Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

New designs for research in delay discounting

Doyle, John R., Chen, C. H. and Savani, K. 2011. New designs for research in delay discounting. Judgment and Decision Making 6 (8) , pp. 759-770.

Full text not available from this repository.

Abstract

The two most influential models in delay discounting research have been the exponential (E) and hyperbolic (H) models. We develop a new methodology to design binary choice questions such that exponential and hyperbolic discount rates can be purposefully manipulated to make their rate parameters orthogonal (Pearson’s R = 0), negatively correlated (R = –1), positively correlated (R = +1), or to hold one rate constant while allowing the other to vary. Then we extend the method to similarly contrast different versions of the hyperboloid model. The arithmetic discounting model (A), which is based on differences between present and future rewards rather than their ratios, may easily be made orthogonal to any other pair of models. Our procedure makes it possible to design choice stimuli that precisely vary the relationship between different discount rates. However, the additional control over the correlation between different discount rate parameters may require the researcher to either restrict the range that those rate parameters can take, or to expand the range of times the participant must wait for future rewards.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: B Philosophy. Psychology. Religion > BC Logic
B Philosophy. Psychology. Religion > BF Psychology
H Social Sciences > H Social Sciences (General)
Uncontrolled Keywords: delay discounting, exponential discounting, hyperbolic discounting, arithmetic discounting, model separation, Excel Solver
Publisher: Society for Judgment and Decision Making
ISSN: 1930-2975
Related URLs:
Last Modified: 04 Jun 2017 04:22
URI: http://orca.cf.ac.uk/id/eprint/37746

Citation Data

Cited 8 times in Google Scholar. View in Google Scholar

Cited 4 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item