The BCD of response time analysis in experimental economics

For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze r...

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Bibliographic Details
Published in:Experimental economics : a journal of the Economic Science Association 2018-06, Vol.21 (2), p.383-433
Main Authors: Spiliopoulos, Leonidas, Ortmann, Andreas
Format: Article
Language:English
Subjects:
Analysis
Behavioral/Experimental Economics
Decision making
Economic theory
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Economists
Experimental economics
Game Theory
Heuristic
Microeconomics
Operations Research/Decision Theory
Original Paper
Psychologists
Reaction time
Social and Behav. Sciences
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Summary:For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.
ISSN:1386-4157
1573-6938
DOI:10.1007/s10683-017-9528-1