Power law tails in the Italian personal income distribution

Abstract

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.

The IncomeGini of Fairness

“…[27][28][29][30] Here in Eq. (2), is the minimal wages and þ is the average wages, where the°u ctuations around the average, , equal .…”

“…Various dynamics were proposed for the combined case that are based on stochastic dynamics. [27][28][29][30] Here, we develop a dynamic equation to the density fðcÞ, where similar to the work about fairness in nations, 1 two camps or circles of society are de¯ned, where these are termed, \society" and \deciders" (SC for society and the DC for deciders) and these interact through the same temperature (general interactions) yet here also directly. The deciders are the top 10% (or the top 5%, also with inner camps in the top \1%" and the top \0.1%") and the rest is the society.…”

“…The income distribution \tells all the stories" of the society [26][27][28] : \who is rich?? ", \who is poor??…”

“…1 For example the Gini 9,26-28 of that distribution tells about the distortion in the income distribution, therefore, suggests to research on whether the opportunities are based on abilities and e®orts rather than on \crony economics" and other biases (e.g., corruption). Gini is a number, 0 Gini 1, where the Gini formula is [26][27][28][29][30][31][32][33][34][35][36] Gini ¼ 1 hci…”

“…The value Gini ¼ 1 is for a society, where only a few are very rich and the rest are poor; Gini ¼ 0 is for \all are the same" society, where we expect that fairness in a society can create the reality, where those with capabilities that take more e®orts can progress and bene¯t more than others. Such society's dynamics create the exponential income density function, [27][28][29][30] where the Gini upper bound is 0.5. Clearly, those that \have money" can make more money, nonetheless, they also face competition that is based on their situation.…”