## wpiea2019106

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---

### I. INTRODUCTION — Key findings and research focus
- Most term-premia regression models assume policy (short-term) rates drive the long end; this paper examines the reverse channel where long-tenor securities affect short-term rates via collateral reuse and market plumbing.
- The collateral market contracted sharply post-global financial crisis (GFC), while expected short-term rates were near zero under quantitative easing (QE), increasing the relevance of collateral-driven transmission.
- Central banks’ sizeable holdings of U.S. treasuries, U.K. gilts, JGBs, German bunds, and other AAA (or somewhat lower) eurozone collateral place them centrally in market plumbing that influences short-term rates.
- The paper argues unwinding central bank balance sheets will likely strengthen monetary policy transmission from long-tenor bonds to short-end money market rates.

### I. INTRODUCTION — Contributions and approach
- Uses a framework adapted from the Global Financial Stability Report (GFSR) October 2018 (Annex I) and data from the global pledged collateral market.
- Focuses on pledged collateral markets where banks and other financial institutions exchange collateral (bonds and equities) for money, and on the role of dealer balance-sheet space and central bank balance sheets.
- Demonstrates that unwinding central bank holdings of “good collateral” is likely to improve transmission to short-end market rates.

### I. INTRODUCTION — Structure overview (as presented)
- Section II: introduces “moneyness” and links to risk premia.
- Section III: uses pledged collateral market data to show transmission post-Lehman (2008–17) is weaker than pre-Lehman (2002–07).
- Section IV: shows interaction of dealer balance sheet space and central bank balance sheets.
- Section V: argues dealer balance sheet space is relatively less constrained and collateral reuse is rebounding; recommends central banks avoid competing with market price discovery.
- Section VI: concludes favoring unwinding good collateral from central bank balance sheets to improve transmission to short-end rates.

### Numeric and factual highlights (exact values preserved)
- Post-Lehman pledged collateral market: about US$10 trillion pre-Lehman; collapsed to about half its peak immediately post-Lehman and remained unchanged until 2016.
- Pre-crisis reserves for the U.S. before the GFC: well below US$50 billion.
- Fed currency-in-circulation example: around US$1.6 trillion and likely to reach around US$2 trillion when the Fed balance sheet is normalized in the medium term.
- IOER tweaks cited: 5 bps each in June 2018, December 2018, and May 19.
- Example yield references: long principal strips with a 3 percent yield; if U.S. treasuries (10 year) are over 3 percent; scenario where 10-year U.S. treasuries are higher (say more than 4 percent).
- Euro area: Bund general collateral overnight rate about negative 50 bps.

### II. MONEYNESS AND RISK PREMIA — Conceptual points
- Term premia reflect compensation demanded for holding long-term bonds but also include services provided by securities: collateral services, alternatives to deposits, regulatory HQLA needs, duration hedging, etc.
- “Moneyness” is the utility value of securities as collateral; features include:
  - (1) acceptability to counterparties worldwide;
  - (2) ease of use—likelihood of becoming “special,” stability of supply;
  - (3) stability of price—expected frequency of posting and recalling margin.
- Moneyness exists on a spectrum, not binary; short-intermediate maturities (six months to two years) often occupy a “sweet” spot with highest collateral utility value.

### II. MONEYNESS — Implications and market dynamics
- Debt management agencies should consider collateral services—“moneyness”—and duration services when planning issuance, alongside conventional criteria.
- At very short tenors (e.g., 3 months), securities’ value as direct alternatives to bank deposits (“moneyness”) can overwhelm reuse value.
- T-bills are broadly acceptable while long bonds are less universally acceptable, making short bills preferred on metric (1).
- Long bonds have higher price volatility, diminishing collateral value on metric (3).
- European Central Bank securities-lending activity has helped contain negative yields by effectively replacing longer-term bonds bought via QE with similar collateral and “moneyness” services.

