Quantitative-Easing | Macro Paper Warehouse

Credit Easing versus Quantitative Easing: Evidence from Corporate and Government Bond Purchase Programs

Mon, 01 Jan 0001 00:00:00 +0000

Using security-level data on individual corporate bond prices and the Bank of England’s published purchase quantities across its gilt purchase programs (QE1: £200bn, QE2: £125bn, QE3: £50bn, QE4: £60bn) and Corporate Bond Purchase Scheme (CBPS: £10bn of investment-grade sterling corporate bonds), this paper estimates supply effects of QE and CE on UK corporate bond prices, credit spreads, and new issuance separately, exploiting cross-sectional variation in quantities purchased as identifying variation via an instrumental variables approach. In the case of QE alone, supply effects on corporate bond prices are significant at announcement and larger over the full stock-effect horizon, but pass-through to credit spreads is found to be limited to the default-free component of corporate yields under normal market conditions — an exception is QE1 during the financial crisis, when QE’s cross-asset supply effects also significantly lowered credit spreads in the longer run. CE via the CBPS is found to be more effective than QE in reducing credit spreads for higher-rated investment-grade bonds even under normal conditions, and is the only program that generates a statistically significant increase in sterling corporate bond issuance. The results are consistent with QE and CE working through partially distinct channels — QE primarily affecting the default-free component of corporate yields, CE additionally compressing the credit-spread component — and complementing each other for higher-rated bonds.

Summary of a forthcoming paper, AI-assisted and human-reviewed. See the linked original for the authoritative claims and full conditions.

In depth

Q1. What is the empirical strategy and why use a security-level approach?

The paper uses a two-stage instrumental variables (IV) approach at the individual corporate bond level, with pre-program bond characteristics — maturity, yield-curve fitting errors, the BoE’s prior ownership share in the gilt bucket — serving as instruments for the expected distribution of purchases across bonds, allowing isolation of the supply channel from signaling and duration channels. The security-level approach offers three advantages over aggregate or event-study methods: it enables construction of “substitute buckets” (bonds whose maturity is close to the purchased bonds’) to estimate cross-asset supply effects; it permits direct comparison of the price elasticity with respect to gilt purchases (cross-asset effect) versus corporate bond purchases (within-asset effect); and it allows estimation of both the announcement-day effect and the stock effect — the cumulative price and spread change over the life of each program — which captures the longer-run portfolio-rebalancing contribution separately from the initial market reaction.

Q2. What are QE’s effects on corporate bond prices and credit spreads?

For QE alone (QE1–3), the instrumented gilt substitute purchases have positive and statistically significant effects on corporate bond prices at announcement across all three programs — in the case of QE1, the average 30 basis-point decline in corporate yields on the announcement day is attributed in full to QE supply effects in the paper’s regression. The stock effect — estimated over the full life of each program — is significantly larger than the announcement-day effect, consistent with gradual portfolio rebalancing as predicted by Greenwood, Hanson, and Liao (2018). However, except for QE1, the supply effects do not carry through to credit spreads in either the short run or the longer run, which the paper interprets as consistent with QE working primarily through the default-free component of the corporate yield: corporate yields fell in line with gilt yields, but spreads over gilts were unchanged.

Q3. When does QE affect credit spreads?

QE1’s cross-asset supply effects significantly lowered credit spreads in the longer run, even though QE2 and QE3 do not generate significant credit spread compression in either the short or long run, suggesting that the supply channel interacts with the liquidity channel specifically under conditions of financial market distress. The paper interprets the QE1 exception as reflecting the severe disruption during the 2008–09 financial crisis: when capital mobility across markets is constrained and liquidity premia are elevated, central bank purchases of safe assets may also improve trading conditions in indirectly targeted, less liquid markets such as the corporate bond market, reducing the liquidity component of corporate spreads. This interaction does not appear to be operative in the more normal market conditions of QE2 and QE3.

Q4. How does CE compare to QE in reducing credit spreads and stimulating issuance?

CE via the CBPS is found to be more effective than QE in reducing credit spreads for higher-rated investment-grade bonds even under normal financial market conditions, and a corporate bond’s price sensitivity to its own CBPS purchases is substantially higher than its price sensitivity to gilt substitute purchases; CE is also the only program with a statistically significant positive effect on new sterling corporate bond issuance. Across QE1–3, there is no statistically significant impact of gilt purchases on sterling corporate issuance, while CBPS purchases have positive and statistically significant effects on new sterling corporate bond issuance. The paper characterizes CE and QE as complementary for higher-rated bonds: CE’s credit-spread reduction layers on top of QE’s default-free component effect, making the total stock effect larger than either program alone.

