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Modeling Household Fertility Decisions: Estimation and Testing of Censored Regression Models for Count Data

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  • Caudill, Steven B
  • Mixon, Franklin G, Jr

Abstract

This paper adds to the recent body of research on fertility by estimating and testing censored Poisson regression models and censored negative binomial regression models of household fertility decisions. A novel feature of this study is that in each case the censoring threshold varies from individual to individual. Also, a Lagrange multiplier or score test is used to investigate overdispersion. In these regression models the dependent variable is the number of children. In this situation, censored Poisson regression models and censored negative binomial regression models have statistical advantages over OLS, uncensored Poisson regression models, and uncensored negative binomial regression models. The censored models employed in this study are estimated using panel data collected from the Consumer Expenditure Survey compiled by the Bureau of Labor Statistics. The findings of this study support the fertility hypothesis of Becker and Lewis (1965-70).

Suggested Citation

  • Caudill, Steven B & Mixon, Franklin G, Jr, 1995. "Modeling Household Fertility Decisions: Estimation and Testing of Censored Regression Models for Count Data," Empirical Economics, Springer, vol. 20(2), pages 183-196.
  • Handle: RePEc:spr:empeco:v:20:y:1995:i:2:p:183-96
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    Cited by:

    1. Mohamed Amara, 2015. "Multilevel Modelling of Individual Fertility Decisions in Tunisia: Household and Regional Contextual Effects," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 124(2), pages 477-499, November.
    2. Marwân-al-Qays Bousmah, 2017. "The effect of child mortality on fertility behaviors is non-linear: new evidence from Senegal," Review of Economics of the Household, Springer, vol. 15(1), pages 93-113, March.
    3. Famoye, Felix & Wang, Weiren, 2004. "Censored generalized Poisson regression model," Computational Statistics & Data Analysis, Elsevier, vol. 46(3), pages 547-560, June.
    4. Dimitris Karlis & Purushottam Papatla & Sudipt Roy, 2016. "Finite mixtures of censored Poisson regression models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(2), pages 100-122, May.
    5. Livia Elisa Ortensi, 2015. "Engendering the fertility-migration nexus: The role of women's migratory patterns in the analysis of fertility after migration," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(53), pages 1435-1468, June.
    6. Jörgen Hellström, 2006. "A bivariate count data model for household tourism demand," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 213-226.
    7. Westerberg, Thomas, 2006. "MoreWork, Less Kids - The Relationship Between Market Experience and Number of Children," Umeå Economic Studies 682, Umeå University, Department of Economics.
    8. Rafal Raciborski, 2011. "Right-censored Poisson regression model," Stata Journal, StataCorp LP, vol. 11(1), pages 95-105, March.
    9. Westerberg, Thomas, 2006. "Two Papers On Fertility - The Case Of Sweden," Umeå Economic Studies 683, Umeå University, Department of Economics.
    10. Igor Fedotenkov, 2016. "Labour Shares, Fertility and Longevity in an OLG model," Bank of Lithuania Working Paper Series 28, Bank of Lithuania.

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