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- W2183387789 abstract "The Lorenz curve relates the cumulative proportion of income to the cumulative proportion of population. When a particular functional form of the Lorenz curve is specified it is typically estimated by linear or nonlinear least squares assuming that the error terms are independently and normally distributed. Observations on cumulative proportions are clearly neither independent nor normally distributed. This paper proposes and applies a new methodology which recognizes the cumulative proportional nature of the Lorenz curve data by assuming that the proportion of income is distributed as a Dirichlet distribution. Five Lorenz-curve specifications were used to demonstrate the technique. Once a likelihood function and the posterior probability density function for each specification are derived we can use maximum likelihood or Bayesian estimation to estimate the parameters. Maximum likelihood estimates and Bayesian posterior probability density functions for the Gini coefficient are also obtained for each Lorenz-curve specification." @default.
- W2183387789 created "2016-06-24" @default.
- W2183387789 creator A5033137110 @default.
- W2183387789 creator A5082218804 @default.
- W2183387789 date "1999-01-01" @default.
- W2183387789 modified "2023-09-26" @default.
- W2183387789 title "Working Papers in Econometrics and Applied Statistics" @default.
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