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Fed’s Poor Data, Not Greed, Drove Wall Street Off Cliff: Books

February 17, 2012

Feb. 16 (Bloomberg) -- Pick a rogue, any rogue: Villains pervade the story of the worst financial train wreck since 1929.

Yet economist William A. Barnett resists the urge to wag a scolding finger at greedy bankers, feckless homebuyers or even Alan Greenspan, whom he calls a salesman, not a monetary maestro.

“While there is plenty of blame to spread around, something deeper has happened and needs to be understood to recognize the real source” of the crisis, says Barnett, a former Federal Reserve Board staffer.

That “something” was shoddy monetary data and how it fooled some of the smartest people on Wall Street, he argues in “Getting It Wrong,” an important contribution to our understanding of the $2 trillion meltdown.

Barnett is a professor at the University of Kansas who started out as a rocket scientist -- “a real one,” he says, at a company that developed engines for the Apollo space project. He specializes in a corner of economic measurement known as index-number and aggregation theory.

This sounds like daunting stuff, and it is. The second part of the book brims with mathematical formulas and arcane argot -- talk of vectors, intertemporal utility and strict quasiconvexity.

No matter. Barnett doesn’t expect lay readers to grind through the calculations. Eager to make his insights accessible, he devotes the first part of the book to making his argument in (mostly) plain English.

Poor and Useless

The Fed’s monetary data are poor, inadequate and “nearly useless to the public,” he says. The totals suffer from the common error of adding apples and oranges or, as he puts it, subway trains and roller skates.

Suppose you were measuring New York City’s transportation services. You wouldn’t assign equal weight to trains and skates, would you? Yet that, in essence, is what the Fed does when it measures the money supply. The M2 measure, for example, is a “simple-sum” aggregate: It merely adds up the dollar amounts of assets including currency, demand deposits, savings accounts and some certificates of deposit.

Dollar bills and CDs aren’t the same, of course. Cash pays zero interest, for starters. It’s also more liquid -- more useful as a medium of exchange -- than money parked in a CD.

To avoid adding apples and oranges, Barnett originated Divisia monetary aggregates, which are named after Francois Divisia, a Frenchman who published groundbreaking work on consumer-goods indexes in the 1920s.

Liquid Components

Adapted to financial assets, Divisia measurements give the greatest weight to the most liquid components, or those “most used in transactions,” as a Bank of England paper puts it. This offers a more accurate reflection of the money actually being spent in the economy (or, to be precise, the “monetary services in the economy”).

Barnett’s argument culminates in two fever-line charts. They indicate that the nation’s money supply in recent decades grew at a far faster pace, when measured by Divisia, than the Fed’s data suggest.

For M1, Divisia shows about $400 billion more being added to the money supply from 1980 to 2005 than the Fed’s simple sums record. For M2, the deviation increased by an astonishing $2 trillion.

The charts offer a clue about why many Wall Street bankers were lulled into thinking that Maestro Greenspan had engineered a Great Moderation, inducing them to ratchet up leverage.

Feeding the Bubbles

The graphs also suggest that the data may have misled the Fed itself: “The Federal Reserve could have been feeding the asset bubbles without the Fed’s being aware of it,” Barnett says.

After the housing bubble sprang a leak, the Fed unwittingly tightened the money supply, judging from two additional Divisia charts displayed here. One shows the monthly rate of money growth in the past two years plunging to negative levels. The picture grows even more disturbing in the second graph, which presents year-over-year growth rates.

“The monetary tightening, leading into the financial crisis and recession, is the largest and most precipitous that has occurred over the entire 42-year period for which the data were available,” Barnett writes.

The U.S. government has no excuse for not compiling and distributing better data, and Barnett is right to press the issue. Yet his thesis makes me somewhat uneasy.

Blaming the Data

In the bubble years, all too many economists supported the dangerous notion that the Fed had succeeded in taming the business cycle. Now they may be tempted to use Barnett’s admirable book as an excuse: The data made us do it.

No, they didn’t. Mavericks including Robert Shiller and Nouriel Roubini didn’t require finely tuned monetary aggregates to predict that the bubble would end badly. All anyone needed, really, was skepticism and context.

Excessive borrowing has turned lethal throughout financial history, from 14th-century Florence to Lehman Brothers Holdings Inc. Another recurring theme is that an ongoing boom won’t end in bust because we’re smarter now, a fallacy Carmen Reinhart and Kenneth Rogoff discredit in “This Time Is Different.”

No amount of improved data can prevent rational people from doing irrational things, especially when bonuses beckon. In the end, mankind always falls for “lies, damned lies and statistics.”

“Getting It Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System and the Economy” is from MIT Press (322 pages, $35, 24.95 pounds). To buy this book in North America, click here.

(James Pressley writes for Muse, the arts and leisure section of Bloomberg News. The opinions expressed are his own.)

--Editors: Laurie Muchnick, Jeffrey Burke.

To contact the writer on the story: James Pressley in Brussels at

To contact the editor responsible for this story: Manuela Hoelterhoff at

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