What’s the Big Deal with Rational Expectations?

I have some problems with the rational expectations hypothesis. To hear some macro economists talk about it, you’d think that it was a wonderful scientific innovation for economists to start assuming that the agents in their models know the structure of the economy and only make random errors in forecasting.  Such sentiments are entirely misguided.

Is it really the case that the market behaves as if the people in the market do not make systematic errors? If so, this is a highly interesting feature of the market economy, one that economists should explain rather than simply asserting.

It is entirely possible to construct a theory of markets without presupposing the specific types of errors (systematic or random) that people make. In doing so, we should ask ourselves what would happen to an entrepreneur who repeatedly and systematically failed in forecasting the future state of prices. Such a person would repeatedly earn losses. Faced with these losses, he would be forced either to revise his forecasting method such that his predictions would improve, or face continual losses and eventual bankruptcy. Thus, the market process tends, in the limit, towards something like rational expectations.

The advantage of the argumentation above is that it can tell us something about the circumstances under which we should not expect rational expectations to prevail. The selective market process that tends toward rational expectations does not happen instantaneously, so we should not expect entrepreneurs to immediately adapt to major structural changes to the economy. Nor can the market perform its selective function under any conceivable set of government interventions; a government that bails out unprofitable companies is directly interfering with the market’s ability to select good forecasters over bad.

I suspect that the economists who assume rational expectations as an ex ante condition of market actors will not disagree with much of the above analysis. They may even use some of the same reasoning to justify the assumption. The problem is that removing one of the market’s chief functions from one’s formal models can blind one to the possibility that this function could ever be impaired.

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What’s the Big Deal with Rational Expectations?

I have some problems with the rational expectations hypothesis. To hear some macro economists talk about it, you’d think that it was a wonderful scientific innovation for economists to start assuming that the agents in their models know the structure of the economy and only make random errors in forecasting.  Such sentiments are entirely misguided.

Is it really the case that the market behaves as if the people in the market do not make systematic errors? If so, this is a highly interesting feature of the market economy, one that economists should explain rather than simply asserting.

It is entirely possible to construct a theory of markets without presupposing the specific types of errors (systematic or random) that people make. In doing so, we should ask ourselves what would happen to an entrepreneur who repeatedly and systematically failed in forecasting the future state of prices. Such a person would repeatedly earn losses. Faced with these losses, he would be forced either to revise his forecasting method such that his predictions would improve, or face continual losses and eventual bankruptcy. Thus, the market process tends, in the limit, towards something like rational expectations. (more…)

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Significance Tests as Leading Questions

Under the common law, lawyers are not allowed to ask witnesses “leading questions,” as witnesses can be influenced by the way questions are asked. A leading question is one that suggests a particular answer, for instance, “Were you at the country club on Saturday night?” is a leading question, while, “Where were you on Saturday night?” is not.

Econometricians should be as careful as lawyers when questioning the most unreliable of all witnesses: economic data. Most statistical software will automatically spit out t-tests for whether the coefficients in regression models equal zero. This is equivalent to asking the data, “Data, given these modelling assumptions, can you deny with 95% certainty that this coefficient equals zero?” That’s a leading question, and the econometrician shouldn’t ask it unless he has special reason to suspect that the coefficient is zero.

For example, suppose an economist was attempting to test the effect on employment of an increase in the minimum wage (I choose this example only because I am familiar with it). If he observes many people working below the new minimum immediately before it goes into effect, he can believe with high certainty that the new minimum will be binding. Furthermore, if he observes many businesses employing low-skilled workers, as well as a stream of new businesses entering the market for low-skilled labour, he can believe with high certainty that the market for low-skilled labour is competitive rather than monopsonistic. Putting on his economist hat, he can infer from these two observations that the reduction in employment caused by the minimum wage will correspond to the elasticity of the demand curve for low-skilled labour.

Given this situation, would it be appropriate for this economist to ask the data, “Data, given these modelling assumptions, can you deny with 95% certainty that the minimum wage has zero effect on employment?” I hope the reader can see the problem with such a question. The economist has no special reason to believe that the demand curve for low-skilled labour is perfectly inelastic, any more than he has a special reason to believe that this demand curve has an elasticity of exactly 0.73. The question he should be asking is, in the case of this particular historical event, how much did the increase in the minimum wage increase unemployment? “Not at all” is a valid answer, but with no special reason to believe it is the correct answer, he should not bias his conclusion by phrasing the question in such a way that he leads his “witness” to favour zero.

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