Response times in economics: Looking through the lens of sequential sampling models

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. Application of the DDM 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.