Annex 1. Collateral and Money Aggregates
In this box, we integrate the collateral angle to the traditional money metrics. Typically, the role of collateral plays in money markets is often overlooked in macroeconomics. The renewal of quantitative easing (QE) in response to the Covid-19 pandemic means central banks will continue to play a major role in the collateral markets for some time to come. QE removes good collateral—typically sovereign bonds, but even corporates and equities—from the market. This has implications for associated rates, such as repo, securities lending, prime brokerage financing and derivatives margins – the nuts and bolts of market plumbing
Many textbooks still use the conventional IS-LM model to describe the relationship between interest rates and economic output. Here, the IS curve represents investment and savings. The LM curve represents liquidity demand and money supply. The point where they intersect represents the equilibrium in output and money markets. One drawback of this model is that it does not explicitly account for exogenous shifts in collateral. The LM curve is typically derived from the equation M= f(Y, r), where the supply of money is a function of output (Y) and benchmark interest rates (r). The latter is assumed to be sufficient to determine the entire yield curve, inclusive of all money market rates and risk premia (Figures A1 and A2).
The role of pledged collateral markets in the transmission of monetary policy is ignored. A simple way to address this is to re-write this equation as M= f (Y,r, cp), where cp is a variable measuring the efficiency of pledged collateral (that can be reused). This ‘new’ LM curve, factoring in the role of collateral in money markets, adds a new wrinkle to the monetary policy framework.1/ When collateral markets are constrained, and their lubrication effect is lower for a given supply of money (M), a larger change in benchmark interest rates (r) will be needed to produce the same change in output (Y)
All else equal, this implies the efficiency of monetary policy transmission is reduced when collateral supply shrinks. More broadly, cp can be interpreted as a parameter governing the efficiency of monetary policy transmission given the role of collateral as a lubricant in secured finance markets. This enriched IS-LM model more accurately describes how changes in collateral supply after the global financial crisis have impacted economic outcomes.
When collateral use drops, financial intermediation slows, with effects similar to the drying of interbank markets. The stock of collateral can decline as investors become more concerned about counterparty risk, making them less willing to lend securities, and resulting in idle collateral sitting in segregated accounts. It can also be affected by large scale QE, which drains good collateral from the system, or a widening of the pool of eligible assets, which increases pledgeability, as part of central bank’s collateral framework.
In the ‘new’ IS-LM model, changes in monetary policy may not always result in a parallel shift in the LM curve, as depicted in the conventional IS-LM framework; here, the LM curve may pivot and intersect the IS curve at a different point, depending on the slope. Recent research suggests that QE may increase output initially but may have a decreasing effect as QE increases in scale (Geanakopolos and Wang, 2020). The new IS-LM model supports these findings.
Figure A3 depicts the crash in pledged collateral (notably, the alphabet soup of AAA and AA securitizations) in the aftermath of the Lehman-crisis. This market was growing sizably since 2001–2007. Pledged collateral volumes, including the price effect, fell from around US$10 trillion before the crisis to around US$5.5 trillion afterwards (Singh 2011); volumes are inching back slowly to US$8.5 trillion Overall financial collateral efficiency, cp, declined considerably as a result. Figure A4 demonstrates the impact of QE, shown by a rightward shift in the LM curve, and a countervailing move due to the effect on collateral efficiency of the central bank purchasing vast amounts of treasury securities and other good collateral.
Even with a large debt issuance pipeline, there is dealer balance sheet constraints to “digest” all U.S. Treasuries. Dealers have shied away from making a market in U.S. Treasury repo in September 2019, and then again shied away from making a market in off-the-run US Treasuries in March 2020. So, a rebound in pledged collateral “reuse” rate depends on dealer balance sheet space.
This new IS-LM model has important policy implications. The Covid-19 pandemic has forced interest to near-zero rates and QE is back; As policymakers chart a course through the crisis, and looking beyond money aggregates as discussed in Section II and III, they should recognize the trade-off between the negative effects of constraining collateral markets and the positive effects of QE.
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Hereafter, when we mention “central banks” we refer primarily to central banks in those countries.
This concept is variously called “central bank or outside money”, M0, “high powered money”, and the “monetary base”.
Though some central banks provide deposit facilities to certain nonbanks the latter are rarely significant from a macro standpoint and will be ignored here.
Japan, which started to experiment with balance sheet expansion in 2001 is the obvious exception to this statement.
See Evans and Honkapohja (2003), “Our findings show the importance of conditioning policy appropriately, not just on fundamentals, but also directly on observed households and firm expectations”, See also Evans and Honkapohja (2001).
Once central banks reached the effective lower bound on nominal interest rates, they purchased assets in unconventional policy actions and allowed the corresponding excess bank reserves created to remain in the system. Thus, the banking system held substantially more “excess reserves” than had heretofore been demanded for settlement of interbank payments.
