UNIVERSITY OF GHENT
FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION
Academic year 2010 – 2011
On the effectiveness of the monetary policy during the financial crisis of 2007
Federal Reserve vs. European Central Bank
Master thesis presented to obtain the degree of
Master in Applied Economics: Business Engineering
Alexander Naessens & Sabien Windels
under the leadership of
Prof. dr. Gert Peersman Selien De Schryder
UNIVERSITY OF GHENT
FACULTY OF ECONOMICS AND BUSINESS ADMINISTRATION
Academic year 2010 – 2011
On the effectiveness of the monetary policy during the financial crisis of 2007
Federal Reserve vs. European Central Bank
Master thesis presented to obtain the degree of
Master in Applied Economics: Business Engineering
Alexander Naessens & Sabien Windels
under the leadership of
Prof. dr. Gert Peersman Selien De Schryder
Ondergetekenden verklaren dat de inhoud van deze masterproef mag geraadpleegd en/of gereproduceerd worden, mits bronvermelding.
We hereby declare that the content of this thesis may be consulted, and/or reproduced on condition that the source is quoted.
Alexander Naessens Sabien Windels
“As long as the music is playing, you’ve got to get up and dance. We’re still dancing”
Charles Prince, former CEO of Citigroup Financial Times, July 2007
ACKNOWLEDGEMENTS
First and foremost, we would like to thank our promoter, prof. dr. Gert Peersman and our co-promoter, Selien De Schryder for their guidance on this master thesis over these past two years. We are very grateful to Jef Boeckx, Economist at the National Bank of Belgium, Luc Aucremanne, Head of Monetary Policy Research Department at the National Bank of Belgium, Alfons Verplaetse, former Governor of the National Bank of Belgium and Burcu Duygan-Bump, Senior Financial Economist at the Federal reserve Bank of Boston for their time, advice and for sharing their knowledge in their domain of expertise. Furthermore, we would like to render thanks to Nasser Hanafy, Senior Communications Assistant at the European Central Bank, for giving us the opportunity to attend the workshop on the “Macroeconomic impact of non-standard monetary policy measures” in Frankfurt Am Main. Last, special thanks go to our parents for their moral and financial support, not only during the last two years but during our entire academic career.
May 2011, Alexander Naessens & Sabien Windels
I
TABLE OF CONTENTS
Acknowledgements ...... I Table of contents ...... II Abbreviations ...... IV List of figures ...... VI List of tables ...... VII 0 Introduction ...... - 1 - PART I A comparison between the Federal Reserve and the European Central Bank ...... - 3 -
1 A short refreshment ...... - 5 - 1.1 Macroeconomic causes ...... - 5 - 1.2 Microeconomic causes ...... - 6 - 1.3 Concurrence of circumstances ...... - 7 - 2 A high-level comparison ...... - 9 - 2.1 Differences in economical and financial structure ...... - 9 - 2.1.1 Economic structure ...... - 9 - 2.1.2 Financial structure ...... - 10 - 2.2 Comparison between the Federal Reserve and the European Central Bank ...... - 15 - 2.2.1 A typology ...... - 15 - 2.2.2 Beyond the typology...... - 20 - 2.3 Conclusion ...... - 26 - 3 The toolbox of the Federal Reserve and the European Central Bank ...... - 28 - 3.1 Theoretical introduction ...... - 29 - 3.2 The toolbox of the Federal Reserve ...... - 30 - 3.2.1 The pre-Lehman period ...... - 30 - 3.2.2 The post-Lehman period ...... - 34 - 3.3 The toolbox of the European Central Bank ...... - 45 - 3.3.1 The pre-Lehman period ...... - 46 - 3.3.2 The post-Lehman period ...... - 48 - 3.4 Conclusion ...... - 52 - PART II On the effectiveness ...... - 53 -
4 The effectiveness of the non-standard measures: the Federal Reserve ...... - 57 - 4.1 Interbank market ...... - 57 -
II
4.1.1 Market response ...... - 57 - 4.1.2 Data ...... - 59 - 4.1.3 Econometrical analysis ...... - 62 - 4.2 The asset-backed commercial paper market ...... - 73 - 4.2.1 Market response ...... - 73 - 4.2.2 Data ...... - 76 - 4.2.3 Econometrical analysis ...... - 77 - 4.3 The commercial paper market ...... - 82 - 4.3.1 Market response ...... - 82 - 4.3.2 Data ...... - 83 - 4.3.3 Econometrical analysis ...... - 84 - 4.4 The asset-backed securities market ...... - 88 - 4.5 Other key markets ...... - 92 - 4.5.1 Market response ...... - 93 - 4.5.2 Data ...... - 95 - 4.5.3 Econometrical analysis ...... - 96 - 5 The effectiveness of the non-standard measures: the European Central Bank- 102 - 5.1 Interbank market ...... - 102 - 5.1.1 Market response ...... - 102 - 5.1.2 Data ...... - 105 - 5.1.3 Econometrical analysis ...... - 107 - 5.2 Covered bond market ...... - 113 - 6 Joint effort between Federal Reserve & European Central Bank: Swap Lines - 117 - 6.1 FX swap market ...... - 117 - 6.1.1 Market response ...... - 117 - 6.1.2 Data ...... - 119 - 6.1.3 Econometrical analysis ...... - 121 - 7 Conclusion ...... - 126 - Exhibits ...... VII
