The Slicing Method: Determining Insensitivity Regions of Probability Weighting Functions

Martín Egozcue (), Luis Fuentes García () and Ričardas Zitikis ()
Additional contact information
Martín Egozcue: University of Montevideo
Luis Fuentes García: Universidade da Coruña
Ričardas Zitikis: Western University

Computational Economics, 2023, vol. 61, issue 4, No 3, 1369-1402

Abstract: Abstract A popular rule of thumb, usually called “heuristic technique” in Behavioral Economics, for determining the likelihood insensitivity regions of probability weighting functions (pwf’s) is based on searching for points at which the pwf’s are twice their values at half the points. Although this technique works remarkably well for many commonly used pwf’s, it sometimes fails to provide the correct answer. In order to cover the class of pwf’s for which the heuristic technique does not work, in this paper we propose, discuss, and illustrate an extension of the technique into what we call the “slicing method,” which is capable of finding the subadditivity and insensitivity regions of any continuous pwf.

Keywords: Behavioural economics; Probability weighting function; Subadditivity; Likelihood insensitivity; Probabilistic insensitivity (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s10614-022-10252-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:kap:compec:v:61:y:2023:i:4:d:10.1007_s10614-022-10252-8

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-022-10252-8

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().