Repo over the Financial Crisis: Copeland & Martin (2025)

What this is. The paper’s core results, the data sources it introduces, and the empirical specifications it runs: enough to know what it found and how, without reading all 26 pages. To replicate or extend it, read the original at doi.org/10.1111/jofi.13406.

TL;DR

Using new confidential data that cover all four segments of the U.S. repo market (interdealer and dealer-to-client, general collateral and mixed), the paper documents three facts about the 2007-2009 Global Financial Crisis: (1) the decline in repo activity was far larger in bilateral (MIX) segments than in tri-party (GC) segments; (2) more than half the decline was concentrated in Treasury-backed repos, the safest and most liquid asset class, contradicting the flight-to-quality narrative; and (3) the decline was not correlated with measures of dealer counterparty credit risk (CDS spreads, CP rates), but was instead driven by a pullback in securities-driven market-making trades by large securities dealers. The paper uses a securities-dealer panel and a seemingly unrelated regression (SUR) design to trace the repo decline to a reduction in back-to-back securities-driven trades entered by large dealers, particularly after the Lehman Brothers bankruptcy.

Core results

Magnitudes and significance are as reported; \* = 10%, \*\* = 5%, \*\*\* = 1%. Locators point into the source PDF.

#	Result	Locator	Magnitude
R1	Treasury repo fell more than other asset classes despite the flight-to-quality narrative	Table I, p. 920	Total repo -17% (-$798B pre-crisis to crisis); Treasury -20% (-$470B); All others -15% (-$328B); agency MBS only -1%
R2	MIX (bilateral) segments contracted sharply; GC (tri-party) segments were stable or grew	Table II, p. 921	MIX ID: -24%; MIX DtC: -31%; GC ID: +7%; GC DtC: -10%. For Treasuries: MIX ID: -23%; MIX DtC: -37%; GC ID: +52%; GC DtC: +7%
R3	CDS and CP spreads have no statistically significant association with MIX repo activity; counterparty credit concerns do not explain the decline	Table IV, p. 925; Table V, p. 927	CDS coeff = -3.757 (SE 12.733), p>0.10; R² = 0.029. CP coeff = 0.035 (SE 0.055), p>0.10
R4	Post-Lehman, the association between MIX repo and MIX reverse repo falls, while MIX reverse repo and DtC GC repo become correlated for large dealers, indicating a pivot to cash-driven trades	Table VI, p. 929	PL × delta MIX Revr coeff in MIX repo: -0.17 (insig.); PL × delta MIX Revr coeff in DtC GC repo: 0.20** (SE 0.09)
R5	Large dealers drive the change: the post-Lehman drop in securities-driven repo is concentrated among above-median dealers	Table VII, p. 931	PL × Large × delta MIX Revr in MIX repo: -0.60* (SE 0.33); in DtC GC repo: +0.70** (SE 0.30); no significant change for small dealers
R6	On-the-run Treasury repo, a direct proxy for securities-driven trades, fell $155 billion (54%) from Q2 to Q4 2008; this decline is concentrated at large dealers	Figure 4, p. 933	From $286B (Q2 2008) to $131B (Q4 2008); distribution narrows, with the 75th percentile falling more than the median or 25th percentile

Overall (paper’s conclusion). The massive decline in repo over the financial crisis was driven primarily by a pullback in securities-driven trades that support Treasury market-making by securities dealers, not by a generalized disruption in funding conditions or by clients fleeing dealers out of counterparty credit concerns. Copeland and Martin (2025) and Copeland, Martin, and Walker (2014) jointly show that the GC (funding) segment remained stable, so funding disruptions did occur but were institution-specific (Bear Stearns, Lehman Brothers), not market-wide. The extent of true funding disruption was considerably smaller than the decline in overall repo activity implies.

Theory / model

The paper has no formal model. Its identification strategy rests on the institutional structure of the repo market: the U.S. repo market is segmented into four segments that differ in clearing platform and in whether they accommodate securities-driven versus cash-driven trades (pp. 914-915).

Key institutional distinction. The general collateral (GC) segment settles on the tri-party platform. By design, all GC trades are cash-driven: parties agree only on an asset class, not a specific security, so the GC segment cannot support securities-driven price-discovery trades. The mixed (MIX) bilateral segment accommodates both cash-driven and securities-driven trades. This segmentation means that changes in MIX activity capture changes in both motives, while changes in GC activity capture only changes in cash-driven (funding) motives.

