LOOKING BEHIND THE AGGREGATES:
A REPLY TO “FACTS AND MYTHS ABOUT THE
FINANCIAL CRISIS OF 2008”
Working Paper No. QAU08-5
Ethan Cohen-Cole
Burcu Duygan-Bump
Jose Fillat
Judit Montoriol-Garriga
Federal Reserve Bank of Boston
This paper can be downloaded without charge
from:
The Quantitative Analysis Unit of the Federal
Reserve Bank of Boston
http://www.bos.frb.org/bankinfo/qau/index.htm
The Social Science Research Network Electronic
Paper Collection:
http://ssrn.com/abstract=1294766
Looking Behind the Aggregates:
A reply to “Facts and Myths about the Financial Crisis of 2008” *
Ethan Cohen-Cole
Burcu Duygan-Bump
Jose Fillat
Judit Montoriol-Garriga
FEDERAL RESERVE BANK OF BOSTON
12 November 2008
Abstract
As Chari et al (2008) point out in a recent paper, aggregate trends are very hard to interpret. They
examine four common claims about the impact of financial sector phenomena on the economy and
conclude that all four claims are myths. We argue that to evaluate these popular claims, one needs to look
at the underlying composition of financial aggregates. Our findings show that most of the commonly
argued facts are indeed supported by disaggregated data.
*
We thank numerous colleagues in Bank Supervision, and especially Patrick de Fontnouvelle, Peggy Gilligan,
Jamie Marsh, Maureen Tighe, and Christina Wang for sharing their comments and expertise on the subject of banks
and financial markets. We would also like to thank Jonathan Larson for excellent research assistance. The views
expressed herein are those of the authors and do not reflect those of the Federal Reserve Bank of Boston or the
Federal Reserve System.
Overview
The US and world economies are in the midst of a severe financial crisis. The crisis is undoubtedly linked
in some fashion to financial institutions. The fundamental question Chari et al (2008), henceforth CCK,
seek to address is the degree to which varied claims about the way the crisis affects the real economy are
true.
CCK make two primary arguments. First, they argue that a set of four now common claims about the
nature of the crisis are false. Second, they assert that interest rate spreads, in particular the spread between
the London Interbank Offered Rate (LIBOR) and the fed funds rate may be informative about the cost of
borrowing during normal times, but misleading during crises as the increased spreads may be “due to the
drop in the real return to Treasury securities as a result of the flight to quality and does not constitute an
increase in the real cost of borrowing.”
In this short note, we consider their first argument and present further evidence on the four claims that are
examined in CCK. Using publicly available data, we show that these facts are indeed true and not
mythical. Their second argument on spreads remains a more theoretical one that we leave for another
short note.
The four claims: Myth or Fact?
CCK present four claims that both the press and policymakers have made about the nature of the crisis
and the associated impact on the rest of the economy. Here, we present further evidence that the first three
of these are facts and not myths. The fourth claim requires a more nuanced view which we also address
below.
1. Bank lending to nonfinancial corporations and individuals has declined sharply.
CCK show a number of graphs using Federal Reserve data that plot total loans from bank balance sheets
over time. They conclude from these charts, which show an increasing trend over time, that there has not
been an impact on lending to non-financial firms or consumers during the crisis. We agree that the
aggregate patterns show no evidence of a decline. However, these aggregates hide the underlying
dynamics and belie the fact that the components of this data show a sharp weakening of credit conditions.
During crises, bank balance sheets expand for a number of reasons. First, one consequence of the credit
crisis is that loan "securitization," the business of packaging various loans (home, business, auto and
other) into assets for investors, has become more difficult. Accordingly, banks have had to keep the loans
2
they make on their balance sheets. Figures 1A–1B present strong evidence on the declining issuance in
securitization markets.
Second, during this and other times of financial weakening, companies increasingly rely on their existing
loan commitments and lines of credit. This is because general liquidity dries up and commercial paper
markets become strained. As a result, the aggregate figures in CCK do not reveal the weakening in new
lending. In fact, CCK acknowledge this point in the revised version of their working paper and highlight
the fact that they would like to see data supporting this argument. In Figure 1C, we plot the ratio of total
outstanding to total commitments in syndicated loans and show a significant increase in draw-downs from
lines of credit, comparable to the levels during the Savings and Loan crisis in the early 1990s. Similarly,
in Figures 1D and 1E, we plot data based on publicly available call reports and show that unused lending
commitments at commercial banks, especially for commercial and industrial loans, have contracted since
the last quarter of 2007. 1
Two drivers may be behind this pattern. The first is that banks are actively managing lines of credit by not
renewing them at maturity, reducing the limit or even closing some of the lines. A second explanation is
that firms are actually using the lines of credit, inducing so-called “involuntary lending”. Both reasons
imply that banks are reducing new lending, especially to businesses. Unfortunately, the call report data
are released with a lag and still do not cover the most recent events following the Lehman default.
