is a notable correlate of partial progress, thus apparently undermining synergies in reaching the MDGs. In light of the current discussions about the post-MDG system, our results suggest that synergies between MDG progress can be achieved but they cannot be taken for granted. Improving institutional performance and reducing inequality appear particularly important drivers of promoting such synergies. Copyright Springer Science+Business Media Dordrecht 2013

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  • Maria Lo Bue & Stephan Klasen, 2013. "Identifying Synergies and Complementarities Between MDGs: Results from Cluster Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 113(2), pages 647-670, September.
  • Handle: RePEc:spr:soinre:v:113:y:2013:i:2:p:647-670
    DOI: 10.1007/s11205-013-0294-y
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    2. Carlos de Miguel Ramos & Rafael Laurenti, 2020. "Synergies and Trade-offs among Sustainable Development Goals: The Case of Spain," Sustainability, MDPI, vol. 12(24), pages 1-14, December.
    3. Amir Mousavi & Jeremy Clark, 2021. "The effects of natural resources on human capital accumulation: A literature survey," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1073-1117, September.
    4. Klasen Stephan & Fleurbaey Marc, 2018. "Leaving No one Behind: Some Conceptual and Empirical Issues," Journal of Globalization and Development, De Gruyter, vol. 9(2), pages 1-9, December.
    5. Shizuki Fukuda & Michio Murakami & Keigo Noda & Taikan Oki, 2016. "How Achieving the Millennium Development Goals Increases Subjective Well-Being in Developing Nations," Sustainability, MDPI, vol. 8(2), pages 1-19, February.
    6. Salim Bagadeem & Mohammed Moosa Ageli & Bader Alhafi, 2022. "Individuals and Organizations: The Sustainability Connect," Journal of Sustainable Development, Canadian Center of Science and Education, vol. 15(3), pages 147-147, May.
    7. Christian Kroll & Anne Warchold & Prajal Pradhan, 2019. "Sustainable Development Goals (SDGs): Are we successful in turning trade-offs into synergies?," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-11, December.

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    More about this item

    Keywords

    Millennium Development Goals; Human development; Cluster analysis; Developing countries;
    All these keywords.

    JEL classification:

    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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