Subjective well-being and individual material situation in four countries of central Europe

Informace o vysokoškolské kvalifikační práci

Název práce:
Subjective well-being and individual material situation in four countries of central Europe
Autor práce:
Švorc, Jan
Typ práce:
Disertační práce / info:eu-repo/semantics/doctoralThesis
Vedoucí práce:
Vomlel, Jiří
Osoba oponující práci:
Malá, Ivana; Mysíková, Martina
Jazyk práce:
Czech
Abstrakt:
The general goal of our research is to explore the association 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). Material situation is measured by income; relative in-come compared to others as well as to one’s own past; perceived economic strain; fi-nancial problems; material deprivation; and housing problems. The analysis is based on an empirical data from European Quality of Life Study. First, the associations were ana-lyzed using appropriate statistical methods (Welch t-test and ANOVA for unequal vari-ances). The results show that a better material situation is associated with improved SWB in all examined countries with only few exceptions. The hypotheses on the associa-tion of SWB with income and economic strain were not confirmed in Hungary. The hy-potheses on the association with the relative income compared to others were not con-firmed in Slovakia. Also, the hypothesis that the life satisfaction is associated with the income was not confirmed in case of Slovakia. The subjective financial situation relative to most people and the subjective economic strain seem to be especially important fac-tors. Bayesian networks as a graphical representation of the relations among SWB and the material situation were constructed in five versions. They were compared using the BIC criteria, the SWB prediction accuracy, and compared with the ordinal logistic re-gression (OLR). The expert knowledge as well as three different algorithms (greedy, Gobnilp, and Tree-augmented Naïve Bayes) were used for learning the structures. Network parameters were learnt using the EM algorithm. The expert model parameters were also learned using OLR. The expert version with OLR parameters best predicts SWB (the prediction accuracy of 41%). The Gobnilp model, Markov equivalent to the greedy model, is BIC optimal. Differences between BIC optimal and expert versions are discussed. We conclude that the objective material conditions influence SWB rather indirectly through the subjective situational assessment of the material conditions.
Klíčová slova:
Material situation; Bayesian Networks; Subjective well-being

Informace o studiu

Studijní program a Studijní obor:
Ekonomika a management/Management
Typ studijního programu:
Doktorský studijní program
Jméno přidělované hodnosti:
Ph.D.
Instituce přidělující hodnost:
University of Economics, Prague
Název fakulty:
Faculty of Management
Název katedry:
Department of Exact Methods
Instituce archivující a zpřístupňující VŠKP:
University of Economics, Prague

Informace o odevzdání a obhajobě

Datum zadání práce:
17. 5. 2018
Datum podání práce:
26. 4. 2019
Datum obhajoby:
27.06.2019

Soubory ke stažení

Hlavní práce:
66008_xsvoj16.pdf [4,65 MB]
Oponentura:
63304_Malá.pdf [486,95 kB]
Oponentura:
63305_Mysíková.pdf [223,31 kB]

Údaje ze systému InSIS

Identifikátor:
https://insis.vse.cz/zp/66008/podrobnosti