### III. LEAN CENTRAL BANK BALANCE SHEETS AND MONETARY TRANSMISSION — Observations
- Some argue large reserves are unnecessary if monetary policy normalizes; Stella (2015) notes banking systems worked with minimal reserves pre-GFC.
- Post-crisis regulatory requirements for HQLA increased importance of bank liquidity.
- Holdings of HQLA vary across global banks—some prefer reserves, others prefer collateral (Ihrig et al., 2017; Kaminska, 2015; Citi and Morgan Stanley prefer collateral).

### III. LEAN BALANCE SHEETS — Liability-side dynamics and plumbing
- Excess reserves and overnight reverse repo programs (RRPs) disintermediate market functioning: RRPs allow money to be drained from the system without releasing collateral to the market.
- Characterized as an accounting reshuffle on the Fed’s liability side (Potter, 2015, footnote 2); money accesses the Fed directly and skirts market plumbing.
- Post-Lehman regulatory tweaks (e.g., leverage ratio) and central bank programs (e.g., Fed’s reverse repo since September 2013; ECB collateral framework expansion and security-lending since January 2017) affect effective supply and balance-sheet “space” of major dealers (XYZ).
- When reserves decline, private-sector bank balance-sheet space increases; this has complex plumbing dynamics and may not result in tightening (Singh, 2017b).

### Box 1 — Global banks footprint in financial plumbing (primer)
- Only a small number of large global dealers (the large 10–15 banks) regularly move financial collateral across borders on a large scale; examples listed include:
  - U.S.: Goldman Sachs, Morgan Stanley, JPMorgan, Bank of America/Merrill, Citibank.
  - Europe/elsewhere: Deutsche Bank, UBS, Barclays, Credit Suisse, Société Générale, BNP Paribas, HSBC, Royal Bank of Scotland (declining share), Nomura. Recently Canadian banks have entered the market.
- These dealers connect the broader set of financial entities that demand and supply collateral; entry is expensive and requires title transfer, rehypothecation, ISDA/prime-brokerage capabilities.
- Cross-border pledged collateral trades (repo, securities-lending, OTC derivative margins) require legal perfection and standard master agreements.
- The bilateral pledged collateral market is the domain that prices mark-to-market all HQLA securities.
- Regulatory tweaks can increase effective collateral supply by softening balance-sheet constraints for XYZ.
- Central bank programs can augment dealers’ balance-sheet space (e.g., Fed reverse repo program, ECB collateral framework and securities-lending).

### Box 2 — Analytics on Reverse Regressions — Methodology
- Dependent variable: risk premia (actual yield minus OIS forwards) at 3, 6, 12, and 24 months.
- Independent variables:
  - Size of the Global Pledged Collateral Market
  - Determinants of Risk Premia (formalized as: Risk Premia = α + β * Global Collateral + ∑ γ * Proxy)
- Sample periods:
  - Full sample: 2002–17
  - Subsamples due to structural break in late 2007: 2002–07 (pre-Lehman) and 2008–17 (post-Lehman)
- Estimation strategy:
  - Run 216 regressions from all combinations across variable groups (3 x 3 x 2 x 2 x 3 x 2).
  - Shortlist regressions within the 90th percent of highest R^2 to avoid spurious results.
- Determinant groups used in regressions (Annex I):
  - Group 1: Inflation Dynamics (3 variables) — Expected Inflation, Oil Spot Price, percent odds on deflation
  - Group 2: Growth Dynamics (3 variables) — Expected GDP growth, Expected Unemployment, percent odds on < 0 GDP growth decline
  - Group 3: Supply (2 variables) — Expected budget surplus/GDP, Foreign Custody Holdings

