arbiter
JournalsAccount

Optimal tax information with privacy concerns

Joel Slemrod & Damián Vergara

International Tax and Public Finance2026https://doi.org/10.1007/s10797-026-09962-8article
AJG 2ABDC A
Weight
0.50

Abstract

Having more information about taxpayers facilitates tax enforcement, but generates utility losses due to privacy concerns. We posit that individuals put negative value on two distinct aspects of privacy: revealing their level of affluence, and revealing details of their income conditional on affluence. We characterize the enforcement-privacy tradeoff for optimal income tax policy by introducing the granularity of the tax base as a key policy variable. The first-order conditions reveal the sufficient statistics needed to describe the optimal tax rate structure and the extent of granularity. We discuss how future theoretical and empirical research could improve the characterization of optimal information.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1007/s10797-026-09962-8

Or copy a formatted citation

@article{joel2026,
  title        = {{Optimal tax information with privacy concerns}},
  author       = {Joel Slemrod & Damián Vergara},
  journal      = {International Tax and Public Finance},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1007/s10797-026-09962-8},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Optimal tax information with privacy concerns

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.