In order to make the data “talk,” economists utilize a range of statistical methods that vary from highly complex models to a simple display of historical data.
It is generally held that by means of statistical correlations one can organize historical data into a useful body of information, which in turn can serve as the basis for assessments of the state of the economy.
It is held that through the application of statistical methods on historical data, one can extract the facts of reality regarding the state of the economy.
Unfortunately, things are not as straightforward as they seem to be. For instance, it has been observed that declines in the unemployment rate are associated with a general rise in the prices of goods and services.
Should we then conclude that declines in unemployment are a major trigger of price inflation?
To confuse the issue further, it has also been observed that price inflation is well correlated with changes in money supply. Also, it has been established that changes in wages display a very high correlation with price inflation.
So what are we to make out of all this? We are confronted here not with one, but with three competing “theories” of inflation. How are we to decide which is the right theory?
According to the popular way of thinking, the criterion for the selection of a theory should be its predictive power. On this Milton Friedman wrote,
The ultimate goal of a positive science is the development of a theory or hypothesis that yields valid and meaningful (i.e., not truistic) predictions about phenomena not yet observed.
So long as the model (theory) “works,” it is regarded as a valid framework as far as the assessment of an economy is concerned. Once the model (theory) breaks down, we look for a new model (theory).
For instance, an economist forms a view that consumer outlays on goods and services are determined by disposable income.
Once this view is validated by means of statistical methods, it is employed as a tool in assessments of the future direction of consumer spending. If the model fails to produce accurate forecasts, it is either replaced, or modified by adding some other explanatory variables.
The tentative nature of theories implies that our knowledge of the real world is elusive.
Since it is not possible to establish “how things really work,” then it does not really matter what the underlying assumptions of a model are. In fact anything goes, as long as the model can yield good predictions. According to Friedman,
The relevant question to ask about the assumptions of a theory is not whether they are descriptively realistic, for they never are, but whether they are sufficiently good approximation for the purpose in hand. And this question can be answered only by seeing whether the theory works, which means whether it yields sufficiently accurate predictions.
Theoretical versus practical economist
The view that our knowledge is tentative and that we can never be certain about anything, has given rise to two groups of economists – in one camp there are the so-called theoreticians, or “ivory-tower economists,” who generate various imaginary models and use them to form an opinion on the world of economics.
In the other camp we have the so-called “practical” economists, who derive their views solely from the data. Whereas the ivory-tower economists are of the belief that the key to the secret of the economic universe is via abstract models, the “practical” economists hold that if one “tortures” the data long enough, it will ultimately confess and the truth will reveal itself.
But statistical methods are of no help in this regard. All that various statistical methods can do is just compare the movements of various historical pieces of information.
These methods cannot identify the driving forces of economic activity. Likewise, models that are based on economists’ imaginations are not of much help either since these theories are not ascertained from the real world.
Economic theory, however, must have only one purpose–to explain the essence of economic activity.
We hold that economics is about human activities that seek to promote people’s lives and well-being. One can observe that people are engaged in a variety of activities. They are performing manual work, they drive cars, and they walk on the street and dine in restaurants.
The distinguishing characteristic of these activities is that they are all purposeful.
Thus manual work may be a means for some people to earn money, which in turn enables them to achieve various goals such as buying food or clothing.
Dining in a restaurant could be a means to establishing business relationships.
Driving a car could be a means for reaching a particular place. In other words, people operate within a framework of ends and means; they are using various means to secure ends.
Purposeful action implies that people assess or evaluate various means at their disposal against their ends.
At any point in time, people have an abundance of ends that they would like to achieve. What limits the attainment of various ends is the scarcity of means.
Hence, once more means become available, a greater number of ends, or goals, can be accommodated–i.e., people’s living standards will increase.
Another limitation on reaching various goals is the availability of suitable means. Thus to quell my thirst in the desert, I require water. Diamonds in my possession will be of no help in this regard.
Making sense of the data
Now, during an economic slump, a general fall in the demand for goods and services is observed. Are we then to conclude that the fall in the demand is the cause of an economic recession?
We know that people strive to improve their life and well-being. Their demands or goals are thus unlimited. The only way then for general demand to fall is via people’s inability to support their demand. In short, problems on the production side, i.e., with means, are the likely causes of an observed general fall in demand.
Alternatively, consider the situation in which the central bank announces that increasing money supply growth while price inflation is low can lift real economic growth.
To make sense of this proposition we must examine the essence of money. Money is the medium of exchange. Being the medium of exchange, money can only facilitate existing real wealth. It cannot create more wealth. Money cannot be used in production. It cannot be used in consumption.
