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A Stata module for computing fertility rates and TFRs from birth histories: tfr2

Author

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  • Bruno Schoumaker

    (Université catholique de Louvain)

Abstract

Background: Since the 1970s, birth history data have become widely available, thanks to the World Fertility survey and the Demographic and Health Surveys programs. Despite their wide availability, these data remain under-exploited. Computation, even of simple indicators (fertility rates, total fertility rates, mean age at childbearing) and their standard errors, is not direct with such data, and other types of analysis (fertility differentials, reconstruction of fertility trends et cetera) may also involve reorganization of data sets and statistical modeling that present a barrier to the use of birth history data. Objective: This paper presents a Stata software module (tfr2) that was prepared to analyze birth history data in a user-friendly and flexible way. It is designed to be used primarily with DHS data, but can also be used easily with birth histories from other sources. Three types of analysis are performed by tfr2: (1) the computation of age-specific fertility rates and TFRs, as well as their standard errors, (2) the reconstruction of fertility trends, and (3) the estimation of fertility differentials (rate ratios). Methods: The tfr2 module is composed of two parts: (1) a Stata command to transform birth history data into a table of births and exposure (tabexp), and (2) a Poisson regression model to compute fertility rates, fertility trends and fertility differentials from a table of births and exposure (produced by tabexp). Comments: One can obtain tfr2 free of charge. It will work with Stata 10 and more recent versions of Stata.

Suggested Citation

  • Bruno Schoumaker, 2013. "A Stata module for computing fertility rates and TFRs from birth histories: tfr2," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(38), pages 1093-1144.
    • Handle: RePEc:dem:demres:v:28:y:2013:i:38
    DOI: 10.4054/DemRes.2013.28.38
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    Cited by:

    1. Apsara Karki Nepal & Martin Halla & Steven Stillman, 2018. "Violent Conflict and the Child Quantity-Quality Tradeoff," Economics working papers 2018-15, Department of Economics, Johannes Kepler University Linz, Austria.
    2. Kathryn Grace & Stuart Sweeney, 2016. "Ethnic Dimensions of Guatemala’s Stalled Transition: A Parity-Specific Analysis of Ladino and Indigenous Fertility Regimes," Demography, Springer;Population Association of America (PAA), vol. 53(1), pages 117-137, February.
    3. Valeria Cetorelli, 2014. "The Effect on Fertility of the 2003–2011 War in Iraq," Population and Development Review, The Population Council, Inc., vol. 40(4), pages 581-604, December.
    4. Frola, Alessia & Delprato, Marcos & Chudgar, Amita, 2024. "Lack of educational access, women's empowerment and spatial education inequality for the Eastern and Western Africa regions," International Journal of Educational Development, Elsevier, vol. 104(C).
    5. Ewa Batyra, 2016. "Fertility and the changing pattern of the timing of childbearing in Colombia," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(46), pages 1343-1372.
    6. Aristide Romaric Bado & A Sathiya Susuman, 2016. "Women's Education and Health Inequalities in Under-Five Mortality in Selected Sub-Saharan African Countries, 1990–2015," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-18, July.
    7. Frans Willekens & Hein Putter, 2014. "Software for multistate analysis," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 31(14), pages 381-420.
    8. 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.
    9. Andrés F. Castro Torres & Ewa Batyra & Mikko Myrskylä, 2021. "Income inequality and increasing dispersion of the transition to first birth in the Global South," MPIDR Working Papers WP-2021-009, Max Planck Institute for Demographic Research, Rostock, Germany.
    10. 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.
    11. Isabel Günther & Kenneth Harttgen, 2016. "Desired Fertility and Number of Children Born Across Time and Space," Demography, Springer;Population Association of America (PAA), vol. 53(1), pages 55-83, February.
    12. Orsola Torrisi, 2020. "Armed Conflict and the Timing of Childbearing in Azerbaijan," Population and Development Review, The Population Council, Inc., vol. 46(3), pages 501-556, September.
    13. Zakarya Al Zalak & Anne Goujon, 2017. "Exploring the fertility trend in Egypt," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 37(32), pages 995-1030.
    14. Robert Stelter, 2016. "Fertility and health insurance types in Germany," LIDAM Discussion Papers IRES 2016021, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    15. Yoonjoung Choi & Qingfeng Li & Blake Zachary, 2018. "Measuring fertility through mobile‒phone based household surveys: Methods, data quality, and lessons learned from PMA2020 surveys," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 38(55), pages 1663-1698.
    16. Wazir Asif & Goujon Anne, 2021. "Exploratory Assessment of the Census of Pakistan Using Demographic Analysis," Journal of Official Statistics, Sciendo, vol. 37(3), pages 719-750, September.
    17. Maia Sieverding & Nasma Berri & Sawsan Abdulrahim, 2018. "Marriage and fertility patterns among Jordanians and Syrian refugees in Jordan," Working Papers 1187, Economic Research Forum, revised 03 May 2018.
    18. Delprato, Marcos & Akyeampong, Kwame & Dunne, Máiréad, 2017. "Intergenerational Education Effects of Early Marriage in Sub-Saharan Africa," World Development, Elsevier, vol. 91(C), pages 173-192.
    19. Delprato, Marcos & Chudgar, Amita & Frola, Alessia, 2024. "Spatial education inequality for attainment indicators in sub-saharan Africa and spillovers effects," World Development, Elsevier, vol. 176(C).
    20. 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.
    21. Delprato, Marcos & Akyeampong, Kwame & Sabates, Ricardo & Hernandez-Fernandez, Jimena, 2015. "On the impact of early marriage on schooling outcomes in Sub-Saharan Africa and South West Asia," International Journal of Educational Development, Elsevier, vol. 44(C), pages 42-55.
    22. Muhammad Asif Wazir & Anne Goujon, 2019. "Assessing the 2017 Census of Pakistan Using Demographic Analysis: A Sub-National Perspective," VID Working Papers 1906, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    23. Andrés F. Castro Torres & Ewa Batyra & Mikko Myrskylä, 2022. "Income Inequality and Increasing Dispersion of the Transition to First Birth in the Global South," Population and Development Review, The Population Council, Inc., vol. 48(1), pages 189-215, March.

    More about this item

    Keywords

    fertility; total fertility rate (TFR); trends; Demographic and Health Surveys (DHS); birth history; Poisson regression; Stata;
    All these keywords.

    JEL classification:

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

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