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Data Gap Analysis, Indicator Selection and Index Development: A Case for Developing Economies

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Abstract

Sustainable Development Goals (SDG) and its measurement is a key policy focus across the globe. Despite existence of several indices and reporting agencies, it is a challenging task to identify progress, specifically in the case of developing economies. These economies are predominantly in Asia and Africa and have a great bearing on global performance. These countries have diverse geographical and cultural elements with an active sub-national institutional framework. Data gap coupled with poor data quality and limited financial support does not help their case. Without appropriate indicator selection and index measurement it is not possible to judge the actual current situation or compare the SDG situation around the world. This paper attempts a practical and simpler approach to overcome the constraints, provide direction and facilitate measurement of SDG position in such countries using the case of India. This is done by identifying gaps, suggesting a tailored approach to indicator selection and measurement and further, developing a suitable index for SDG measurement at the sub-national level. The results and findings should be of great interest for policy making and implementing agencies.

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Notes

  1. https://www.un.org/millenniumgoals/.

  2. The details about the 17 SDGs can be referred to at: https://www.undp.org/content/undp/en/home/sustainable-development-goals.html.

  3. The VNR database and official country VNR reports can be accessed at https://sustainabledevelopment.un.org/vnrs/.

  4. Union Territories (UTs) are administrative divisions in India, which like states, do not have their own elected governments and are in the direct control of the central government.

  5. The states included in this study are: Andhra Pradesh (AP), Assam (AS), Bihar (BR), Chhattisgarh (CT), Delhi (DL), Gujarat (GJ), Haryana (HY), Himachal Pradesh (HP), Jammu and Kashmir (J&K), Jharkhand (JH), Karnataka (KA), Kerala, Madhya Pradesh (MP), Maharashtra (MH), Odisha (OD), Punjab (PB), Rajasthan (RJ), Tamil Nadu (TN), Telangana (TL), Uttar Pradesh (UP), Uttarakhand (UK), West Bengal (WB).

  6. https://stats.oecd.org/Index.aspx?DataSetCode=SOCX_AGG.

  7. http://www.undatarevolution.org/.

  8. http://www.data4sdgs.org/.

  9. http://ggim.un.org/.

  10. https://www.unglobalpulse.org/.

  11. https://data-innovation.unsystem.org/.

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Acknowledgements

We thank Professor Tara Chandra Kandpal, Dhwani Gambhir and Sapan Thapar for valuable comments at different stages of this research. We wish to also acknowledge Pankaj Singh Rawat for his assistance in formatting of this paper.

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Correspondence to Ahmad Mohd Khalid.

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Appendices

Appendix 1

See Table 6.

Table 6 SDG Most Representative Indicator Set for India

Appendix 2

See Table 7.

Table 7 SDG Index Scores for Select SDGs for Major States in India

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Khalid, A.M., Sharma, S. & Dubey, A.K. Data Gap Analysis, Indicator Selection and Index Development: A Case for Developing Economies. Soc Indic Res 148, 893–960 (2020). https://doi.org/10.1007/s11205-019-02225-6

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  • DOI: https://doi.org/10.1007/s11205-019-02225-6

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