Prediction Record of the US Federal Reserve: The Sun Will Come Out Tomorrow

The US Federal Reserve’s supposed transparency has only been exposing their string of serial forecasting blemishes.

Evan Solitas has been tracking the Fed’s performance and observed, (bold emphasis mine)

The Bernanke Fed has made a significant effort since June 2009, when the NBER judges the recession to have ended, to increase transparency by providing guidance about future policy and macroeconomic forecasts. What is striking, however, is how this transparency has not prevented in the slightest the intellectual dishonesty in ignoring its failure to meet its own goals.

A disparaging but not unfair comparison would be to little orphan Annie. "The sun'll come out tomorrow," Annie sang. "Bet your bottom dollar that tomorrow there'll be sun." The 3-to-4 percent recovery growth we've been long promising will come out tomorrow, the FOMC basically says every quarterly meeting. Bet your bottom dollar that tomorrow there'll be lower unemployment.

The Fed must love tomorrow. Because, as they say, it's always a day away.

What I mean by this is the Fed makes projections, misses them by miles and consistently in the wrong direction, and then doesn't own up to it. They just push back their forecast. The forecasts are not inappropriately optimistic, either -- it's just that the Fed's actions have fallen short, and that there is zero accountability to target the forecast.

Their transparency, however, allows us to demonstrate thoroughly the extent of this failure.

Their fundamental error: the haughty assumptions that human action can be aggregated into mathematical expressions similar to natural sciences or positivism.

The late economist Percy Greaves lucidly explained of the mainstream’s basic shortcomings (bold emphasis mine)

Reason and experience show us that there are two separate realms: the external world of physical, chemical, and physiological phenomena, and the internal world, in our minds, of our thoughts, feelings, valuations, and purposes in life. There is no bridge connecting these two spheres. They are not connected automatically. We always have the right to choose our actions. Identical external events often produce different human reactions, and different external events sometimes produce identical human actions. We do not know why.

So, the science of human action is different from the physical sciences. We cannot experiment with human beings except in a physiological, medical, or biological sense. In the realm of ideas, we cannot experiment as we can in the physical sciences. We cannot duplicate situations in which all things are maintained the same as before. We cannot change one condition and always get the same consequences. We cannot experiment with human actions, because the world, its population, its knowledge, its resources are all constantly changing and cannot be held still.

In economics we must use our minds to deduce our conclusions. We have to say, Other things being equal, other things being the same, this change will produce such and such an effect. We have to trace in our minds the inevitable results of contemplated changes. We are dealing with changeable human beings. We cannot perform actual experiments, because the human conditions cannot be duplicated, controlled, or completely manipulated in real life like chemical experiments in a laboratory. Therefore, there are great differences between economics and the physical sciences. We cannot experiment and we cannot measure. There are no constants with which to measure the actions and the forces which determine the actions and the choices of men. In order to measure you must have a constant standard, and there is no constant standard for measuring the minds, the values, or the ideas of men.

More, Federal Reserve (central bank) 'experts' are unlikely to produce unorthodox or radical or ‘out of the box’ thinking as they are supposed to uphold the institutions that employ them, thus the “zero accountability”. It's not about being right or wrong but what needs to broached by such institutions.

Bluntly put, their studies are basically designed to rationalize or justify the existence of their institutions. You may call this biased analysis. Also the conflict of interests between politicized money and the citizenry highlights the agency problem or the principal agent dilemma.

And such outlook applies to almost all political and politically affiliated institutions.

Why is this important? Because the Fed or central bank policies or centrally planned monetary actions have essentially been derived from their analysis or outlook.

And analysis with consistently large deviance from economic reality would only translate to high probability that their accompanying actions would have negative implications or consequences than the intended or expected goals or objectives.

Policy errors, thus, are likely to be the rule than the exception.

In short, we shouldn’t trust central bankers. We don’t even need them.

Thus, prudent investors need to anticipate of such centrally planned monetary misdiagnosis-malpractice, and take appropriate action to protect or insure themselves from their adverse effects.

