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

Amal Soliman, Philip Jones, John Cullis

Research output: Contribution to journalArticle

6 Citations (Scopus)
25 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)175-186
JournalJournal of Economic Psychology
Volume40
Early online date17 Jun 2013
DOIs
Publication statusPublished - Feb 2014

Fingerprint Dive into the research topics of 'Learning in experiments: dynamic interaction of policy variables designed to deter tax evasion'. Together they form a unique fingerprint.

  • Cite this