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The Parametric Approach to Income and Wealth Distributional Analysis

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Part of the book series: New Economic Windows ((NEW))

Abstract

This chapter provides a brief overview of the main advantages associated with using parametric models of income/wealth distribution. It also instructs the reader about the numerous statistical models of income/wealth distribution that have been proposed in both the statistical and economic literature for over 100 years since Pareto’s breakthrough contribution.

Essentially, all models are wrong, but some are useful.

George Edward Pelham Box

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Notes

  1. 1.

    In standard kernel method the bandwidth remains constant at all points where the distribution is estimated. This constraint can be particularly onerous when the concentration of data is markedly heterogeneous in the sample. Hence, there would be advantages from using a narrower bandwidth in the dense part (the middle) of the distribution and wider ones in the more sparse tails—as in “adaptive” kernel estimation (Van Kerm 2003)—especially in the cases of heavy-tailed income and wealth distributions. Greater modeling flexibility can also be achieved by means of finite mixture densities, defined as convex combinations of two or more parametric densities. The separate analysis of the components of the mixtures and of the relative importance of these components over time are the main advantages over a non-parametric approach, as they allow capturing the effect of unobserved heterogeneity (Cowell and Flachaire 2015).

  2. 2.

    There exists a huge amount of literature on parametric models for the size distributions of income and wealth. Here we limit ourselves to consider the most frequently cited contributions in the area. For the interested reader, a comprehensive survey can be found in Kleiber and Kotz (2003).

  3. 3.

    In his pioneering contributions at the end of the nineteenth century, Pareto (1896, 1897a, b) suggested two variants of his distribution, occasionally called the three-parameter Pareto distributions. These further Pareto distributions, however, have not been used much in empirical economic studies.

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Correspondence to Fabio Clementi .

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Clementi, F., Gallegati, M. (2016). The Parametric Approach to Income and Wealth Distributional Analysis. In: The Distribution of Income and Wealth. New Economic Windows. Springer, Cham. https://doi.org/10.1007/978-3-319-27410-2_2

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