However, the trend is in line with more recent anecdotal evidence. A Wall Street Journal article from
October 16th, 2008 reports mass draw-downs by cash-strapped companies since mid-September with a
few exclusions of big banks who have not witnessed such a rush to tap revolvers.
Unfortunately, neither the figures in CCK nor the ones just presented capture the complete picture. We
believe that the more relevant claim here is not the one CCK formulated but is instead the following:
“Bank credit has become more difficult and expensive to obtain”. This is because the increased LIBOR
rates translate to higher nominal funding expenditures, something CCK do not discuss even though they
include these rates in their figures. We strongly believe that to assess whether changes in bank lending
have had an impact on the real economy, one needs information on prices as well as quantities. Some
evidence for this is seen in the spread between exclusively private jumbo mortgages and conforming
loans underwritten with prior commitment to buy from government sponsored entities such as Fannie
Mae and Freddie Mac (Figure 1F).
1
There is also strong survey evidence based on the most recent Senior Loan Officer Opinion Survey on Bank
Lending Practices, which shows a significant increase in the net fraction of domestic institutions that report having
tightened their lending standards and terms on all major loan categories over the previous three months.
3
2. Interbank lending is essentially nonexistent.
CCK plot a chart of “interbank loans” based on weekly data on commercial banks’ assets and liabilities
(H8) that is largely unchanging over time. This figure appears to be derived from the H8 item of the same
name. They conclude from this figure that interbank lending has indeed not decreased.
Unfortunately, this category of “Interbank Loans” from H8 data is very opaque. We know for example
that it does not include lending to non-bank brokers and dealers, which is of similar magnitude as bankto-bank transactions and also shows significant declines. In order to assess the true health of the interbank
lending market, we need to better understand this aggregate interbank lending number and to decompose
it by maturity and type (unsecured vs. secured, and in the latter case, type of collateral). For example,
there is a significant amount of anecdotal evidence that a large portion of the interbank market has
become overnight repos exclusively backed by government securities, which suggest that interbank
lending is not working as usual. We agree with CCK that additional information would be useful here.
To re-iterate our point that such aggregated facts in isolation are hard to interpret and hide the underlying
dynamics, we also consider movements in other line items from the H8 data. For example, Figure 2A
shows the evolution of “cash assets” of banks and highlights the extent of cash hoarding. The picture is
even sharper when we disaggregate the numbers for big vs. small banks as in Figure 2B. This figure adds
further support to this second claim as well as the first one discussed above. After all, if interbank lending
markets were functional and banks were not worried about meeting various liquidity demands (e.g. drawdowns on existing commitments), they would not carry such a high volume of cash given the significant
opportunity cost.
Finally, the short-term demand for interbank funds is known to be highly inelastic such that one would
not expect to see a large change in quantities of these funds. 2 In other words, looking at quantities alone
to make inferences about the health of interbank lending cannot be very informative, and rates are likely
to be the true indicators of strain in this market as shown in Figure 2C (also reported in CCK).
3. Commercial paper issuance by nonfinancial corporations has declined sharply, and rates have risen
to unprecedented levels.
CCK plot commercial paper (CP) outstanding for financials vs. non-financials and 90-day CP rates to
argue that non-financials have been largely unaffected. The argument is largely based on the fact that AA
non-financial firms show little change in quantities outstanding or in 90 day rates.
2
In recent weeks, interbank lending is likely to have been affected also by the increased lending by the Fed.
4
Again, we argue that it is important to look behind these aggregate numbers and the underlying dynamics.
First, there is a large difference in outcomes for AA and A2/P2 non-financial companies as can be seen in
CCK’s Figure 7A. Here we plot the further disaggregated commercial paper outstanding numbers for AA
Non-financials and A2/P2 Non-financials (Figure 3A), and show that there were indeed non-financials
affected by the crisis. Similarly, Figure 3B shows the overnight (1–4 day) and 30 day yields on various
sub-categories of CP (Figure 3B) and highlights the strains in the ABCP market (top panel) as well as the
A2/P2 market (the bottom panel). This last panel is actually not surprising as A2/P2 borrowers are the
marginal borrowers. While one may take comfort in the fact that AA borrowers can obtain CP funding, it
does not necessarily reflect the absence of problems in the CP market overall. In fact, we interpret this as
evidence of flight to quality.
