International Research Network on Infants and Child Protection Systems

Poverty, Infant Placements into Foster Care and Disparity

My aim here is to stratify counties by the attributes they share. On the dependent variable side, the county attribute of interest is the number of infant admissions to foster care per 1000 children. On the independent variable side of the model, I am interested primarily in White and Black poverty rates, notwithstanding the problems with poverty as a marker for the strain families often face. It is a starting point. 

The measure of disparity involves the ratio of two rates – the number of Black and White infant placements per 1,000. I am interested in whether the disparity rate varies with other attributes of place with specific emphasis on Black and White poverty rates.

Here is a synopsis of the evidence as it pertains to the placement of infants into out-of-home care:

Entries into out-of-home care 
a) The White infant placement rate is about 5 per 1,000 children (4.98).
b) The Black infant placement rate is 9.6 per 1,000 children.
c) The ratio of the Black infant placement rate to the White infant placement rate is 1.93. This is the conventional measure of admission rate disparity.

Disparity and poverty 
a) The White infant placement is marginally higher in counties with high Black child poverty rates but substantially higher in counties with above average White child poverty rates.
b) Black infant placement rates do not vary strongly with Black child poverty rates.
c) Regarding disparity, Black child poverty is not correlated with the ratio of the two rates. In other words, we do not see greater levels of disparity where Black child poverty rates are higher.
d) In the case of White child poverty, the disparity ratio gets smaller with increases in White poverty, not larger, because White infant placement rates and White poverty rates are so strongly correlated. In effect, the White infant placement comes much closer to the level of the Black infant placement rate

As a last consideration, I monetized the placement rate differences. I accomplished this by adding to each placement, the average number of days spent in care and then computed the gross expenditures per 1,000 children in the general population using a simple blended board and care rate, which represents the cost of maintaining a child in someone else’s home, less the administrative spending.  These findings show the per capita spending for foster care after adjusting for poverty.


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