Since
facts are not explainable by facts, using theory to explain phenomenon must to
a certain degree be abstract. Abstract concept is non-factual. This led many
people to consider theory, having lost touch with reality, merely empty
rhetoric with no applications. “Realism” therefore grew to be a big
controversy. Today such controversy has died down, yet this issue deserves to
be clarified.
“Reality”
has several meanings. If we are unclear as to which aspect we are focusing on,
controversy will never end. Abstract concept is certainly not factual,
therefore it is acceptable to say that “theory” is not reality. But the
ultimate goal of a theory with explanatory power involves its empirical testing
and prediction. We can therefore also say that practical theory has its share
of reality. For certain theories, no testable implications can be derived
(e.g., the various economic development theories in the 1950s and 60s), hence
they could at best be counted as “games” that have no connections with the real
world whatsoever.
However,
there are at least four denotations in respect of the non-realism of theories
with explanatory power, three of which are very trivial. First, the theory
itself must have its abstract component. To say it is not reality is certainly
right, but it is wrong to say since it is not reality, it has no explanatory
power. Given facts cannot explain facts, without an abstract starting point,
real-world phenomena generally cannot be explained. Second, portrayal of all
facts or observations must be simplified – such simplification makes fact
“unreal”. This is a middling yet finicky viewpoint. Let’s use apple as an
example. Suppose we need to comprehensively portray an apple, we will fail even
after exhausting all the papers in the world. Just portraying the colors and
shapes of the apple – not to mention its tastes or the vitamins it contains –
is difficult to be exact! Under a finicky yardstick, no portrayal of a
phenomenon or a fact in the whole world is reality. However, criticizing
empirical science this way – such people do exist – is not scientific.
The third
type of non-reality also comes from simplification. The world is so complicated
that simplifying assumption (different from the notion of an abstract assumption)
is necessary. But the objective of simplification is purely for ease of
handling. Since simplification has no apparent effect on the outcome, it is
therefore allowed. For instance, let’s assume there are only two countries in
the world (in fact more than this, so not reality) and examine the outcome when
they trade with each other, etc. Changing two countries to three or four would
yield roughly the same outcome. For certain peculiar topic, however, changing
two to three would yield different outcome. So in researching such peculiar
topic, the distinction between two and three cannot be ignored, though some
other simplification is also necessary.
The last
type of non-reality is non-trivial. The aforementioned additional test
conditions are treated by many as a kind of assumption. Such assumption would
certainly become unreal due to simplification, yet we cannot treat that as a
castle in the air like abstract thinking, and sever ties with the real world.
The assumption of test conditions must be traceable, and test conditions in
their simplified form must be essentially congruent with reality. For instance,
given that a chemistry experiment requires a clean test tube (clean is a test
condition), we cannot use a dirty test tube and assume it is clean.
In
economics, test conditions are usually called constraints. Economics does not
have theories “with no constraints”. Like other scientific theories, economic
theories necessitate test conditions, otherwise they would have no explanatory
power. Suppose we say, under a situation of no transaction costs (a constraint,
may be grudgingly called an assumption), the occurrence of “A” would lead to
the occurrence of “B”. To test this implication, we must work under a real
situation with negligible transaction costs. In other words, the “assumption”
of constraints cannot lose touch with the real world. That is, other than
inevitable simplification, test conditions must have their realism.
We can
therefore draw the following conclusion. For scientific theory using abstract
thinking or concept as a starting point, since fact is not self-explanatory, it
is necessary to be “unreal”. “Impossibility to be too detailed” and
“simplification” are allowed. Yet test conditions losing touch with the real
world is a fatal mistake. Truthful investigation and simplification of
constraints (test conditions) are the most arduous processes in economic
explanation. Real-world phenomena are like chess games in that every game is
novel. It is only common that a few years’ effort is needed before getting a
little basic knowledge in certain constraints. People age as time flies,
therefore economists who undertake empirical studies often have to be sure of
the importance of the issue before committing their last bet.
In the great methodological debate during the 1950s
– 60s, there was an embarrassing fallacy on the realism of theories. That was:
if the occurrence of “A” leads to the occurrence of “B”, then we can go on to
say if “Not B”, then “Not A”. However, we cannot say if “Not A”, then “Not B”.
The fallacy of the latter has earlier been discussed. In that great debate,
many economists forgot about this first lesson in logic that “Not A” has no
impact on what “B” would be. The gentleman who investigated Boston’s
transportation companies considered the hypothesis of “A” unreal, then made a
big fuss to predict how “B” would be. Such mentally-deficient analysis was
originally not worth responding to, yet so inexplicable was scientific
advancement that feedbacks from numerous scholars led to a vastly constructive
debate.
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