Optimal Tax Administration
Michael Keen and
Joel Slemrod
No 2017/008, IMF Working Papers from International Monetary Fund
Abstract:
This paper sets out a framework for analyzing optimal interventions by a tax administration, one that parallels and can be closely integrated with established frameworks for thinking about optimal tax policy. Its key contribution is the development of a summary measure of the impact of administrative interventions—the “enforcement elasticity of tax revenue”—that is a sufficient statistic for the behavioral response to such interventions, much as the elasticity of taxable income serves as a sufficient statistic for the response to tax rates. Amongst the applications are characterizations of the optimal balance between policy and administrative measures, and of the optimal compliance gap.
Keywords: WP; tax rate; taxable income; Tax administration; tax compliance; optimal taxation; enforcement elasticity; administration cost; cost-revenue ratio; marginal revenue-cost ratio; elasticity rule; implementation cost; IRS initiative; Personal income; Tax administration core functions; Tax gap; Compliance costs (search for similar items in EconPapers)
Pages: 27
Date: 2017-01-20
References: Add references at CitEc
Citations: View citations in EconPapers (70)
Downloads: (external link)
http://www.imf.org/external/pubs/cat/longres.aspx?sk=44555 (application/pdf)
Related works:
Journal Article: Optimal tax administration (2017)
Working Paper: Optimal Tax Administration (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:imf:imfwpa:2017/008
Ordering information: This working paper can be ordered from
http://www.imf.org/external/pubs/pubs/ord_info.htm
Access Statistics for this paper
More papers in IMF Working Papers from International Monetary Fund International Monetary Fund, Washington, DC USA. Contact information at EDIRC.
Bibliographic data for series maintained by Akshay Modi ().