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Related Experiment Video

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Two Different Real-Time Place Preference Paradigms Using Optogenetics within the Ventral Tegmental Area of the Mouse

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Published on: February 12, 2020

Variable time preference.

Lisheng He¹, Russell Golman², Sudeep Bhatia¹

¹University of Pennsylvania, United States.

Cognitive Psychology

|March 31, 2019

Summary

This summary is machine-generated.

This study introduces a variable exponential model for intertemporal choice, explaining decreasing impatience and improving predictions of individual choices over fixed models.

Keywords:

Computational modeling Decision making Intertemporal choice Preference variability Stochastic choice

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Area of Science:

Behavioral Economics
Decision Science
Psychology

Background:

Traditional exponential discounting models assume fixed time preferences.
Hyperbolic discounting is often used to explain decreasing impatience.
Existing models struggle to fully capture individual-level choice variability.

Purpose of the Study:

To evaluate the explanatory power of a variable exponential model for intertemporal choice.
To compare the variable exponential model against fixed exponential and hyperbolic discounting models.
To investigate the model's ability to predict choice patterns, including decreasing impatience and stochastic transitivity violations.

Main Methods:

Developed analytical results for a variable exponential discounting model.
Conducted three experiments to collect individual-level choice data.
Quantitatively fitted models to experimental data and compared predictive accuracy.

Main Results:

The variable exponential model significantly improves the fit of exponential discounting.
The variable exponential model outperforms hyperbolic discounting models in explaining choice probabilities.
Evidence supports the variable exponential model's prediction of stochastic transitivity violations in intertemporal dominance choices.

Conclusions:

Exponential discounting, when allowing for variable discount factors, can explain complex intertemporal choice behaviors.
The variable exponential model offers a more accurate account of individual decision-making than previously assumed.
Acknowledging sources of randomness is crucial for robust choice modeling.