Daniel Millimet, Shuo Qi

Subject Area



In chapter 1, I assess the long-term education and labor market effects of missed ADHD diagnoses. Doing so is challenging for two reasons. First, a person's true ADHD status is unobserved; only their diagnosed status is known. Second, even if diagnostic errors are observed, they are likely akin to non-classical misclassification errors and therefore endogenous. To overcome these empirical challenges, I use and extend on a partial observability model with genetic data from Add Health. Through the lens of the partial observability model. I recover an estimate of true ADHD status, and the probability of underdiagnosis. Then, I estimate their effect on educational attainment and adult financial outcomes. The model finds striking results. The first is that the model predicts ADHD is underdiagnosed with large diagnostic gaps based on the lines of sex, race, ethnicity, and parental socioeconomic status. Second, the model separates the effects of an ADHD diagnosis and true ADHD status on human capital development. The model predicts that both ADHD and underdiagnosis are highly detrimental for human capital development outcomes, such as likelihood of employment in adulthood, education performance, and educational attainment. Large improvements can be made by correctly diagnosing a child who likely has ADHD, however little to no gains can be made by diagnosing a child who does not have ADHD. These results also find evidence of vicious intergenerational cycles in which inequity in mental health care drives and is driven by socioeconomic inequities. I also show through an empirical monte carlo that the model results are robust to relaxing the key assumption of the partial observability model.

In chapter 2, we assess partisan politics as a determinant for geographic inequity in mortality. Geographic inequities in mortality rates in the US are pronounced and growing. Yet, the causes of this inequality are not understood. Recently, the focus has turned to the role of place-specific factors. Here, we explore the importance of politics as a place-specific factor contributing to mortality inequality. Specifically, we test for the existence of {\it partisan mortality cycles} using panel data on counties from 1968-2016. We confirm the existence of partisan mortality cycles, finding lower mortality in counties governed by more liberal political regimes; the evidence regarding political party is mixed. Several sources of heterogeneity are also uncovered.

In chapter 3, we assess the effect of social stigma in peer networks at the primary school level on social capital development and adult wages. Mental health is increasingly being recognized as a public health crisis. However, mental illness is more likely than other physical health issues to go untreated. This is particularly true in the case of adolescent mental health, where there has been growing concerns of the epidemic of depression and anxiety among teenage students. One potential barrier in adolescents receiving mental health care could be the stigmatization from peers. Normalizing the treatment of mental health care through counseling among children can have important consequences. We assess the role of peer networks on the selection into mental health care, using the Add Health data. We do this by introducing a stigma effect and mental health care selection into a network model on child cognitive and social capital development.

Degree Date

Spring 5-13-2023

Document Type


Degree Name





Daniel Millimet

Second Advisor

Nathaniel Pattison

Third Advisor

Wookun Kim

Fourth Advisor

Augustine Denteh

Number of Pages




Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License