Bibliographic Details
| Title: |
Family Income and Young Children's Development. |
| Authors: |
Wimer, Christopher1,2, Wolf, Sharon3 |
| Source: |
Future of Children. Fall2020, Vol. 30 Issue 2, p191-211. 21p. 2 Charts. |
| Subject Terms: |
*Child development, *Families, Income, Health policy, Health & social status |
| Abstract: |
Is income during children's earliest years a key determinant of long-term child and adult success in the longer run? The research to date, Christopher Wimer and Sharon Wolf write, suggests that it is. Wimer and Wolf review substantial descriptive evidence that income can enhance child development and later adult outcomes, and that it does so most strongly during children's earliest years. Next they wrestle with the question of whether this relationship is causal. After outlining the challenges in identifying such causal relationships, they describe a number of studies that purport to overcome these challenges through quasi- or natural experiments. Among other topics, the authors examine how family income affects the outcomes of young children compared to those of older children, and how its effects vary among poor, lowincome, and higher-income families. They also look at the evidence around other dimensions of income, including nonlinear relationships between income and key outcomes, instability in income versus the absolute level of income, and various forms of income, and they review the evidence for impacts of in-kind or near-cash income supports. Finally, Wimer and Wolf highlight some recently launched studies that will shed further light on the relationship between income and development in children's earliest years, and they suggest how policy might better provide income support to low-income families and their children. [ABSTRACT FROM AUTHOR] |
|
Copyright of Future of Children is the property of Future of Children and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Education Research Complete |