### Box 2 — Empirical findings (Collateral’s role in risk premia)
- Collateral’s predictive power is significant across short and medium-term horizons when using the full 2002–17 sample.
- Structural break in late 2007 implies different transmission dynamics pre- and post-Lehman.
- Coefficient of collateral is lower post-Lehman relative to pre-Lehman, consistent with QE and regulation siloing much of the good collateral.
- Specific regression summary statistics:
  - 6m Risk Premia, 2002-07:
    - Ave. R^2: 40%
    - Weighted-Ave Beta: 0.23524
    - Ave. P val.: 0.0053439
  - 6m Risk Premia, 2008-17:
    - Ave. R^2: 54%
    - Weighted-Ave Beta: -0.015143
    - Ave. P val.: 0.40027
  - 12m Risk Premia, 2002-07:
    - Ave. R^2: 57%
    - Weighted-Ave Beta: 0.17113
    - Ave. P val.: 0.067458
  - 12m Risk Premia, 2008-17:
    - Ave. R^2: 54%
    - Weighted-Ave Beta: 0.053382
    - Ave. P val.: 0.083095
- The 6–12 month horizon shows a kink and represents the “sweet spot” for collateral moneyness (time interval for at least one reuse, plus minimal duration risk).

### Box 2 — Market plumbing, balance sheets, and transmission
- Excess reserves of the banking system are presently around US$1.8 trillion.
- Letting central bank balance sheets shrink would release “good” collateral (e.g., U.S. treasury securities) while reducing excess reserves.
- Good collateral, when pledged, is constantly reused (similar to money creation), so good collateral and excess reserves have different market implications.
- Transmission from long-tenor bonds to short-end market rates is weaker in the post-Lehman period when central banks are normalizing, in contrast to the stronger pre-Lehman transmission—especially pronounced for the 6–12 months duration.
- Central bank large balance sheets in steady-state warrant further research because parts of market plumbing moving onto central bank balance sheets weaken monetary policy transmission.

### Box 2 — Collateral reuse, market size, and velocity (exact series)
- As of end-2017, pledged collateral received by major banks that could be onward re-pledged in their own name was around US$7.5 trillion, an increase of 25 percent relative to end-2016.
- The pledged collateral market was approximately US$6 trillion for almost a decade since 2008.
- Velocity (reuse) and volumes by year (Hedge Funds, Securities Lending, Total, Volume of Pledged Collateral, Reuse Rate):
  - 2007: Hedge Funds 1.7, Securities Lending 1.7, Total 3.4; Volume of Pledged Collateral 10.0; Reuse Rate (or Velocity) 3.0
  - 2010: Hedge Funds 1.3, Securities Lending 1.1, Total 2.4; Volume 6.0; Reuse Rate 2.5
  - 2011: Hedge Funds 1.4, Securities Lending 1.05, Total 2.5; Volume 6.3; Reuse Rate 2.5
  - 2012: Hedge Funds 1.8, Securities Lending 1.0, Total 2.8; Volume 6.1; Reuse Rate 2.2
  - 2013: Hedge Funds 1.85, Securities Lending 1.0, Total 2.85; Volume 6.0; Reuse Rate 2.1
  - 2014: Hedge Funds 1.9, Securities Lending 1.1, Total 3.0; Volume 6.1; Reuse Rate 2.0
  - 2015: Hedge Funds 2.0, Securities Lending 1.1, Total 3.1; Volume 5.8; Reuse Rate 1.9
  - 2016: Hedge Funds 2.1, Securities Lending 1.2, Total 3.3; Volume 6.1; Reuse Rate 1.8
  - 2017: Hedge Funds 2.2, Securities Lending 1.5, Total 3.7; Volume 7.5; Reuse Rate 2.0
- Additional collateral stock details:
  - Non-hedge fund sources had US$1.5 trillion in securities on loan as of end-2017.
  - Hedge funds had assets under management of US$3.0 trillion (end-2017).
  - Total pledged collateral from non-hedge funds (US$1.5 trillion) and from hedge funds (US$2.2 trillion) amount to US$3.7 trillion.

### Box 2 — Implications for short-term rates and data needs
- Two main implications looking forward:
  - Unwinding good collateral (U.S. treasuries, bunds) from central bank balance sheets back to market is likely to improve transmission to short-end money market rates.
  - An increase in collateral reuse as central banks contemplate tightening eases financial conditions by increasing dealer balance sheet space, reducing the rationale for plumbing to rely on central bank balance sheets.
- Monitoring and data needs:
  - More frequent data reporting by all large global banks would improve understanding of transmission from long-term bonds to short-end market rates.
  - It is useful to discern the extent to which regulatory demand for collateral has adversely impacted the pledged collateral market.

