Why Economists Get It Wrong
By Adrián Ravier
The media, and public debate, are currently home to many complaints that economists are failing to make accurate macroeconomic predictions. The critique goes beyond doubts about the art of prediction, often also attacking the scientific character of economics.
For economics is a science, and perhaps one of the most complex there is. While economists can be grouped into distinct methods and theoretical traditions, we generally share a common language, using models with causal relationships between variables to predict what would happen in a certain geographical area as a result of specific changes in economic policy.
Economics in the Dock
Economics is one of the most complex sciences largely because the economist can’t create experimental conditions to simulate the market in the same way as a physics or chemistry laboratory. While he or she can gather a sufficient number of people to approximate a market system, as experimental economics tries to do, differences still remain relative to the “hard” sciences.
In physics or chemistry, all other things being equal, the agents involved will always react in the same way before a certain stimulus. In economics, this isn’t the case. Human beings act, they don’t simply react. Individuals react differently to the same stimulus. The same individual will even act differently to the same stimulus at different moments.
We should remember, however, that while the economist can predict what will happen in a market under certain political economy stimuli, this prediction will only be qualitative, regarding the direction that a single variable will take in the short or long term.
The discipline doesn’t allow the economist to scientifically predict with exact precision the size of changes to certain variables, nor the specific moment when these changes will be produced: nothing other than the problem of timing. We know what’s going to happen, but we can’t specify the exact moment it will take place.
The business world, however, is guided by these macroeconomic variables, some of which can be measured: inflation, unemployment, economic growth (GDP) or exchange rates. It’s in the interest of business owners that economists transmit with the least margin of error possible the values that these and other variables will acquire in the short and medium term: their investment decisions directly depend on it.
As theoretical economists we’re failing to properly explain to people the limits of our science, while consultant economists are failing to inform their clients about the limits of their predictions.
It’s in this regard that I suggest we learn to distinguish between the scientific economist, concerned with economic theory, and the business of the practising or consultant economist, who tries to quantitatively predict what will happen with these variables on the basis of economic analysis.
It often turns out that the economist makes an analysis based on an incorrect economic model. But the consultant can also make mistakes if he uses an appropriate model. There are many reasons behind this, but in the interests of brevity, here are a few factors.
No Crystal Ball
In the first place, the consultant can’t know with precision which approach to political economy the government will apply. Right now in Argentina predictions are circulating as to whether the government will devalue the official exchange rate.
Secondly, the practising economist can’t know the precise moment when a new economic policy will be launched. We can predict the that government will devalue, but knowing when is a determining factor in establishing at what point the results predicted by science will come to pass.
Point number three: although the economist might predict the evaluation, and know from an insider source exactly when the policy will come into effect, it’s still impossible for she or he to predict exactly every ramification, because the variables in question are also determined by the decisions taken by people in the face of specific policies.
Predicting, for example, the value that the exchange rate will reach on a specific day requires information about what the government will do, but the activities of people on the exchange market will also determine the rate. If enough people act in a different way to government expectations, it’s possible that the intervention will end up having to use currency reserves to maintain the exchange rate, as has happened many times in the history of several countries.
The art of prediction needs economic theory, but an incorrect prediction doesn’t necessarily invalidate economic theory, as many positivists suggest. A faulty prediction could result from several different factors.
Clive Granger, winner of the Nobel Prize for Economics in 2003 for his work in constructing empirical models, highlighted the team effort involved in his work. It required theoretical inputs, data, awareness of on the ground data and relevant institutional limits. The bigger the project, he said, the greater the need for teamwork.
So the practising economist is confronted by a fairly complex art. Grounding themselves in the economic theory they believe to be correct, forming data sets with market information (which in itself is often defective), he or she has to be aware of institutional limits and remain contact with both the policy and market spheres. If they do all this, they can build a hard-won conclusion which will allow their clients, business leaders, to take decisions on the firmest possible evidence.
As theoretical economists we’re failing to properly explain to people the limits of our science, while consultant economists are failing to inform their clients about the limits of their predictions. If we correct these shortcomings, it would no longer be such cause for astonishment if and when our predictions are only an approximation of the values that these various figures can reach.
Adrian Ravier is a professor of economics at Francisco Marroquín University, Guatemala, and holds a doctorate in applied economics from Madrid’s Rey Juan Carlos University. Follow @AdrianRavier.