Q5. What happens for lower-rated investment-grade bonds?

For lower-rated investment-grade bonds, the evidence for both cross-asset QE supply effects and within-asset CE supply effects is weaker, and the paper suggests that CE’s stimulation of new bond issuance may have counterbalanced its positive price effects for these bonds through the dilutive effect of new supply. The mechanism is that CE’s reduction in the cost of corporate bond issuance for lower-rated firms induced enough new bond issuance to partially offset the price increase from CBPS purchases, consistent with the issuance channel being most active for the market segment where CBPS created the largest pricing improvement. This dilution effect implies that the net price benefit of CE for lower-rated bonds is smaller than the gross supply-effect estimate.

Key concepts

stock effect : the cumulative effect of the total quantity of bonds purchased under a program on bond prices and spreads, estimated over the full life of the program; in this paper the stock effect is significantly larger than the announcement-day effect, consistent with gradual portfolio rebalancing.

cross-asset supply effect : the pass-through of government bond (gilt) purchase supply shocks to the prices of corporate bonds — an asset class not directly targeted by QE; the paper provides the first estimates of this cross-market supply channel at the security level.

credit spread : the difference between the yield on a corporate bond and the yield on a risk-free government bond of the same maturity; the paper finds QE pass-through is generally limited to the default-free component of corporate yields rather than the credit spread.

default-free component : the part of a corporate bond’s yield attributable to the risk-free interest rate rather than credit risk; the paper finds that QE supply shocks affect this component but generally leave the credit spread unchanged in normal market conditions.

within-asset substitution effect : the price effect of CE purchases on the bonds directly purchased and their corporate bond substitutes, as distinct from cross-asset effects; the paper finds this effect is substantially larger in magnitude than the cross-asset QE effect on corporate bonds.

issuance channel : the mechanism by which lower corporate borrowing costs induced by CE stimulate new corporate bond issuance; the paper finds this channel operates under CE (CBPS) but not under QE (gilt purchases).

Passive Quantitative Easing: Bond Supply Effects through Lower Debt Issuance

Mon, 01 Jan 0001 00:00:00 +0000

The paper introduces the concept of “passive quantitative easing” (passive QE): a deliberate reduction in government debt issuance that lowers anticipated future bond supply and reduces long-term yields through the same supply channel as central bank asset purchases, without involving asset purchases or reserves creation. The authors develop a unified classification scheme for central bank balance sheet policies organized by their net effect on anticipated future bond supply, and show that the Danish government’s unexpected January 2015 debt halt — which removed approximately 29.9 billion DKK from the outstanding bond stock over roughly nine months — was followed by a two-day yield decline of approximately 25 basis points across the entire yield curve. Regression estimates controlling for concurrent ECB and SNB actions imply that the halt raised the safety premium on Danish bonds by 17–22 basis points and reduced the ten-year term premium by 37–70 basis points, with combined effects pointing to 54–92 basis points in lower yields relative to the counterfactual. The Danish episode ranks approximately on par with the Federal Reserve’s QE3 in the classification scheme, and the paper argues that passive QT — unexpectedly higher debt issuance — is contractionary through two additional portfolio balance channels not present in active QT and should be treated as an active policy tool rather than a neutral background condition.

Summary of a forthcoming paper, AI-assisted and human-reviewed. See the linked original for the authoritative claims and full conditions.

In depth

Q1. What is “passive QE” and what distinguishes it from conventional QE?

The paper defines passive QE as a reduction in government debt issuance that lowers anticipated future bond supply, arguing this is functionally equivalent to central bank asset purchases in its effects on long-term yields, even though it involves neither asset purchases nor reserves creation. The supply-side equivalence holds because what matters for term premia and safe-asset premia is the anticipated future stock of bonds available to private investors: whether the central bank withdraws bonds via outright purchases or the government simply issues fewer new ones, the anticipated future supply declines, requiring downward adjustment in the compensation investors demand for duration risk and scarcity. The distinction from active QE is therefore operational rather than economic: passive QE leaves the central bank’s balance sheet unchanged, makes no reserve injection, and requires no fiscal–monetary coordination beyond the government’s own debt management decisions.

Q2. How do the authors classify central bank balance sheet policies?

