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By David Greenaway (eds.)

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Such adjustment, however, is lacking in the Keynesian approach. Consider, by way of example, Keynesian interest-rate theory. Individuals are assumed to entertain some expectation of future interest rates. If they believe that interest rates will rise in the future they will sell bonds and hoard cash in order to avoid the prospect of a capital loss. But what if interest rates remain unchanged? How long will individuals continue to hoard cash and lose out on profitable investment in government bonds?

Those agents acquainted with the laws of chancethat is, knowing the behaviour of the model governing the outcome - would work it out for themselves. Those agents ignorant of the model would learn from experience or would rely upon the opinions of others versed in probability theory. Either way, it is not unreasonable to assume that all agents would eventually settle on the one value which coincides with the true objective mathematical expectation. This is very close to the concept underlying Muthian rational expectations.

It follows that a potential consumer need not be indifferent in the purchase of two products which possess identical mean value outcomes; in particular, if he is risk-averse he may choose the product with the smaller variance to minimise the risk of an unacceptable outcome. Expectations formation therefore, with respect to economic variables involves not only mean values but, in principle, an expectation of the entire probability distribution pertaining to the variable. Whether economic agents possess adequate information to be able to generate subjective probability distributions in this manner which are useful in programming and optimising their behaviour remains a contentious area of controversy in macroeconomics and one which is very close to the heart of many research agendas.

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