### Conclusions and policy recommendations (from Box 2 and main text)
- Empirical conclusion:
  - Transmission from long-tenor bonds to short-end market rates weakened in the post-Lehman era, largely due to reduced availability of good collateral driven by central banks’ QE programs and regulatory constraints on dealer balance sheets.
- Policy considerations and recommendations:
  - Central banks should be careful when unwinding balance sheets to return securities to market possession, recognizing that reuse dynamics lie outside central bank control.
  - The balance between reserves and money-like U.S. treasuries needs stronger economic justification; arguments for large steady-state central bank balance sheets warrant further research.
  - Regulatory tweaks (for example, leverage ratio adjustments) and clearer market-driven choices between private and public balance sheet provisioning could restore plumbing and improve monetary policy transmission.
  - Choice between private and public balance sheet provision should be transparent and market-driven.
  - Large balance sheet unwinds are likely to be spread over significant periods, not short-term conflicts assumed in some policy literature.

### 4. Group 4: Real Term Premia — Variables
- a. Standard Deviation of GDP growth, S&P GARCH Return Volatility

*Source: wpiea2019106 - References (excerpt).*

### References................................................................................................ 19

### I. INTRODUCTION

### Key findings and research focus
- Most term-premia regression models assume policy (short-term) rates drive the long end; this paper examines the reverse channel where long-tenor securities affect short-term rates via collateral reuse and market plumbing.
- The collateral market contracted sharply post-global financial crisis (GFC), while expected short-term rates were near zero under quantitative easing (QE), increasing the relevance of collateral-driven transmission.
- Central banks’ sizeable holdings of U.S. treasuries, U.K. gilts, JGBs, German bunds, and other AAA (or somewhat lower) eurozone collateral place them centrally in market plumbing that influences short-term rates.
- The paper argues unwinding central bank balance sheets will likely strengthen monetary policy transmission from long-tenor bonds to short-end money market rates.

### Contributions and methodological approach
- Uses a framework adapted from the Global Financial Stability Report (GFSR) October 2018 (Annex I) and data from the global pledged collateral market.
- Focuses on pledged collateral markets where banks and other financial institutions exchange collateral (bonds and equities) for money, and on the role of dealer balance-sheet space and central bank balance sheets.
- Demonstrates that unwinding central bank holdings of “good collateral” is likely to improve transmission to short-end market rates.

### Structure of the paper (as presented)
- Section II: introduces “moneyness” and links to risk premia.
- Section III: uses pledged collateral market data to show transmission post-Lehman (2008–17) is weaker than pre-Lehman (2002–07).
- Section IV: shows interaction of dealer balance sheet space and central bank balance sheets.
- Section V: argues dealer balance sheet space is relatively less constrained and collateral reuse is rebounding; recommends central banks avoid competing with market price discovery.
- Section VI: concludes favoring unwinding good collateral from central bank balance sheets to improve transmission to short-end rates.

---

### Numeric and factual highlights (exact values preserved)
- Post-Lehman pledged collateral market: about US$10 trillion pre-Lehman; collapsed to about half its peak immediately post-Lehman and remained unchanged until 2016.
- Pre-crisis reserves for the U.S. before the GFC: well below US$50 billion.
- Fed currency-in-circulation example: around US$1.6 trillion and likely to reach around US$2 trillion when the Fed balance sheet is normalized in the medium term.
- IOER tweaks cited: 5 bps each in June 2018, December 2018, and May 19.
- Example yield references: long principal strips with a 3 percent yield; if U.S. treasuries (10 year) are over 3 percent; scenario where 10-year U.S. treasuries are higher (say more than 4 percent).
- Euro area: Bund general collateral overnight rate about negative 50 bps.