III
ABBREVIATIONS
ABCP Asset-Backed Commercial Paper ABS Asset-Backed Securities AMLF Asset -Backed Commercial Paper Money Market Mutual Fund Liqu idity Facility BP Basis points CBPP Covered Bond Purchase Programme CDO Collateralized Debt Obligation CDS Credit Default Swap CIP Covered Interest Parity CP Commercial Paper CPFF Commercial Paper Funding Facility EA Euro area ECB European Centr al Bank EONIA Euro OverNight Index Average Fed Federal Reserve FOMC Federal Open Market Committee FRFA Fixed-Rate Full-Allotment FX Foreign Exchange GSE Government -Sponsored Enterprises LSAP Large -Scale Asset Purchases LTRO Longer-Term Refinancing Operation MBS Mortgage -Backed Securities MMIFF Money Market Investor Funding Facility MMMF Money Market Mutual Fund MRO Main Refinancing Operation NAV Net Asset Value PDCF Primary Dealer Credit Facility RMBS Residential Mortgage-Backed Securities
IV
SIV Special Investment Vehicle SLTRO Special Longer -Term Refinancing Operation SPV Special Purpose Vehicle TAF Term Auction Facility TALF Term Asset -backed securities Loan Facility TSLF Term Securities Lending Facility
V
LIST OF FIGURES
Figure 1: Assets on the balance sheets of the Euro system and the Federal Reserve...... - 11 - Figure 2: External financing of the non-financial sector in the euro area and the United States ...... - 12 - Figure 3: Spread between Eonia and MRO rate ...... - 24 - Figure 4: Libor-OIS spread and Federal Funds Target rate ...... - 31 - Figure 5: Spread between ABCP and Federal Funds target rate (overnight & 3-month) ..- 37 - Figure 6: Frequency of fine-tuning operations at the ECB ...... - 47 - Figure 7: Amounts of MRO and LTRO outstanding ...... - 48 - Figure 8: Libor-OIS spread and amount of TAF loans outstanding...... - 58 - Figure 9: Amount of AMLF loans outstanding ...... - 73 - Figure 10 Spreads between asset-backed & financial commercial paper (overnight, 1-month and 3-month maturities) ...... - 75 - Figure 11: 3-month commercial paper rates ...... - 82 - Figure 12: Commercial Paper Funding Facility loans outstanding ...... - 82 - Figure 13: Asset-Backed Securities yield ...... - 89 - Figure 14: Spread on accepted and rejected Commercial Mortgage-Backed Securities ....- 91 - Figure 15: Market yields on 2-year, 10-year and 20-year Treasury securities ...... - 93 - Figure 16: BAA Corporate Bond Yields ...... - 94 - Figure 17: Euribor-OIS spread (3-month maturity) ...... - 102 - Figure 18: Euribor-MRO spread (3-month maturity) ...... - 104 - Figure 19: Covered bond yield spread with sovereign yields (France, Germany, Spain) - 113 - Figure 20: Covered bond spread (euro area) ...... - 114 - Figure 21: Covered Interest Parity Deviation ...... - 118 -
VI
LIST OF TABLES
Table 1: Announcement effects of the TAF, PDCF and TSLF on the Libor-OIS spread ...... - 66 - Table 2: Extended regressions of TAF, PDCF and TSLF on the Libor-OIS spread ...... - 71 - Table 3: Asset-backed commercial paper market ...... - 81 - Table 4 Commercial paper market ...... - 87 - Table 5: Treasury market ...... - 101 - Table 6: European interbank market...... - 112 - Table 7: FX swap market ...... - 125 -
VII
0 INTRODUCTION
In August 2007, financial markets throughout the world began to quiver as a consequence of the burst of the United States housing bubble. The turmoil persevered until September 2008, when the situation escalated owing to the collapse of Lehman Brothers. This seism and its aftershocks tormented financial markets for a considerable period of time and were also highly perceptible in Europe. These extraordinary times put central banks to the test healing the deep wounds caused by this shockwave. Many central banks stepped into the breach by stepping out of their traditional operational frameworks and by undertaking unprecedented measures in combating the financial crisis. Albeit central banks did not provide a panacea, it seems that, in the meantime, most strains have ebbed away. Given the unconventionality and the scale of the monetary policy response, it is interesting to probe to which extent these great efforts have been effective. Moreover, given the numerous differences that exist between the US and Europe, a broader