Information nudges and tax compliance: Evidence from a field experiment in China

Wenhui Yang, Jing Zhao and Hao Zhou

Journal of Economic Behavior & Organization, 2024, vol. 228, issue C

Abstract: Tax administrations worldwide employ various policy tools to enhance tax compliance, but the effectiveness of nudges remains uncertain. To address this gap, we conducted a field experiment in China to evaluate the causal effects of deterrence and non-deterrence nudges on individual income tax compliance. Our findings indicate that all reminder messages significantly increase tax compliance compared to a no-message control group. Furthermore, when compared to a basic information control group, deterrence nudges – such as those highlighting credit penalties and overdue fines – significantly boost tax compliance, while non-deterrence nudges, such as appeals to tax morality or public services, have an insignificant impact. Deterrence nudges also show heterogeneous effects on tax compliance, being primarily short-term with diminishing influence over time. They are particularly effective in motivating males and individuals in market sectors to comply, but fail to improve compliance among firm owners and the super-rich.

Keywords: Information nudges; Tax compliance; Field experiment (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167268124003937
Full text for ScienceDirect subscribers only

Related works:
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:jeborg:v:228:y:2024:i:c:s0167268124003937

DOI: 10.1016/j.jebo.2024.106779

Access Statistics for this article

Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.

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