We investigate the shape of the Italian personal income distribution using microdata from the Survey on Household Income and Wealth, made publicly available by the Bank of Italy for the years 1977-2002. We find that the upper tail of the distribution is consistent with a Pareto-power law type distribution, while the rest follows a twoparameter lognormal distribution. The results of our analysis show a shift of the distribution and a change of the indexes specifying it over time. As regards the first issue, we test the hypothesis that the evolution of both gross domestic product and personal income is governed by similar mechanisms, pointing to the existence of correlation between these quantities. The fluctuations of the shape of income distribution are instead quantified by establishing some links with the business cycle phases experienced by the Italian economy over the years covered by our dataset.

We analyze three sets of income data: the US Panel Study of Income Dynamics (PSID), the British Household Panel Survey (BHPS), and the German Socio-Economic Panel (GSOEP). It is shown that the empirical income distribution is consistent with a two-parameter lognormal function for the low-middle income group (97%-99% of the population), and with a Pareto or power law function for the high income group (1%-3% of the population). This mixture of two qualitatively different analytical distributions seems stable over the years covered by our data sets, although their parameters significantly change in time. It is also found that the probability density of income growth rates almost has the form of an exponential function.

Starting from the generalized exponential function exp Kaniadakis, Physica A 296, 405 (2001)], the survival function P > (x) = exp κ (−βx α ), where x ∈ R + , α, β > 0, and κ ∈ [0, 1), is considered in order to analyze the data on personal income distribution for Germany, Italy, and the United Kingdom.The above defined distribution is a continuous one-parameter deformation of the stretched exponential function P 0 > (x) = exp (−βx α )-to which reduces as κ approaches zero-behaving in very different way in the x → 0 and x → ∞ regions. Its bulk is very close to the stretched exponential one, whereas its tail decays following the power-law P > (x) ∼ (2βκ) −1/κ x −α/κ . This makes the κ-generalized function particularly suitable to describe simultaneously the income distribution among both the richest part and the vast majority of the population, generally fitting different curves. An excellent agreement is found between our theoretical model and the observational data on personal income over their entire range.