We can conclude that printing money is not the right means to promote economic growth. The goal–of lifting real economic growth–cannot be achieved by means of printing money. Hence if one gets positive correlation between the rate of growth of money supply and economic activity one shouldn’t jump to the conclusion that money can grow an economy.
The knowledge that people are pursuing purposeful actions also permits us to evaluate the popular way of thinking that holds that the “motor” of the economy is consumer spending–i.e., demand creates supply. We know, however, that without means, no goals can be met. But means do not emerge out of the blue; they must be produced first hence the driving force is supply and not demand.
The fact that people consciously pursue purposeful actions provides us with definite knowledge, which is always valid as far as human beings are concerned. This knowledge sets the base for a coherent framework that permits meaningful assessments of the state of an economy.
The data should be regarded as a description of historical events. By itself it “cannot talk” – it must be interpreted by means of a theory, which wasn’t derived from the data. Again such a theory can be derived from some elementary knowledge such as that humans are operating in the goal – means framework and that their conduct is conscious.
On this Rothbard wrote,
One example that Mises liked to use in his class to demonstrate the difference between two fundamental ways of approaching human behavior was in looking at Grand Central Station behavior during rush hour. The “objective” or “truly scientific” behaviorist, he pointed out, would observe the empirical events: e.g., people rushing back and forth, aimlessly at certain predictable times of day. And that is all he would know. But the true student of human action would start from the fact that all human behavior is purposive, and he would see the purpose is to get from home to the train to work in the morning, the opposite at night, etc. It is obvious which one would discover and know more about human behavior, and therefore which one would be the genuine “scientist”.
We hold that also conclusions that were reached from “purely” theoretical models are likely to be questionable since these conclusions are derived from economists’ imaginations and are not based on the facts of reality.
A model, which is not derived from reality, cannot possibly explain the real world. (In this sense a statement that people pursue conscious and purposeful actions is a fact of reality. So anything, which is correctly derived from this statement, is in line with the reality).
For example, in order to explain the economic crisis in Japan, the famous mainstream economist Paul Krugman employed a model that assumes that people are identical and live forever and that output is given.
Whilst admitting that these assumptions are not realistic, Krugman nonetheless argued that somehow his model can be useful in offering solutions to the economic crisis in Japan.
Does predictive capability should be criterion for accepting a model?
The popular view that sets predictive capability as the criterion for accepting a model is questionable.
Even the natural sciences, which mainstream economics tries to emulate, don’t validate their models this way.
For instance, a theory that is employed to build a rocket stipulates certain conditions that must prevail for its successful launch.
One of the conditions is good weather. Would we then judge the quality of a rocket propulsion theory on the basis of whether it can accurately predict the date of the launch of the rocket?
The prediction that the launch will take place on a particular date in the future will only be realized if all the stipulated conditions hold.
Whether this will be so cannot be known in advance. For instance, on the planned day of the launch it may be raining.
All that the theory of rocket propulsion can tell us is that if all the necessary conditions will hold, then the launch of the rocket will be successful.
The quality of the theory, however, is not tainted by an inability to make an accurate prediction of the date of the launch.
The same logic also applies in economics. Thus we can say confidently that, all other things being equal, an increase in the demand for bread will raise its price. This conclusion is true, and not tentative.
Will the price of bread go up tomorrow, or sometime in the future? This cannot be established by the theory of supply and demand.
Should we then dismiss this theory as useless because it cannot predict the future price of bread?
According to Mises,
Economics can predict the effects to be expected from resorting to definite measures of economic policies. It can answer the question whether a definite policy is able to attain the ends aimed at and, if the answer is in the negative, what its real effects will be. But, of course, this prediction can be only “qualitative.”
The arbitrary nature of mainstream economics has given rise to the view that there is a gulf between theory and practice. A distinction is made between theoretical and practical assessments. Comments like “it is a great theory; however, I cannot make use of it” are often heard. Yet there is no such thing as a good but not applicable theory. To be applicable, a theory must emanate from the facts of reality, such as that human beings are engaged in purposeful actions. This knowledge permits to make valid assessment regarding the workings of the economy without making arbitrary assumptions.
 Milton Friedman, Essays in Positive Economics, Chicago: University of Chicago Press, 1953.
 Milton Friedman, ibid,
 Murray N. Rothbard preface in Theory and History by Ludwig von Mises.
 Paul Krugman, Japan’s Trap May 1998 in Krugman’s website.
 Ludwig von Mises, The Ultimate Foundation of Economic Science, p 67.