This dissertation consists of three chapters which explore the usefulness of partial identification methods for estimating treatment effects in applied health economics research. Each one applies the methodology to different settings in which establishing causality has traditionally been difficult, and seeks to demonstrate when a bounding approach can—and cannot—aid researchers in learning about causal relationships.The first chapter studies the Housing Choice Voucher program in the United States and estimates bounds on the effect that receiving this form of housing assistance has on self-reported health status and the likelihood of hospitalization within the eligible population of renters. The second chapter aims to understand the relationship between mental health and labor market outcomes. We bound the impact depressive symptom severity has on both the probability of employment and on earnings. The third chapter provides a thorough exposition of the bounding strategy used throughout the dissertation and examines how genetic data might be used in the framework to study questions of public health interest. We demonstrate the latter by estimating bounds on the causal effect of both education and body mass index on mental health.
","abstract_html":"<p>This dissertation consists of three chapters which explore the usefulness of partial identification methods for estimating treatment effects in applied health economics research. Each one applies the methodology to different settings in which establishing causality has traditionally been difficult, and seeks to demonstrate when a bounding approach can—and cannot—aid researchers in learning about causal relationships.The first chapter studies the Housing Choice Voucher program in the United States and estimates bounds on the effect that receiving this form of housing assistance has on self-reported health status and the likelihood of hospitalization within the eligible population of renters. The second chapter aims to understand the relationship between mental health and labor market outcomes. We bound the impact depressive symptom severity has on both the probability of employment and on earnings. The third chapter provides a thorough exposition of the bounding strategy used throughout the dissertation and examines how genetic data might be used in the framework to study questions of public health interest. We demonstrate the latter by estimating bounds on the causal effect of both education and body mass index on mental health.</p>","abstract_has_math":false,"creators":["Germinario, Giuseppe"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Flores-Lagunes, Alfonso"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-05-15T07:00:00Z","date_published":"2022-05-15T07:00:00Z","updated_at":"2026-07-24T04:56:14Z","subjects":["Bounds","Depression","Employment","Health and poverty","Subsidized housing","Treatment effects","Economics","Labor Economics","Social and Behavioral Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://surface.syr.edu/etd/1503","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Flores-Lagunes, Alfonso"]},{"key":"dc:creator","label":"Author","values":["Germinario, Giuseppe"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Bounds","Depression","Employment","Health and poverty","Subsidized housing","Treatment effects","Economics","Labor Economics","Social and Behavioral Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://surface.syr.edu/etd/1503"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This dissertation consists of three chapters which explore the usefulness of partial identification methods for estimating treatment effects in applied health economics research. Each one applies the methodology to different settings in which establishing causality has traditionally been difficult, and seeks to demonstrate when a bounding approach can—and cannot—aid researchers in learning about causal relationships.The first chapter studies the Housing Choice Voucher program in the United States and estimates bounds on the effect that receiving this form of housing assistance has on self-reported health status and the likelihood of hospitalization within the eligible population of renters. The second chapter aims to understand the relationship between mental health and labor market outcomes. We bound the impact depressive symptom severity has on both the probability of employment and on earnings. The third chapter provides a thorough exposition of the bounding strategy used throughout the dissertation and examines how genetic data might be used in the framework to study questions of public health interest. We demonstrate the latter by estimating bounds on the causal effect of both education and body mass index on mental health.
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