On the Functional Form of Temporal Discounting: An Optimized Adaptive Test

Area of Science:

• Behavioral Sciences
• Decision Science
• Cognitive Psychology

Background:

• Temporal discounting, the tendency to devalue future rewards, is extensively studied.
• Hyperbolic discounting is a dominant model, but consensus on the best model is lacking.
• Existing models struggle to capture the full spectrum of discounting behavior.

Purpose of the Study:

• To introduce an Adaptive Design Optimization (ADO) method for fitting and comparing temporal discounting models.
• To empirically discriminate among six popular temporal discounting models using ADO.

Main Methods:

• Developed and applied an Adaptive Design Optimization (ADO) framework.
• Conducted an ADO experiment to test multiple temporal discounting models.
• Analyzed subject behavior to identify model-specific limitations.

Main Results:

• No single tested model adequately described all observed discounting behaviors across subjects.
• The ADO method provided precise results, pinpointing specific model deficiencies.
• Results indicate a need for models accommodating dynamic changes in impatience (increasing and decreasing).

Conclusions:

• Current popular models of temporal discounting are insufficient to explain the breadth of human behavior.
• ADO is a powerful tool for model comparison and identifying necessary features for future models.
• Future models must incorporate flexibility, such as accounting for both increasing and decreasing impatience.