Beyond the Fed: “Shadow Banking” and the Global Market for Dollars
[This article is part of the Understanding Money Mechanics series, by Robert P. Murphy. The series will be published as a book in 2021.]
Although it conjures up scary imagery, shadow banking is simply a term for banking operations that occur through financial intermediaries that are not traditional commercial banks. The term was coined in 2007 by economist Paul McCulley and is related to the fact that standard banking regulations often do not apply to nonbank institutions (such as hedge funds and private equity lenders), which are hence operating “in the shadows.” According to estimates of nonbank credit intermediation made by the Financial Stability Board, “the global shadow system peaked at $62 trillion in 2007, declined to $59 trillion during the crisis, and rebounded to $92 trillion by the end of 2015.”1
The existence of a shadow banking system thus limits the ability of governments to regulate the credit markets if they merely restrict attention to traditional banks. To understand the mechanics of today’s monetary system, it is therefore important to recognize that the nexus between savers and borrowers doesn’t necessarily flow through a commercial bank, the way economics textbooks often imply.
Similarly, American textbook treatments often provide a USA-specific viewpoint, even though in reality there is a global market for US dollars. In this chapter we will provide an overview of these complications to give a more accurate description of money and banking practices.
Mises and Hayek on Regulation versus Economic Reality
Although they didn’t use the term “shadow banking,” the Austrian economists Ludwig von Mises and Friedrich von Hayek made observations consistent with the theme of this chapter. Mises argued that Peel’s Act of 1844 failed in its attempt to mitigate the business cycle because it limited the ability of banks to issue paper banknotes unbacked by gold but didn’t limit banks’ ability to issue customer checkbook deposits. This inconsistent regulation—which ignored the economic equivalence between banknotes and “checkbook money”—ended up discrediting the Currency school, which (in Mises’s view) correctly perceived unbacked bank credit as the source of business instability.2 See chapter 9 for more on Mises’s theory of the boom-bust cycle, and see this chapter’s endnotes for an academic paper extending Misesian business cycle theory in light of shadow banking.3
For his part, Hayek in a 1931 lecture gave a very modern statement of the issues involved with shadow banking, though he did not use the term:
[I]t is necessary to take account of certain forms of credit not connected with banks which help, as is commonly said, to economize money, or to do the work for which, if they did not exist, money in the narrower sense of the word would be required. The criterion by which we may distinguish these circulating credits from other forms of credit which do not act as substitutes for money is that they give to somebody the means of purchasing goods without at the same time diminishing the money spending power of somebody else. This is most obviously the case when the creditor receives a bill of exchange which he may pass on in payment for other goods. It applies also to a number of other forms of commercial credit, as, for example, when book credit is simultaneously introduced in a number of successive stages of production in the place of cash payments, and so on. The characteristic peculiarity of these forms of credit is that they spring up without being subject to any central control, but once they have come into existence their convertibility into other forms of money must be possible if a collapse of credit is to be avoided. (bold added)4
These brief references illustrate that economists have been aware of the issues surrounding shadow banking for a century. The specific market structures may be new, but the issue is not.
Shadow Banking during the Housing Boom
The nature and potential problems with the shadow banking system became apparent during the housing boom of the 2000s. To illustrate, we can consider a typical example: suppose in 2006, during the height of the boom, a couple in Phoenix applies for a traditional mortgage at their local bank. The bank approves the application and lends the money to the couple, who then buy the house, which serves as the collateral on the loan. However, rather than holding the mortgage for thirty years as an asset on its own books, the commercial bank in Phoenix turns around and sells it to a major investment bank in New York.
The Wall Street–based investment bank then takes the mortgage tied to the home in Phoenix and packages it with hundreds of other mortgages tied to houses across the United States, in order to create a “mortgage-backed security” (MBS). Every month, the incoming mortgage payments from the homebuyers across the country flow into the bucket represented by the MBS. The investment bank then sells “tranches” of the MBS to other investors, and these tranches have different risk characteristics. For example, the safest claims represent the lowest “slice” of the bucket being filled each month, whereas the riskiest claims point to the highest “slice” of the bucket. If, in a given month, some of the homebuyers fall behind on their mortgage payments, then the top slices of the bucket do not get filled, and the investors holding those particular tranches don’t get paid. This relative risk was reflected in the original (lower) price for these tranches, however; there was a chance to make a higher rate of return if things went well, but it came with a higher risk of loss.5
In contrast, those investors who purchased the safest tranches of the MBS thought they were being quite prudent—and indeed, the credit ratings agencies (such as Moody’s, Fitch, and S&P) agreed with them, giving these complex derivative assets triple-A ratings. Because the pool of mortgages was spread across the country, and because people believed “real estate was local,” it seemed very unlikely that homebuyers would fall behind in their mortgages for the whole bucket. Even though the credit agencies’ computer models recognized that, say, the Phoenix real estate market could suddenly crash 20%, that same outcome happening in Miami or San Francisco was treated as an independent statistical event. In retrospect, what actually happened—namely, all of the major US real estate markets crashed simultaneously—had been modeled as a once-in-a-thousand-years scenario.
Because the major ratings agencies gave their highest seal of approval to (certain types of) derivative assets tied to mortgages, pension funds and other institutional investors—including foreign ones—were allowed to gain exposure to t
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