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来源类型Working Paper
规范类型报告
DOI10.3386/w17774
来源IDWorking Paper 17774
Child Care Subsidies, Maternal Well-Being, and Child-Parent Interactions: Evidence from Three Nationally Representative Datasets
Chris M. Herbst; Erdal Tekin
发表日期2012-01-20
出版年2012
语种英语
摘要A complete account of the U.S. child care subsidy system requires an understanding of its implications for both parental and child well-being. Although the effects of child care subsidies on maternal employment and child development have been recently studied, many other dimensions of family well-being have received little attention. This paper attempts to fill this gap by examining the impact of child care subsidy receipt on maternal health and the quality of child-parent interactions. The empirical analyses use data from three nationally representative surveys, providing access to numerous measures of family well-being. In addition, we attempt to handle the possibility of non-random selection into subsidy receipt by using several identification strategies both within and across the surveys. Our results consistently indicate that child care subsidies are associated with worse maternal health and poorer interactions between parents and their children. In particular, subsidized mothers report lower levels of overall health and are more likely to show symptoms consistent with anxiety, depression, and parenting stress. Such mothers also reveal more psychological and physical aggression toward their children and are more likely to utilize spanking as a disciplinary tool. Together, these findings suggest that work-based public policies aimed at economically disadvantaged mothers may ultimately undermine family well-being.
主题Health, Education, and Welfare ; Health ; Labor Economics ; Demography and Aging
URLhttps://www.nber.org/papers/w17774
来源智库National Bureau of Economic Research (United States)
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条目标识符http://119.78.100.153/handle/2XGU8XDN/575447
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Chris M. Herbst,Erdal Tekin. Child Care Subsidies, Maternal Well-Being, and Child-Parent Interactions: Evidence from Three Nationally Representative Datasets. 2012.
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