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Getting It Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy
Published by EH.Net (July 2012)
William A. Barnett, Getting It Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy. Cambridge, MA: MIT Press, 2012. xxxiii + 322 pp. $35 (paperback), ISBN: 978-0-262-51688-4.
Reviewed for EH.Net by J. Peter Ferderer, Department of Economics, Macalester College.
It is widely agreed that excessive risk-taking led to the sub-prime financial crisis and the Great Recession. Mortgages without down payments, historically high leverage ratios, maturity mismatch, and the list goes on. What were people thinking? Was it mass hysteria? Was it greed gone wild?
In Getting It Wrong, William A. Barnett, the Oswald Distinguished Professor of Macroeconomics at the University of Kansas, places blame squarely on the shoulders of the Federal Reserve Board in Washington, DC. He argues that the quality of monetary data provided by the Board has been declining for decades at the same time that the need for good data has grown due to the increasing complexity of financial markets and instruments. Unable to accurately measure the amount of liquidity in the system, the Fed has lurched between overly expansionary policies that fueled bubbles to excessively restrictive ones that have produced unnecessarily deep recessions. Because the public was left in the dark, they mistakenly attributed the Great Moderation to better monetary policy and misperceived it to be a permanent feature of the macroeconomic landscape. As a consequence, lenders, borrowers, Wall Street firms and just about everyone did what was rational – they took on more risk.
Barnett is well qualified to offer this critique. He was a staff economist at the Federal Reserve Board between 1973 and 1981 when financial innovation created the “missing money” problem and Paul Volcker led the great monetarist experiment. Barnett left the Fed for a series of university professorships in the early 1980s, has made numerous contributions to the literature on monetary aggregation, and is the editor of Macroeconomic Dynamics.
Barnett’s main criticism of the Fed is that it does not utilize state-of-the-art aggregation theory to measure the quantity of monetary services in the economy. Instead, it relies on simple-sum aggregates that are fundamentally flawed. For instance, M1 underestimates the amount of monetary services available in the economy because it excludes savings accounts and other near-monies. In contrast, the broader aggregates – M2, M3 and L – overestimate monetary services because they give equal weight to, in the case of M3, currency and CDs. If apples and cars are given different weights when GDP is calculated, shouldn’t we do the same when measuring the amount of money in the economy?
Barnett originated the Divisia Index in the early 1980s to address this problem. The Divisia Index weights a monetary asset by its “user-cost price” measured as the difference between the asset’s own interest rate and the rate earned on the best available pure investment. Thus currency and checkable deposits, which earn no interest, receive large weights. Savings accounts, CDs and other instruments, which earn interest as compensation for their illiquidity, receive smaller weights. One of the central claims of Getting It Wrong is that the velocity of money is stable once money is properly measured using the Divisia Index. Thus the equation of exchange (MV = PY) can be used to guide monetary policy and stabilize the macroeconomy.
For Barnett the Board’s data mismanagement does not end with their unwillingness to embrace the Divisia Index. He describes the practice of publishing data on checking-account deposits after banks “sweep” funds to money market deposit accounts as an attempt to “cover up reserve requirement evasion” and a “scandal” (p. 143). This practice causes demand deposits to be underreported by 50 percent, “rendering M1 monetary aggregate data nearly useless” (p. 132). Also, the Fed tossed the baby out with the bath water in 2006 when it stopped reporting M3, L and their component aggregates. One of these component assets, repurchase agreements, is the quasi-money created by the shadow banking system and greater transparency here might have reduced risk-taking prior to the sub-prime crisis.
Why has the Federal Reserve Board done such a poor job measuring “the most fundamental variable over which a central bank does have influence – money?” (p. 34). According to Barnett, the public was deliberately kept in the dark so the Fed would be less accountable for its policies. Barnett provides many cloak-and-dagger stories from his years at the Fed to build a case for this hypothesis. For example, he describes how his superiors at the Board blocked his attempts to communicate about the Divisia Index with Board governors and recounts a case where the FBI was brought in to investigate colleagues for leaking interest rate data that was already publically available. The Federal Reserve Bank of St. Louis carried the torch by publishing the Divisia Index for years, but Barnett suggests that they stopped doing so as the sub-prime financial crisis began due to political pressure from the Board.
Barnett provides a valuable service by exposing the Fed’s poor data management. Moreover, his main policy proposal – the creation of a Bureau of Financial Statistics along the lines of the Bureau of Labor Statistics – makes a great deal of sense. Nevertheless, I am not convinced by his argument that defective monetary data was largely responsible for excessive risk-taking prior to the financial crisis.
First, it is problematic to argue that increasingly defective monetary data simultaneously caused (i) the Fed to make more policy errors, and (ii) the public to believe that the macroeconomy had become more stable. These two phenomena can occur at the same time if some third factor caused the business cycle to become less variable, but Barnett is silent on what that might be. An alternative explanation is that monetary policy did improve and contribute to the Great Moderation, but the stability was ultimately destabilizing because it caused agents to reduce their margins of safety.
Second, the public could gauge the stance of monetary policy using the Taylor rule and did not need monetary aggregates, simple-sum or Divisia, to do so. In the years leading up to the sub-prime crisis the Fed kept the fed funds rate too low for too long. It presumably did so out of concern that the U.S. would experience a Japanese-like debt deflation after the dot-com bubble burst. It appears that the public largely ignored the signal sent by the low fed funds rate – both in terms of what it implied about the stance of policy and the Fed’s willingness to adhere to rules – and continued to take on more risk. This suggests that other factors like moral hazard or the availability heuristic (probability judgments based on how easily examples come to mind) explain the excessive risk-taking.
Finally, cross-country evidence is inconsistent with the hypothesis that defective central bank data played a pivotal role. For example, the Bank of England is Barnett’s poster child for proper data management with its longstanding and transparent use of the Divisia monetary aggregates and yet the recession in the United Kingdom has been deeper and longer than that experienced in the United States.
I agree with Barnett when he demands, in the words of fictional NFL wide receiver Rod Tidwell, that the Fed should “Show Me the Money!” Clearly, the benefit-to-cost ratio of publishing better monetary data is very large. However, it is a stretch to suggest that defective monetary data was the principle cause of the excessive risk-taking leading up to the sub-prime financial crisis. To better understand this phenomenon we need to step outside of mainstream economic theory, which Barnett defends so admirably, and take seriously the heuristics and biases that characterize human decision making.
J. Peter Ferderer is currently working on a book which examines the development of the over-the-counter securities markets over the past two centuries.
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