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A Computable Overlapping Generations Model For Gender And Growth Policy Analysis

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  • Agénor, Pierre-Richard

Abstract

This paper develops a computable overlapping generations (OLG) model for gender and growth policy analysis that brings to the fore the role of access to public infrastructure. The model accounts for human and physical capital accumulation, intra- and intergenerational health persistence, fertility choices, and women's time allocation between market work, child rearing, and home production. Bargaining between spouses and gender bias, in the form of discrimination in the work place and mothers' time allocation between daughters and sons, are also accounted for. The model is calibrated for a low-income country and various experiments are conducted, including improved access to infrastructure, an increase in subsidies to child care, a reduction in gender bias, and a composite gender-based reform program to assess the role of policy complementarities. The results illustrate the importance of accounting for changes in women's time allocation in assessing the impact of public policy on economic growth.

Suggested Citation

  • Agénor, Pierre-Richard, 2017. "A Computable Overlapping Generations Model For Gender And Growth Policy Analysis," Macroeconomic Dynamics, Cambridge University Press, vol. 21(1), pages 11-54, January.
  • Handle: RePEc:cup:macdyn:v:21:y:2017:i:01:p:11-54_00
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    Cited by:

    1. Manuel Santos Silva & Stephan Klasen, 2021. "Gender inequality as a barrier to economic growth: a review of the theoretical literature," Review of Economics of the Household, Springer, vol. 19(3), pages 581-614, September.
    2. Kato, Ryuta Ray, 2018. "The future prospect of the long-term care insurance in Japan," Japan and the World Economy, Elsevier, vol. 47(C), pages 1-17.
    3. Youssouf Merouani & Faustine Perrin, 2022. "Gender and the long-run development process. A survey of the literature [Rethinking age heaping: A cautionary tale from nineteenth-century Italy]," European Review of Economic History, Oxford University Press, vol. 26(4), pages 612-641.

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