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A double-hurdle count model for completed fertility data from the developing world

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  • Alfonso Miranda

    (CIDE)

Abstract

I report on a study of the socioeconomic determinants of completed fertility in Mexico. An innovative Poisson double-hurdle count model is developed for the analysis. This methodological approach allows low- and high-order parities to be determined by two different data-generating mechanisms and explicitly accounts for potential endogenous switching between regimes. Unobserved heterogeneity is properly controlled. Special attention is given to study how socioeconomic characteristics such as religion and ethnic group affect the likelihood of transition from low- to high-order parities. Findings indicate that education and Catholicism are associated with reductions in the likelihood of transition from parities lower than four to high-order parities. However, being an indigenous language speaker increases the odds of a large family.

Suggested Citation

  • Alfonso Miranda, 2013. "A double-hurdle count model for completed fertility data from the developing world," Mexican Stata Users' Group Meetings 2013 13, Stata Users Group.
    • Handle: RePEc:boc:msug13:13
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    1. Alfonso Miranda, 2010. "A double-hurdle count model for completed fertility data from the developing world," DoQSS Working Papers 10-01, Quantitative Social Science - UCL Social Research Institute, University College London.
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    15. Steven T. Yen & Chao‐Hsiun Tang & Shew‐Jiuan B. Su, 2001. "Demand for traditional medicine in Taiwan: a mixed Gaussian–Poisson model approach," Health Economics, John Wiley & Sons, Ltd., vol. 10(3), pages 221-232, April.
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    Cited by:

    1. Alfonso Miranda, 2010. "A double-hurdle count model for completed fertility data from the developing world," DoQSS Working Papers 10-01, Quantitative Social Science - UCL Social Research Institute, University College London.
    2. Bastien CHABE-FERRET, 2013. "The Importance of Fertility Norms: New Evidence from France," LIDAM Discussion Papers IRES 2013012, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    3. Llerena, Freddy, 2012. "Determinantes de la fecundidad en el Ecuador [Determinants of fertility in Ecuador]," MPRA Paper 39887, University Library of Munich, Germany, revised Feb 2012.
    4. Miranda, Alfonso & Trivedi, Pravin K., 2020. "Econometric Models of Fertility," IZA Discussion Papers 13357, Institute of Labor Economics (IZA).
    5. 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).
    6. Yigezu, Yigezu Atnafe & Mugera, Amin & El-Shater, Tamer & Aw-Hassan, Aden & Piggin, Colin & Haddad, Atef & Khalil, Yaseen & Loss, Stephen, 2018. "Enhancing adoption of agricultural technologies requiring high initial investment among smallholders," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 199-206.

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    More about this item

    JEL classification:

    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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