The paper proposes a unified classification scheme that maps central bank balance sheet policies by their net effect on anticipated future bond supply, placing passive QE in the same stimulative category as active QE programs and ranking the Danish halt at approximately −0.0104 on this measure — nearly on par with the Federal Reserve’s QE3 at −0.0120. The scheme allows cross-country and cross-program comparisons of unconventional monetary policy actions by reducing them to a common currency of anticipated supply change. The classification also distinguishes passive QT from active QT: the paper argues that passive QT (higher-than-anticipated issuance) is more contractionary than active QT of equal magnitude because higher issuance also reduces safe-asset scarcity value and shifts duration risk back to the market through two additional portfolio balance channels.

Q3. What does the Danish debt halt episode show?

The January 30, 2015 announcement by Denmark’s debt management office that it would halt new government bond issuance for the remainder of the year was unexpected and was followed within two trading days by a yield decline of approximately 25 basis points across the entire yield curve. The halt lasted roughly nine months and reduced the outstanding Danish government bond stock by approximately 29.9 billion DKK. The reaction is interpreted as evidence that market participants immediately revised down their expectations of future bond supply, compressing the compensation required for holding duration risk and raising the relative value of the now-scarcer safe assets.

Q4. What do the regression estimates imply?

Controlling for the concurrent SNB and ECB announcements in January 2015, the authors’ regression estimates imply that the Danish halt raised the safety premium on Danish bonds by 17–22 basis points and reduced the ten-year term premium by 37–70 basis points, pointing to a combined reduction in bond yields of 54–92 basis points relative to the counterfactual without the halt, measured over the halt period. The term-premium decline is interpreted as consistent with supply-induced portfolio balance effects: fewer bonds requiring lower duration-risk compensation. The safety-premium increase is consistent with safe-asset scarcity effects: a tighter supply of high-quality government bonds raising their relative scarcity value. These two channels are identified separately in the yield decomposition and estimated to be independently significant.

Q5. How does the paper treat passive QT?

The paper argues that passive QT — a higher-than-anticipated level of government debt issuance — is not a neutral background condition but an active contractionary force, and potentially more contractionary than active QT of equal magnitude through two additional portfolio balance channels. The argument is that higher issuance reduces safe-asset scarcity value and directly shifts duration risk from the central bank to the market, while active QT (central bank balance sheet reduction) lacks these two additional channels. This implies that fiscal authorities’ debt issuance decisions carry monetary policy implications that are not captured in frameworks treating issuance as a non-monetary decision.

Key concepts

passive QE : a deliberate reduction in government debt issuance that lowers anticipated future bond supply and reduces long-term yields through supply effects; the paper treats it as functionally equivalent to central bank asset purchase programs despite involving no asset purchases or reserves creation.

passive QT : higher-than-anticipated government debt issuance; the paper treats it as an active contractionary tool, potentially more contractionary than active QT of equal magnitude, because it triggers two additional portfolio balance channels.

safety premium : the premium on high-quality safe assets such as government bonds reflecting their scarcity value; in the Danish halt episode this rose as supply tightened.

term premium : the component of a long-term bond yield compensating investors for bearing duration risk; in the Danish halt episode this fell as anticipated future bond supply declined.

classification scheme : the paper’s taxonomy of central bank balance sheet policies organized by their net effect on anticipated future bond supply, allowing cross-program comparisons including passive QE and passive QT.

Danish debt halt : the January 30, 2015 announcement by Denmark’s debt management office of a halt to new government bond issuance for the remainder of the year, used as the natural experiment to test the passive QE hypothesis.

The Liquidity of the Government Bond Market — What Impact Does Quantitative Easing Have? Evidence from Sweden

Mon, 01 Jan 0001 00:00:00 +0000

This paper uses transaction-level bond data under MiFID I and II to measure five dimensions of Swedish government bond market liquidity during the Riksbank’s QE program (2015–2020) and identifies two offsetting effects: a demand effect, whereby outright purchases temporarily improve liquidity on the day of a transaction, and a scarcity (holding) effect, whereby the accumulated stock of central bank holdings persistently reduces liquidity. Across all five liquidity measures — Turnover (TURN), Turnover Ratio (TR), Yield Impact (YI), Market Efficiency Coefficient (MEC), and Volume-Adjusted Imputed Volatility (VAIV) — the scarcity effect is statistically significant and negative for all five, while the demand effect is positive and significant for four of five. Quantitatively, the scarcity effect is five times larger than the demand effect at average holding levels, and is nonlinear: both effects are near zero when the Riksbank’s holding share is below 40 percent of outstanding bonds, but the scarcity effect on transaction costs (YI) is approximately four times larger when holdings exceed that 40 percent threshold. The Swedish Debt Management Office’s Securities Lending Facility (SLF) partially mitigates the scarcity effect on two of five measures (YI and VAIV) but not on volume-based measures.

