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Updated: May 12, 2025

Measuring Delay Discounting in Humans Using an Adjusting Amount Task
Published on: January 9, 2016
Delay preference in intertemporal choice: Sooner or later OR faster or slower?
Marc Scholten1, Adam Sanborn2, Lisheng He3
1Faculdade de Design, Tecnologia e Comunicação, Universidade Europeia, Portugal; Unidade de Investigação em Design e Comunicação, Universidade Europeia, Portugal; Centro de Estudos em Gestão do Instituto Superior Técnico, Instituto Superior Técnico, Universidade de Lisboa, Portugal.
This study introduces a new perspective on intertemporal choices, moving beyond sooner-or-later decisions to a faster-or-slower framework. The faster-or-slower model better predicts how people make decisions involving monetary losses.
Area of Science:
- Behavioral economics
- Decision science
- Psychology
Background:
- Intertemporal choices traditionally focus on sooner vs. later outcomes.
- Most research uses single-dated outcomes, limiting understanding of decision processes.
- An alternative framing considers the speed of outcome accumulation.
Purpose of the Study:
- To empirically distinguish between sooner-or-later and faster-or-slower models of intertemporal choice.
- To assess model generalizability using choices with single and multiple dated outcomes (payment sequences).
- To evaluate parameter generalizability by linking preferences for multiple payments to single payment preferences.
Main Methods:
- An experiment involving choices between single-dated outcomes and outcome sequences (monetary losses).
- Development of convergent and discriminant validity criteria for model assessment.
- Fully Bayesian analysis to compare model performance.
Main Results:
- The faster-or-slower model demonstrated superior predictive power over the sooner-or-later model.
- The faster-or-slower model showed better generalizability across different choice structures.
- Bayesian analysis strongly favored the faster-or-slower model.
Conclusions:
- The faster-or-slower model provides a more accurate account of intertemporal decision-making, particularly for losses.
- Experimental designs incorporating outcome sequences are crucial for distinguishing between decision models.
- Individual differences in loss timing preferences can be effectively modeled.
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