Essays on the Prediction and Measurement of Individual Well-being

Reference : Essays on the Prediction and Measurement of Individual Well-being


	Document type :	Dissertations and theses : Doctoral thesis
	Discipline(s) :	Business & economic sciences : Microeconomics Business & economic sciences : Special economic topics (health, labor, transportation…)
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/55174

Title :	Essays on the Prediction and Measurement of Individual Well-being
Language :	English
Author, co-author :	Taye, Alemayehu Demissew [University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > >]
Publication date :	2023
Institution :	University of Luxembourg, Luxembourg
Name of the degree :	Docteur de l’université du Luxembourg En Sciences Économiques
Supervisor :	d'Ambrosio, Conchita
Keywords :	[en] Machine Learning ; Vulnerability ; Poverty ; Wellbeing ; SOEP ; Material deprivation ; SARS CoV 2 ; individual behaviour ; Explainable AI ; policy response ; EU-SILC
Permalink :	http://hdl.handle.net/10993/55174
FnR project :	FnR ; FNR12252781 > Andreas Zilian > DRIVEN > Data-driven Computational Modelling And Applications > 01/09/2018 > 28/02/2025 > 2017

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