Response Times in Economics: Looking Through the Lens of Sequential Sampling Models

52 Pages Posted: 17 Jun 2016 Last revised: 22 Nov 2016

See all articles by John A. Clithero

John A. Clithero

Lundquist College of Business, University of Oregon

Date Written: November 20, 2016

Abstract

Economics is increasingly using process data to make novel inferences about preferences and predictions of choices. The measurement of response time (RT), the amount of time it takes to make a decision, offers a cost-effective and direct way to study the choice process. Yet, relatively little theory exists to guide the integration of RT into economic analysis. This article presents a canonical process model from psychology and neuroscience, the Drift-Diffusion Model (DDM), and shows that many RT phenomena in the economics literature are consistent with the predictions of the DDM. Additionally, use of the class of sequential sampling models facilitates a more principled consideration of findings from cognitive science and neuroeconomics. An application of the DDM to a binary choice dataset demonstrates the rich inference made possible when using models that can jointly model choice and process, highlighting the need for more work in this area.

Keywords: drift-diffusion model, experiments, process, response times

JEL Classification: C9, D03, D87

Suggested Citation

Clithero, John A., Response Times in Economics: Looking Through the Lens of Sequential Sampling Models (November 20, 2016). Available at SSRN: https://ssrn.com/abstract=2795871 or http://dx.doi.org/10.2139/ssrn.2795871

John A. Clithero (Contact Author)

Lundquist College of Business, University of Oregon ( email )

Lundquist College of Business
1208 University of Oregon
Eugene, OR 97403
United States

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