In parts 2 and 3, one of the issues with interpreting the plots was that there was too much data. In this post, I have simplified the data by combining some of the family income baskets together. Deciding which baskets to combine is a subjective exercise which is why I started the analysis with the full dataset.
With the new datasets, I re-ran the same R code shown in part 2.
Using simplified datasets, we obtain plots that are easier to interpret.
Positive Analysis: Figures 1b and 2b show that the proportion of people in the highest income bracket has grown over time. Figure 3b shows that the distribution of of market income for unattached individuals has remained fairly stable over the time series. Therefore the increase in the proportion of population in the highest income bracket is mostly represented by families of 2 of more individuals. Figures 1b and 2b show that for families, the proportion of the population in the 50k-99,999 range has gradually decreased over time.
Normative Analysis: Although the graphs do show some growth in the highest income bracket and some decline in the middle income brackets, the change has been both small and slow. There are no trends in these graphs that I find alarming. The situation that I would find concerning would be a large decrease in middle income with a large increase in lower income and a slight increase in higher income. However, this does not appear to be the case.
The question that I ask myself is why has so little changed? Especially with respect to unattached individuals, the distribution of income has varied very little over time. One would think that with all the advances in education, healthcare, social programs, and technology, that the unattached individuals of 2011 would be much more productive than in 1976. Shouldn’t that increase in productivity have resulted in higher wages in the labour market?