Sarah Miller
Hosmer Hall
Discussing joint work with Laura Wherry, Beth Rhodes and others
Strong link between health at birth and adult achievement (see Almond and Currie 2011 for an overview).
Notoriously poor health outcomes for low income mothers and babies.
Could an early life health intervention break this cycle?
Miller and Wherry, forthcoming Journal of Human Resources
From 1979 to 1993, fraction of women eligible for Medicaid in the event of a pregnancy more than tripled.
Single largest effort to improve prenatal and birth outcomes in the United States.
Initial evidence (e.g. Currie and Gruber 1996) suggested moms used more prenatal care, had more health interventions at the hospital, and gave birth to healthier babies.
Did better health at birth lead to better adult outcomes for those who gained coverage "in utero"/as newborns?
Use an instrumental variables model to separate policy-driven changes in eligibility from changes driven by (potentially endogenous) economic factors.
Those who gained coverage in utero/as newborns:
Lower incidence of chronic disease in adulthood (particularly diabetes, high blood pressure).
Fewer hospitalizations for these types of conditions.
More likely to graduate high school.
Higher incomes, lower food stamps receipt rates [suggestive].
Effects are not huge, but show that health interventions can change economic outcomes
Follow-up work using the same identification strategy looks at what happens when these cohorts themselves have children.
Can these policies echo across generations?
East, Miller, Page, and Wherry. 2018. "Multi-generational Impacts of Childhood Access to the Safety Net: Early Life Exposure to Medicaid and the Next Generation's Health" (r&r)
Mothers who gained Medicaid eligibility in utero gave birth to babies with:
East, Miller, Page, and Wherry. 2018. "Multi-generational Impacts of Childhood Access to the Safety Net: Early Life Exposure to Medicaid and the Next Generation's Health" (r&r)
Meaningful improvements in economic and financial outcomes that result from health interventions. But could we reduce health disparities by targeting the "other" arrow?
With Y Combinator and University of Chicago Poverty Lab, I am working on a randomized controlled trial of a "basic" income.
Intervention: $1000/month for 3 years; N=1100.
Control: $50/month for 3 years, N=2000.
In-person enrollment and surveys conducted by UMich's SRC.
Collecting outcome data on:
Biomarkers (height, weight, blood pressure, blood sugar, cholesterol).
Healthy behaviors (sleep, exercise).
Nutrition diaries.
Use of health care services.
Insurance coverage.
Stress and mental health (including cognition/decision-making).
Pilot:
This fall, SRC enrolled 100 individuals in our pilot which runs until the end of January.
Goals of the pilot:
April 2019: Enrollment in the main study begins.
Study will run through 2022.
Bringing big (bigger!) data to early life health research:
Linked all birth records for those born in California from 1960 to 2014 to:
the 2000 Census
2001-2017 American Community Survey
Administrative records on mortality from SSA
Admin records on SSI receipt
Admin records on TANF receipt
Admin data on quarterly earnings from UIAs
Admin data on Medicaid/Medicare enrollment
Admin data on college attendance from NSC
All at different stages of progress...
Always happy for feedback:
mille@umich.edu