Tested hypotheses. Given the segmentation above, the paper tests three hypotheses:

1. Whether the decline in repo was disproportionately in MIX (bilateral) versus GC (tri-party) segments. Gorton and Metrick (2012) and Gorton, Metrick, and Ross (2020) document large aggregate haircut increases and net-repo declines at banks; Copeland, Martin, and Walker (2014) and Krishnamurthy, Nagel, and Orlov (2014) find that DtC GC (tri-party) activity held up. This paper unifies both views by showing MIX segments drove most of the decline.
2. Whether the decline was correlated with measures of dealer counterparty credit risk (a “run on repo” hypothesis in the spirit of Gorton and Metrick (2012)).
3. Whether, post-Lehman, the statistical association between dealers’ MIX repo and MIX reverse repo weakened while the MIX reverse repo and DtC GC repo association strengthened (a pivot-to-cash-driven-trades hypothesis). Musto, Nini, and Schwarz (2018) document the corresponding price effects in Treasuries; this paper documents the associated quantity decline in securities-driven Treasury repo.

Method

The paper applies two estimation strategies: aggregate descriptive comparisons across periods and segments, and a dealer-level panel regression.

Aggregate analysis. Using FR 2004C data (a weekly Federal Reserve survey of primary dealers) plus FICC GCF Repo and FICC DVP service data, the paper constructs average daily repo outstanding by segment and asset class for the pre-crisis period (July 1 to September 13, 2008) and the crisis period (October 15 to December 17, 2008), then computes differences. This is a descriptive before-after comparison with no causal identification design (p. 919).

Dealer-level panel: counterparty credit risk. The paper estimates four OLS regressions (equations 1-4, p. 924) relating changes in MIX repo to contemporaneous or lagged changes in CDS spreads, plus Treasury-related controls. Standard errors are clustered at the dealer level (18 dealers, 21 weeks, 378 observations). The specifications are (pp. 924-926):

$$\Delta \text{MIXRepo}_{i,t} = \alpha_0 + \alpha_1 \Delta \text{CDS}_{i,t} + \Delta X_t \beta_0 + \varepsilon^1_{i,t} \tag{1}$$ $$\Delta \text{MIXRepo}_{i,t} = \alpha_2 + \alpha_3 \Delta \text{CDS}_{i,t-1} + \Delta X_t \beta_1 + \varepsilon^2_{i,t} \tag{2}$$

and log-level variants (equations 3 and 4). The CP spread regressions (equations 5 and 6, p. 926) are:

$$\log(\text{MIXRepo})_{i,t} = \alpha_0 + \beta_0 \text{CP}_{i,t} + \log X_t \gamma_0 + \eta_i + \varepsilon^1_{i,t} \tag{5}$$ $$\Delta \log(\text{MIXRepo})_{i,t} = \alpha_1 + \beta_1 \Delta \text{CP}_{i,t} + \Delta \log X_t \gamma_1 + \varepsilon^2_{i,t} \tag{6}$$

Dealer-level panel: repo flow analysis. The paper estimates a seemingly unrelated regression (SUR) system (equations 7-9, p. 928) with three left-hand side variables: change in MIX repo, change in DtC GC repo, and change in ID GC repo. The key right-hand side variables are MIX reverse repo and ID GC reverse repo, interacted with a post-Lehman dummy (PL) to allow strategies to differ across the two periods:

$$\Delta \text{MIXRepo}_{j,t} = \alpha_0 + \alpha_1 \Delta \text{MIXRevr}_{j,t} + \alpha_2 PL_t + \alpha_3 PL_t \cdot \Delta \text{MIXRevr}_{j,t} + \Delta X_t \beta_0 + \varepsilon^0_{j,t} \tag{7}$$ $$\Delta \text{DtC\text{-}GCRepo}_{j,t} = \alpha_4 + \alpha_5 \Delta \text{MIXRevr}_{j,t} + \alpha_6 \Delta \text{ID\text{-}GCRevr}_{j,t} + \alpha_7 PL_t + \alpha_8 PL_t \cdot \Delta \text{MIXRevr}_{j,t} + \alpha_9 PL_t \cdot \Delta \text{ID\text{-}GCRevr}_{j,t} + \Delta X_t \beta_1 + \varepsilon^1_{j,t} \tag{8}$$ $$\Delta \text{ID\text{-}GCRepo}_{j,t} = \alpha_{10} + \alpha_{11} \Delta \text{MIXRevr}_{j,t} + \alpha_{12} \Delta \text{ID\text{-}GCRevr}_{j,t} + \alpha_{13} PL_t + \alpha_{14} PL_t \cdot \Delta \text{MIXRevr}_{j,t} + \alpha_{15} PL_t \cdot \Delta \text{ID\text{-}GCRevr}_{j,t} + \Delta X_t \beta_2 + \varepsilon^2_{j,t} \tag{9}$$

SUR allows correlated error terms across the three equations. Standard errors are clustered at the dealer level. The 288-observation sample reflects 18 dealers over the full weekly sample. Table VII repeats the cross-sectional analysis with dealer-size and domestic/foreign dummy interactions.