---

### II. MONEYNESS AND RISK PREMIA

### Conceptual points
- Term premia reflect compensation demanded for holding long-term bonds but also include services provided by securities: collateral services, alternatives to deposits, regulatory HQLA needs, duration hedging, etc.
- “Moneyness” is the utility value of securities as collateral; its features include:
  - (1) acceptability to counterparties worldwide;
  - (2) ease of use—likelihood of becoming “special,” stability of supply;
  - (3) stability of price—expected frequency of posting and recalling margin.
- Moneyness exists on a spectrum, not binary; short-intermediate maturities (six months to two years) often occupy a “sweet” spot with highest collateral utility value.

### Implications for issuance and debt management
- Debt management agencies should consider collateral services—“moneyness”—and duration services when planning issuance, alongside conventional criteria.
- At very short tenors (e.g., 3 months), securities’ value as direct alternatives to bank deposits (“moneyness”) can overwhelm reuse value.

### Market dynamics and examples
- T-bills are broadly acceptable while long bonds are less universally acceptable, making short bills preferred on metric (1).
- Long bonds have higher price volatility, diminishing collateral value on metric (3).
- European Central Bank securities-lending activity has helped contain negative yields by effectively replacing longer-term bonds bought via QE with similar collateral and “moneyness” services.

---

### III. LEAN CENTRAL BANK BALANCE SHEETS AND MONETARY TRANSMISSION—SOME ANALYTICS

### Observations on reserves and HQLA
- Some argue large reserves are unnecessary if monetary policy normalizes; Stella (2015) notes banking systems worked with minimal reserves pre-GFC.
- Post-crisis regulatory requirements for HQLA increased importance of bank liquidity.
- Holdings of HQLA vary across global banks—some prefer reserves, others prefer collateral (Ihrig et al., 2017; Kaminska, 2015; Citi and Morgan Stanley prefer collateral).

### Central bank liability-side dynamics and plumbing effects
- Excess reserves and overnight reverse repo programs (RRPs) disintermediate market functioning: RRPs allow money to be drained from the system without releasing collateral to the market.
- This is characterized as an accounting reshuffle on the Fed’s liability side (Potter, 2015, footnote 2); money accesses the Fed directly and skirts market plumbing (Figure 2 referenced in source).

### Regulatory and central bank effects on collateral supply
- Post-Lehman regulatory tweaks (e.g., leverage ratio) and central bank programs (e.g., Fed’s reverse repo since September 2013; ECB collateral framework expansion and security-lending since January 2017) affect effective supply and balance-sheet “space” of major dealers (XYZ).
- When reserves decline, private-sector bank balance-sheet space increases; this has complex plumbing dynamics and may not result in tightening (Singh, 2017b).

---

### Box 1. Global Banks Footprint in Financial Plumbing—A Primer

### Market structure and key intermediaries
- Only a small number of large global dealers (the large 10–15 banks) regularly move financial collateral across borders on a large scale; examples listed include:
  - U.S.: Goldman Sachs, Morgan Stanley, JPMorgan, Bank of America/Merrill, Citibank.
  - Europe/elsewhere: Deutsche Bank, UBS, Barclays, Credit Suisse, Société Générale, BNP Paribas, HSBC, Royal Bank of Scotland (declining share), Nomura. Recently Canadian banks have entered the market.
- These dealers (XYZ) connect the broader set of financial entities (A to Z) that demand and supply collateral; entry is expensive and requires a global footprint and legal/operational capabilities (title transfer, rehypothecation, ISDA/prime-brokerage agreements).

### Implications for cross-border collateral flows and reuse
- Cross-border pledged collateral trades (repo, securities-lending, OTC derivative margins) require legal perfection and standard master agreements.
- The bilateral pledged collateral market is the domain that prices mark-to-market all HQLA securities.
- Regulatory tweaks can increase effective collateral supply by softening balance-sheet constraints for XYZ.
- Central bank programs can augment dealers’ balance-sheet space (e.g., Fed reverse repo program, ECB collateral framework and securities-lending).

