2006
DOI: 10.1016/j.physa.2006.04.023
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A study of the personal income distribution in Australia

Abstract: We analyze the data on personal income distribution from the Australian Bureau of Statistics. We compare fits of the data to the exponential, log-normal, and gamma distributions. The exponential function gives a good (albeit not perfect) description of 98% of the population in the lower part of the distribution. The log-normal and gamma functions do not improve the fit significantly, despite having more parameters, and mimic the exponential function. We find that the probability density at zero income is not z… Show more

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Cited by 86 publications
(69 citation statements)
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“…(19), with the empirical data for the whole income range. However, the analytical form of this theoretical complementary cumulative distribution function is unknown in the closed explicit form.…”
Section: Resultsmentioning
confidence: 99%
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“…(19), with the empirical data for the whole income range. However, the analytical form of this theoretical complementary cumulative distribution function is unknown in the closed explicit form.…”
Section: Resultsmentioning
confidence: 99%
“…Apparently, the number of free (effective) parameters driving the two-branch distribution function, Eq. (19), is reduced because this function depends only on the ratio of the initial parameters defining the Langevin dynamics (1).…”
Section: Our Extensionmentioning
confidence: 99%
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“…In addition, the PDFs analyzed seem to be quite complicated when compared to the Fréchet distribution equation. Therefore, in the present work the authors have followed the suggestion by Banerjee et al (2006), who stated 'that a useful description of the data is the one that has the minimal number of parameters, yet reasonably (but not necessarily perfectly) agrees with the data'.…”
Section: Introductionmentioning
confidence: 85%
“…Because the cumulative income distribution is normalized to one, the function must be zero at μ n , in order to fulfil Eq. (14). Hence, we can approximate the function close to μ n by a Taylor expansion.…”
mentioning
confidence: 99%