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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
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, firstname.lastname@example.org, Tel.: 266 052 201. Year of Publishing 2021
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