Análise da composição do faturamento nos setores da indústria química brasileira com a distribuição de Gompertz-Pareto

O trabalho foi inspirado em estudos anteriores a respeito da distribuição de renda, como o de Moura Jr e Ribeiro (2009), que buscavam uma caracterização matemática para essa distribuição. A partir destes, pensou-se na possibilidade da distribuição de faturamento dos setores da indústria no Brasil seguir o modelo de distribuição de Gompertz-Pareto desenvolvido por Chami Figueira, Moura Jr e Ribeiro (2011). O objetivo deste trabalho, portanto, é realizar um estudo sobre o comportamento da distribuição de faturamento de alguns setores da economia, divididos em Indústria, Indústria Química, Indústria Química Inorgânica e Indústria Química Orgânica. Através da modelagem dessas distribuições utilizando o modelo de distribuição Gompertz-Pareto, foram encontrados os três parâmetros positivos que a descrevem e também determinado o valor de corte entre as duas regiões. Este valor foi de aproximadamente R$450 bilhões. Assim, foi possível compreender melhor o comportamento dos setores da região de maior faturamento, Paretiana, de duas subdivisões, a Indústria Química Inorgânica e a Indústria Química Orgânica. Através desta análise, concluiu-se que para a Indústria Inorgânica, os setores de maior faturamento apresentam como principal característica a aplicação na indústria de fertilizantes e estão localizadas próximas ao mercado consumidor. Já para a Indústria Orgânica, a localização próxima a matéria-prima, nos quatro pólos petroquímicos brasileiros, Bahia, São Paulo, Rio Grande do Sul e Rio de Janeiro caracteriza os setores provenientes da Indústria petroquímica. Além disso, com os dados disponibilizados pelo anuário da ABIQUIM e pela pesquisa do IBGE, PIAproduto, foi possível analisar os setores quanto a sua capacidade instalada, produção, importação, preços e percentual de vendas comparando os resultados para as duas principais subdivisões da Indústria Química, Inorgânica e Orgânica

Income distribution patterns from a complete social security database

We analyze the income distribution of employees for 9 consecutive years (2001-2009) using a complete social security database for an economically important district of Romania. The database contains detailed information on more than half million taxpayers, including their monthly salaries from all employers where they worked. Besides studying the characteristic distribution functions in the high and low/medium income limits, the database allows us a detailed dynamical study by following the time-evolution of the taxpayers income. To our knowledge, this is the first extensive study of this kind (a previous japanese taxpayers survey was limited to two years). In the high income limit we prove once again the validity of Pareto's law, obtaining a perfect scaling on four orders of magnitude in the rank for all the studied years. The obtained Pareto exponents are quite stable with values around $\alpha \approx 2.5$, in spite of the fact that during this period the economy developed rapidly and also a financial-economic crisis hit Romania in 2007-2008. For the low and medium income category we confirmed the exponential-type income distribution. Following the income of employees in time, we have found that the top limit of the income distribution is a highly dynamical region with strong fluctuations in the rank. In this region, the observed dynamics is consistent with a multiplicative random growth hypothesis. Contrarily with previous results obtained for the japanese employees, we find that the logarithmic growth-rate is not independent of the income.Comment: 10 pages, 7 Figure

From microscopic taxation and redistribution models to macroscopic income distributions

We present here a general framework, expressed by a system of nonlinear differential equations, suitable for the modelling of taxation and redistribution in a closed (trading market) society. This framework allows to describe the evolution of the income distribution over the population and to explain the emergence of collective features based on the knowledge of the individual interactions. By making different choices of the framework parameters, we construct different models, whose long-time behavior is then investigated. Asymptotic stationary distributions are found, which enjoy similar properties as those observed in empirical distributions. In particular, they exhibit power law tails of Pareto type and their Lorenz curves and Gini indices are consistent with some real world ones.Comment: 12 pages, 4 figures. Version submitted to Physica A on Feb 15, 201

The Gompertz-Pareto Income Distribution

This work analyzes the Gompertz-Pareto distribution (GPD) of personal income, formed by the combination of the Gompertz curve, representing the overwhelming majority of the economically less favorable part of the population of a country, and the Pareto power law, which describes its tiny richest part. Equations for the Lorenz curve, Gini coefficient and the percentage share of the Gompertzian part relative to the total income are all written in this distribution. We show that only three parameters, determined by linear data fitting, are required for its complete characterization. Consistency checks are carried out using income data of Brazil from 1981 to 2007 and they lead to the conclusion that the GPD is consistent and provides a coherent and simple analytical tool to describe personal income distribution data.Comment: 13 pages, 5 figures, LaTeX. Accepted for publication in "Physica A

The Gompertz-Pareto Income Distribution

This work analyzes the Gompertz-Pareto distribution (GPD) of personal income, formed by the combination of the Gompertz curve, representing the overwhelming majority of the economically less favorable part of the population of a country, and the Pareto power law, which describes its tiny richest part. Equations for the Lorenz curve, Gini coefficient and the percentage share of the Gompertzian part relative to the total income are all written in this distribution. We show that only three parameters, determined by linear data fitting, are required for its complete characterization. Consistency checks are carried out using income data of Brazil from 1981 to 2007 and they lead to the conclusion that the GPD is consistent and provides a coherent and simple analytical tool to describe personal income distribution data.

No effects without causes: the Iron Dysregulation and Dormant Microbes hypothesis for chronic, inflammatory diseases

Since the successful conquest of many acute, communicable (infectious) diseases through the use of vaccines and antibiotics, the currently most prevalent diseases are chronic and progressive in nature, and are all accompanied by inflammation. These diseases include neurodegenerative (e.g. Alzheimer's, Parkinson's), vascular (e.g. atherosclerosis, pre-eclampsia, type 2 diabetes) and autoimmune (e.g. rheumatoid arthritis and multiple sclerosis) diseases that may appear to have little in common. In fact they all share significant features, in particular chronic inflammation and its attendant inflammatory cytokines. Such effects do not happen without underlying and initially 'external' causes, and it is of interest to seek these causes. Taking a systems approach, we argue that these causes include (i) stress-induced iron dysregulation, and (ii) its ability to awaken dormant, non-replicating microbes with which the host has become infected. Other external causes may be dietary. Such microbes are capable of shedding small, but functionally significant amounts of highly inflammagenic molecules such as lipopolysaccharide and lipoteichoic acid. Sequelae include significant coagulopathies, not least the recently discovered amyloidogenic clotting of blood, leading to cell death and the release of further inflammagens. The extensive evidence discussed here implies, as was found with ulcers, that almost all chronic, infectious diseases do in fact harbour a microbial component. What differs is simply the microbes and the anatomical location from and at which they exert damage. This analysis offers novel avenues for diagnosis and treatment