Empirical specifications

Sample. Dealer-level weekly data covering July 1 to December 17, 2008 (excluding two quarter-end weeks and the week of Lehman’s bankruptcy), leaving 21 weeks and 18 primary dealers (378 observations for the CDS panel, 288 for the SUR after excluding Lehman Brothers). The pre-crisis period is July 1 to September 13; the crisis period is October 15 to December 17.

Counterparty-risk regressions (R3). OLS with four specifications (level and log, contemporaneous and lagged CDS; level and change in CP). Controls: net Treasury bill issuance, net coupon issuance, Federal Reserve SOMA operations, total UST holdings by the Fed. Standard errors clustered at the dealer level. The R-squared statistics are very low (0.013-0.031), and all CDS and CP coefficients are statistically insignificant, confirming no systematic relationship between dealer risk measures and MIX repo (Tables IV-V, pp. 925, 927).

SUR repo-flow regressions (R4, R5). The identifying variation is the differential post-Lehman change in the association between a dealer’s repo and reverse repo activity across segments. The PL interaction terms capture this change. The null hypothesis tested is that these associations did not change after Lehman; rejection implies dealers shifted strategies. Table VII adds size (large vs small) and location (domestic vs foreign) dummies to capture heterogeneous responses (p. 930).

On-the-run Treasury repo (R6). Using the FR 2004SI survey (a special-purpose data collection), the paper tracks repo involving specifically identified on-the-run Treasuries, which are almost never used in cash-driven transactions. The time series of aggregate on-the-run Treasury repo and the cross-sectional distribution across dealers are plotted in Figure 4 (p. 933) as direct evidence of the securities-driven trade decline.

Datasets used

Dataset	Role in paper	Wiki page
FR 2004C (Federal Reserve weekly survey of primary dealers)	Primary source for repo and reverse repo outstanding by asset class; covers all primary dealers at weekly frequency, 2004-2013	No page yet
FICC GCF Repo Service data (dealer-level daily, licensed via FRBNY)	Interdealer GC segment repo and reverse repo by asset class at dealer level	No page yet
FICC DVP Service data (aggregate-level daily)	Interdealer MIX segment repo; aggregate only	No page yet
DtC TPR (tri-party repo) data (confidential, from FRBNY)	Dealer-to-client GC segment repo by dealer and asset class	No page yet
Markit Group CDS spreads (five-year modified restructuring, USD)	Proxy for dealer counterparty credit risk; matched to 13 of 18 dealers	Markit CDS (licensed)
DTCC commercial paper interest rates (confidential)	Dealer-level weekly CP interest rates; proxy for dealer counterparty risk	No page yet
FR 2004SI (special-purpose survey)	On-the-run Treasury repo activity by primary dealer; direct proxy for securities-driven trades	No page yet

Sample: second half of 2008 (July-December) for dealer-level analysis; 2004-2013 for aggregate FR 2004C time series. Weekly frequency. 18-19 primary dealers (Lehman excluded from panel analysis).

When to read the full paper

Read the original if you are: analyzing the drivers of repo market stress during the 2007-2009 GFC; studying the comparative resilience of tri-party versus bilateral repo markets; investigating the role of securities dealers as intermediaries in Treasury market-making; or examining whether the March 2020 Treasury market disruptions share mechanisms with the 2008 crisis (the paper’s conclusion draws this parallel explicitly). The Internet Appendix contains additional robustness tables (IA.II) and a map of the U.S. repo market (Section III).

Attribution and rights

Source: peer-reviewed, The Journal of Finance 80(2), April 2025, pages 911-936. DOI: 10.1111/jofi.13406. This article is a U.S. Government work and is in the public domain in the USA (as stated on p. 911 of the artifact). Crossref records Wiley standard terms; the artifact’s public-domain notice takes precedence for U.S. readers. This distillation was extracted by an LLM on 2026-06-06 and is not human-verified or independently reproduced. Extract-only: the verbatim PDF is not hosted here.

Citation. Copeland, Adam, and Antoine Martin. “Repo over the Financial Crisis.” The Journal of Finance 80, no. 2 (April 2025): 911-936. DOI: 10.1111/jofi.13406.