Drastic changes in central bank operations and monetary institutions in recent years have made previously standard approaches to explaining the determination of the price level obsolete. Recent expansions of central bank balance sheets and of the levels of rich-country sovereign debt, as well as the evolving political economy of the European Monetary Union, have made it clear that fiscal policy and monetary policy are intertwined. Our thinking and teaching about inflation, monetary policy, and fiscal policy should be based on models that recognize fiscal-monetary policy interactions (Sims, 2013).
See Patinkin (1969) for an interesting interpretation of Friedman’s role within the Chicago School and whether he diverged from his predecessors vis-à-vis monetary theory.
In theory, the value of Gross Domestic Income and Gross Domestic Product are equal so either could be used in the QTM and in empirical work. The U.S. Bureau of Economic Analysis considers GDP to be a more reliable measure of output than GDI as it considers the source data underlying GDP to be more timely and accurate. See BEA (2007), p.22. Empirical work will usually employ GDP. As it is easier to motivate the demand for money as relating to spending and income, rather than to output, it is common in conceptual discussions to consider the demand for money as directly related to income rather than output. In Lucas (1972), e.g., individuals first receive money/income, then spend it, leading to an increase in nominal output.
That wholesale payments systems were the first to experience technological change is not surprising as the fixed costs of adopting innovating technology could be spread over a much higher value of payments. JPMorgan, one of the leading adopters of blockchain technology reportedly handles the equivalent of US$ 6 trillion in cross-border payments daily—the initial target market for its JPM Coin. See Son (2020). For an insightful treatment of technological innovation in general see Christensen (1997).
The sum of payments effected in 2017 through the two U.S. large value transfer systems alone (Fedwire and CHIPS), was 1 quadrillion 133 trillion dollars compared with U.S. GDP that same year of US$19.5 trillion.
Among the reasons are technological innovation, deregulation and the development of the eurocurrency markets.
“In circulation” means in the hands of the public, i.e. having been paid out and duly recorded by the central bank. It thus includes notes in mattresses, buried underground or destroyed as well as those being used. The total in circulation is, of course, reduced when the central bank destroys unfit notes.
Milton Friedman, Money Mischief, page 206.
For the remainder of the paper we eschew the terms “monetary base”, “high-powered money”, “outside money”, etc., as being rhetorically biased toward the monetarist view that CBDL are “special and powerful”.
Assuming C accounts for 15 percent of purchases of final goods and services and summing up the transactions executed through CHIPS and Fedwire in 2007. The 2015–16 U.S. Diary of Consumer Payment Choice estimates that by value, C accounts for 7.9 percent of consumer payments. See FRB Boston, et. Al. (2017).
Numbers for average currency in circulation and reserves are from the FRB St. Louis online database FRED.
We are excluding the Soviet Union and some of its successor states and a few other outliers.
The exception being Japan we will discuss shortly.
The U.S. Board of Governors reduced reserve requirement ratios on net transaction accounts to 0 effective March 26, 2020. This eliminated reserve requirements for all depository institutions.
Okina (1999), p. 174. In short, Japan’s first experiment with targeting a large increase in bank reserves failed to elicit a commensurate increase in inflation expectations and ten years after even higher increases in reserves were witnessed in other advanced economies without commensurate effects it seems wise to focus communication on the duration for which interest rate targets will be held low while explaining that monetary aggregates are tangential to objectives. Some central bank researchers and policymakers have done this though the point may be in need of reinforcement owing to increasing magnitudes of reserves increases in reserves increases in advanced economies and more widespread adoption of unconventional policies in emerging markets.
See Bowman, Cai, Davies, and Kamin (2011) for more discussion of the relationship between BOJ’s expansion in reserves and its impact on bank credit including consideration of the counterfactual situation wherein BOJ did not engage in QE.
Lucas (1995) “We need to be explicit…about the way the new money gets into the system, and it matters how this is done.” p. 257.
Central banks invariably view M0 creation as being against either domestic debt or foreign exchange purchases thus in line with Wallace (1981). See the discussion of Wallace (1981) elsewhere in this paper.
2014 Homer Jones Memorial Lecture – Robert E. Lucas Jr.
Since monetary aggregates are typically available weekly, while quarterly GDP figures are available with a lag and subject to significant revisions, a close correlation of money and GDP—regardless of any causal relationship—would allow policymakers to infer real time developments in GDP through the monetary aggregates.
The panel included three eventual Nobel Laureates in Economics, James Tobin, Edmund Phelps and Christopher Sims, as well as William Baumol, a pioneer in modelling the transactions demand for money.
Sargent and Wallace (1981) say that if fiscal policy dominates monetary policy, “if the fiscal authority’s deficits cannot be financed solely by new bond sales, then the monetary authority is forced to create money and tolerate additional inflation. set up a model where fiscal deficits beyond a certain threshold must be financed with money regardless of the central bank’s monetary target”.
The advocates of monetary finance often talk as if “conservative” central banks engage in zero monetary finance. This is far from the truth. Every central bank that issues its own currency provides a certain amount of permanent finance this way and has for decades if not centuries. The issue is about “how much” is optimal, the amount determined by the market or by the government, not about “whether”.