Don’t forget half of every transactions we make has been coursed through political (fiat legal tender based) money. And distortions of the economics of money through interventions only extrapolates to parallel disruptions in the production or economic structure. This is why boom bust cycles and hyperinflation exists.

Quote of the Day: Blinded by Science

Even some from the mainstream gets it.

Finance is often said to suffer from Physics Envy. This is generally held to mean that we in finance would love to write out complex equations and models as do those working in the field of Physics. There are certainly a large number of market participants who would love this outcome.

I believe, though, that there is much we could learn from Physics. For instance, you don’t find physicists betting that a feather and a brick will hit the ground at the same time in the real world. In other words, they are acutely aware of the limitations imposed by their assumptions. In contrast, all too often people seem ready to bet the ranch on the flimsiest of financial models.

Someone intelligent (if only I could remember who!) once opined that rather than breaking the sciences into the usual categories of “Hard” and “Soft,” they should be split into “Easy” and “Difficult.” The “Hard” sciences are generally “Easy” thanks to the ability to perform repeated controlled experiments. In contrast, the “Soft” sciences are “Difficult” because they involve trying to understand human behaviour.

Put another way, the atoms of the feather and brick don’t try to outsmart and exploit the laws of physics. Yet financial models often fail for exactly this reason. All financial model underpinnings and assumptions should be rigorously reviewed to find their weakest links or the elements they deliberately ignore, as these are the most likely source of a model’s failure.

That’s from GMO’s James Montier (source Zero Hedge).

Mr. Montier also discusses the psychological aspects of people’s predisposition for mathematical or science based models: particularly “complexity to impress” (The penchant to signal “intelligence” to acquire social acceptance—my opinion) and “defer to authority”.

And here is the warning against being blinded by science from the dean of the Austrian school of economics the great Professor Murray N. Rothbard,

Not only measurement but the use of mathematics in general in the social sciences and philosophy today, is an illegitimate transfer from physics. In the first place, a mathematical equation implies the existence of quantities that can be equated, which in turn implies a unit of measurement for these quantities. Second, mathematical relations are functional; that is, variables are interdependent, and identifying the causal variable depends on which is held as given and which is changed. This methodology is appropriate in physics, where entities do not themselves provide the causes for their actions, but instead are determined by discoverable quantitative laws of their nature and the nature of the interacting entities. But in human action, the free-will choice of the human consciousness is the cause, and this cause generates certain effects. The mathematical concept of an interdetermining "function" is therefore inappropriate.

Video: Economics is Fun: Why Economics Isn't (Natural) Science

Dr Madsen Pirie of Adam Smith Institute does a great job in explaining vivaciously why economics isn't (natural) science, which conventional practitioners try to mold them into--through statistical or econometric models.

Here's a good quote [1:07]

When an economist tries to simplify it by leaving out stuff by, so that a small model can be created you have assumed away the real world.

(hat tip Greg Ransom)



Economics is the youngest of all sciences to quote the great Ludwig von Mises.

And it is important to note that the science of economics represents a subdiscipline to the science of human action. Again Professor Mises in his magnum opus Human Action,

The scope of praxeology is the explication of the category of human action. All that is needed for the deduction of all praxeological theorems is knowledge of the essence of human action. It is a knowledge that is our own because we are men; no being of human descent that pathological conditions have not reduced to a merely vegetative existence lacks it. No special experience is needed in order to comprehend these theorems, and no experience, however rich, could disclose them to a being who did not know a priori what human action is. The only way to a cognition of these theorems is logical analysis of our inherent knowledge of the category of action. We must bethink ourselves and reflect upon the structure of human action. Like logic and mathematics, praxeological knowledge is in us; it does not come from without.

All the concepts and theorems of praxeology are implied in the category of human action. The first task is to extract and to deduce them, to expound their implications and to define the universal conditions of acting as such.

