Gross Output (GO) vs. Gross Domestic Expenditure (GDE) vs. Gross Domestic Transactions (GDT) and why we need to use readily available banking system data to estimate GDT

Mark Skousen is part of the Austrian economics heterodox tradition, and he promoted a measure called Gross Output (GO) as a measure of the economy. Skousen likes to quote Steve Forbes who called it “revolutionary” and such “a big deal” that Skousen “deserves a Nobel” for it. Forbes and Skousen think it is “far more comprehensive and accurate” than GDP because it reduces the measured share of consumption and net exports by double-counting some steps of the production process which boosts the measured size of business activity relative to government and consumption. I don’t share their ideological goal of making consumption seem like a smaller part of the economy, but Skousen did have one excellent point even though he didn’t take it to the logical conclusion.

Skousen wrote that, “Gross Domestic Expenditures (GDE) …includes gross sales at the wholesale and retail level …I estimate GDE in 2014 at over $37.5 trillion.” Skousen is trying to measure business transactions, but both GO and GDE seem to arbitrarily decide what transactions to include and what to exclude. Skousen argues that his measures would be more useful for analysis with the quantity theory of money: MV=PY, and this is true, but his measures are still incomplete for this purpose because ALL monetary transactions should be included. The variables in the equation are:

M = The quantity of Money.

V = Velocity of money (the number of times each unit changes hands on average).

P = The Price level.

Y = The total number of transactions.

The standard interpretation of the model defines Y as GDP, but that is completely wrong. It should be all transactions that money is used for or Gross Domestic Transactions (GDT). GDP only measures the final consumption and investment goods whereas probably most transactions are for intermediary goods and interpersonal transactions that are not counted in GDP. Fluctuations in the quantity of transactions (GDT) are undoubtedly correlated with fluctuations in GDP, but they won’t be the same thing as GDP. Skousen found that his measures show greater fluctuation than GDP because they include more intermediate transactions. That helps explain why the “velocity” of money used with GDP has much more volatility than standard theory would predict. In fact this was one of the failings of the 1960s monetarists. The velocity of money cannot be directly measured and is merely calculated using the above equation and solving for V=PY/M.  Although none of the other three variables are calculated perfectly, the habit of using GDP to measure Y must be the biggest source of error of all. Here is FRED’s official calculation for the velocity of money:

It really is hard to explain why it is so volatile, but perhaps it isn’t volatile and transactions just fluctuate a lot more than GDP like Skousen’s data suggest. The quantity theory of money predates the concept of GDP and was originally intended to be used with GDT, not GDP. But when GDP was developed, it came to be used for Y because we didn’t have anything any better.

Skousen’s measurements are closer to GDT, but they still fall far short. For example, just the ACH transaction volume alone reached $40 trillion in 2014 according to the National Automated Clearinghouse Association, and all cash transactions should be added to that number plus other electronic payments like PayPal that do not use the ACH system. The ACH system is the Automated Clearing House that all US banks use for reconciling all their electronic transfers and payments by check. Oddly, a Fed study estimated that the total non-cash transactions in 2015 totaled nearly $178 trillion which is over four times greater than the NACA estimate! I don’t know who is right, but in either case, the total value of transactions is clearly much larger than the $37.5 trillion that Skousen estimated for GDE.

Since Skousen is only measuring arbitrary subsets of total GDT, I’m not sure what his measures are good for, but his idea that we should use a broader measure of transactions in addition to GDP is excellent. We should start with just using the volume of ACH transactions. This information is already being collected daily by the banks that the Fed controls, so the Fed has the ability to make them provide this incredibly rich source of big data. It is incredible that it is being neglected! It could be more useful than GDP for monetary policy because it is collected daily rather than with long lags like GDP and is measured incredibly precisely, much more precisely than GDP can ever hope to be measured. And, as Skousen points out, there are advantages to attempting to measure more transactions rather than just final output. Ideally we should measure GDT, and we can get very close by just using the ACH system that the Fed already controls, but isn’t using for some strange reason.

The Fed has over a half million different timeseries of data including trivia like the number of Automated Teller Machines (ATMs), in Zambia and most other countries of the world. Using the quantity of transactions recorded daily in the ACH system would be much more important for the Fed’s primary mandate, setting monetary policy and stabilizing the banking system.

And if there is some technical reason why America’s ACH system hasn’t been collecting the data every day, it is because our system is incredibly antiquated and needs to be updated and streamlined. Planet Money did a nice podcast about the ridiculous secrecy surrounding the system and its ridiculous inefficiency compared to the system in Britain and presumably in many other countries although if other nations are as secretive as the US, it could be hard to find out.

Posted in Macro

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