Browsing by Author "Leino, Nea"

The aim of this research is to examine the impact of population aging on income inequality in Finland over the time period from 1991 to 2016. The research question is relevant since population aging is a part of reality around the world because of the declining trend in the rate of birth in addition to greater longevity. These vast demographic and socio-economic changes stress the well-being of nations. This study offers some important insights into the discussion of income inequality in Finland as no similar study has been conducted before. Understanding the link between aging and income inequality will help us to direct our attention to where policy decisions might need to be directed if inequality is seen to grow adversely. This study will be carried out by both a decomposition analysis and a shift-share analysis. These methods are commonly used for examining the contribution to inequality of particular characteristics, as they manage to gauge the relative importance of different determinants in overall inequality. These methods will be applied to the traditional inequality measures belonging to the family of generalized entropy (GE), such as the mean logarithmic deviation, Theil’s index, and the half-squared coefficient of variation. The use of multiple different measures in inequality research is recommendable, for they provide information about the distribution from different perspectives, and clarify where in the distribution the change has taken place. In order to study the impact of population aging on income inequality, the population was partitioned into five different age cohorts; 0-39, 40-60, 61-65, 66-70, and 71+, and one- or two-person households were examined in this research. Data for this study was received from the Luxembourg Income Study Database (LIS). Income inequality was investigated by disposable household income, which was equivalized by the square root scale. The decomposition analysis allows us to answer the question of how much of total inequality is attributable to variability in the first subgroup, in the second, etc., and how much to between subgroups. To complement the results from the decomposition analysis, by the shift-share analysis we are able to simulate such a Finland which would have not aged at all since both 1991 and 2000 while other factors remain unchanged at the 2016 level. The results of the decomposition analysis led us to a clear conclusion that variations within groups are much more significant in the formation of total inequality than the variations between groups. In the light of the shift-share analysis, interestingly, the aged Finland is less unequal than the Finland, which would use the population shares of 1991 and 2000. Hence such a study of aging, which only examines changes in population shares ceteris paribus, shows that aging has slowed down the rise of inequality in Finland. This is because the age structure of the years 1991 and 2000 put the most weight on people in most unequal, or second most unequal age group in proportion to other age groups than the population distribution of the year 2016.