Bias in Tax Progressivity Estimates

Johannes König

EconStor Open Access Articles and Book Chapters, 2023, vol. 76, issue 2, 267-289

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.

Keywords: Income taxation; progressivity; nonlinear estimation (search for similar items in EconPapers)
JEL-codes: C51 H20 H31 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:espost:296752

DOI: 10.1086/724186

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