A self-funding reward mechanism for tax compliance

Enrique Fatas (), Daniele Nosenzo, Martin Sefton and Daniel Zizzo

Journal of Economic Psychology, 2021, vol. 86, issue C

Abstract: We compare in a laboratory experiment two audit-based tax compliance mechanisms that collect fines from those found non-compliant. The mechanisms differ in the way fines are redistributed to individuals who were either not audited or audited and found to be compliant. The first, as is the case in most extant tax systems, does not discriminate between the un-audited and those found compliant. The second targets the redistribution in favor of those found compliant. We find that targeting increases compliance when paying taxes generates a social return. We do not find any increase in compliance in a control treatment where individuals audited and found compliant receive symbolic rewards. We conclude that existing tax mechanisms have room for improvement by rewarding those audited and found compliant.

Keywords: Tax evasion; Rewards; Audits (search for similar items in EconPapers)
JEL-codes: C91 C92 D91 H26 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167487021000544
Full text for ScienceDirect subscribers only

Related works:
Working Paper: A Self-Funding Reward Mechanism for Tax Compliance (2015)
Working Paper: A self-funding reward mechanism for tax compliance (2015)
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:eee:joepsy:v:86:y:2021:i:c:s0167487021000544

DOI: 10.1016/j.joep.2021.102421

Access Statistics for this article

Journal of Economic Psychology is currently edited by G. Antonides and D. Read

More articles in Journal of Economic Psychology from Elsevier
Bibliographic data for series maintained by Catherine Liu ().