Bias in Tax Progressivity Estimates

IF 1.8 3区经济学 Q2 BUSINESS, FINANCE

National Tax Journal Pub Date : 2023-05-19 DOI:10.1086/724186

Johannes König

引用次数: 1

Abstract

Tax progressivity is central in public and political debates when questions of vertical equity are raised. Applied, structural research demands a simple way to capture it. A power function approximation delivers one parameter that captures the residual income elasticity — a summary measure of progressivity. This approximation is accurate, tractable, and interpretable, and hence immensely popular. The most common procedure to estimate this parameter, a log ordinary least squares specification, produces biased and inconsistent estimates. A nonlinear estimator solves this issue and, using different data sets, I find differences in estimates between 6 and 14 percent.

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税收累进性估计的偏差

当纵向公平问题被提出时，税收累进性是公共和政治辩论的核心。应用和结构研究需要一种简单的方法来捕获它。幂函数近似值提供了一个参数来捕捉剩余收入弹性——累进性的汇总度量。这种近似是准确的、易于处理的和可解释的，因此非常受欢迎。估计该参数的最常用程序是对数普通最小二乘规范，它会产生有偏差和不一致的估计。非线性估计器解决了这个问题，使用不同的数据集，我发现估计的差异在6%到14%之间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

National Tax Journal Multiple-

CiteScore

3.40

自引率

11.80%

发文量

期刊介绍： The goal of the National Tax Journal (NTJ) is to encourage and disseminate high quality original research on governmental tax and expenditure policies. Articles published in the regular March, June and September issues of the journal, as well as articles accepted for publication in special issues of the journal, are subject to professional peer review and include economic, theoretical, and empirical analyses of tax and expenditure issues with an emphasis on policy implications. The NTJ has been published quarterly since 1948 under the auspices of the National Tax Association (NTA). Most issues include an NTJ Forum, which consists of invited papers by leading scholars that examine in depth a single current tax or expenditure policy issue. The December issue is devoted to publishing papers presented at the NTA’s annual Spring Symposium; the articles in the December issue generally are not subject to peer review.