Adaptive expectations
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Adaptive Expectations
Also known as the error learning hypothesis, the term refers to expectations about the future based on past information and experience. In economics, it has a more precise meaning in the prediction of the value of variables based on past values. According to the standard method, a variable's future value will be an average of all previous values, which are themselves weighted to emphasize the greater importance of the recent past. Work on inflation and macroeconomics in the 1960s drew heavily on this hypothesis. Among the advantages of the adaptive expectations rule was that it had the appearance of being an application of classical statistical inference; also, it was empirically easy to implement and achieved a high degree of explanatory power. The model was eventually abandoned, however, in the 1970s in favor of the rational expectations hypothesis, which proved more satisfactory on logical grounds. Adaptive expectations implied that it was possible to systematically fool economic agents over time—a position the rational expectations hypothesis denies.
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Adaptive expectations
In economics, adaptive expectations means that people form their expectations about what will happen in the future based on what has happened in the past. For example, if inflation has been higher than expected in the past, people would revise expectations for the future.
One simple version of adaptive expectations is stated in the following equation, where 
is the next year's rate of inflation that is currently expected; 
is this year's rate of inflation that was expected last year; and 
is this year's actual rate of inflation:
where 
is between 0 and 1. This says that current expectations of future inflation reflect past expectations and an "error-adjustment" term, in which current expectations are raised (or lowered) according to the gap between actual inflation and previous expectations. This error-adjustment is also called "partial adjustment."
The theory of adaptive expectations can be applied to all previous periods so that current inflationary expectations equal:
where 
equals actual inflation 
years in the past. Thus, current expected inflation reflects a weighted average of all past inflation, where the weights get smaller and smaller as we move further in the past.
Once a forecasting error is made by agents, due to a stochastic shock, they will be unable to correctly forecast the price level again even if the price level experiences no further shocks since they only ever incorporate part of their errors. The backward nature of expectation formulation and the resultant systematic errors made by agents (see Cobweb model) was unsatisfactory to economists such as John Muth, who was pivotal in the development of an alternative model of how expectations are formed, called rational expectations. This has largely replaced adaptive expectations in macroeconomic theory since its assumption of optimality of expectations is consistent with economic theory.
References
- George W. Evans and Seppo Honkapohja (2001), Learning and Expectations in Macroeconomics. Princeton University Press, ISBN 978-0-691-04921-2.
See also
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