Dynamic Analysis of Maternal Employment, Child Care, Quality and Early Childhood Development

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  • March 19, 2019
Creator
  • Pekkurnaz, Didem
    • Affiliation: College of Arts and Sciences, Department of Economics
Abstract
  • This dissertation analyzes the effects of maternal employment and non-parental child care on early childhood developmental outcomes (i.e., health, cognitive achievement and behavioral problems). For this purpose, hybrid production functions are estimated within a dynamic framework using a two-step system Generalized Method of Moments (two-step system GMM) estimator. Nationally representative data, the Early Childhood Longitudinal Study-Birth Cohort (ECLS-B), provide information on parenting style as well as both home and child care environments. Using this information, non-parental child care and home quality indices are created from the first principal components derived from a factor analysis and included in the models. My model also allows for an estimation of the causal effects of health variables (obesity and acute health conditions) on both cognitive achievement and behavior problems. The results show that a high quality home environment reduces the risk of childhood obesity, being overweight, and behavior problems and also improves a child's general health status and cognitive achievement in children. In addition, high quality out-of-home child care improves cognitive development and reduces behavior problems. High quality non-parental in-home child care significantly reduces a child's risk of being overweight. More maternal hours of works, particularly combined with child care, increases the obesity risk while decreasing behavior problems and improving general health status. Center-based child care also improves cognitive achievement of children. Another important finding is that childhood obesity significantly reduces cognitive achievement and emotional development. Including quality variables in the estimations alters the magnitude and significance of maternal employment and child care variables. Additionally, the quality variables have theoretically expected signs when the GMM estimator is used to control for unobserved heterogeneity.
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  • In Copyright
Advisor
  • Joubert, Clement
  • Peter, Klara
  • Guilkey, David
  • Akin, John S.
  • Tauchen, Helen
Degree
  • Doctor of Philosophy
Degree granting institution
  • University of North Carolina at Chapel Hill Graduate School
Graduation year
  • 2014
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  • Chapel Hill, NC
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  • There are no restrictions to this item.
Date uploaded
  • April 22, 2015

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