What it means
Earlier economic models assumed that people simply extrapolated from the past, expecting next year's inflation to look like last year's. Rational expectations theory argues that this is too naive.
People read the news, understand how policy works and adjust their forecasts accordingly. If forecasts use all available information, the only surprises are genuinely unpredictable ones.
The mistakes people make are random, with some too high and some too low, so they average out to zero over time. That means no one should be able to consistently beat the forecast by using publicly known information.
The idea has important consequences for policy. If a central bank announces that it will cut interest rates, rational people adjust their behaviour in advance, so the announced change has less effect than a surprise would.
It also underpins the efficient market hypothesis, which says that asset prices already reflect all available information. For businesses, the theory is a warning against assuming that customers, workers or investors are slow to catch on.
Wage negotiators build expected inflation into their demands, and investors price in expected profits before they appear. A plan that relies on the other side being surprised by something widely known is likely to fail.
The nuance is that real people do not always process information perfectly, and forecasting errors can be correlated, as in bubbles and panics. The theory is best seen as a benchmark for how well-informed markets behave on average.
It is less reliable for individuals or in situations with confusing information. The theory has a practical lesson for forecasting inside a company.
A forecast that is consistently too high or too low is a sign of bias, because rational forecasting errors should average out. Tracking forecast errors over several periods is a simple way to test whether the planning process is honest.
In practice
Real-world examples.
Example
A union negotiating wages looks at central bank forecasts and current price trends. It builds expected inflation of 3% into its wage claim, rather than waiting to see what happens. The employer must factor the same expectation into its pricing, so the wage settlement and the price rise arrive together.
Example
A bond investor hears that a central bank will raise interest rates next month. She sells bonds before the announcement, so the price falls early. When the central bank acts, the market barely moves because the news was already expected. Investors who waited for the announcement missed the price change.
Example
A retailer notices that its competitors have all been forecasting a strong holiday season and ordering heavily. It realises that the good news is already priced into supplier costs and shelf space. It decides to compete on service rather than expecting a bargain.
Formula
Calculation
Forecast error = actual outcome - expected outcome
Under rational expectations, the average forecast error is zero.
A company forecasts quarterly sales for four quarters and records the errors as +$20,000, -$30,000, +$10,000 and $0. The errors add up to 20,000 - 30,000 + 10,000 + 0 = $0, so the average error is 0 / 4 = $0. The forecasts are sometimes too low and sometimes too high, but there is no systematic bias, which is what rational expectations would predict.Case study
Seen in the real world.
Hollinbrook Manufacturing is an illustrative, fictional exporter that expected a currency to weaken after a policy announcement and planned to benefit by delaying its overseas purchases. The finance director waited for the currency to fall.
It did not, because the announcement had been widely discussed for months and the market had already moved. By waiting, the company missed a favourable rate and paid 2% more, which on a $3,000,000 order was 3,000,000 x 0.02 = $60,000.
The treasurer later adopted a rule of hedging a fixed share of exposures regularly, instead of trying to outguess the market. The board accepted that no one at the company had a special edge on public news. The illustrative lesson is that, if information is public, it is probably already reflected in prices and expectations.
Watch out
Common mistakes.
- Assuming rational expectations means everyone is always correct, when it means errors are random and not systematic.
- Expecting an announced policy to have the same effect as a surprise.
- Believing you can profit repeatedly from widely known information.
Questions
People also ask.
How is it different from adaptive expectations?
Adaptive expectations look backwards and adjust slowly to past errors, while rational expectations use all available information, including forward-looking policy and news.
Does the theory say markets cannot be wrong?
No, it says that errors are not predictable from known information, but bubbles and mispricing can still occur.
Why does it matter for policy?
Because people anticipate policy changes, the effect of an announcement depends on whether it was expected.
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