Electronic Theses and Dissertations

Date

2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Economics

Committee Chair

Andrew Hussey

Committee Member

David Kemme

Committee Member

Jamin Speer

Committee Member

Han Yu

Committee Member

Karar Zunaid Ahsan

Abstract

In the first essay, using data from the Panel Study of Income Dynamics, I estimate the impact of breastfeeding initiation and duration on multiple cognitive, health, and behavioral outcomes spanning early childhood through adolescence. To mitigate the potential bias, I employ a doubly robust (DR) estimation method, addressing misspecification in either the treatment or outcome models while adjusting for selection effects. My novel approach is to use and evaluate a battery of supervised machine learning (ML) algorithms to improve propensity score (PS) estimates. I demonstrate that the gradient boosting machine algorithm removes bias more effectively and minimizes other prediction errors compared to logit and probit models as well as alternative ML algorithms. I find that having been breastfed is significantly linked to multiple improved early cognitive outcomes, though the impact reduces somewhat with age. In contrast, I find mixed evidence regarding the impact of breastfeeding on non-cognitive outcomes, with effects being most pronounced in adolescence. In the second essay, using data from the National Longitudinal Study of Adolescent Health, I examine the impact of breastfeeding on the likelihood of obtaining a college degree and attending graduate school. I find that having been breastfed is linked to an increased probability of obtaining a college degree, but its association with graduate school attendance is largely insignificant. The effect on college degree attainment is primarily concentrated among males, blacks, and whites. The effect of breastfeeding on college degrees may be operating through the impact of breastfeeding on cognitive ability. The third essay focuses on the rural-urban gap in women’s health outcomes. Applying Oaxaca-Blinder and quantile regression-based counterfactual decomposition methods to the data from the latest five rounds (2004-2018) of Bangladesh Demographic and Health Surveys, I identify sources of the sizeable differences in body mass index, underweight, overweight, and obesity across rural and urban areas among women of childbearing age. The estimates reveal that disparities in education, healthcare access, infrastructural developments, and inequitable distribution of wealth explain a major fraction of the rural-urban gap in nutritional outcomes. I also find that sizeable gaps are attributable to differential returns to education, institutional births, and wealth status.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest.

Notes

Embargoed until 07-11-2026

Download

Available for download on Saturday, July 11, 2026

Share

COinS