Summary of a forthcoming paper, AI-assisted and human-reviewed. See the linked original for the authoritative claims and full conditions.

In depth

Q1. What are the five liquidity measures and how are they constructed from MiFID transaction data?

The paper derives five measures from 316,413 filtered dealer-to-client and dealer-to-dealer transactions (out of 802,102 raw transactions) covering Swedish nominal government bonds from 2015 to 2020 under MiFID I and II reporting obligations. Tightness is captured by Yield Impact (YI), defined as the price change per trade divided by time to maturity — higher YI signals lower transaction costs per unit of duration. Immediacy and breadth are captured by Turnover (TURN, total volume traded weekly) and Turnover Ratio (TR, volume as a fraction of outstanding). Resilience is captured by Market Efficiency Coefficient (MEC) and Volume-Adjusted Imputed Volatility (VAIV): MEC compares return variance over long and short horizons — a ratio near one signals efficient absorption of order flow; VAIV measures price volatility after adjusting for volume, so that higher VAIV signals less efficient price formation per unit of trading. These five dimensions track different aspects of market quality and do not always move together, which is why using a single measure would miss the full picture.

Q2. What is the demand effect of QE purchases, and how large is it relative to the scarcity effect?

The demand effect captures the temporary improvement in liquidity on the week of a central bank purchase, measured by the coefficient on the contemporaneous Riksbank purchase variable; it is positive and significant for four of the five measures (TURN, TR, YI, and VAIV), but not for MEC. In the baseline regression (Table 3, Panel 1), a one standard deviation increase in outright purchases increases YI by approximately 4.4 standard deviations. However, this is a one-time event: the coefficient on purchases captures the effect at time t only, and the paper confirms that liquidity in the subsequent week is not significantly affected by prior purchases. By contrast, the scarcity (holding) effect from accumulated bond stock is persistent: at average holding levels of approximately 36 percent of outstanding, the holding variable decreases YI by 0.15 basis points from an average level of around 1.17 basis points per transaction. The scarcity effect is therefore approximately five times larger than the demand effect at these holding levels, and lasts as long as the central bank holds the bonds — effectively until maturity.

Q3. What is the nonlinearity in the scarcity effect and how is the 40 percent threshold identified?

The threshold is identified from a bond-by-bond analysis of the Debt Management Office’s Securities Lending Facility (SLF) usage: both the volume and volatility of SLF activity increase significantly when the Riksbank’s holding share crosses approximately 40 percent of outstanding for a given bond, indicating that market participants seek alternative sources of bond supply precisely at that concentration level. The paper re-estimates the baseline model on two subsamples — bonds with holding below 40 percent and bonds with holding above 40 percent. Below the threshold, neither the demand effect nor the scarcity effect is significant for most measures (all purchase coefficients become insignificant except MEC, which turns negative; all holding coefficients are insignificant except TR which turns negative). Above the threshold, the demand effect strengthens (intuition: with fewer free-float bonds, the marginal impact of a purchase on liquidity is amplified), and the scarcity effect on YI is approximately four times larger than in the baseline. Volume-based turnover measures (TURN and TR) do not show significant scarcity effects above the threshold, suggesting that the scarcity effect concentrates on transaction costs and price efficiency rather than traded volumes when the holding share is large.

Q4. Does the Securities Lending Facility offset the scarcity effect?

The SLF coefficient is consistently positive across all five measures, and statistically significant for YI and VAIV in the baseline, suggesting the facility partially restores liquidity by lending bonds to market makers when the central bank’s holdings reduce free-float supply. However, the SLF does not significantly improve the volume-based measures (TURN and TR), and the effect is only detectable above the 40 percent threshold for turnover measures. The paper orthogonalizes SLF volumes against the Holding variable (to address the 50 percent pooled correlation between them) and finds no material change in the holding coefficients. The interpretation is that the SLF provides a buffer against scarcity-driven deterioration in transaction costs and price efficiency, but it does not fully restore pre-QE liquidity levels when holding shares are high. The paper also notes that the SLF may set a floor for short-term market interest rates relative to the policy rate, partially offsetting QE’s effect on yields — a second-order consideration for the liquidity analysis but relevant for the broader QE transmission mechanism.