Second, a change in the term of new issues is an important indicator as it can potentially be a reflection of
a changing risk or term premium. Figure 3C shows the percentage of overnight (1–4 day maturity) paper
in new gross issuance and highlights how CP has become a short-term instrument during this most recent
period: the share of overnight issuance for ABCP increased to as much as 90% in the days following
Lehman’s failure.
Finally, one needs to note that these yields are based on a selected sample of programs, and particularly
ones that have been able to issue paper during this time. It is highly possible that there were many
programs that have been unable to issue any CP in the past month. Accordingly, the observed prices are
likely to provide an underestimate of the true cost of borrowing. In other words, even though it is true that
strong non-financials have been relatively less affected, we believe that the strains in the CP market are
factual and not mythical.
4. Banks play a large role in channeling funds from savers to borrowers.
CCK argue that 80% of business borrowing takes place outside the banking system. They also suggest
that banks may be tapping into increased deposits to make up for the strained conditions in CP market.
We agree with CCK on this point: the first statement is a well-established fact and there is strong
evidence (as CCK also presents) that deposits indeed flow to banks during liquidity crises and that banks
use these deposits to hedge their liquidity risk to fund the loans against existing commitments (Gatev and
Strahan, 2006).
However, this argument overlooks the impact on small businesses and especially households that still rely
heavily on bank lending given their limited access to capital markets. In fact, data released from the
Federal Reserve shows that total consumer credit (excluding loans secured by real estate) outstanding
5
decreased at an annual rate of 3.7% in August, driven mainly by a 5.4% annual decrease in non-revolving
credit. 3 Moreover, there is no reason to believe that the proportions 80%–20% are static. In other words,
when CP markets become strained, the pressure on banks to fulfill this role increases as those companies
that comprised the 80% now need a different funding source. So, the concern remains: will the banks be
able to fulfill this role given existing balance sheet constraints? Evidence presented above that banks are
hoarding cash suggests either that they are unwilling or unable to do so.
Conclusion
Our analysis has shown that the claims regarding the financial markets and the mechanism through which
they may affect the real economy are largely supported by looking behind the aggregates of publicly
available data. Having said so, we would like to point out the need for a more thorough analysis than the
simple plots we have provided here. After all, there are many other confounding factors that make
interpretation of these numbers difficult. For example, it is hard to even understand what it means to
observe a decrease in lending. Simple plots cannot help us disentangle the extent to which changes in new
bank lending are caused by banks cutting lending or by decreased demand for loans due to a slow-down
in the real economy.
Given that both the US and the world economies are undergoing a financial crisis, we emphasize, along
with CCK, the need for ample data and analyses to support policy decisions. We encourage future studies.
References
Chari, V.V., Lawrence Christiano, and Patrick J. Kehoe, October 2008, “Facts and Myths about the
Financial Crisis of 2008,” Federal Reserve Bank of Minneapolis Research Department Working Paper
No: 666.
Gatev, Evan and Philip E. Strahan, 2006, “Banks’ Advantage in Hedging Liquidity Risk: Theory and
Evidence from the Commercial Paper Market,” Journal Of Finance, Vol. 56 (2).
Kashyap, A., Raghuram Rajan and Jeremy C. Stein, 2002, “Banks as Liquidity Providers: An Explanation
for the Coexistence of Lending and Deposit-Taking,” Journal of Finance, vol. 57(1).
Wall Street Journal (2008) "For Fast Cash, Firms Tap Revolving Loans," October 16.
3
http://www.federalreserve.gov/releases/g19/current/
6
Figure 1A: US Asset Backed Securities Issuance (in $ bil.)
120.0
100.0
80.0
60.0
40.0
20.0
Sep-06
Mar-07
Sep-07
Mar-08
Sep-08
Sep-06
Mar-07
Sep-07
Mar-08
Sep-08
Mar-06
Sep-05
Mar-05
Sep-04
Mar-04
Sep-03
Mar-03
Sep-02
Mar-02
Sep-01
Mar-01
Sep-00
Mar-00
Sep-99
Mar-99
0.0
Source: http://www.abalert.com/Public/MarketPlace/MarketStatistics/index.cfm
Figure 1B: US Non-Agency Mortgage Backed Securities Issuance (in $ bil.)