### Transmission evidence (summary)
- Box 2 (referenced) shows transmission from pledged collateral market to short-end rates was weaker in 2008–17 than in 2002–07, corresponding with a halving of the pledged collateral market size post-Lehman and subdued transmission until 2016.

---

*Source: wpiea2019106 - References (excerpt). PDF: wpiea2019106 - References................................................................................................ 19*

### Box 2. Analytics on Reverse Regressions—Transmission to Short End

### Box 2. Analytics on Reverse Regressions—Transmission to Short End

### Methodology and Variables
- Dependent variable: risk premia (actual yield minus OIS forwards) at 3, 6, 12, and 24 months.
- Independent variables:
  - Size of the Global Pledged Collateral Market
  - Determinants of Risk Premia (formalized as: Risk Premia = α + β * Global Collateral + ∑ γ * Proxy)
- Sample periods:
  - Full sample: 2002–17
  - Subsamples due to structural break in late 2007: 2002–07 (pre-Lehman) and 2008–17 (post-Lehman)
- Estimation strategy:
  - Run 216 regressions from all combinations across variable groups (3 x 3 x 2 x 2 x 3 x 2).
  - Shortlist regressions within the 90th percent of highest R^2 to avoid spurious results.
- Determinant groups used in regressions (Annex I):
  - Group 1: Inflation Dynamics (3 variables) — Expected Inflation, Oil Spot Price, percent odds on deflation
  - Group 2: Growth Dynamics (3 variables) — Expected GDP growth, Expected Unemployment, percent odds on < 0 GDP growth decline
  - Group 3: Supply (2 variables) — Expected budget surplus/GDP, Foreign Custody Holdings

### Empirical Findings — Collateral’s Role in Risk Premia
- Collateral’s predictive power is significant across short and medium-term horizons when using the full 2002–17 sample.
- Structural break in late 2007 implies different transmission dynamics pre- and post-Lehman.
- Coefficient of collateral is lower post-Lehman relative to pre-Lehman, consistent with QE and regulation siloing much of the good collateral.
- Specific regression summary statistics (Collateral variable coefficients and significance across tenors):
  - 6m Risk Premia, 2002-07:
    - Ave. R^2: 40%
    - Weighted-Ave Beta: 0.23524
    - Ave. P val.: 0.0053439
  - 6m Risk Premia, 2008-17:
    - Ave. R^2: 54%
    - Weighted-Ave Beta: -0.015143
    - Ave. P val.: 0.40027
  - 12m Risk Premia, 2002-07:
    - Ave. R^2: 57%
    - Weighted-Ave Beta: 0.17113
    - Ave. P val.: 0.067458
  - 12m Risk Premia, 2008-17:
    - Ave. R^2: 54%
    - Weighted-Ave Beta: 0.053382
    - Ave. P val.: 0.083095
- The 6–12 month horizon shows a kink and represents the “sweet spot” for collateral moneyness (time interval for at least one reuse, plus minimal duration risk).

### Market Plumbing, Central Bank Balance Sheets, and Transmission
- Key observations on balance sheets and plumbing:
  - Excess reserves of the banking system are presently around US$1.8 trillion.
  - Letting central bank balance sheets shrink would release “good” collateral (e.g., U.S. treasury securities) while reducing excess reserves.
  - Good collateral, when pledged, is constantly reused (similar to money creation), so good collateral and excess reserves have different market implications.
  - Transmission from long-tenor bonds to short-end market rates is weaker in the post-Lehman period when central banks are normalizing, in contrast to the stronger pre-Lehman transmission—especially pronounced for the 6–12 months duration.
  - Central bank large balance sheets in steady-state warrant further research because parts of market plumbing moving onto central bank balance sheets weaken monetary policy transmission.
- Policy-relevant mechanics:
  - If central banks unwind and return good collateral to markets, reuse rates are outside central bank control and will affect plumbing and transmission.
  - Large balance sheet unwinds are likely to be spread over significant periods, not short-term conflicts assumed in some policy literature.
  - Choice between private and public balance sheet provision should be transparent and market-driven.

