Biography:
Dr. Jason Baron is an Assistant Professor of Economics at Duke University, where he specializes in applied microeconomics with a particular focus on the economics of education, child welfare, and the economics of crime. He has also contributed extensively to policy research on issues related to human capital, poverty, and social mobility. In addition to his academic work, Baron is a Faculty Research Fellow at the National Bureau of Economic Research (NBER). His work is frequently published in top-tier economics journals, including the American Economic Journal: Applied Economics, American Economic Journal: Economic Policy, and the Journal of Public Economics.
Dr. Baron earned his Ph.D. in Economics from Florida State University in 2020, following his M.S. in Economics from the same institution in 2016. He completed his undergraduate studies at the University of Wisconsin-Whitewater, graduating summa cum laude with a B.B.A. in Economics in 2015.
Student Lecture: 27 March 2025
Child Maltreatment and Social Mobility
Using over 25 years of linked administrative child welfare records and income data from two U.S. states, we examine the impact of child maltreatment and its intergenerational transmission on social mobility. We also explore how policy interventions may help disrupt cycles of maltreatment and economic disadvantage across generations.
Faculty Lecture: 28 March 2025
Mechanism Reform: An Application to Child Welfare
How to allocate tasks among agents is a central question in economics. In many of these problems, new mechanisms are introduced to reform existing systems. Unlike mechanisms developed in isolation, reforms must navigate additional political and institutional constraints. We study this question in the context of assigning Child Protective Services investigators to maltreatment cases, where investigators decide whether to place children in foster care. Given concerns about investigator burnout and turnover, a key constraint is ensuring investigators are not worse off under the new system. We develop a framework that combines an identification strategy for estimating investigator performance with novel mechanism-design results that elicit investigator preferences and allocate cases to improve child welfare while respecting constraints on investigator welfare. Simulations suggest that the proposed mechanism could reduce false positives (unnecessary foster care placements) by up to 11% while also decreasing false negatives (missed maltreatment cases) and overall placements.