Estimating the dynamic role of attention via random utility

Stephanie M. Smith, Ian Krajbich () and Ryan Webb
Additional contact information
Stephanie M. Smith: The Ohio State University
Ian Krajbich: The Ohio State University

Journal of the Economic Science Association, 2019, vol. 5, issue 1, No 9, 97-111

Abstract: Abstract When making decisions, people tend to look back and forth between the alternatives until they eventually make a choice. Eye-tracking research has established that these shifts in attention are strongly linked to choice outcomes. A predominant framework for understanding the dynamics of the choice process, and thus the effects of attention, is sequential sampling of information. However, existing methods for estimating the attention parameters in these models are computationally costly and overly flexible, and yield estimates with unknown precision and bias. Here we propose an estimation method that relies on a link between sequential sampling models and random utility models (RUM). This method uses familiar econometric tools (i.e., logistic regression) and yields estimates that appear to be unbiased and relatively precise compared to existing methods, in a small fraction of the computation time. The RUM thus appears to be a useful tool for estimating the effects of attention on choice.

Keywords: Eye tracking; Sequential sampling; Diffusion model; Random utility; aDDM; Attention (search for similar items in EconPapers)
JEL-codes: C81 C91 D87 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s40881-019-00062-4 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:spr:jesaex:v:5:y:2019:i:1:d:10.1007_s40881-019-00062-4

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/40881

DOI: 10.1007/s40881-019-00062-4

Access Statistics for this article

Journal of the Economic Science Association is currently edited by Nikos Nikiforakis and Robert Slonim

More articles in Journal of the Economic Science Association from Springer, Economic Science Association Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().