### Collateral Reuse, Market Size, and Velocity
- Pledged collateral market developments:
  - As of end-2017, pledged collateral received by major banks that could be onward re-pledged in their own name was around US$7.5 trillion, an increase of 25 percent relative to end-2016.
  - The pledged collateral market was approximately US$6 trillion for almost a decade since 2008.
- Velocity (reuse) of collateral and volumes:
  - 2007: Sources — Hedge Funds 1.7, Securities Lending 1.7, Total 3.4; Volume of Pledged Collateral 10.0; Reuse Rate (or Velocity) 3.0
  - 2010: Hedge Funds 1.3, Securities Lending 1.1, Total 2.4; Volume 6.0; Reuse Rate 2.5
  - 2011: Hedge Funds 1.4, Securities Lending 1.05, Total 2.5; Volume 6.3; Reuse Rate 2.5
  - 2012: Hedge Funds 1.8, Securities Lending 1.0, Total 2.8; Volume 6.1; Reuse Rate 2.2
  - 2013: Hedge Funds 1.85, Securities Lending 1.0, Total 2.85; Volume 6.0; Reuse Rate 2.1
  - 2014: Hedge Funds 1.9, Securities Lending 1.1, Total 3.0; Volume 6.1; Reuse Rate 2.0
  - 2015: Hedge Funds 2.0, Securities Lending 1.1, Total 3.1; Volume 5.8; Reuse Rate 1.9
  - 2016: Hedge Funds 2.1, Securities Lending 1.2, Total 3.3; Volume 6.1; Reuse Rate 1.8
  - 2017: Hedge Funds 2.2, Securities Lending 1.5, Total 3.7; Volume 7.5; Reuse Rate 2.0
- Additional collateral stock details:
  - Non-hedge fund sources had US$1.5 trillion in securities on loan as of end-2017.
  - Hedge funds had assets under management of US$3.0 trillion (end-2017).
  - Total pledged collateral from non-hedge funds (US$1.5 trillion) and from hedge funds (US$2.2 trillion) amount to US$3.7 trillion.

### Implications for Short-Term Money Market Rates and Financial Conditions
- Two main implications looking forward:
  - Unwinding good collateral (U.S. treasuries, bunds) from central bank balance sheets back to market is likely to improve transmission to short-end money market rates.
  - An increase in collateral reuse as central banks contemplate tightening eases financial conditions by increasing dealer balance sheet space, reducing the rationale for plumbing to rely on central bank balance sheets.
- Monitoring and data needs:
  - More frequent data reporting by all large global banks would improve understanding of transmission from long-term bonds to short-end market rates.
  - It is useful to discern the extent to which regulatory demand for collateral has adversely impacted the pledged collateral market.

### Conclusions and Policy Recommendations
- Empirical conclusion:
  - Transmission from long-tenor bonds to short-end market rates weakened in the post-Lehman era, largely due to reduced availability of good collateral driven by central banks’ QE programs and regulatory constraints on dealer balance sheets.
- Policy considerations:
  - Central banks should be careful when unwinding balance sheets to return securities to market possession, recognizing that reuse dynamics lie outside central bank control.
  - The balance between reserves and money-like U.S. treasuries needs stronger economic justification; arguments for large steady-state central bank balance sheets warrant further research.
  - Regulatory tweaks (for example, leverage ratio adjustments) and clearer market-driven choices between private and public balance sheet provisioning could restore plumbing and improve monetary policy transmission.

