Efficient Minimum Distance Estimation of Pareto Exponent from Top Income Shares

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Tác giả: Alexis Akira Toda, Yulong Wang

Ngôn ngữ: eng

Ký hiệu phân loại: 339.2 Distribution of income and wealth

Thông tin xuất bản: 2019

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Bộ sưu tập: Metadata

ID: 162540

We propose an efficient estimation method for the income Pareto exponent when only certain top income shares are observable. Our estimator is based on the asymptotic theory of weighted sums of order statistics and the efficient minimum distance estimator. Simulations show that our estimator has excellent finite sample properties. We apply our estimation method to U.S. top income share data and find that the Pareto exponent has been stable at around 1.5 since 1985, suggesting that the rise in inequality during the last three decades is mainly driven by redistribution between the rich and poor, not among the rich.
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