IDEAS home Printed from https://ideas.repec.org/p/dem/wpaper/wp-2024-001.html
   My bibliography  Save this paper

New adjustment procedure for distortion in age distribution

Author

Listed:
  • Afza Rasul

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Jamal Abdul Nasir
  • Dmitri A. Jdanov

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

Accurate age data is a prerequisite for any demographic inquiry. Unfortunately, in many developing countries visible age heaping is present in census and survey data of reported age at the time of census or survey. In this article, a new method is proposed for age adjustment of the respondent current age at the time of interview/data collection. The method is based on the rectangular distribution probabilities for terminal digits of age. The algorithms-based method is used to estimate true/adjusted age distribution in the presence of age heaping/age misreporting. Application of the method is performed on the most recent demographic and health survey data from Afghanistan, Bangladesh, Pakistan, India, Ethiopia, and Gambia. UN Criteria for age accuracy is used to check the accuracy of adjusted/true age distribution. The result revealed that after adjustment of the terminal digit by the proposed method of digit shift the adjusted age distributions are perfectly accurate. The method will be applicable to survey and census data. The method will be very useful in fertility analysis where the individual year of age of women plays an important role.

Suggested Citation

  • Afza Rasul & Jamal Abdul Nasir & Dmitri A. Jdanov, 2024. "New adjustment procedure for distortion in age distribution," MPIDR Working Papers WP-2024-001, Max Planck Institute for Demographic Research, Rostock, Germany.
    • Handle: RePEc:dem:wpaper:wp-2024-001
    DOI: 10.4054/MPIDR-WP-2024-001
    as

    Download full text from publisher

    File URL: https://www.demogr.mpg.de/papers/working/wp-2024-001.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4054/MPIDR-WP-2024-001?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. John Caldwell, 1966. "Study of age misstatement among young children in Ghana," Demography, Springer;Population Association of America (PAA), vol. 3(2), pages 477-490, June.
    2. Prithwis Gupta, 1975. "A general method of correction for age misreporting in census populations," Demography, Springer;Population Association of America (PAA), vol. 12(2), pages 303-312, May.
    3. A'Hearn, Brian & Baten, Jörg & Crayen, Dorothee, 2009. "Quantifying Quantitative Literacy: Age Heaping and the History of Human Capital," The Journal of Economic History, Cambridge University Press, vol. 69(3), pages 783-808, September.
    4. Mikołaj Szołtysek & R. Poniat & S. Gruber, 2018. "Age heaping patterns in Mosaic data," Historical Methods: A Journal of Quantitative and Interdisciplinary History, Taylor & Francis Journals, vol. 51(1), pages 13-38, January.
    5. James Ntozi, 1978. "The demeny-shorter and three-census methods for correcting age data," Demography, Springer;Population Association of America (PAA), vol. 15(4), pages 509-521, November.
    6. repec:cai:poeine:pope_704_0729 is not listed on IDEAS
    7. repec:cai:popine:popu_p1992_47n4_1041 is not listed on IDEAS
    8. P. Bhat, 1990. "Estimating transition probabilities of age misstatement," Demography, Springer;Population Association of America (PAA), vol. 27(1), pages 149-163, February.
    Full references (including those not matched with items on IDEAS)

    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. Stephane Helleringer & Chong You & Laurence Fleury & Laetitia Douillot & Insa Diouf & Cheikh Tidiane Ndiaye & Valerie Delaunay & Rene Vidal, 2019. "Improving age measurement in low- and middle-income countries through computer vision: A test in Senegal," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(9), pages 219-260.
    2. Brian A'Hearn & Alexia Delfino & Alessandro Nuvolari, 2022. "Rethinking age heaping: a cautionary tale from nineteenth‐century Italy," Economic History Review, Economic History Society, vol. 75(1), pages 111-137, February.
    3. Èric Gómez-i-Aznar, 2020. "Ad maiorem Dei gloriam. Numeracy levels in the Guarani Jesuit missions," Working Papers 0181, European Historical Economics Society (EHES).
    4. Fourie, Johan & Jayes, Jonathan, 2021. "Health inequality and the 1918 influenza in South Africa," World Development, Elsevier, vol. 141(C).
    5. Èric Gómez-i-Aznar, 2019. "Human capital at the beginnings of the 18th century Catalonia: age-heaping and numeracy in a changing economy," Documentos de Trabajo (DT-AEHE) 1904, Asociación Española de Historia Económica.
    6. Grohmann, Antonia & Klühs, Theres & Menkhoff, Lukas, 2018. "Does financial literacy improve financial inclusion? Cross country evidence," World Development, Elsevier, vol. 111(C), pages 84-96.
    7. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    8. Ralph Hippe & Joerg Baten, 2011. "Regional Inequality in Human Capital Formation in Europe, 1790 - 1880," Working Papers 11-07, Association Française de Cliométrie (AFC).
    9. Cassan, Guilhem, 2019. "Affirmative action, education and gender: Evidence from India," Journal of Development Economics, Elsevier, vol. 136(C), pages 51-70.
    10. Anna Aizer & Shari Eli & Joseph P. Ferrie & Adriana Lleras-Muney, 2014. "The Long Term Impact of Cash Transfers to Poor Families," NBER Working Papers 20103, National Bureau of Economic Research, Inc.
    11. Robert C. Allen, 2015. "The high wage economy and the industrial revolution: a restatement," Economic History Review, Economic History Society, vol. 68(1), pages 1-22, February.
    12. Dieter von Fintel & Johan Fourie, 2011. "Settler skills and colonial development," Working Papers 213, Economic Research Southern Africa.
    13. Kravtsova, Maria & Libman, Alexander, 2023. "Historical family structure as a predictor of liberal voting: Evidence from a century of Russian history," Economic Systems, Elsevier, vol. 47(2).
    14. Sascha O. BECKER & Francesco CINNIRELLA, 2020. "Prussia Disaggregated: The Demography of its Universe of Localities in 1871," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 86(3), pages 259-290, September.
    15. Ulrich Pfister & Jana Riedel & Martin Uebele, 2012. "Real Wages and the Origins of Modern Economic Growth in Germany, 16th to 19th Centuries," Working Papers 0017, European Historical Economics Society (EHES).
    16. Zhou, Qingtian, 2017. "Food Prices and Cognitive Development in the United States: Evidence from the 1850-1930 Data," Master's Theses and Plan B Papers 261505, University of Minnesota, Department of Applied Economics.
    17. Claude Diebolt & Ralph Hippe, 2019. "The long-run impact of human capital on innovation and economic development in the regions of Europe," Applied Economics, Taylor & Francis Journals, vol. 51(5), pages 542-563, January.
    18. J. de Dreu & J.A. Bikker, 2009. "Pension fund sophistication and investment policy," Working Papers 09-13, Utrecht School of Economics.
    19. Baten, Joerg & Sohn, Kitae, 2013. "Back to the 'normal' level of human-capital driven growth? A note on early numeracy in Korea, China and Japan, 1550 - 1800," University of Tübingen Working Papers in Business and Economics 52, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    20. Cappelli, Gabriele & Baten, Joerg, 2021. "Numeracy development in Africa: New evidence from a long-term perspective (1730–1970)," Journal of Development Economics, Elsevier, vol. 150(C).

    More about this item

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:dem:wpaper:wp-2024-001. 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: Peter Wilhelm (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    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.