Learning in experiments: Dynamic interaction of policy variables designed to deter tax evasion

Amal Soliman, Philip Jones and John Cullis

Journal of Economic Psychology, 2014, vol. 40, issue C, 175-186

Abstract: While neoclassical economic theory sheds insight into the way that audit rates and penalty rates interact when individuals decide to declare income for taxation, it predicts far lower levels of compliance than observed levels of compliance. This paper analyses experimental responses to explore a dynamic interaction between audit and penalty rates as individuals learn how to comply with taxation. It compares the responses of subjects in experiments with responses that are predicted when individuals rely on an adaptive learning process (that offers information feedback about decision payoffs). This comparison suggests that learning is an important consideration when explaining differences between predicted and observed levels of tax compliance.

Keywords: Tax evasion; Experiment; Adaptive learning; Simulation (search for similar items in EconPapers)
JEL-codes: C91 H26 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S016748701300069X
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:joepsy:v:40:y:2014:i:c:p:175-186

DOI: 10.1016/j.joep.2013.05.012

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 ().