70.0
60.0
50.0
40.0
30.0
20.0
10.0
Source: http://www.abalert.com/Public/MarketPlace/MarketStatistics/index.cfm
7
Mar-06
Sep-05
Mar-05
Sep-04
Mar-04
Sep-03
Mar-03
Sep-02
Mar-02
Sep-01
Mar-01
Sep-00
Mar-00
Sep-99
Mar-99
0.0
Figure 1C: Total Outstanding to Total Commitments in Syndicated Loans
0.5
0.45
0.4
0.35
0.3
2008
2007
2006
2005
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
1991
1990
1989
0.25
Source: Federal Reserve Board, http://www.federalreserve.gov/newsevents/press/bcreg/20081008a.htm
8
Figure 1D: Unused commitments (in $billions)
Unused commitments (b$) - Left scale
Other unused commitments (C&I) (b$) - Right scale
8500
2900
8000
7500
2700
7000
2500
6500
2300
6000
2100
5500
1900
5000
1700
4500
20082
20074
20081
20073
20072
20064
20071
20063
20062
20061
20053
20054
20052
20051
20043
20044
20042
20041
20033
20034
20032
20031
20023
20024
20022
20021
20014
20012
20013
20011
20004
20002
20003
1500
20001
4000
Source: Report of Condition and Income (Call Reports)
http://www.chicagofed.org/economic_research_and_data/commercial_bank_complete_files_2001_2008.cfm
Notes: Pink line: Total unused commitments. RCDF3423 (sum of 3814 3815 3816 6550 3817 3818); Blue Line:
Other unused commitments. RCDF3818.
Figure 1E: Ratio of unused commitments over loans
1.6
1.5
1.4
1.3
1.2
1
20001
20002
20003
20004
20011
20012
20013
20014
20021
20022
20023
20024
20031
20032
20033
20034
20041
20042
20043
20044
20051
20052
20053
20054
20061
20062
20063
20064
20071
20072
20073
20074
20081
20082
1.1
Unused commmitments over loans
Other unused commmitments over C&I loans
Source: Report of Condition and Income (Call Reports)
http://www.chicagofed.org/economic_research_and_data/commercial_bank_complete_files_2001_2008.cfm
Notes: Pink line: Total unused commitments divided by total loans. RCFD3423 divided by RCFD1400; Blue Line:
Other unused commitments divided by C&I loans. RCFD3818 divided by RCFD1766 (*)
(*) the definition of C&I commitment ratio is provided by Kashyap, Rajan and Stein (JF-2002, p.71)
9
Figure 1F: Jumbo and Conforming 30yr. Fixed Mortgage Rates
Jumbo and Conforming 30yr Fixed Mortgage Rates
8
7.5
7
6.5
6
5.5
5
10/1/06
1/9/07
4/19/07
7/28/07
Jumbo
11/5/07
2/13/08
5/23/08
8/31/08
Conforming
Spread between Jumbo and Conforming (bps)
165
145
125
105
85
65
45
25
5
10/1/06
1/9/07
4/19/07
7/28/07
11/5/07
Source: Bloomberg.
10
2/13/08
5/23/08
8/31/08
Figure 2A: Cash Assets of Commercial Banks (n.s.a., in $billions)
600
550
500
450
400
350
300
10/5/2008
7/5/2008
4/5/2008
1/5/2008
10/5/2007
7/5/2007
4/5/2007
1/5/2007
10/5/2006
7/5/2006
4/5/2006
1/5/2006
10/5/2005
7/5/2005
4/5/2005
1/5/2005
250
Source: Federal Reserve Board, http://www.federalreserve.gov/releases/h8/
Figure 2B: Cash Assets of Domestic Commercial Banks, by bank size (n.s.a., in $billions)
350
300
250
200
150
100
Cash (large banks)
10/5/2008
7/5/2008
4/5/2008
1/5/2008
10/5/2007
7/5/2007
4/5/2007
1/5/2007
10/5/2006
7/5/2006
4/5/2006
1/5/2006
10/5/2005
7/5/2005
4/5/2005
0
1/5/2005
50
Cash (small banks)
Source: Federal Reserve Board, http://www.federalreserve.gov/releases/h8/
Notes: “Cash Assets” includes vault cash, cash items in process of collection, balances due from depository
institutions, and balances due from Federal Reserve Banks.” H8 Data downloaded on October 29, 2008.
