Fixed-k Tail Regression: New Evidence on Tax and Wealth Inequality from Forbes 400

Ji Hyung Lee, Yuya Sasaki, Alexis Akira Toda and Yulong Wang

Papers from arXiv.org

Abstract: We develop a novel fixed-k tail regression method that accommodates the unique feature in the Forbes 400 data that observations are truncated from below at the 400th largest order statistic. Applying this method, we find that higher maximum marginal income tax rates induce higher wealth Pareto exponents. Setting the maximum tax rate to 30-40% (as in U.S. currently) leads to a Pareto exponent of 1.5-1.8, while counterfactually setting it to 80% (as suggested by Piketty, 2014) would lead to a Pareto exponent of 2.6. We present a simple economic model that explains these findings and discuss the welfare implications of taxation.

Date: 2021-05, Revised 2022-09
New Economics Papers: this item is included in nep-pbe and nep-pub
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