EconPapers    
Economics at your fingertips  
 

Modeling Imprecision in Perception, Valuation, and Choice

Michael Woodford ()

Annual Review of Economics, 2020, vol. 12, issue 1, 579-601

Abstract: Traditional decision theory assumes that people respond to the exact features of the options available to them, but observed behavior seems much less precise. This review considers ways of introducing imprecision into models of economic decision making and stresses the usefulness of analogies with the way that imprecise perceptual judgments are modeled in psychophysics—the branch of experimental psychology concerned with the quantitative relationship between objective features of an observer's environment and elicited reports about their subjective appearance. It reviews key ideas from psychophysics, provides examples of the kinds of data that motivate them, and proposes lessons for economic modeling. Applications include stochastic choice, choice under risk, decoy effects in marketing, global game models of strategic interaction, and delayed adjustment of prices in response to monetary disturbances.

Date: 2020
References: Add references at CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://doi.org/10.1146/annurev-economics-102819-040518
Full text downloads are only available to subscribers. Visit the abstract page for more information.

Related works:
Working Paper: Modeling Imprecision in Perception, Valuation and Choice (2019) Downloads
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:anr:reveco:v:12:y:2020:p:579-601

Ordering information: This journal article can be ordered from
http://www.annualreviews.org/action/ecommerce

DOI: 10.1146/annurev-economics-102819-040518

Access Statistics for this article

More articles in Annual Review of Economics from Annual Reviews Annual Reviews 4139 El Camino Way Palo Alto, CA 94306, USA.
Bibliographic data for series maintained by http://www.annualreviews.org ().

 
Page updated 2021-06-15
Handle: RePEc:anr:reveco:v:12:y:2020:p:579-601