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Subjective well-being and the individual material situation in Central Europe: A Bayesian network approach

SYSNO ASEP	0537125
Document Type	V - Research Report
R&D Document Type	The record was not marked in the RIV
Title	Subjective well-being and the individual material situation in Central Europe: A Bayesian network approach
Author(s)	Švorc, Jan (UTIA-B) Vomlel, Jiří (UTIA-B)_{RID, ORCID}
Issue data	Praha: ÚTIA AV ČR, 2020
Series	Research Report
Series number	2387
Number of pages	33 s.
Publication form	Print - P
Language	eng - English
Country	CZ - Czech Republic
Keywords	Subjective Well-Being ; Income ; Economic Strain ; Material Deprivation ; Bayesian Networks ; Central Europe
Subject RIV	BB - Applied Statistics, Operational Research
OECD category	Statistics and probability
R&D Projects	GA17-08182S GA ČR - Czech Science Foundation (CSF)
Institutional support	UTIA-B - RVO:67985556
Annotation	The objective of this paper is to explore the associations between the subjective well-being (SWB) and the subjective and objective measures of the individual material situation in the four post-communist countries of Central Europe (the Czech Republic, Hungary, Poland, and Slovakia). The material situation is measured by income, relative income compared to others, relative income compared to one’s own past, perceived economic strain, financial problems, material deprivation, and housing problems. Our analysis is based on empirical data from the third wave of European Quality of Life Study conducted in 2011. Bayesian networks as a graphical representation of the relations between SWB and the material situation have been constructed in five versions. The models have been assessed using the Bayesian Information Criterion (BIC) and SWB prediction accuracy, and compared with Ordinal Logistic Regression (OLR). Expert knowledge, as well as three different algorithms (greedy, Gobnilp, and Tree-augmented Naive Bayes) were used for learning the network structures. Network parameters were learned using the EM algorithm. Parameters based on OLR were learned for a version of the expert model. The Gobnilp model, the Markov equivalent to the greedy model, is BIC optimal. The OLR predicts SWB slightly better than the other models. We conclude that the objective material conditions' influence on SWB is rather indirect, through the subjective situational assessment of various aspects related to the individual material conditions.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2021

Number of the records: 1