Internal consistency
As a direct result of using a deductive method, what Praxeology achieves is to be internally consistent. This is indeed very hard to achieve. This is one of the holy grails of normal sciences.
Internal consistency means that you can reach any conclusion in a science using axioms and logic and vice versa; that you can arrive at axioms starting with any conclusion. If any of these paths cannot be achieved, then the science is not internally consistent.
Internal consistency provides strength. This is so because it gives us a powerful tool to determine what is true and what is not. For example, if one wishes to explore if a conclusion is true all one needs to do is to decompose it and try to obtain an axiom. If an axiom cannot be obtained, then it is not true. Equally, if a contradiction in terms of axiom(s) is obtained, then it is also not true.
Internal consistency provides the mechanisms to keep a discipline on track making sure it does not deviate because the entire discipline is deduced and hence bonded together by strict logic, no deviations.
Rejection of the experimental method
Praxeology rejects the idea that experimentation or quantitative measurements can be used to determine the truth of a theory dealing with human action. The reason for this rejection is that what we are trying to measure is the purpose behind a human action.
Currently our scientific technology is incapable of quantifying such purposes. All we can do is to measure the action itself but this tells us nothing about the purpose behind it; which is what Praxeology studies.
The classic example is a record of human traffic throughout the day around a school. Without knowing the purpose of the school, it is impossible to deduce that students go to class and back to home. All we can say is that there is a pattern of people that changes throughout the day.
As such, trying to prove anything related to human action throughout quantitative methods is a waste of time.
If the day comes when we may be able to read human minds in real time and somehow "copy" their ideas and purpose, then and only then we may be able to use quantitative methods with Praxeology.
Empirical or experimental sciences on the other hand, measure elements that have no will of their own. A molecule of Oxygen cannot suddenly decide not to combine itself with gasoline in a car engine and hence not to produce Carbon Monoxide. A stone cannot decide by itself not to fall on the ground once thrown into the air. All these elements have no choice but to abide absolutely by physical laws because they have no will. Therefore anything that these sciences measure by observation indeed represents the expression of physical laws. It is for this reason that they use observation and testing to discover the validity of such laws.
Forecasts and tests
But if quantitative methods are rejected by Praxeology, does it mean that all statistics are useless?
Statistics have the following two purposes
to provide data for inductive thinking to discover new Laws of Action
to provide data to test forecasts
However, we must be clear what it means to "test" from a Praxeological point of view. All other economic theories have mathematical models which produce quantitative predictions. For example, if interest rates go up by 1% the number of new mortgages will drop by 0.75%.
Praxeology can produce no such numeric forecasts. However, Praxeology does produce qualitative (i.e. non-numerical) forecasts. If we take the previous example, Praxeology will say that if interest rates go up then the number of new mortgages will drop.
Economics has a problem that no other sciences have (excluding sciences studying human behaviour). Take the previous example. Let's say that decreases in new mortgages are measured in different countries and in different years. For some time, the model seems to work and then it suddenly stops working altogether. Is the model "true" or "false"? According to standard experimental scientific principles it is true first (due to preponderance of evidence) and then false under the same conditions! In other words, it is true and false at the same time!
This is so precisely because the model is measuring action and not purpose. The difference between the "true" years and the "false" years is in the purpose that cannot be measured. It is for this reason that Praxeology rejects statistics as determinants of true or falsehood of economic theories.
In the same example, Praxeology would have deduced the purpose of people in the "true" years and the purpose of people in the "false" years and note that they were different and therefore different outcomes should be expected.
In this sense, statistics can put Praxeology to test, but even this test is limited. As peoples' purposes change all the time, there is no guarantee that in the next cycle the purpose of people won't change and a different theory may be required. Furthermore, as action is determined by purpose and each person is unique, there is no guarantee that all people (or a majority) will act in a manner pursuing the same goals. Therefore statistics can never determine the truth or falsehood of a Praxeological theory. It can only provide incidental information to allow for further inductions and new theories.
In a sense Praxeology seems to operate on the principle that if reality does not fit the theory, change reality. However, this could not be further from the truth. If numerical data indicate that a Praxeological theory may seem to be in error, the theory will be changed. This is, of course, nothing unusual and all other standard Economic sciences do the same. Praxeology does not claim to be perfect. The difference is that in general terms, Praxeology is far, far more accurate than any other Economic flavour. This is so much indeed that may critically important Laws of Action have been "borrowed" from Praxeology and inserted in standard Economics! We are willing to bet that you did not know this one.
Behavioural economics
There is a new science that originated as a hybrid between standard Economics (which consider human beings as repetitive and identical machines) and Praxeology (which consider humans as purposeful actors).
This science is attempting to measure human behaviour (and to a degree, purpose) using statistics. So far all its attempts have failed. At this point in time it would seem that Praxeology is more correct than standard Economics.
Laws of Action
The universal truths we deduce in Praxeology from "undeniable facts" are also called the Laws of Action.
What Praxeology claims is that these Laws are indeed universal and they apply to all people of any belief, culture or genetic trait anywhere in the planet.
Some people prefer to think about these laws as patterns of behaviour. This may certainly be a way to think about them, however, Praxeology claims that its Laws of Actions are not statistical, this is, they always apply. The concept of "pattern of behaviour" is statistical in nature. It is possible to apply logic to Laws of Action and achieve absolute truths, while it is not possible to do the same with patterns of behaviour. If we do so, we only obtain probable/possible truths.
However, having said this, we must also remember that as we are unable to know the purposes driving people, we are unable to fully and completely predict their behaviour. The best that Praxeology can say is that if peoples' goals are such-and-such then their actions (according to the applicable Laws of Action) will be such-and-such.
As Praxeology practitioners we can make educated guesses as to peoples' purposes but such efforts are simply best guesses. If our conclusions are faulty is our guesses that are faulty, not the Laws of Action.
This, of course, seems to be a very convenient excuse to protect Laws of Action from ever being tested. This is not the case. As we mentioned before, statistical analysis does provide indications as to the correctness of our forecasts.
If Praxeological conclusions based on Laws of Action would be consistently at odds with statistical analysis, this would make abundantly clear that said laws are flawed. Yet, in practice, this is not the case.
Furthermore, this idea that there are processes that are not fully forecastable or known is not alien to empirical sciences. The most common physical expression stating that there is something that we cannot know due to intrinsical reasons is Heisember's Principle of Uncertainty. This uncertainty exists at the very basic levels of reality and it is nothing new.
Note: please see the Glossary if you are unfamiliar with certain words.
