IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v33y2015i19.html
   My bibliography  Save this article

Modeling the fertility impact of the proximate determinants: Time for a tune-up

Author

Listed:
  • John Bongaarts

    (Population Council)

Abstract

Background: Many analyses of the determinants of fertility make a distinction between proximate and background determinants. The former include behavioral factors such as the use of contraception or abortion through which the background determinants (e.g., social and economic variables) affect fertility. These relationships were first recognized by Davis and Blake (1956), who defined a large set of “intermediate fertility variables.” In the late 1970s Bongaarts (1978) identified a smaller set of proximate determinants and developed a relatively simple model to quantify their fertility effects. Objective: This paper fine-tunes the Bongaarts proximate determinants model in light of new evidence, research, and data that have become available over the past three decades. Reproductive behavior has changed substantially and certain original simplifying assumptions have become less accurate over time. In addition, new research allows some features of the model to be improved. Methods: Six adjustments to the model are proposed and implemented. The revised model is compared with the original version and with a revision proposed by Stover (1998). Results: Revised estimates of the indexes of the proximate determinants and total fecundity are provided for the most recent DHS surveys in 36 developing countries. The revised model provides a better fit than do earlier models. Conclusions: The proximate determinants model, as originally conceived, remains conceptually sound. However, theoretical and empirical evidence accumulated over the past three decades suggests a number of ways to fine-tune the model to make it more robust and accurate in contemporary populations. The resulting revised model provides an improved assessment of the roles of the proximate determinants in national and sub-national populations.

Suggested Citation

  • John Bongaarts, 2015. "Modeling the fertility impact of the proximate determinants: Time for a tune-up," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 33(19), pages 535-560.
  • Handle: RePEc:dem:demres:v:33:y:2015:i:19
    DOI: 10.4054/DemRes.2015.33.19
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol33/19/33-19.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.4054/DemRes.2015.33.19?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. Jane G. Fortson, "undated". "HIV/AIDS and Fertility," Mathematica Policy Research Reports 38387ebd1f044714b4a5ab70e, Mathematica Policy Research.
    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. David A Sánchez-Páez & José Antonio Ortega, 2019. "Reported patterns of pregnancy termination from Demographic and Health Surveys," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-25, August.
    2. Yoonjoung Choi & Madeleine Short Fabic & Jacob Adetunji, 2018. "Does age-adjusted measurement of contraceptive use better explain the relationship between fertility and contraception?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 39(45), pages 1227-1240.
    3. Roch Millogo & Clémentine Rossier, 2022. "Fertility Transition in Dakar, Nairobi, and Ouagadougou Since the 1970s: An Identical Reduction at All Ages Through Modern Contraception?," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(5), pages 2115-2142, October.
    4. Pedzisai Ndagurwa & Clifford Odimegwu, 2019. "Decomposition of Zimbabwe’s stalled fertility change: a two-sex approach to estimating education and employment effects," Journal of Population Research, Springer, vol. 36(1), pages 35-63, March.
    5. Yoko Akachi & Jocelyn Finlay & Iván Mejía-Guevara, 2016. "Delayed marriage, contraceptive use, and breastfeeding: Fertility patterns over time and wealth quintiles in sub-Saharan Africa," WIDER Working Paper Series 043, World Institute for Development Economic Research (UNU-WIDER).
    6. Caroline Krafft & Elizabeth Kula & Maia Sieverding, 2021. "An investigation of Jordan’s fertility stall and resumed decline: The role of proximate determinants," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(19), pages 605-652.
    7. Rotimi Felix Afolabi & Martin Enock Palamuleni, 2022. "Influence of Maternal Education on Second Childbirth Interval Among Women in South Africa: Rural-Urban Differential Using Survival Analysis," SAGE Open, , vol. 12(1), pages 21582440221, March.
    8. Thirunaukarasu Subramaniam & Nanthakumar Loganathan & Erez Yerushalmi & Evelyn Shyamala Devadason & Mazlan Majid, 2018. "Determinants of Infant Mortality in Older ASEAN Economies," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(1), pages 397-415, February.
    9. Frank Götmark & Malte Andersson, 2023. "Achieving sustainable population: Fertility decline in many developing countries follows modern contraception, not economic growth," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(3), pages 1606-1617, June.
    10. John Bongaarts, 2017. "The effect of contraception on fertility: Is sub-Saharan Africa different?," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(6), pages 129-146.
    11. Jocelyn E. Finlay & Iván Mejía-Guevara & Yoko Akachi, 2016. "Delayed marriage, contraceptive use, and breastfeeding: Fertility patterns over time and wealth quintiles in sub-Saharan Africa," WIDER Working Paper Series wp-2016-43, World Institute for Development Economic Research (UNU-WIDER).
    12. David A. Sánchez-Páez & José Antonio Ortega, 2018. "Adolescent contraceptive use and its effects on fertility," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(45), pages 1359-1388.
    13. Laili Rahayuwati & Ikeu Nurhidayah & Rindang Ekawati & Habsyah Saparidah Agustina & Dadang Suhenda & Dean Rosmawati & Vira Amelia, 2023. "Determinant Factors of Post-Partum Contraception among Women during COVID-19 in West Java Province, Indonesia," IJERPH, MDPI, vol. 20(3), pages 1-10, January.
    14. Bruno Arpino & Jordi Gumà-Lao & Albert Julià, 2018. "Family histories and the demography of grandparenthood," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 39(42), pages 1105-1150.
    15. Canning, David & Mabeu, Marie Christelle & Pongou, Roland, 2020. "Colonial origins and fertility: can the market overcome history?," MPRA Paper 112496, University Library of Munich, Germany.
    16. Jamal Abdul Nasir & Sohail Akhtar & Syed Arif Ahmed Zaidi & Andleeb Rani & Hina Bano & Andrew Hinde, 2019. "Is recent Afghanistan survey data suitable for fertility analysis? A regional investigation based on fertility inhibiting determinants," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-14, October.
    17. Dalomi Bahan & Latif Dramani, 2019. "Socioeconomic Status and Fertility Decline in Burkina Faso, 2003-2015," Applied Economics and Finance, Redfame publishing, vol. 6(2), pages 56-70, March.