And the difference between the science of human action from natural science in the words of Mises (emphasis added)

WHAT differentiates the realm of the natural sciences from that of the sciences of human action is the categorical system resorted to in each in interpreting phenomena and constructing theories. The natural sciences do not know anything about final causes; inquiry and theorizing are entirely guided by the category of causality. The field of the sciences of human action is the orbit of purpose and of conscious aiming at ends; it is teleological.

Both categories were resorted to by primitive man and are resorted to today by everybody in daily thinking and acting. The most simple skills and techniques imply knowledge gathered by rudimentary research into causality. Where people did not know how to seek the relation of cause and effect, they looked for a teleological interpretation.

Quote of the Day: Financial Markets will Never Be an Exact Science

The factors that determine activity on the Exchange are innumerable, with events, current or expected, often bearing no apparent relation to price variation. Beside the somewhat natural causes for variation come artificial causes: The Exchange reacts to itself, and the current trading is a function, not only of prior trading, but also of its relationship to the rest of the market. The determination of this activity depends on an infinite number of factors: It is thus impossible to hope for mathematical forecasting. Contradictory opinion about these variations are so evenly divided that at the same instant buyers expect a rise and sellers expect a fall.

The calculus of probability can doubtless never be applied to market activity, and the dynamics of the Exchange will never be an exact science. But it is possible to study mathematically the state of the market at a given instant—that is to say, to establish the laws of probability for price variation that the market at that instant dictates. If the market, in effect, does not predict in fluctuations, it does assess them as being more or less likely, and this likelihood can be evaluated mathematically.

That’s from the opening lines of “Theorie de la Spéculation” by 20th century French Mathematician Louis Bachalier (1870-1946). Mr Bachalier has been credited with being the first person to model the stochastic process now called Brownian motion, which was part of his PhD thesis The Theory of Speculation, (published 1900). [Wikipedia.org]

Source: Benoit B. Mandelbrot and Richard L. Hudson, The (Mis) Behaviour of Markets p.51

Quote of the Day: Discontinuity

Financial prices certainly jump, skip, and leap—up and down. In fact, I contend the capacity for jumps, or discontinuity, is the principal conceptual difference between economics and classical physics. In a perfect gas, as molecules collide and exchange heat, their billions of individually infinitesimal transactions collectively produce a genuine “average” temperature, around which smooth gradients lead up or down the scale. But in a financial market, the news that impels an investor can be minor or major. His buying power can be insignificant or market-moving. His decision can be based on an instantaneous change of heart, from bull to bear and back again. The result is a far wilder distribution of price changes: not just price movements, but price dislocations.

That’s from the illustrious French American mathematician and author Benoit Mandelbrot (November 20, 1924—October 14, 2010) in his bestseller, The (Mis)Behavior of Markets: a fractal view of risk, ruin and reward (p.237).

It is important to note that a distinguished mathematician can spot the indispensable difference between ‘discontinuity’ as consequence of human action with that of the ‘averages’ as an output of natural ‘physics’ sciences.

Flaws of Economic Models: Differentiating Social Sciences from Natural Sciences

David Freedman of the Scientific American asks “Why Economic Models Are Always Wrong?”

He gives the answer,

The problem, of course, is that while these different versions of the model might all match the historical data, they would in general generate different predictions going forward--and sure enough, his calibrated model produced terrible predictions compared to the "reality" originally generated by the perfect model. Calibration--a standard procedure used by all modelers in all fields, including finance--had rendered a perfect model seriously flawed. Though taken aback, he continued his study, and found that having even tiny flaws in the model or the historical data made the situation far worse. "As far as I can tell, you'd have exactly the same situation with any model that has to be calibrated," says Carter.

That financial models are plagued by calibration problems is no surprise to Wilmott--he notes that it has become routine for modelers in finance to simply keep recalibrating their models over and over again as the models continue to turn out bad predictions. "When you have to keep recalibrating a model, something is wrong with it," he says. "If you had to readjust the constant in Newton's law of gravity every time you got out of bed in the morning in order for it to agree with your scale, it wouldn't be much of a law But in finance they just keep on recalibrating and pretending that the models work."

