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Which model do people carry in their minds when they forecast inflation rates
... The adaptive expectations hypothesis has also been supported by empirical evidence. Valentine (1977), Defris and Williams (1979), Jacobs and Jones (1980) and Jonung (1983) have found some empirical support for this hypothesis in their empirical work with actually observed expectations in Australia, USA and Sweden. Theoretical support for the adaptive expectations is given in Turnovsky (1969), who shows that a decision maker, forming expectations by using Bayesian sampling procedure, will change his expectations adaptively. ...
This paper presents three different methods for obtaining and representing information about cognitive representations of economic variables. In the first study, variables considered related to a focal variable (inflation) were elicited. The second study presents numerical ratio scales for the strengths of relationships between different economic variables related to the focal variable. The third study gives a method for deriving causal chains of variables linked to each other so that a change in the first variable in the chain ultimately may lead to a change in the focal variable. The cognitive representation of this was mapped onto a causal tree structure. This study also presents causal chains for the effects of a change in the focal variable (viz., effects of inflation directly and indirectly). Although the paper was primarily methodological in character a few observations of differences between economists and non-experts were reported.
The purpose of this article is to test for the ‘rationality’ of a time series of expected values of a variable the actual values of which were created by a simple autoregressive (exponential) process. The data was obtained by means of a small scale experiment using economists as respondents. We are also interested in the possible learning processes involved when the respondents form their expectation about the future values of the variable. Finally, we investigate our data both on the aggregate and on the individual level to see whether aggregate results tend to be consistent with what the individual results imply or whether aggregation tends to conceal important information.To test for rationality we use both a test for unbiasedness and a so-called orthogonality test. Neither of the tests applied provides unambiguous support for the REH. However, the first half of the experiment, where the rate of change in the variable values to be forecast is relatively small. produces results much more in support of the rationality hypothesis than the second one. The difficulty of the task seems to be an important determinant for the ability of people to behave rationally, in the technical sense tested for here. Besides casting doubts on the REH. our results point at considerable differences between individual and aggregate behaviour.Our results suggest that there seems to be a learning process leading to a convergence between the actual and predicted time series. When assessing the importance of this, as well as the results of the rationality tests, we should keep in mind the relatively simple prediction task, and the fact that the respondents may be regarded as ‘experts’. All results should therefore he interpreted with a good deal of caution.
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