Q5. Why does bond market liquidity not respond to QE announcements?

The paper tests whether QE announcement dates predict liquidity improvements and finds that they do not: liquidity responds only to actual purchases, not to forward-looking price adjustments at announcement. This contrasts with asset prices, which are forward-looking and respond immediately to announced changes in the expected path of central bank asset holdings. Bond market liquidity depends on the physical quantity of bonds available for trading, which changes only when purchases are executed, not when they are anticipated. This asymmetry has a policy implication: policymakers cannot exploit an announcement effect to improve market liquidity in advance of purchases, and the liquidity costs of QE (the scarcity effect) accumulate gradually over the purchase period rather than being front-loaded at announcement.

Q6. How robust are the results to time aggregation, time fixed-effects, outliers, and alternative specifications?

The baseline results are robust across six groups of robustness checks. (1) Time aggregation: results are materially unchanged at monthly frequency. (2) Time fixed-effects: switching from month FE to year FE or to no FE (replacing FE with macroeconomic controls including VIX, business confidence, money market premium, 5–2 year yield spread, debt-to-GDP, and the ESMA sovereign bond liquidity index) does not change the sign or significance of the demand and scarcity coefficients. (3) Outliers: winsorizing or truncating at the 5th and 95th percentile preserves the main results despite removing 10–18 percent of observations. (4) SLF specifications: orthogonalizing SLF volumes against Holding, normalizing by total outstanding rather than free float, and lagging up to four periods do not materially change results. (5) Inflation-linked bonds: including inflation-linked bonds (which are less liquid than nominal bonds) amplifies both effects as expected. (6) The paper also checks that the threshold of 40 percent is not driven by threshold choice: results at alternative thresholds (both lower and higher) are consistent in direction.

Q7. What is the broader implication for QE program design?

The results imply that QE programs face a liquidity-yield tradeoff: large-scale asset purchases that achieve meaningful yield compression must reach holding concentrations that materially impair government bond market liquidity, and this impairment is nonlinear and accelerates once concentration exceeds approximately 40 percent of outstanding per bond. For central banks designing future purchase programs, the threshold suggests a natural limit on per-bond concentration, consistent with the ECB’s 33 percent issuer limit for its own purchase programs. The paper also highlights the role of complementary facilities: the SLF partially offsets the scarcity effect on transaction costs, suggesting that security lending programs are a useful adjunct to large-scale asset purchases. The finding that the scarcity effect persists as long as holdings are maintained — rather than reverting when purchases stop — implies that balance sheet normalization (quantitative tightening) may be needed to restore liquidity, not merely a pause in purchases.

Key concepts

demand effect: the temporary improvement in government bond market liquidity on the day of a Riksbank outright purchase, reflecting the positive price impact of incremental buyer demand; positive and significant for four of five liquidity measures, but transitory (does not persist to the following week).

scarcity effect (holding effect): the persistent deterioration in government bond market liquidity caused by the accumulated stock of bonds held by the Riksbank, which reduces free-float supply available to market participants; negative and significant for all five measures, five times larger than the demand effect at average holding levels, and nonlinear — concentrated and amplified when holding share exceeds 40 percent of outstanding.

Yield Impact (YI): a transaction-cost measure of tightness defined as the price change per trade divided by time to maturity; higher YI indicates lower transaction costs per unit of duration; the paper’s primary measure for quantifying the demand and scarcity effects.

Market Efficiency Coefficient (MEC): a resilience measure comparing return variance over long and short horizons; a ratio near one signals efficient absorption of order flow; the measure for which the demand effect is not positive and significant in the baseline, suggesting QE purchases may temporarily disrupt price efficiency rather than improve it.

Securities Lending Facility (SLF): the Swedish Debt Management Office’s bond-lending program that lends government bonds to market makers against collateral; partially offsets the scarcity effect on transaction costs (YI, VAIV) but not on volume-based measures (TURN, TR), and its activity accelerates when Riksbank holdings exceed 40 percent.

free-float supply: the quantity of a government bond available for trading in the secondary market after subtracting the central bank’s holdings; the mechanism through which the scarcity effect operates — lower free-float reduces order book depth and increases transaction costs.