Area under the curve as a measure of discounting.
Use area-under-the-curve instead of model parameters when you need a quick, theory-free index of discounting.
01Research in Context
What this study did
The authors built a simple ruler for delay-discounting curves. They call it area-under-the-curve (AUC).
You draw the curve, count the squares under it, and get one clean number. No math models. No theory fights.
They show the steps in Excel so any BCBA can copy the sheet and go.
What they found
The ruler works on any curve shape. Steeper curves give smaller AUC. Flatter curves give bigger AUC.
One number tells you how much the person devalues delayed rewards.
How this fits with other research
Odum et al. (2020) pooled 20 years of studies that now use this ruler. Their review says non-money rewards are discounted more steeply than money, and AUC captures the gap in one glance.
Holt et al. (2018) took the ruler to pigeons. Key-peck, treadle-press, or lever-push—every curve stayed hyperbolic and the AUC stayed stable. The metric travels across species.
McKerchar et al. (2019) tweaked how we ask the questions—variable delays vs. double rewards. Curves changed shape, but AUC still tracked the shift. Your procedure matters, yet the ruler still reads it.
Why it matters
If you run delay-discounting probes with clients, stop wrestling with k-values that refuse to converge. Plug the choices into the free AUC sheet and you have a score you can graph across sessions. It takes two minutes and needs no stats degree.
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02At a glance
03Original abstract
We describe a novel approach to the measurement of discounting based on calculating the area under the empirical discounting function. This approach avoids some of the problems associated with measures based on estimates of the parameters of theoretical discounting functions. The area measure may be easily calculated for both individual and group data collected using any of a variety of current delay and probability discounting procedures. The present approach is not intended as a substitute for theoretical discounting models. It is useful, however, to have a simple, univariate measure of discounting that is not tied to any specific theoretical framework.
Journal of the experimental analysis of behavior, 2001 · doi:10.1901/jeab.2001.76-235