MODELING THE HUMAN CAPITAL DEVELOPMENT OF YOUNG POOR CHILDREN
Embargo until
2024-05-01
Date
2020-01-14
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Johns Hopkins University
Abstract
There are a substantial number of high achieving poor students. These students have similar or better academic outcomes than their non-poor peers. Masten and other resilience scholars argue that the families of resilient children are better able to provide nurturing parenting and educational resources. This explanation neither explains why only a fraction of impoverished families are able to provide such environments, nor fully explicates how these skills develop. This dissertation integrates social and human capital theories with resilience to provide a cohesive framework that addresses these weaknesses. Poor families lean on their social networks for resources and emotional support, which in turn helps mitigate the negative impact of poverty on parenting quality and the availability of resources in the home. This network, however, is a limited resource, meaning that social networks are of little use for families with the greatest need. Human capital develops dynamically; past levels of human capital influence future levels. Together with social capital theory, the dynamic nature of human capital development implies that poor children that are consistently provided with quality parenting and educational resources will develop high levels of human capital.
To test this framework, this dissertation uses Fragile Families. Fragile Families follows a cohort of 4900 children from birth to age nine and oversamples disadvantaged families Regression and growth curve analysis are used to investigate a number of mechanisms affecting human capital including the effects of consistently providing adequate environments, the effects of social support on reducing the negative effects of parental stress, and whether the moderating effects of social support decreases with poverty. There was little support for many of the framework’s hypotheses. The conclusion chapter argues that this is mainly due to a combination of severe amounts of missing data and the reliance on interaction terms to test the framework’s mechanisms. The framework and its assumptions are strongly supported by the empirical literature and will provide future scholars a guide to unpacking the resilience process with other datasets.
Description
Keywords
Sociology