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Uncertain Infant Mortality, Learning, And Life-Cycle Fertility

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  • Pedro Mira

Abstract

This article examines the links between infant mortality and fertility in an environment with unobserved heterogeneity in infant mortality risk across mothers. In such an environment, replacement behavior (i.e., the fertility response to an experienced child death) might be influenced by mothers' learning about a family-specific component of infant mortality risk. I explicitly introduce learning by mothers in a dynamic stochastic model of life-cycle marital fertility, and I estimate the model's structural parameters using Malaysian panel data. The framework is used to estimate replacement rates and to correct for birth selectivity in the estimation of the relationship between infant mortality risk and "health inputs." Copyright 2007 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

Suggested Citation

  • Pedro Mira, 2007. "Uncertain Infant Mortality, Learning, And Life-Cycle Fertility," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(3), pages 809-846, August.
    • Handle: RePEc:ier:iecrev:v:48:y:2007:i:3:p:809-846
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    Cited by:

    1. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    2. Masaru Nagashima & Chikako Yamauchi, 2023. "Pregnant in haste? The impact of foetus loss on birth spacing and the role of subjective probabilistic beliefs," Review of Economics of the Household, Springer, vol. 21(4), pages 1409-1431, December.
    3. Raquel Fernandez, 2007. "Culture as Learning: The Evolution of Female Labor Force Participation over a Century," NBER Working Papers 13373, National Bureau of Economic Research, Inc.
    4. Gilleskie, Donna, 2010. "Work absences and doctor visits during an illness episode: The differential role of preferences, production, and policies among men and women," Journal of Econometrics, Elsevier, vol. 156(1), pages 148-163, May.
    5. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    6. Fernández, Raquel, 2007. "Culture as Learning: The Evolution of Female Labour Force Participation Over a Century," CEPR Discussion Papers 6451, C.E.P.R. Discussion Papers.
    7. Michael Darden, 2017. "Smoking, Expectations, and Health: A Dynamic Stochastic Model of Lifetime Smoking Behavior," Journal of Political Economy, University of Chicago Press, vol. 125(5), pages 1465-1522.
    8. Yu Zheng & Juan Pantano, 2012. "Using Subjective Expectations Data to Allow for Unobserved Heterogeneity in Hotz-Miller Estimation Strategies," 2012 Meeting Papers 940, Society for Economic Dynamics.
    9. Juan Pantano & Qi Li, 2013. "The Demographic Consequences of Gender Selection Technology," 2013 Meeting Papers 1161, Society for Economic Dynamics.
    10. Gahramanov, Emin & Gaibulloev, Khusrav & Younas, Javed, 2017. "Parental Transfers and Fertility: Does the Recipient's Gender Matter?," MPRA Paper 79531, University Library of Munich, Germany.
    11. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    12. Sebastian Galiani & Juan Pantano, 2021. "Structural Models: Inception and Frontier," NBER Working Papers 28698, National Bureau of Economic Research, Inc.

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