“Optimal Honesty” in the Context of Fiscal Crimes
Lory Barile (),
John Cullis and
Philip Jones
Additional contact information
Lory Barile: Department of Economics, Faculty of Social Sciences, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK
John Cullis: Department of Economics, Faculty of Humanities and Social Sciences, University of Bath, Claverton Down, Bath BA2 7AY, UK
Philip Jones: Department of Economics, Faculty of Humanities and Social Sciences, University of Bath, Claverton Down, Bath BA2 7AY, UK
Economies, 2024, vol. 12, issue 9, 1-11
Abstract:
This paper begins by contrasting the caricatures ‘ homo and femina economicus ’ with ‘ homo and femina realitus ’. Against this backdrop, the paper considers three ‘apparently falsified’ empirical predictions of the standard expected utility model of individual decision-making concerning participation in fiscal crimes: that tax evasion and benefit fraud can be treated identically; fiscal crimes should be endemic; and that all individuals, depending on parameter values, should be either honest or dishonest. A utility function relating to decisions with a moral dimension is used to offer insight into the rationalization of the predictions and involves defining an individual’s ‘optimal honesty’ in the context of fiscal crimes. The policy implications of the approach are briefly explored.
Keywords: benefit fraud; tax evasion; optimal honesty; moral costs (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/2227-7099/12/9/242/pdf (application/pdf)
https://www.mdpi.com/2227-7099/12/9/242/ (text/html)
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:gam:jecomi:v:12:y:2024:i:9:p:242-:d:1475831
Access Statistics for this article
Economies is currently edited by Ms. Hongyan Zhang
More articles in Economies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().