Analysis of Life Satisfaction Determinants

This thesis examines the analysis of selected life satisfaction determinants, especially the level of income, unemployment, level of education, self-reported safety, self-reported health and divorce rate. The least squares method was used to compile two models that estimate the impact of the selected determinants on life satisfaction. The first model works with the data of 35 OECD countries in the year of 2015, whereas the second model works only with the data of 30 OECD countries in the year of 2015. Five countries with the highest GDP per capita were removed from the data of the second model, thereby the model attempts to prove the Easterlin paradox. In the first model, the variable of GDP per capita is shown to be insignificant, but in the second model it becomes significant, thus confirming Easterlin paradox. Variables of unemployment, self-reported health and self-reported safety are, according to the first model, statistically significant determinants of life satisfaction. Conversely, the second model confirms statistical significance for GDP per capita, unemployment and self-reported health. The variables of unemployment and self-reported health can be described as very strong determinants of life satisfaction. According to our study, unemployment is expected to affect life satisfaction negatively, while self-reported health positively.