11
Figure 2C: Libor-OIS 1-month spreads
3
2.5
2
1.5
1
0.5
Sep-08
Aug-08
Jun-08
9/29/2008
Jul-08
May-08
8/29/2008
Apr-08
Apr-08
Mar-08
Feb-08
Jan-08
Dec-07
Nov-07
Oct-07
Sep-07
Aug-07
Aug-07
Jul-07
Jun-07
May-07
Apr-07
Mar-07
Feb-07
Jan-07
0
Source: Bloomberg.
Figure 3A: Commercial Paper Issuance, Non-Financials by rating (in $millions)
8000
7000
6000
5000
4000
3000
2000
1000
A2/P2 Nonfinancial
7/29/2008
6/29/2008
5/29/2008
4/29/2008
3/29/2008
2/29/2008
1/29/2008
12/29/2007
11/29/2007
10/29/2007
9/29/2007
8/29/2007
7/29/2007
6/29/2007
5/29/2007
0
AA Nonfinancial
Source: Federal Reserve Board, http://www.federalreserve.gov/DataDownload/Choose.aspx?rel=CP.
Notes: Daily, 20-day moving averages based on "Volume Statistics for Commercial Paper Issuance", total value of
issues with a maturity between 1 and 4 days.
12
Figure 3B: Commercial Paper Spreads (bps)
Overnight AA Asset-backed Commercial Paper Spread
30-Day AA Asset-backed Commercial Paper Spread
500
500
450
450
400
400
350
350
300
300
250
250
200
200
150
150
100
100
50
50
0
-50
7/1/07
8/20/07
10/9/07
11/28/07
1/17/08
3/7/08
4/26/08
6/15/08
8/4/08
9/23/08
11/12/08
0
7/1/07
8/20/07
Overnight AA Financial Commercial Paper Spread
10/9/07
11/28/07
1/17/08
3/7/08
4/26/08
6/15/08
8/4/08
9/23/08
11/12/08
9/23/08
11/12/08
9/23/08
11/12/08
9/23/08
11/12/08
30-Day AA Financial Commercial Paper Spread
100
250
80
200
60
150
40
20
100
0
50
-20
0
-40
-60
7/1/07
8/20/07
10/9/07
11/28/07
1/17/08
3/7/08
4/26/08
6/15/08
8/4/08
9/23/08
11/12/08
-50
7/1/07
8/20/07
Overnight AA Nonfinancial Commercial Paper Spread
10/9/07
11/28/07
1/17/08
3/7/08
4/26/08
6/15/08
8/4/08
30-Day AA Nonfinancial Commercial Paper Spread
200
100
150
50
100
0
50
0
-50
-50
-100
-100
-150
-150
-200
-200
-250
7/1/07
8/20/07
10/9/07
11/28/07
1/17/08
3/7/08
4/26/08
6/15/08
8/4/08
9/23/08
11/12/08
-250
7/1/07
8/20/07
Overnight A2/P2 Nonfinancial Commercial Paper Spread
11/28/07
1/17/08
3/7/08
4/26/08
6/15/08
8/4/08
30-Day A2/P2 Nonfinancial Commercial Paper Spread
500
500
400
400
300
300
200
200
100
100
0
0
-100
-100
-200
-300
7/1/07
10/9/07
-200
8/20/07
10/9/07
11/28/07
1/17/08
3/7/08
4/26/08
6/15/08
8/4/08
9/23/08
11/12/08
-300
7/1/07
8/20/07
10/9/07
11/28/07
1/17/08
3/7/08
4/26/08
6/15/08
8/4/08
Source: Bloomberg; Federal Reserve Board, http://www.federalreserve.gov/DataDownload/Choose.aspx?rel=CP
Notes: The “overnight” spreads are 1-4 day paper spreads over the effective federal funds rate, while the 30 day
spreads are over the 1-month OIS.
13
Figure 3C: Commercial Paper Gross Issuance, % of “overnight” paper (daily, 1-week moving averages)
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
5/1/2007
8/9/2007
11/17/2007
2/25/2008
Overnight AA ABCP as % of total ABCP issuance
Overnight A2/P2 Nonfinancial CP as % of total A2/P2 Nonfinancial issuance
6/4/2008
9/12/2008
Overnight AA Financial CP as % of total AA Financial issuance
Overnight AA Nonfinancial CP as % of total AA Nonfinancial issuance
Source: Federal Reserve Board, http://www.federalreserve.gov/DataDownload/Choose.aspx?rel=CP
14