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Mind the Gap: Analyzing the Impact of Data Gap in Millennium Development Goals’ (MDGs) Indicators on the Progress toward MDGs

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  • Jacob, Arun

Abstract

This paper analyzes the impact of data gap in Millennium Development Goals’ (MDGs) performance indicators on actual performance success of MDGs. Performance success, within the MDG framework, is quantified using six different ways proposed in the existing literature, including both absolute and relative performance and deviation from historical transition paths of MDG indicators. The empirical analysis clearly shows that the data gap in performance measurement is a significant predictor of poor MDG performance in terms of any of the six progress measures. Larger the data gap or weaker the performance measurement system, lesser is the probability of MDG performance success. The empirical methodology used in the paper combines a Heckman correction and instrumental variable estimation strategies to simultaneously account for potential endogeneity of the key data gap variable and bias due to sample selection. This result holds true even after controlling for overall national statistical capacity and a variety of socioeconomic factors. The paper underlines the need to strengthen the performance measurement system attached to the 2030 agenda for sustainable development and the associated Sustainable Development Goals (SDGs). This paper is the first attempt at empirically evaluating the value of data in the context of international development goals and gives empirical evidence for the need to harness the “data revolution” for sustainable development.

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  • Jacob, Arun, 2017. "Mind the Gap: Analyzing the Impact of Data Gap in Millennium Development Goals’ (MDGs) Indicators on the Progress toward MDGs," World Development, Elsevier, vol. 93(C), pages 260-278.
    • Handle: RePEc:eee:wdevel:v:93:y:2017:i:c:p:260-278
    DOI: 10.1016/j.worlddev.2016.12.016
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    Cited by:

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    2. McArthur, John W. & Rasmussen, Krista, 2018. "Change of pace: Accelerations and advances during the Millennium Development Goal era," World Development, Elsevier, vol. 105(C), pages 132-143.
    3. Dang, Hai Anh H. & Jolliffe, Dean & Serajuddin, Umar & Stacy, Brian, 2024. "Country statistical capacity: a recent assessment tool and further reflections on the way forward," LSE Research Online Documents on Economics 124060, London School of Economics and Political Science, LSE Library.
    4. Yani Wang & Mingyi Du & Lei Zhou & Guoyin Cai & Yongliang Bai, 2019. "A Novel Evaluation Approach of County-Level City Disaster Resilience and Urban Environmental Cleanliness Based on SDG11 and Deqing County’s Situation," Sustainability, MDPI, vol. 11(20), pages 1-13, October.
    5. MacFeely Steve, 2020. "Measuring the Sustainable Development Goal Indicators: An Unprecedented Statistical Challenge," Journal of Official Statistics, Sciendo, vol. 36(2), pages 361-378, June.
    6. SERRANO-GUZMAN, Maria Fernanda & PEREZ-RUIZ, Diego-Dario & MUÑOZ-RAMIREZ, Andres Felipe, 2020. "Dimensional Analysis Applied In The Estimation Of An Ideal City Profile And Its Impact On The Development: Case Study In Guadalajara De Buga (Colombia)," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 20(1), pages 5-18.
    7. Biggeri, Mario & Clark, David A. & Ferrannini, Andrea & Mauro, Vincenzo, 2019. "Tracking the SDGs in an ‘integrated’ manner: A proposal for a new index to capture synergies and trade-offs between and within goals," World Development, Elsevier, vol. 122(C), pages 628-647.
    8. Edvins Karnitis & Janis Bicevskis & Girts Karnitis, 2021. "Measuring the Implementation of the Agenda 2030 Vision in Its Comprehensive Sense: Methodology and Tool," Energies, MDPI, vol. 14(4), pages 1-17, February.
    9. Wiktoria Sobczyk & Eugeniusz Jacek Sobczyk, 2021. "Varying the Energy Mix in the EU-28 and in Poland as a Step towards Sustainable Development," Energies, MDPI, vol. 14(5), pages 1-19, March.
    10. Raj, Anita & Dey, Arnab & Rao, Namratha & Yore, Jennifer & McDougal, Lotus & Bhan, Nandita & Silverman, Jay G. & Hay, Katherine & Thomas, Edwin E. & Fotso, Jean Christophe & Lundgren, Rebecka, 2024. "The EMERGE framework to measure empowerment for health and development," Social Science & Medicine, Elsevier, vol. 351(S1).
    11. Barbier, Edward B. & Burgess, Joanne C., 2019. "Sustainable development goal indicators: Analyzing trade-offs and complementarities," World Development, Elsevier, vol. 122(C), pages 295-305.
    12. Madisen Fuller & Puneet Dwivedi, 2019. "Assessing Changes in Inequality for Millennium Development Goals among Countries: Lessons for the Sustainable Development Goals," Social Sciences, MDPI, vol. 8(7), pages 1-13, July.

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    More about this item

    Keywords

    MDG; SDGs; value of data; performance measurement; monitoring and evaluation; goal setting;
    All these keywords.

    JEL classification:

    • F02 - International Economics - - General - - - International Economic Order and Integration
    • F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development
    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate
    • H53 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Welfare Programs
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • O19 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - International Linkages to Development; Role of International Organizations
    • P35 - Political Economy and Comparative Economic Systems - - Socialist Institutions and Their Transitions - - - Public Finance
    • P47 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - Performance and Prospects
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

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