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Journal of Public Economics
Article . 2025 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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SSRN Electronic Journal
Article . 2025 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2025
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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An Inverse-Ramsey Tax Rule

Authors: Micheletto, Luca; Moore, Dylan T.; Reck, Daniel; Slemrod, Joel;

An Inverse-Ramsey Tax Rule

Abstract

Traditional optimal commodity tax analysis, dating back to Ramsey (1927), prescribes that to maximize welfare one should impose higher taxes on goods with lower demand elasticities. Yet policy makers do not stress minimizing efficiency costs as a desideratum. In this note we revisit the commodity tax problem, and show that the attractiveness of the Ramsey inverse-elasticity prescription can itself be inverted if the tax system is chosen -- or at least strongly influenced -- by taxpayers who are overly confident of their ability, relative to others, to substitute away from taxed goods.

20 pages, 4 figures

Country
Italy
Keywords

FOS: Economics and business, General Economics (econ.GN), Economics, commodity taxation; overconfidence; behavioral anomalies, General Economics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
hybrid