Statistical Discrimination in Foster Care Placements

Statistical Discrimination in Foster Care Placements

Nicholas Kahn, Instructor for American University’s online MA in Economics, wrote his Ph.D. dissertation and a research paper on Measuring Racial Disparities in Foster Care Placement: A Case Study of Texas. Nick shares highlights of his research and his perspective on statistical discrimination in foster care placements:

There is substantial evidence of racial disparities in foster care placements. For example, in the U.S., of the 186,602 children removed from their homes in 2022, 21% were Black and 45% were white (US DHHS, 2023). Yet, in the general population, only 13.9% of children were Black and 48.8% were white (ChildStats, 2022). Black children are disproportionately represented in the foster care population. Research has demonstrated the negative effects of long-term foster care, such as employment and housing instability, addiction, and poor educational achievement. If Black children enter foster care at a higher rate than white children, they will disproportionately experience these negative effects.

While most people would not be surprised by the notion that there are racial disparities in foster care placements, this isn’t a topic typically studied by economists. There is a traditional economic model, however, that can help explain the sources of these racial disparities. The theory of statistical discrimination shows how decision-makers do not have to purposefully discriminate in order for racial disparities in outcomes to exist and persist.

All applications of a statistical discrimination framework have a common structure: a decision-maker possesses prior information, observes additional information, and finally, must decide how to allocate a scarce resource. The most common application of statistical discrimination is in explaining earnings disparities in labor markets; however, I have found the theory to also be useful in explaining racial disparities in foster care placements.

Consider a non-discriminatory social worker investigating a case of child maltreatment. The social worker wants to know the child’s true risk of future maltreatment if left in their home, a variable that is very costly (difficult) to observe. The child’s race is low-cost information the social worker can use, perhaps even subconsciously, to proxy for more costly information. In making a decision, the social worker uses a weighted average of the imperfect information they observe, and what they know about racial or ethnic groups based on statistical averages. In this scenario, two children who are observably identical aside from their race can experience different outcomes if the social worker’s beliefs about true risk vary by child’s race, or if the social worker has more difficulty interpreting information about families with culturally different backgrounds than their own.

Statistical discrimination arises in the face of imperfect information, one of the many topics that students will explore more fully in courses such as Microeconomic Theory (ECON-600). Just as the application of statistical discrimination can help us understand racial disparities in foster care placements, other microeconomic models can be used to analyze a wide range of social problems – even those not traditionally studied by economists. ECON-600 provides students with an expansive understanding of the behavior of consumers and producers as they relate in the marketplace. However, one soon learns that these analytical tools can address the broadest range of social phenomena.


ChildStats: Forum on Children and Family Statistics. POP3 Race and Hispanic Origin Composition: Percentage of U.S. children ages 0–17 by race and Hispanic origin, 1980–2022 and projected 2023–2050 , Federal Interagency Forum on Child and Family Statistics.
U.S. Department of Health and Human Services. The AFCARS Report: Preliminary FY 2022 Estimates published in May 2023 (30), Administration for Children and Families, Children’s Bureau.

About the Author

Nick Kahn earned his Ph.D. in economics from American University in December 2013. He has taught principles of microeconomics for the economics department, and PUAD-601, PUAD-602, PUAD-630, PUAD-670, and PUAD-671 for the department of public administration and policy. In his time at AU, Nick has received the James H. Weaver Award for excellence in teaching, the Simon Naidel award for outstanding work in economic theory, and the Richard Brown Dissertation Fellowship. Professor Kahn's current research focuses on providing empirical measurements of racial disparities in numerous aspects of the U.S. child welfare system.

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