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Adaptive Expectations Hypothesis Definition
Adaptive Expectations hypothesis theory states that people adjust their expectations on what the future will be based on experience and events of the recent past. This hypothesis is important in decision making and a common example is when predicting inflation.
People willing to make an investment may use this theory to predict the stock price or inflation rates and adjust their expectations based on that. For instance, if the inflation rate has been high in the past, individual would adjust their expectations to a higher inflation rate in future.
A Little More on What is Adaptive Expectations Hypothesis
Predicting markets expectation based on the past experience is common. If the market is going down, most individuals will likely expect the market pattern to continue going down in future. The theory sometimes maybe detrimental as it makes people lose focus on the long term market tendency and concentrate on the expectation. When people focus too much on expectation, they might not notice things turning in a positive way as they already have an expectation. This may make them miss out an opportunity.
Adaptive expectation is more close and related to rational expectations.In rational expectations, an individual bases his or her expectation based on three factors, which are information available, past experience and human reasoning.
It suggests that what people expect the economy to be in future influences the economy in future. For instance, if the inflation rate were higher than expected in the past, then people might expect that the inflation in the future might also exceed the expectation.
The main difference between adaptive expectations and rational expectation is that adaptive expectation use real time data while rational expectation uses historical data. Public at large mostly hold adaptive expectations while government corporations uses rational expectations.
Adaptive Expectation Formula
A simple formula of adaptive expectation theory is:
pe = pe-1+ ג (p-pe-1)
pe is next year’s inflation rate that is expected currently
pe-1 is this year’s inflation rate that was expected the previous year
p is this year’s actual rate of inflation
ג is between 0 and 1
If an error is made while predicting the price of the stock which can be caused by the price shocks, it is usually difficult to forecast the price level again even when there are no further shocks. This is because the future expectation still factors in the error made initially. According to Friedman, workers can come up with adaptive expectation for the government to surprise them with unforeseen monetary policy changes.
Limitation of adaptive expectation hypothesis
This model is simple whereby people base their expectations on what has happened in the past. Adaptive expectation is not commonly used in economics like rational expectations. In real world, historical date is one of the things that influence future trends. Adaptive expectation is limited especially if the inflation has an upward or downward movement. In this case, the past data will not be sufficient enough to make a conclusive expectation. It was due to this limitations that many economists and government agency use rational expectations since it factors in many other factors in their decision making process.
Example of adaptive expectation hypothesis
There was a time in U.S when housing bubble burst was experienced. Housing bubble is when the prices of housing go up due to high demand. This continued for a considerable period of time. Investors purchased assets assuming the prices will go up indefinitely. There was no possibility of prices going down since this had happened for quite some time. Later on, the bubble bursts and the prices fell and cycles turned.
The prices of an asset may go up due to high demand. This may continue for a considerable period of time. People might continue buying the assets assuming and expecting the prices will continue going up indefinitely in the future.
Reference for “Adaptive Expectations Hypothesis”
Academics research on “Adaptive Expectations Hypothesis”
Rational expectations and the theory of price movements, Muth, J. F. (1961). Rational expectations and the theory of price movements. Econometrica: Journal of the Econometric Society, 315-335. In order to explain fairly simply how expectations are formed, we advance the hypothesis that they are essentially the same as the predictions of the relevant economic theory. In particular, the hypothesis asserts that the economy generally does not waste information, and that expectations depend specifically on the structure of the entire system. Methods of analysis, which are appropriate under special conditions, are described in the context of an isolated market with a fixed production lag. The interpretative value of the hypothesis is illustrated by introducing commodity speculation into the system.
Rational and adaptive performance expectations in a customer satisfaction framework, Johnson, M. D., Anderson, E. W., & Fornell, C. (1995). Rational and adaptive performance expectations in a customer satisfaction framework. Journal of consumer research, 21(4), 695-707. This article develops and tests alternative models of market-level expectations, perceived product performance, and customer satisfaction. Market performance expectations are argued to be largely rational in nature yet adaptive to changing market conditions. Customer satisfaction is conceptualized as a cumulative construct that is affected by market expectations and performance perceptions in any given period and is affected by past satisfaction from period to period. An empirical study that supports adaptive market expectations and stable market satisfaction using data from the Swedish Customer Satisfaction Barometer is reported.
Rational versus adaptive expectations in present value models, Chow, G. C. (1991). Rational versus adaptive expectations in present value models. In Econometric Decision Models (pp. 269-284). Springer, Berlin, Heidelberg. Using data on stock price and dividends, and on long-term and short-term interest rates, we test an important implication of present value models, that current value is a linear function of the conditional expectations of the next-period value and the current determining variable. This implication, combined with rational expectations RE, is strongly rejected. Combined with adaptive expectations AE, it is accepted. The latter model can also explain the observed negative relation between the rate of return and stock price. Thus the RE assumption should be used with caution; the AE assumption may be useful in econometric practice.
Econometric implications of the rational expectations hypothesis, Wallis, K. F. (1980). Econometric implications of the rational expectations hypothesis. Econometrica: journal of the Econometric Society, 49-73. The implications for applied econometrics of the assumption that unobservable expectations are formed rationally in Muth’s sense are examined. The statistical properties of the resulting models and their distributed lag and time series representations are described. Purely extrapolative forecasts of endogenous variables can be constructed, as alternatives to rational expectations, but are less efficient. Identification and estimation are considered: an order condition is that no more expectations variables than exogenous variables enter the model. Estimation is based on algorithms for nonlinear-in-parameters systems; other approaches are surveyed. Implications for economic policy and econometric policy evaluation are described.
A test of the” expectations hypothesis” using directly observed wage and price expectations, Turnovsky, S. J., & Wachter, M. L. (1972). A test of the” expectations hypothesis” using directly observed wage and price expectations. The Review of Economics and Statistics, 47-54.