We can’t simplify, through mathematical models, what truly is a highly complex environment. Repeated “recalibrating their models” or “calibration problems” only exposes on these structural analytical errors.

The ultimate reason why economic models are always wrong is that investigations have been patterned after natural sciences. Yet analyzing natural sciences isn’t the same as social sciences. That’s what modelers and their disciples cannot seem to grasp.

The great Ludwig von Mises draws a clear distinction between the two sciences, (bold emphasis mine, italics original)

Since the elements of social cognition are abstract and not reducible to concrete images one would like to have metaphors. First there were biological metaphors, now mostly mechanistic ones. These are based in positivist view of social science that holds that social science should be built up by experimental method as ideally applied in Newtonian physics. Economics becomes experimental, mathematical and about measurement. This is all wrong:

1. Social sciences cannot be based on experience like the natural sciences. Social experience is of a complexity and cannot be experimented with

2. Therefore the social sciences can never use experience to verify their statements. Every fact and experience is open to multiple interpretations (but see Kuhn. KS)

3. The impossibility of experimenting implies the impossibility of measurement. In human behavior there are no invariable relations like there are between physical properties, which means that it is pointless to mathematize them in order to make predictions. Statistics merely studies history.

4. Mathematics does not deal with actual operations of human actions but with a fictitious concept, static equilibrium (tomorrow is like today, no uncertainty), that economists build up for instrumental purposes. But not only is this unrealistic, it is also inconsistent for lack of uncertainty and change implies lack of actions. The only purpose mathematics can have in economics is the study of the nature of relations between costs and prices and thereby of profits.

5. Mathematics cannot tell us how the market arrives at a static equilibrium.

6. Mathematicians are prone to consider the price either as measurement of value or as equivalent to the commodity. But prices are neither; they are simply the amount of money exchanged for a commodity and there is reversed valuation.

Economics deals with human action, not with objects (as physics does) such as commodities, economic quantities or prices. Therefore economists do not consider their subject matter from without, but from within, through our own understanding of what it is to be human and to act. What makes natural science possible is the power to experiment, what makes social science possible is the power to grasp the meaning of human action….

Social sciences have a distinct method, praxeology and verstehen, due to the special character of their objects, and owe their progress through it and do not have to and cannot use the method of the natural sciences.

Praxeological concepts refer exactly and with certainty to the reality of human action because both the science of human action and human action itself have their toot in human reason. The quantitative approach would not render them more exact.

Nobody denies that economics is not perfect yet, but:

1. the present unsatisfactory state of social and political affairs is not due to deficiencies in economic theory, but in policy. People just don’t use economic theory enough.

2. even if economics needs to be drastically reformed someday it cannot take the direction proposed by those who use the model of the natural sciences. This idea has been thoroughly refuted forever.

Again many people seem to find comfort in models, for many possible reasons such as social signaling, conversation, career, politics and others.

But in terms of the predictive value, as the Scientific American article’s inquiry as indicated by the title, economic models have always been wrong.

Cities, Mathematics and Human Action

Below is an interesting talk by physicist Geoffrey West at the TED forum on Cities.

Some points he makes;

-It’s hard to kill a city.

-He places tremendous emphasis on the scalability phenomenon where he connects size with social impact, e.g. bigger city bigger wealth more AIDs

-However he says that optimism bias tends to prevail over the city’s growth dynamics where people tend to see ‘wonderful things and forget the ugly and bad’

-He rightly points out that social networks are key to the growth of cities; ‘We are the city’ which is a result of people’s “clustering interaction”.

-Further he says that for cities to develop it needs ‘faster innovation in a continuous basis’.

-Lastly he says that he can predict the size of a city or company given the sublinear scaling from ‘sigmoidal growth’

Here are my thoughts

It’s interesting to see how mathematically inclined people try to quantify people’s actions.

