Simulação computacional e abordagem numérica para um modelo heterogêneo e adaptativo de distribuição de renda

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: SANTOS, Alan de Andrade lattes
Orientador(a): FIGUEIRÊDO, Pedro Hugo de
Banca de defesa: FERREIRA, Tiago Alessandro Espínola, OLIVEIRA, Viviane Moraes de
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal Rural de Pernambuco
Programa de Pós-Graduação: Programa de Pós-Graduação em Física Aplicada
Departamento: Departamento de Física
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/6096
Resumo: A key feature of income distribution P(m) study is characterize the inequalities implied by microeconomic models based on the mechanisms of exchange of goods and services. One way to quantify such inequalities is based on the Gini index 0 6 G 6 1, a parameter that sets the maximum (G = 1) and minimum (G = 0) concentration of resources. Current studies indicates that income distribution P(m) has two distinct regimes separated by a scale mc. The rst one associated to a low-regime income (m 6 mc) described by a gamma distribution and a second one related to a high-income regime (m > mc), mathematically represented by a power law function with a parameter 1 6 6 3, usually called Pareto's exponent. In this work we introduce an adaptive heterogeneous model in order to describe quantitatively the relationship among the average expenditure rate of economic agents, and the Gini index associated to the income distribution. In this approach a fraction p0 of all economic agents N do not modify their expenditure rates, a fraction p1 are able to modify their consumption rate positively correlated with their income and lastly a fraction p2 negatively. With the view to obtain boundaries values for income distribution parameters we conduct a numeric calculation using an entropy maximization approach. After that we investigate the impact of taxation on inequality income distribution through a redistribution rate p. We conclude that the model where adaptive agents coexist with di erent characteristics for the expenditure rate provides results closer to real data producing Gini indexes and expenditure rates, emerging features of the dynamics. At the instantaneous adaptive scenario the maximum Gini index [Gmax] is inversely proportional to taxation rate p. Moreover we can establish at the space parameters (G,), a limited region that corresponds to that observed in real data, taken from the World Bank to 139 countries.