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In behavioral economics, time preference (or time discounting, [1] delay discounting, temporal discounting, [2] long-term orientation [3]) is the current relative valuation placed on receiving a good at an earlier date compared with receiving it at a later date. [1] Applications for these preferences include finance, health, climate change.
The term of present bias was coined in the second half of the 20th century. In the 1930s economic research started investigating time preferences. The findings led to the model of exponential discounting, thus time consistent discounting. However, later research led to the conclusion that time preferences were indeed not consistent, but ...
A study by Daniel Read introduces "subadditive discounting": the fact that discounting over a delay increases if the delay is divided into smaller intervals. This hypothesis may explain the main finding of many studies in support of hyperbolic discounting—the observation that impatience declines with time–while also accounting for ...
Intuitively, it seems odd that the welfare of an 80-year-old born in 1970 is intrinsically superior to the welfare of an 80-year-old born in 1980; in the context of social (rather than private) discount rates, when asked for their preferences over the welfare of others, most peoples' apparent "pure time preferences" becomes smaller or even ...
Discounting can also be related to the risk sensitivity of animals. Rather than relating risk to delay, risk sensitivity acts as a function of delay discounting. [54] In a study conducted by Haden and Platt, macaque monkeys were given the choice of a medium reward that they knew they would receive, versus a more risky choice.
Exponential discounting yields time-consistent preferences. Exponential discounting and, more generally, time-consistent preferences are often assumed in rational choice theory, since they imply that all of a decision-maker's selves will agree with the choices made by each self. Any decision that the individual makes for himself in advance will ...
Preference learning is a subfield of machine learning that focuses on modeling and predicting preferences based on observed preference information. [1] Preference learning typically involves supervised learning using datasets of pairwise preference comparisons, rankings, or other preference information.
In economics, a discount function is used in economic models to describe the weights placed on rewards received at different points in time. For example, if time is discrete and utility is time-separable, with the discount function f(t) having a negative first derivative and with c t (or c(t) in continuous time) defined as consumption at time t, total utility from an infinite stream of ...