The Science of Demand (6) - Unofficial Translation of Steven Cheung's 经济解释 - 科学说需求

Section 6.  Non-factual and Unrestrained

I have repeatedly stated the significance of “a theory refutable by facts”. I have also pointed out that tautologies, ambiguous, or contradictory theories are not refutable by facts. There remain two other types – of “theories” without explanatory power – that are not refutable by facts. One is when the phenomenon used for empirical testing is non-factual; the other is when the phenomenon inferred to occur is unrestrained.

Suppose I say: “If it rains, then there are clouds in the sky.” In this statement, “rain” and “clouds” are factual and observable. If “rain” and “clouds” are merely castles in the air and non-factual, then the statement cannot be tested. This embodies a non-trivial philosophy of empirical science. For every inference with explanatory power, its testing must have the following implication: if “A” happens, then “B” follows suit – and both “A” and “B” are observable facts. No matter how costly or how much time it takes to do the testing, in principle at least, the existence of “A” and “B” have to be confirmable. Albert Einstein’s theory of relativity involved the gene theory in genetics. Though its implication was initially difficult to be empirically tested, it was nonetheless confirmed subsequently.

The question is, as aforementioned, facts cannot be explained by facts. The occurrence of “A” cannot explain the occurrence of “B”. Any regularity between “A” and “B” can only serve to confirm the implication of a certain theory. No matter how abundant the facts are and how obvious the regularity is, they are not self-explanatory. Therefore, a theory with explanatory power often starts from abstract thinking and non-factual postulates, then through logical reasoning to derive testable implication – the latter is the “If it rains, then there are clouds” hypothesis.

This is no easy project. A testable implication has to be refutable by facts; however, facts are not self-explanatory, and abstract theory itself cannot be tested. In the subtle transition from abstract reasoning to empirical testing, the difference in capability between a master and a mediocrity will be clearly revealed.

Let me quote a fundamental example. In economics, the renowned law of demand says: if the price of a good falls, its quantity demanded will increase. Price and its movement are observable, but quantity demanded is non-factual! Quantity demanded, referring to consumers’ desired or intended demand, is an abstract term. Therefore, the law of demand itself cannot be empirically tested. However, this law is indispensably significant in economics. The average person often treats quantity transacted in the market as quantity demanded. Similar to treating a deer as a horse, this is undoubtedly wrong. The correct approach is very different. We should say: if the law of demand is right, then by logical reasoning, under certain observable circumstances, the occurrence of “A” will lead to the occurrence of “B”, and both “A” and “B” are observable facts (this is a testable implication inferred by the non-testable law of demand). If “A” occurs yet “B” does not occur, then the law of demand is highly problematic – it either requires addition of other conditions, or be counted as refuted by facts. If “Not B” implies “Not A”, then the law of demand is not refuted, and can be interpreted as having explained the regularity between “A” and “B”.

Indeed – if amazingly done, such prediction and empirical testing can be extremely laudable. This is the beauty of science. In this book I will go to great lengths to demonstrate the astonishing explanatory power of the law of demand. The aforementioned additional conditions could be ever-changing, aplenty or just a few. In scientific methodology, additional conditions are called test conditions, while in economics they are termed constraints. Sometimes we could say the occurrences of “A” and “B”, or the occurrence of “A” or “B”, will lead to the occurrence of “C”. We could also say the occurrence of “A” will lead to the occurrences of “B” and “C”. These variables could be aplenty or just a few; could occur simultaneously; one or several of them could occur in several or many possible observations. These all fulfill the requirements of theories with explanatory power. No matter how many phenomena are involved in testing, one restraint is necessary.

Suppose the occurrence of “A” will lead to the occurrence of an infinite list of “B”, or “C” or “D” or “F” …, then such an implication is neither deniable nor refutable. Strictly speaking, this is the so-called disequilibrium in economic theory. Equilibrium, on the other hand, is attained when a refutable implication is derived from restrained hence definite phenomena.

The aforementioned concepts of “equilibrium” and “disequilibrium” are different from the traditional equilibrium theory adopted by economists. I consider the traditional concepts fundamentally wrong. “Equilibrium” in traditional economics was copied from physics. Equilibrium in physics refers to a pendulum, after oscillating, reaching a static state at the center; or an egg, after rolling on the floor, reaching a stationary point; or an incessant object, after entering an orbit, displaying regularity. This type of “equilibrium” refers to certain phenomena that are indeed observable.

“Equilibrium” in economics is a different matter. For instance, economists say that the intersection of the demand curve and the supply curve is an equilibrium point. Yet there is neither demand curve nor supply curve in this world – these are merely conceptual tools conceived by economists. Without economists, these conceptual tools will not exist. Similarly, “equilibrium” and “disequilibrium” in economics are merely concepts that do not exist in the real world. Being neither phenomena nor facts, they cannot be observed.

In the spring of 1969, Coase and I drove from Vancouver to Seattle. In the over two-hour journey we debated about the “equilibrium” concept in economics. He considered “equilibrium” and “disequilibrium”, being castles in the air, should be abolished. I assented to the viewpoint of castles in the air, but considering so popular were “equilibrium” and “disequilibrium” in economics, I could provide a little remedy for these concepts.

I pointed out to Coase that “disequilibrium” could be interpreted as a theory lacking a refutable implication since inferred phenomena are not restrained; whereas “equilibrium” refers to a testable theory since inferred phenomena are restrained. This is the difference between the aforementioned “unrestrained” and “restrained”. Coase at that time agreed this interpretation could salvage the economic “equilibrium” and “disequilibrium” concepts which ought to have been trashed. That was more than forty years ago. Today, the number of economists who understand and concur with this concept can be counted on the fingers of both hands.

Abstract theory itself cannot be empirically tested. In order to have explanatory power, abstract theory must possess one or more implications that can be tested. For implication to be testable, it must be refutable by facts. The implication can have many additional conditions and inferences of phenomena, and they can be linked by the affirmative “and” or the not-so-affirmative “or”, though they cannot be infinite. Undoubtedly, the affirmative “and” has stronger explanatory power than the not-so-affirmative “or”, and the simpler the abstract reasoning and test implication, the more convincing they are. Gifted scientists are capable of marvelously simplifying complexities.