    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. David E. BLOOM & Michael KUHN & Klaus PRETTNER, 2017. "Africa’s Prospects for Enjoying a Demographic Dividend," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 83(1), pages 63-76, March.
    2. Ruben Castro & Jere Behrman & Hans-Peter Kohler, 2015. "Perception of HIV risk and the quantity and quality of children: the case of rural Malawi," Journal of Population Economics, Springer;European Society for Population Economics, vol. 28(1), pages 113-132, January.
    3. Dick Durevall & Annika Lindskog, 2016. "Adult Mortality, AIDS, and Fertility in Rural Malawi," The Developing Economies, Institute of Developing Economies, vol. 54(3), pages 215-242, September.
    4. Lee, Melissa M. & Izama, Melina Platas, 2015. "Aid Externalities: Evidence from PEPFAR in Africa," World Development, Elsevier, vol. 67(C), pages 281-294.
    5. Martin Karlsson & Stefan Pichler, 2015. "Demographic consequences of HIV," Journal of Population Economics, Springer;European Society for Population Economics, vol. 28(4), pages 1097-1135, October.
    6. Magadi, Monica Akinyi & Agwanda, Alfred O., 2010. "Investigating the association between HIV/AIDS and recent fertility patterns in Kenya," Social Science & Medicine, Elsevier, vol. 71(2), pages 335-344, July.
    7. David E. Bloom & Michael Kuhn & Klaus Prettner, 2016. "Africa’s Prospects for Enjoying a Demographic Dividend," VID Working Papers 1604, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    8. Yao Yao, 2022. "Fertility and HIV Risk in Africa," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 109-133, July.
    9. Kudo, Yuya, 2016. "Malaria infection and fetal growth during the war : evidence from Liberia," IDE Discussion Papers 556, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    10. Wilson, Nicholas, 2015. "Child mortality risk and fertility: Evidence from prevention of mother-to-child transmission of HIV," Journal of Development Economics, Elsevier, vol. 116(C), pages 74-88.
    11. Yoo-Mi Chin & Nicholas Wilson, 2018. "Disease risk and fertility: evidence from the HIV/AIDS pandemic," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(2), pages 429-451, April.

    More about this item

    Keywords

    fertility; proximate determinants; model;
    All these keywords.

    JEL classification:

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

    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:demres:v:33:y:2015:i:19. 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: Editorial Office (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.