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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.
Time discounting or temporal discounting is a wide range of ideas involving the connection between time and the extent to which an object, situation, or course of action is seen as valuable. The overall theory is that people put more value and worth into immediate events and outcomes, and apply less value to future outcomes or events.
Hyperbolic discounting is mathematically described as = + where g(D) is the discount factor that multiplies the value of the reward, D is the delay in the reward, and k is a parameter governing the degree of discounting (for example, the interest rate).
Hyperbolic discounting, where discounting is the tendency for people to have a stronger preference for more immediate payoffs relative to later payoffs. Hyperbolic discounting leads to choices that are inconsistent over time—people make choices today that their future selves would prefer not to have made, despite using the same reasoning. [52]
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 ...
It is calculated as the present discounted value of future utility, and for people with time preference for sooner rather than later gratification, it is less than the future utility. The utility of an event x occurring at future time t under utility function u, discounted back to the present (time 0) using discount factor β, is
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 ...
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.