Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/296752 
Year of Publication: 
2023
Citation: 
[Journal:] National Tax Journal [ISSN:] 1944-7477 [Volume:] 76 [Issue:] 2 [Publisher:] The University of Chicago Press [Place:] Chicago, IL [Year:] 2023 [Pages:] 267-289
Publisher: 
The University of Chicago Press, Chicago,IL
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.
Subjects: 
Income taxation
progressivity
nonlinear estimation
JEL: 
H20
C51
H31
Persistent Identifier of the first edition: 
Document Type: 
Article
Document Version: 
Published Version

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