In the past killing a city or a decline of relevance or marginal utility of a city comes in the form of war (Nineveh, Babylon, Selucia, Carthage, Rome, Pagan and Angkor Wat as examples), change in economic patterns (introduction of Cape Good lead to the decline of Venice) natural calamity (Pompeii) or cyclical-behavioral-political elements- such as overconfidence, which led to overexpansion or lack of diversity (fall of Rome).****

In addition, scale does not automatically translate to magnitude.

In history, autonomous small cities played vital role as Amalfi, Cadiz, Goa, Batavia, Geneva, Abu Dhabi and Monaco.*** Today we have semi-independent city states as (pre-China) Hong Kong and Singapore.

Social network is indeed important. But Professor West does not specify how social network would result to “clustering interaction”. Are cities politically or economically driven?

In the past, strong arm societies depended on the capability of leaders, such as Alexander the Great, Attila the Hun, Genghkis Khan, Timur, Akbar, and Kublai Khan***. When they passed away so did their respective empires and cities.

History shows that many cities emerged from trading routes and proximity thereof, particularly in coastal areas (Tripoli, Sidon, Carthage, Athens, Marseille, Syracuse, in recent centuries Venice, Famagusta, Genoa, Constantinople, Kafffa, Lisbon and etc.)***

Many factors are involved in city dynamics: some of the important ones are economic growth cycles, legal systems, economic freedom, infrastructure, adherence to property rights, (in the past) military power [Assyrians, Romans, Mongols], political climate or conditions (interaction between minority and majority, in the past conflict resulted to dislocations which have caused diasporas of Jews, Huguenots, Armenians) innovation and intellectual tolerance.

To quote the legendary investor Marc Faber***,

A dynamic society arises where there is also intellectual tolerance freedom of conscience, social mobility, freedom of ideas, and the expression of ideas which may be hostile to established beliefs or to the government. Where intellectuals, scientist, and philosophers were persecuted, imprisoned, tortured or murdered, they fled. But it is in their know-how on which progress depends.

Deidre McCloskey would call this the Bourgeois Virtue.

And it is upon this climate of free interaction by people which induces Professor West’s innovation dynamics.

An example from the local setting:

In the Philippines, Manila as the Philippines’ capital played a pivotal role economically (Manila-Acapulco Galleon Trade) and also had been politically important; under American rule Daniel Burnham planned a government center spanning Luneta to Taft which almost like every centrally planned projects failed.

Today, Manila’s relevance has been apparently declining, in terms of population growth and per capita income.

While Manila still has the second largest population second only to Quezon City, the growth rate has been stagnating and relatively underperforming against a vibrant Quezon City according to the 2007 census. The fastest growth rate is seen in Taguig, Paranaque and Kalookan City.

Manila still has the largest population density

However, in terms of per capita GDP, Manila ranks 5^th to the following order Makati, Mandaluyong, San Juan and Muntinlupa (Wikipedia).

The obvious point is that city scale and magnitude while having some correlation does not exhibit strong causation. The huge gap in Professor West’s talk is how social interaction has led to city dynamics.

I have stated why I am a skeptic of centrally planned urbanization as this runs contrary to the forces of technology enabled decentralization. The obvious evidence can be seen in several 'huge' but empty ghost cities in China which are products of politically induced bubble cycles.

Finally Professor West says that he can predict growth dynamics of companies and cities from “sublinear scaling”.

My guess is by now he should have bettered the record of Warren Buffett as an investor.

I am reminded by the admonitions of the great Ludwig von Mises of relating natural sciences with social or human actions,

Nothing could be more mistaken than the now fashionable at­tempt to apply the methods and concepts of the natural sciences to the solution of social problems. In the realm of nature we cannot know anything about final causes, by reference to which events can be explained. But in the field of human actions there is the finality of acting men. Men make choices. They aim at certain ends and they apply means in order to attain the ends sought.

***Nury Vittachi Doctor Doom Riding the Millennial Storm