Originally used by American economist Irving Fisher (1867-1947), adaptive expectations principle was popularized and given its current name during the 1950s in the study of hyper-inflation.

Adaptive expectations principle posits that future values may be calculated on the basis of previous values and their margin of error.

For example, next year’s inflation rate can be estimated by judging how inaccurate this year’s rate is compared with last year’s forecast.

Adaptive expectations principle, by its nature, underestimates or overestimates constantly changing variables. Also called the error learning hypothesis, it was finally abandoned as inadequate in the early 1970s because forecasters frequently take into account information other than the past behaviour of the variable under study.
Adaptive expectation models are ways of predicting an agent’s behaviour based on their past experiences and past expectations for that same event. They are first used by Irving Fisher in his book “The Purchasing Power of Money”, 1911, and further developed in the 1940s and 1950s, especially by Phillip Cagan in his article “The Monetary Dynamics of Hyper-Inflation”, 1956 and, most famously, by Milton Friedman in 1957, in his book “A Theory of the Consumption Function”.

Et xt+1 is our expectation (E) in year t for a variable x in the year t+1. It is based on our expectation from the year before (t-1) for variable x in our current year, and a weighted proportion of our past expectations. Remember that our expectations from last year were, in turn, based on those of the year before, so all our expectations from the first time we ever dared assume anything are contained within the equation.

λ will depend on how much we were off last year versus this year: if our predictions are proving to be volatile, we will be more likely to adjust them. It will also depend on how much groundbreaking new information we have received, rendering previous expectations useless. Basically, it depends on how much we feel we might have been off last year when we predicted things for next year.

The easiest way to know how adaptive expectations work, is to understand the expectations-augmented Phillips curve. Using also this same curve, it is also easy to understand how rational expectations work.

Also see: rational expectations theory, random walk hypothesis