Pareto extrapolation: An analytical framework for studying tail inequality

Émilien Gouin‐Bonenfant and Alexis Akira Toda

Quantitative Economics, 2023, vol. 14, issue 1, 201-233

Abstract: We develop an analytical framework designed to solve and analyze heterogeneous‐agent models that endogenously generate fat‐tailed wealth distributions. We exploit the asymptotic linearity of policy functions and the analytical characterization of the Pareto exponent to augment the conventional solution algorithm with a theory of the tail. Our framework allows for a precise understanding of the very top of the wealth distribution (e.g., analytical expressions for top wealth shares, type distribution in the tail, and transition probabilities in and out of the tail) in addition to delivering improved accuracy and speed.

Date: 2023
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https://doi.org/10.3982/QE1817

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Persistent link: https://EconPapers.repec.org/RePEc:wly:quante:v:14:y:2023:i:1:p:201-233

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