ABSTRACT
This chapter discusses the discount rates and discounting are re-examined by considering discounting as a stochastic process. It provides a foundation for the quantitative formulation of dynamic models. Modeling a memory process therefore becomes essential if a “view” of the past and of the expected “view” of the future is desired at a given present time. The main difference between inference by statistical sampling and anticipating the future is that statistical populations change in time, so that although a statistical description of an environment is true for one instant of time, it may not be true for another. Stationarity, ergodicity and independent increments of time are properties which are sometimes necessary for the mathematical tractability of stochastic processes. The record of a moving particle or a random variable as it progresses in time is a time series. Decisions are made for short periods of time and are reviewed and changed often.
