Universität zu Köln

Zenzes, Johanna Maria (2023). Heterogeneous Treatment Effects of Behavioral and Environmental Risk Factors on Infants' Health at Birth: A Causal Machine Learning Approach. PhD thesis, Universität zu Köln.

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Abstract

Behavioral and environmental risk factors, such as maternal smoking during pregnancy and in-utero exposure to extreme weather events are significant threats to infants’ health at birth. Effects of these risk factors on infant health have been extensively studied using traditional methods, while mostly neglecting possible heterogeneity in the effects. Causal machine learning has emerged as an effective approach for estimating heterogeneous treatment effects, but identifying the causal pathways driving heterogeneity remains challenging. This dissertation consists of three essays that apply and adapt causal machine learning techniques to study heterogeneity in the effects of different behavioral and environmental risk factors on health at birth. Chapter 2 uncovers heterogeneity in the effects of maternal smoking during pregnancy on infant health at birth by proposing a novel decomposition approach, while Chapter 3 studies how smoking during pregnancy can be regulated using smoking bans. Chapter 4 studies the effects of in-utero heat shock exposure on health at birth and possible heterogeneity in the effect found.

Item Type:	Thesis (PhD thesis)
Creators:	Creators Email ORCID ORCID Put Code Zenzes, Johanna Maria zenzes@wiso.uni-koeln.de UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-703522
Date:	2023
Language:	English
Faculty:	Faculty of Management, Economy and Social Sciences
Divisions:	Faculty of Management, Economics and Social Sciences > Economics > Econometrics and Statistics > Professorship for Statistics and Econometrics
Subjects:	Economics
Uncontrolled Keywords:	Keywords Language Causal Machine Learning English Heterogeneous Treatment Effects English Effect Decomposition English Health at Birth English Smoking English Extreme Weather English
Date of oral exam:	12 July 2023
Referee:	Name Academic Title Zimmermann, Tom Prof. Dr. Wiesen, Daniel Prof. Dr.
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/70352