This master thesis leverages two German micro-level data sets – the TwinLife data sample and the German Socio-Economic Panel (GSOEP) – to gain insights into the relationshipbetween income and young German adults’ life satisfaction. Accounting for the relevance of unobserved heterogeneities in the context of happiness research, it does so by applying two different control mechanisms to both data samples in connection with fixed effect ordered logit models. The estimation results for young respondents in the GSOEP data sample are contrasted with information on twin pairs from the TwinLife data set to explore three aspects of happiness determination: Firstly, the relevance of income in determining young German adults’ life satisfaction is evaluated. Income is found to play a neglectable role in influencing German youngsters’ happiness. Secondly, this thesis explores the extent to which twin differencing as a mechanism to control for unobserved heterogeneities yields outcomes different from those of competing approaches. Since the estimation results do not offer greatly diverging outcomes, itis concluded that twin differencing constitutes a sufficient instrument to control for unobserved heterogeneities. Lastly, this finding is refined by exploiting the information given on identical and non-identical twins in the TwinLife data set to disentangle in how far genetic endowments determine life satisfaction. Unobserved identical genetic dispositions are found to play a rolein influencing someone’s well-being. Hence, data such as information on twins that explicitly allow the control of these unobserved heterogeneities should be considered for happiness research.
Date of Award | 14 Oct 2021 |
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Original language | English |
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Awarding Institution | - Universidade Católica Portuguesa
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Supervisor | Pedro Miguel Raposo (Supervisor) |
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- Life satisfaction
- Income
- Young adults
- Young adults models
Money can’t buy happiness: income and young adults’ life satisfaction in Germany
Deres, L. R. S. (Student). 14 Oct 2021
Student thesis: Master's Thesis