Income distribution and inequality in some major industrialized countries

This chapter analyzes four sets of income data: the US Panel Study of Income Dynamics (PSID), the British Household Panel Survey (BHPS), the German Socio-Economic Panel (GSOEP) and the Italian Survey on Household Income and Wealth (SHIW). It is firstly shown that a two-parameter lognormal distribution can give very accurate fits to the low-medium income range (98%–99% of the population), whereas the high income range (1%–2% of the population) is well fitted by a Pareto's (power-law) function. This combination of two qualitatively different distributions seems stable over the years covered by the datasets, although the indexes specifying them fluctuate over time. These fluctuations are quantified by establishing some links with the country specific business cycle phases, and show how the separation between the two regimes of the income distributions may be due to different income dynamics. In particular, it is found that for the top percentiles of the distributions returns on capital account for a significant share of the total income, so that their contribution to the latter may be responsible for the observed power-law behavior in the tail. Secondly, to assess the contribution of the individual factors and their relative importance to the overall inequality, we investigate income inequality using a decomposition analysis by income sources. The results suggest that capital income makes a significant contribution to overall inequality, confirming in this way its role in determining the Pareto's tail.