IDEAS home Printed from https://ideas.repec.org/a/wly/jintdv/v34y2022i2p349-378.html
   My bibliography  Save this article

The role of administrative data in gender statistics: Supporting inclusive development for women and girls

Author

Listed:
  • Nicola Richards
  • Lauren Pandolfelli
  • Bouchra Bouziani
  • Bernice Ofosu‐Baadu
  • Karen Carter

Abstract

Gender data are essential for assessing gender‐equitable outcomes for children. However, significant data gaps continue to compromise country ability to implement gender‐responsive policies and monitor gender equality. This study explores the potential role of administrative systems in filling critical gender data gaps. It notes the substantial challenges to sourcing gender data from administrative systems—challenges related to limitations of administrative data itself, and challenges specific to the production and use of gender statistics. Overall, while data from administrative systems alone cannot address all gender data gaps, they are critical to a holistic approach to addressing national gender data needs.

Suggested Citation

  • Nicola Richards & Lauren Pandolfelli & Bouchra Bouziani & Bernice Ofosu‐Baadu & Karen Carter, 2022. "The role of administrative data in gender statistics: Supporting inclusive development for women and girls," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(2), pages 349-378, March.
  • Handle: RePEc:wly:jintdv:v:34:y:2022:i:2:p:349-378
    DOI: 10.1002/jid.3600
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/jid.3600
    Download Restriction: no

    File URL: https://libkey.io/10.1002/jid.3600?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. -, 2014. "A World that Counts: Mobilising the Data Revolution for Sustainable Development," Coediciones, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), number 40319 edited by United Nations, May.
    2. Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2015. "Household Surveys in Crisis," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 199-226, Fall.
    3. Sabina Alkire & Emma Samman, 2014. "Mobilising the Household Data Required to Progress toward the SDGs," OPHI Working Papers 72, Queen Elizabeth House, University of Oxford.
    4. Buvinic, Mayra & Carey, Eleanor, 2019. "The promise and challenges of gender data," IFPRI book chapters, in: 2019 Annual trends and outlook report: Gender equality in rural Africa: From commitments to outcomes, chapter 12, pages ReSAKSS17, International Food Policy Research Institute (IFPRI).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Suyu Liu, 2023. "Statistical challenges for achieving Sustainable Development Goals: Some reflections on Indicator 14.7.1," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(7), pages 1913-1924, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alvaredo, Facundo & Bourguignon, François & Ferreira, Francisco H. G. & Lustig, Nora, 2023. "Seventy-five Years of Measuring Income Inequality in Latin America," IDB Publications (Working Papers) 13157, Inter-American Development Bank.
    2. Carr-Hill, Roy, 2017. "Improving Population and Poverty Estimates with Citizen Surveys: Evidence from East Africa," World Development, Elsevier, vol. 93(C), pages 249-259.
    3. Pulkit Sharma & Achut Manandhar & Patrick Thomson & Jacob Katuva & Robert Hope & David A. Clifton, 2019. "Combining Multi-Modal Statistics for Welfare Prediction Using Deep Learning," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    4. Charles Courtemanche & Augustine Denteh & Rusty Tchernis, 2019. "Estimating the Associations between SNAP and Food Insecurity, Obesity, and Food Purchases with Imperfect Administrative Measures of Participation," Southern Economic Journal, John Wiley & Sons, vol. 86(1), pages 202-228, July.
    5. Ana Andries & Stephen Morse & Richard J. Murphy & Jim Lynch & Emma R. Woolliams, 2019. "Seeing Sustainability from Space: Using Earth Observation Data to Populate the UN Sustainable Development Goal Indicators," Sustainability, MDPI, vol. 11(18), pages 1-20, September.
    6. de Pedraza, Pablo & Vollbracht, Ian, 2020. "The Semicircular Flow of the Data Economy and the Data Sharing Laffer curve," GLO Discussion Paper Series 515, Global Labor Organization (GLO).
    7. Bradley Hardy & Timothy Smeeding & James P. Ziliak, 2018. "The Changing Safety Net for Low-Income Parents and Their Children: Structural or Cyclical Changes in Income Support Policy?," Demography, Springer;Population Association of America (PAA), vol. 55(1), pages 189-221, February.
    8. Morgan, Mary S. & Bach, Maria, 2018. "Measuring development - from the UN’s perspective," LSE Research Online Documents on Economics 90557, London School of Economics and Political Science, LSE Library.
    9. Deniz Dutz & Ingrid Huitfeldt & Santiago Lacouture & Magne Mogstad & Alexander Torgovitsky & Winnie van Dijk, 2021. "Selection in Surveys," NBER Working Papers 29549, National Bureau of Economic Research, Inc.
      • Deniz Dutz & Ingrid Huitfeldt & Santiago Lacouture & Magne Mogstad & Alexander Torgovitsky & Winnie van Dijk, 2021. "Selection in Surveys," Discussion Papers 971, Statistics Norway, Research Department.
    10. Laura Recuero Virto, 2017. "A preliminary assessment of indicators for SDG 14 on " Oceans "," Post-Print hal-01639008, HAL.
    11. Bruce D. Meyer & Derek Wu & Victoria R. Mooers & Carla Medalia, 2019. "The use and misuse of income data and extreme poverty in the United States," AEI Economics Working Papers 1018925, American Enterprise Institute.
    12. Bruckmeier, Kerstin & Riphahn, Regina T. & Wiemers, Jürgen, 2019. "Benefit underreporting in survey data and its consequences for measuring non-take-up: new evidence from linked administrative and survey data," IAB-Discussion Paper 201906, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    13. Robert Moffitt & John Karl Scholz, 2010. "Trends in the Level and Distribution of Income Support," NBER Chapters, in: Tax Policy and the Economy, Volume 24, pages 111-152, National Bureau of Economic Research, Inc.
    14. Adrian Chadi, 2019. "Dissatisfied with life or with being interviewed? Happiness and the motivation to participate in a survey," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(3), pages 519-553, October.
    15. Tuttle, Charlotte, 2016. "The Stimulus Act of 2009 and Its Effect on Food-At-Home Spending by SNAP Participants," Economic Research Report 262193, United States Department of Agriculture, Economic Research Service.
    16. -, 2016. "Horizons 2030: Equality at the centre of sustainable development," Libros y Documentos Institucionales, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), number 40160 edited by Eclac, May.
    17. Francisco Parro & Loreto Reyes, 2017. "The rise and fall of income inequality in Chile," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 26(1), pages 1-31, December.
    18. Robert Collinson & John Eric Humphries & Nicholas Mader & Davin Reed & Daniel Tannenbaum & Winnie van Dijk, 2024. "Eviction and Poverty in American Cities," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(1), pages 57-120.
    19. Lorenza Campagnolo & Carlo Carraro & Fabio Eboli & Luca Farnia, 2015. "Assessing SDGs: A New Methodology to Measure Sustainability," Working Papers 2015.89, Fondazione Eni Enrico Mattei.
    20. Ha Trong Nguyen & Huong Thu Le & Luke B Connelly, 2021. "Who's declining the “free lunch”? New evidence from the uptake of public child dental benefits," Health Economics, John Wiley & Sons, Ltd., vol. 30(2), pages 270-288, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:jintdv:v:34:y:2022:i:2:p:349-378. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/journal/5102/home .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.