Rational Expectations

What are Rational Expectations?

Rational expectations is an economic theory that states that individuals make decisions based on the best available information in the market and learn from past trends. Rational expectations suggest that people will be wrong sometimes, but that, on average, they will be correct.

Understanding the Concept of Rational Expectations

The idea of rational expectations was first developed by American economist John F. Muth in 1961. However, it was popularized by economists Robert Lucas and T. Sargent in the 1970s and was widely used in microeconomics as part of the new classical revolution.

The theory states the following assumptions:

• With rational expectations, people always learn from past mistakes.
• Forecasts are unbiased, and people use all the available information and economic theories to make decisions.
• People understand how the economy works and how government policies alter macroeconomic variables such as price level, level of unemployment, and aggregate output.

The rational expectations theory comes in weak and strong versions. The “strong” version assumes that actors are able to access all available information and make rational decisions based on the information.

The “weak” versions assume that people lack time to access all relevant information but make decisions based on their limited knowledge. For example, if they buy cornflakes, it is “rational” to keep buying the same brand and not worry about getting perfect information about relative prices of other cornflakes brands.

Rational Expectations in Theory and Practice

Most macroeconomists today use rational expectations as an assumption in their analysis of policies. When thinking about the effects of economic policy, the assumption is that people will do their best to work out the implications.

The rational expectations approach is often used to test the accuracy of inflation forecasts. For example, P^e_t is an individual’s forecast in year t-1 of the price level in year t. The actual price level is denoted by P_t. The difference between the actual price level and the individual’s forecast is the forecast error for year t.

P_t – P^e_t = r_t is the individual’s forecast error in year t. With rational expectations, the forecast errors are due to unpredictable numbers. However, if people systematically under-predict or over-predict numbers, the price level expectations are not rational.

Under rational expectations, what happens today depends on the expectations of what will happen in the future. But what happens in the future also depends on what happens today. Many macroeconomic principles today are created with the assumption of rational expectations.

The theory is also used by many new Keynesian economists because it fits well with their assumption that people want to pursue their own self-interest. If people’s expectations were not rational, the economic decisions of individuals would not be as good as they are.

Adaptive Expectations

While individuals who use rational decision-making use the best available information in the market to make decisions, adaptive decision-makers use past trends and events to predict future outcomes. This is also known as backward thinking decision-making.

Adaptive expectations can be used to predict inflation. If inflation increased in the previous year, people expect an increased rate of inflation in the following year. The formula for adaptive expectations is P^e_t = P_t -1. It shows that people expect the trend of inflation to be the same as last year.

People will change their expectations of any variable if there is a difference between what they were expecting and what actually occurred. However, if their expectations turned out to be right, their future expectations likely will not change.

Limitations of Adaptive Expectations

While adaptive expectations allow us to measure expected variables and actual variables, they are not as commonly used in macroeconomics as rational expectations because of their limitations. The adaptive model is simplistic because it assumes that people base their decisions based on past data. However, in the real world, past data is just one of the factors that influence future behavior. Rational expectations incorporate many factors into the decision-making process.

The Expectation Augmented Phillips Curve (EAPC)

The Expectation Augmented Phillips Curve (originally based on A.W. Phillips’ work on the statistical relationship between unemployment and inflation) incorporates the role of expectations in the traditional Phillips Curve relationship.

In the graph above, we assume that the inflation rate is 2%, and the people’s expected inflation is also 2%.  However, the government increases aggregate demand, causing a rise in wages. Wages increase more than expectations of inflation, causing a “money illusion.” Workers think real wages have risen and increased the supply of labor, causing a fall in unemployment.

However, the rise in demand causes a rise in inflation, which is now at 3.5%. Consumers now adapt their inflation expectations at a rate of 3.5%. Due to high inflation expectations, there is now a worse trade-off between inflation and unemployment, which is shown as SPRC 2.

In the third year, if the government increases demand again and inflation pushes up to 5%, people will modify their inflationary expectations again. In predicting inflation, the Phillips Curve believes that stating the previous year’s inflation rate is a better guide than using inflation forecasts.

Additional Resources

CFI is the official provider of the global Financial Modeling & Valuation Analyst (FMVA)® certification program, designed to help anyone become a world-class financial analyst. To keep advancing your career, the additional CFI resources below will be useful:

• Marginal Propensity to Consume
• Moral Hazard
• Local Expectations Theory
• Behavioral Finance Glossary
• See all economics resources