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Optimal sequential fertility choices under discriminatory preferences

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  • Jianxun Lyu

    (University of Electronic Science and Technology of China)

Abstract

This paper investigates the optimal fertility strategy and its impact on the fertility rate and parental investment in a patriarchal society. Parents with son bias first make sequential fertility choices and then make parental investment decisions based on the realized sex composition of children. The optimal fertility strategy is a one-stage look-ahead strategy and represents a son-preferring stopping rule. I characterize the resulting population distribution of the possible sex combinations of children in a family, which shows that females are disproportionately born into larger families and, as a result, receive less investment than males, on average. In addition, both under- and over-reproduction occur in a patriarchal society, but the average fertility rate may be lower than in a gender-neutral society. Lastly, I show that the son-preferring stopping rule as the optimal strategy is robust to the introduction of sex selection and alternative investment options for a large set of parameters.

Suggested Citation

  • Jianxun Lyu, 2025. "Optimal sequential fertility choices under discriminatory preferences," Journal of Population Economics, Springer;European Society for Population Economics, vol. 38(1), pages 1-51, March.
    • Handle: RePEc:spr:jopoec:v:38:y:2025:i:1:d:10.1007_s00148-025-01095-2
    DOI: 10.1007/s00148-025-01095-2
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    More about this item

    Keywords

    Optimal fertility strategy; Son preference; Sibling sex composition; Gender inequality;
    All these keywords.

    JEL classification:

    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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