*Source: Box 2. Analytics on Reverse Regressions—Transmission to Short End (WPIEA2019106).*

### 4. Group 4: Real Term Premia (2 variables)

### 4. Group 4: Real Term Premia (2 variables)

### Variables in Group 4
- a. Standard Deviation of GDP growth, S&P GARCH Return Volatility

### Context in adjacent groups (as listed in source)
- 5. Group 5: Inflation and Nominal Risk Premia (3 variables)  
  - a. Standard deviation of inflation, Standard deviation of Rate Survey, GARCH 1-year Return Volatility
- 6. Group 6: Correlation Dynamics (2 variables)  
  - a. M-GARCH A-DCC, M-GARCH A-DC Beta

### References (as listed in source)
- Adrian, Tobias, Richard Crump, and Emanuel Moench, 2013, “Pricing the Term Structure with Linear Regressions,” Journal of Financial Economics, Vol. 110.
- Anderson, Ronald W, and Joeveer Karin, 2013, “The Economics of Collateral” DTCC.
- Arrata, William, Benoit Nguyen, Imene Rahmouini-Rousseau, and Miklos Vari, 2018, “The Scarcity Effect of Quantitative Easing on Repo Rates: Evidence from the Euro Area,” IMF Working Paper 18/258, (Washington: International Monetary Fund).
- Baranova, Yuliya, Zijun Liu, and Joseph Noss, 2016, “The Role of Collateral in Supporting Liquidity,” Bank of England Working Paper No 609.
- Bindseil, Ulrich, 2016, “Evaluating Monetary Policy Operational Frameworks,” Federal Reserve Bank of Kansas City Presentation on “Designing Resilient Monetary Policy Frameworks for the Future.”
- Brainard, Governor Lael, 2017, “Cross-Border Spillovers of Balance Sheet Normalization,” Speech at the National Bureau of Economic Research’s Monetary Economics Summer Institute, Cambridge, Massachusetts, July.
- Cheung, Belinda, Mark Manning, and Angus Moore, 2014, “The Effective Supply of Collateral in Australia” Reserve Bank of Australia, Quarterly Bulletin (September).
- Christensen, Jens H.E., and Glenn D Rudebusch, 2012, “The Response of Interest Rates to U.S. and U.K. Quantitative Easing,” Federal Reserve Bank of New York, May.
- Copeland, Adam, Linsey Molloy, and Anya Tarascina, 2018, What Can We Learn from the Timing of Interbank Payments? https://libertystreeteconomics.newyorkfed.org/2019/02/what-can-we-learn-from-the-timing-of-interbank-payments.html
- Del Negro, Marco, Domenico Giannone, Marc P Giannoni, Andrea Tambalotti, 2017, “Safety, Liquidity and the Nature Rate of Interest,” Federal Reserve Bank of New York, May.
- Domanski, Dietrich, Hyun Song Shin and Vladyslav Sushko, 2015, “The Hunt for Duration: Not Waving but Drowning,” BIS Working Papers, No. 519.
- Dudley, William C. 2017, “The Importance of Financial Conditions in the Conduct of Monetary Policy,” Remarks at the University of South Florida Sarasota-Manatee, Sarasota, Florida, March.
- Financial Stability Board, 2017, “Transforming Shadow Banking Into Resilient Market-Based Finance: Re-Hypothecation and Collateral Re-Use: Potential Financial Stability Issues, Market Evolution and Regulatory Approaches,” January.
- Gelos, Gaston, Federico Grinberg, Shujaat Khan, Tommaso Mancini-Griffoli, Machiko Narita, and Umang Rawat, 2019, “Household Indebtedness did not Weaken U.S. Monetary Transmission Post-Crisis,” VOX CEPR Policy Portal, February.
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- Singh, Manmohan, and Phil Prince, 2018b, Moneyness and Term Premia, Financial Times Alphaville, Feb 15, https://ftalphaville.ft.com/2018/02/15/2198837/guest-post-moneyness-and-term-premia/.
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- Williamson, Stephen D., 2014, “Scarce Collateral, the Term Premium, and Quantitative Easing” Federal Reserve Bank of St Louis, March.

*Source: wpiea2019106 - 4. Group 4: Real Term Premia (2 variables).*

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_Source: https://www.imf.org/-/media/files/publications/wp/2019/wpiea2019106.pdf_