Non-Certeris Paribus Markets
Introductory economics textbooks usually begin with a certeris
paribus assumptions. That is, holding
everything else equal, if a increases then b decreases. “To beginners, it
can seem odd to claim that economics is a science. After all, economists do not
work with test tubes or telescopes. The essence of science, however, is the
scientific method – the dispassionate development and testing of theories about
how the world works. This method of inquiry is as applicable to studying a
nation’s economy as it is to studying the earth’s gravity or a species’
evolution.” (Markiw’s Principles of Economics)
He continues,
“Although economists use theory and observation like other scientists,
they face an obstacle that makes their task especially challenging: In
economics, conducting experiments is often difficult and sometimes impossible.
Economists, like astronomers and evolutionary biologists, usually have to make
do with whatever data the world happens to give them.” […] “To find a
substitute for laboratory experiments, economists pay close attention to the
natural experiments offered by history. Economists make assumptions for the
same reason: Assumptions can simplify the complex world and make it easier to
understand.”
However, the scientific method cannot be applied in macroeconomics,
because theories are not verifiable as the “everything else equal” assumption
does not hold.
Again, the scientific method assumes that if everything else is kept
without change then we can see the effect of changing variable x on variable y.
Thus, the structure of the scientific method is:
If A, and everything else without change, then B.
However, if one of the two conditions of the logical statement is always
false, no meaningful conclusion can be reached. The statement above cannot be
verified, because we can never affirm with observations that if A is true then
B is true, as we will never be able to hold everything else without change.
This is not a small matter. We can and do have academic results that
contradict each other. A paper claims that if A increases then B increases, and another one finding that
if A increases B decreases. The
environment in which the two experiments took place were different and were changing,
perhaps they were different countries, or different time periods; perhaps a
country was at war, there was a global crisis or different economic policies,
and thus we can reach opposing conclusions using the scientific method in a
non-scientific environment.
In physics we cannot have the apple falling from the tree and another
scientist concluding that it should fly up from the tree. There might be
disconfirming evidence that requires the development of a new theory or a
refinement of the current theory, but there is no two or more widely accepted
theories that reach different conclusions over the same event with supporting data.
Thus, it is better to stop pretending that economics is a science and
think how we can better understand the economics of the world. One alternative
is to realize that economics is not a science, and its models are “parables” with
varying degrees of usefulness which in turn depend on their application.
In financial markets, the conclusions reached by economics and finance
are far off the mark in terms of investing. If one were to listen to efficient
market theories one would reach the conclusion that there it is futile to try
to beat the market, and yet some people consistently beat it. Another way to
see the world is to use differentiated analysis to untangle cause and effect.
For instance, we observe that banking profitability increases in Brazil from
2003 to 2007. On the other hand, concentration of the industry increased, so an
financier-scientist gathers data, constructs measures of profitability and
concentration, runs some regressions and some tests and reached the conclusion
that indeed increased concentration and be associated with increased
profitability. However, more knowledge about the world will reveal that indeed
during 2003 and 2007 profitability increased in most countries. Now, the common
sense analysis will tell us that if most banking systems profitability
increased, it is probably due to some global factor during those years and not
to banking concentration in Brazil. It could be the case that banking
concentration increased in all countries during those years, which although
plausible does not seem to be the most reasonable explanation as each country
has its own competition regulator with different criteria to allow mergers and
acquisitions and different willingness of the banks themselves to consolidate.
So before spending months analyzing this hypothesis, it would be better to
investigate the system overall going back decades of history to try to
disentangle the most probable factor that might affect many banking systems at
the same time. Perhaps, a decrease in interest rates in the US. This
explanation seems more reasonable.
The next step would be to analyze banking profitability in other
instances in which the Fed decreased interest rates. We will observe that that
during the early 80s to mid-80s interest rates were decreasing and Reagan’s tax
cuts and star wars spending led to increasing deficits, at the same time bank
profitability increases and shares increased. However, not at the global level,
as in the 80s episode the dollar was rising and thus negatively affected
commodity prices and emerging-market banks. So as you can see, the analysis is
not so simple. However, with a lot of knowledge of different episodes,
variables, and countries one can begin to reach the most likely to be correct
conclusions and not the oftentimes spurious conclusions of so-called scientific
conclusion of tests.
Thus somebody like George Soros, without the technical tools of the
academic scientist can beat the market. Soros and other investors like him do
not assume that everything else is equal, but analyze the whole situation and
reach a more profitable and accurate conclusion for the specific situation at
hand.
In the meantime, economists are busy trying to reach generalizations,
knowledge useful for the long-run, for the average to try to obtain tendencies,
which are much less accurate and profitable for analyzing a specific situation.
Predicting Human Behavior and Knowledge
Moreover, trying to analyze complex problems requires, not only
information, but knowledge. That is the way in which that information is
processed to reach conclusions. Knowledge is virtually impossible to model with
equations and math. The creation of financial and business knowledge is long
process that takes years of thinking, reading, and using differentiating
analysis.
For instance, economists do not study the fundamentals of different
sectors of the economy. Balance sheets, income statements, and how specific
businesses make money. Thus they cannot know if a company will generate alfa.
Economist-scientists simply do not have the tools to make those predictions.
Those predictions are based on having the correct knowledge, not on econometric
tests or simulations.
So there are two main reasons economists do not get the most profitable
and accurate answers. At the global macro level, they do not take into account
the situation in its unique context, and they do not apply differentiating
analysis to generate knowledge that can serve to predict the evolution of a
specific problem in a specific context.
Second, economists trying to have far-reaching tools that can analyze
from the labor market to international finance, to game theory, simply do not
have the specific knowledge required to understand specific businesses in
specific sectors.
On the other hand, we have Warren Buffett how has studied specific
businesses all his life and is able to make a few accurate predictions among
thousands of businesses. This is enough to generate outstanding returns.
Moreover, as he demonstrated in his piece from 1984, there is a group of
investors with common style of investing that can produce superior returns
which is difficult to attribute to chance. It is easier to attribute to some
knowledge they share in common, namely, having a similar style of processing
information acquired from the same professor.
Simply, economics tries to do too much and ends up transmitting
inaccurate knowledge and inaccurate reach of its tools to those who studied it,
resulting on lost social welfare economic-scientific thinking has led to costly
financial crisis, among other things.
The scientific method consists of,
1.
Observation
2.
Hypothesis
3.
Testing
4.
Conclusion
Economics cannot do scientific testing as the environment is not kept
equal. Thus, the scientific method cannot be applied and reach true and
accurate conclusions. Economists can pretend to scientifically test by using
sophisticated statistical and econometrics tests on a complex mathematical
model, but that is just shifting the attention from the real problem. There is
no real scientific environment to be able to test the hypothesis.
Economists in academia can life until retirement pretending to do
science as there is colleagues confirm the conclusions that they are performing
scientific experiments. However, if an economist were to reach investing
conclusions and put the money in their scientific theories and lost it, I think
they would rethink the seriousness of the science.
It is easy to say that economics is wrong, but it is more difficult to
say with solid arguments in the language of economics why economics is wrong.
