Not sure what you mean by “non-realized parts”. The deductive method is simply a mechanical derivation of conclusions from premises and there is nothing unique to Austrian theory about the use of deduction… even mainstream theory uses deduction. The difference is the kinds of things that Austrians hold to be suitable objects of deductive logic. Combined with methodological dualism, (thinking about humans as if they have a material body and an immaterial soul while not actually asserting that this is the case) Austrian theory enables the use of deductive reasoning about people’s intentions and mental states such as ends, means, satisfactions, wants, and so on.
If I had to point to any one thing that I think is responsible for the large divergence between Austrian and mainstream theory, I would think it is the methodological dualism. Materialism is the dominant metaphysical theory in modern science but I suspect that the politicization and dichotomization of religion and science has played a role in making scientists too sensitive to accusations of mysticism or irrationality (supernatural explanations). The Austrian approach simply takes it for granted that we cannot (at least, for now) explain human action on the basis of a purely material theory of the brain and, therefore, we have to reason about human behavior as if there were some intangible component to it if we hope to make any sense of it at all.
Well, here you’re touching on some deep philosophical problems that are not completely resolved. What does it mean to explain a phenomenon, that is, when has it been explained? What exactly is causation? What does it really mean to say that A caused B to happen?
Mainstream theory isn’t meaningless, it just can’t ever say anything about causality without going beyond itself. Take Steven Levitt’s (of Freakonomics fame) work, for example. He posits explanations of cause-and-effect… for example, he has made the controversial claim that the murder rate dropped in the 1990’s as an unforeseen and utterly inevitable consequence of the legalization of abortion. The connection? Unwanted children are more likely to become criminals. Fewer unwanted children = fewer criminals. I’ve boiled his work down to a cartoon summary so read it before you criticize it. The point I want to make is that in order to construct this theory, he had to introduce assumptions about cause-and-effect in human behavior (assumed facts about human action), which is praxeological methodology even if he doesn’t use that term to describe it.
Let’s say, for the sake of argument, that Levitt’s theory is true. He did a lot of empirical analysis of murder rates in cities across the US and controlled for all sorts of potential causes (increased police budgets, increased drug enforcement, stricter punishments and laws, etc. etc.) using the most sophisticated statistical tools available to economists today. He found that the many colloquial explanations that were offered at the time by journalists, academics and self-serving mayors wanting to claim that they did something to be responsible for the decline in murder rates simply didn’t agree with the data. Good so far.
But would anyone imagine that Levitt proved any of the following with this study?:
- Humans sometimes do not want the children they have
- Unwanted children are less likely to receive parental care and resources than their wanted peers
- Children who grow up in conditions of privation are more likely than their less-deprived peers to resort to crime in order to survive
Every one of these facts about human beings is simply assumed by the theory itself! And that’s what praxeology generally does… assume facts about human beings which, by their nature, are too complex to be “proved” by scientific means. Is there a region of the brain that lights up in a parent’s head when shown a picture of an unwanted child that tells you whether the child is wanted or not? It’s probably not that simple. Lacking such a simple physiological indicator of wantedness, there is no sense in which we can say it is a “scientific fact” that parents sometimes do not want the children they have. All we can do is take it as a given for the sake of theorizing about something else we’re actually interested in explaining (a declining murder rate, for example).
Praxeology is the generalization of this approach to human social science. There is nothing specific to economics about the praxeological method. In fact, Austrians wouldn’t even categorize Levitt’s work as economics (though they would recognize it as a praxeological method). Economics is concerned with a subset of human action regarding what Mises called “catallactics” or voluntary exchange and its results hold with respect to human choices generally (past, present and future), not only to a specific historical episode.
Mainstream economics, on the other hand, frequently gets mired in this absurd conception of economics or social science as answering fundamental questions about human nature. Are humans self-interested or altruistic? In response to such a question, the mainstream economist instinctively wants to find refuge in data. What does the data say? He has an idea: let’s run polynomial regressions of charity donations versus welfare entitlements to see if they are correlated, anti-correlated or uncorrelated!!
But no matter what the correlation is between these two variables or any other variables, for that matter, it will tell us absolutely nothing about whether humans are self-interested or altruistic for the same reason that Levitt’s theory can tell us nothing about whether humans sometimes have unwanted children. They’ve essentially reversed the correct method of studying human behavior. They want to work their way from the phenomena back to human nature (a theory of human behavior). What they should be doing is starting with human nature and comprehending or explaining the phenomena.
That is not to say that a theory of human behavior based on empirical observation is utterly without hope. It’s just that we don’t have much to go on right now. The brain is not just a few kilograms of an amorphous gray substance, it’s a highly interconnected, electro-chemical neural-network computing device. It is ridiculously difficult to reverse engineer even toy neural-networks that do a simple task such as recognize a correlation between the on/off state of two switches. Such toy neural networks are less complex than the neural center of a fruit-fly. The idea that we can casually reverse-engineer the human brain with statistical analyses is hopelessly naive and - to the extent that its methods presuppose that this is the case - mainstream social science is simply negligent.
Clayton -
