–Who, in the world of economics, is asking for that next super-computer?

  Friday, Jun 22 2012

Uncategorizedcut debt, cut deficits, cut medicaid, cut medicare, cut social security, cut spending, cut taxes, cut the budget, grow the economy, MMT, modern monetary theory, monetarily non-sovereign, monetarily sovereign, monetary sovereignty, MS, stimulate economy, what is the federal debtRodger Malcolm Mitchell11:47 am

 

 

 

Mitchell’s laws:
●The more budgets are cut and taxes increased, the weaker an economy becomes.
●Until the 99% understand the need for federal deficits, the 1% will rule.
●To survive long term, a monetarily non-sovereign government must have a positive balance of payments.
●Austerity = poverty and leads to civil disorder.
●Those, who do not understand the differences between Monetary Sovereignty and monetary non-sovereignty, do not understand economics.

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First question: How much economic data is there? The Federal Reserve Bank of St. Louis’s

 

“FRED” service lists the following data categories:

Money, Banking, & Finance (3,812)
National Accounts (704)
Population, Employment, & Labor Markets (2,234)
Production & Business Activity (1,331)
Prices (1,613)
International Data (5,046)
U.S. Regional Data (31,376)

That’s about forty five thousand categories, with each category having thousands of individual data points – many millions of individual pieces of data – and that’s just from FRED alone.

Now add all the economic data from every nation on earth. Add all the data from every stock, commodity and financial exchange. Add all weather data from around the world. And all patent data. And all river/lake/ocean data. All geographical data. Add the compositions of the atmospheric layers. Add every position of the moon and the sun.

The list goes on and on, trillions upon trillions of individual data points — more than the number of water drops in the ocean (that too, is a data point).

Second question: Which of these data and combinations of data, has zero effect on the U.S. economy? There is reason to believe economics is a chaotic system, in which small changes can have large effects. In meteorology, which is a chaotic system, they call that the “butterfly effect,” whereby a butterfly flapping its wings in Africa can cross a tipping point that causes a hurricane to hit the New Orleans.

If economics is indeed a chaotic system, then all data – all trillions upon trillions of data points – affect the U.S. economy.

I again thought about that when I saw an article in the Global Economic Intersection describing The Conference Board’s Leading Economic Index (LEI) and Coincident Economic Index (CEI). They look like this:

The LEI has 10 categories and the CEI has 4 categories — at most a few thousand data points between them — an infinitesimal fraction of the data that affects the current status and the future status of the the U.S. economy. And because that tiny data is insufficient, the best the users can hope (emphasis on the word “hope”) to do is predict some generalizations about the economy, perhaps a couple months in advance.

In meteorological terms, this is like predicting the possibility of rain, two minutes in advance — virtually useless.

The problem is not a shortage of data. We have the data. We have the communications systems that can assemble the data. We have the ability to plug all this data into a multiple regression formula:

MULTIPLE REGRESSION ANALYSIS
by Amit Choudhury (2009)
Multiple regression analysis is a powerful technique used for predicting the unknown value of a variable from the known value of two or more variables- also called the predictors. More precisely, multiple regression analysis helps us to predict the value of Y for given values of X1, X2, …, Xk.
For example the yield of rice per acre depends upon quality of seed, fertility of soil, fertilizer used, temperature, rainfall. If one is interested to study the joint affect of all these variables on rice yield, one can use this technique.
An additional advantage of this technique is it also enables us to study the individual influence of these variables on yield.

In multiple regression analysis, adding variables generally increases accuracy. That is why the federal government is spending many millions of dollars to build a huge super-computer (100 racks of servers and 72,000 core processors, so many parts that they must be delivered in the back of a 747. It will be capable of performing 1.5 quadrillion calculations — a quadrillion is a 1 followed by 15 zeros — every second).

Unfortunately (for economists), the supercomputer will be used my meteorologists.

The Jun 12 2012 post titled, “Which is more important to our lives: Meteorology or Economics?” ended with this: “Considering its affect on human lives, economics is the most important science of all. So where are the super computers? We want that next machine. We need that next machine. The American people need us to have that next machine. My question is: Who in the world of economics, is asking for that next machine?”

Today, the science, most immediately to our lives, science uses a prediction system based on ten categories. Ten categories! It’s pitiful.

By its dollar allocation, the federal government seems to tell us, “Predicting the economy isn’t all that important. Understanding the future effects of present day Congressional decisions isn’t meaningful. The President really doesn’t need to know what his signing or vetoing of a bill will do to the economy, now or in the future.”

Wearing blindfolds, Congress and the President play darts. Their speeches assure us, they know exactly where their darts will land. Because of political considerations, they toss their darts in all directions. When the public complains that the darts have missed their target, Congress and the President, still wearing blindfolds, tell the Fed to move the dart board, somewhere. Then they throw again.

And this is how our economy is managed: Blindfolded.

The great nation of the United States of America needs to evaluate the future economic effects of present-day decisions. Just as with weather prediction, evaluating a handful of data won’t do it. We need to evaluate millions, even trillions, of data points.

So I ask again, “Who in the world of economics, is asking for that next super-computer?”

Rodger Malcolm Mitchell
http://www.rodgermitchell.com