context has to be established in order to make a fruitful comparison between the monetary responses of the Federal Reserve and the European Central Bank. In this work, we scrutinize the different non- standard measures both central banks have undertook in response to the financial crisis and further, we will examine their effectiveness in the financial markets they were designed to address. This work builds on the existing literature, but takes a more holistic view. By econometrically examining the effectiveness of each measure in a same study, we can draw a more general conclusion on the effectiveness of the unconventional response to the crisis as a whole. Moreover, by taking a look at both the Federal Reserve and the European Central Bank, we can make a thorough analysis of the differences and the similarities in approach. However, we limit our efforts to the impact of the monetary policy response on financial markets and leave the effect on the real economy out of consideration. In a first part, we will make a sketch of the situation at the outset of the financial crisis and we will shortly elaborate on the differences in economic and financial structure between the US and Europe. Moreover, we will compare the operational framework of both central banks and the toolbox they developed to relieve the emerged strains in financial markets. In a second part, we will look at how the different financial markets have responded to the
- 1 - crisis and at the impact of the unprecedented measures initiated in both currency areas. Furthermore, for each one of these measures, an econometrical analysis will be performed. Overall, we can conclude that the Federal Reserve had to go to much greater lengths in the expansion of its operational framework compared to the European Central Bank. Although we will never know how the financial landscape would have looked like without central bank intervention, our results show that both central banks, albeit the differences in approach, have played a major role in the recovery of financial markets after the 2007-2008 seism.
- 2 -
PART I A comparison between the Federal Reserve and the European Central Bank
- 3 -
In this first part, we will create the setting for part 2 by making an analysis of the various differences that exist between the United States and Europe, between the Federal Reserve (Fed) and the European Central Bank (ECB). This outline is necessary to understand the rationale behind the monetary policy decisions of both central banks during the period of financial turmoil. Such an understanding will contribute to a balanced interpretation of the results of the econometrical analysis that will be performed in part 2. Part 2 will conclude with a broader assessment of the effectiveness of the monetary policy of the Federal Reserve versus the European Central Bank within the context drafted in part 1. In a first chapter, we will shortly refresh some relevant events and trends that have played an important role in the period leading up to the financial crisis. In chapter 2, we will make a high-level comparison of both sides of the Atlantic. They are characterized by a different economical and financial structure which has influenced monetary policy in the past and steered the monetary response during the financial crunch. These differences are briefly described in section 2. 1. Next, in section 2. 2, we will introduce a framework based on Lenza, Pill et al. (2010), that we will use to categorize the various measures. In section 2. 3, we will dilate upon some relevant similarities and differences concerning the monetary policy reaction of the Fed and the ECB. We will end part 1 with chapter 3, which offers a description of the specific measures and the rationale behind their initiation.
- 4 -
1 A SHORT REFRESHMENT
In this first chapter, we provide a short refreshment of what has lead to the elevated strains in many financial markets which arose in August 2007. Given the long run-up that preceded the financial crisis and the widely spread consequences that manifested throughout the whole economy, it is important to focus on what is relevant for this work. We will especially emphasize the relevant events and trends in financial markets, as these compose the playground for central banks. The contamination of the problems in financial markets to the real economy will be left out of consideration. In section 1.1, we will elaborate on the macroeconomic causes that were at the basis of low interest which have played an important role in the run-up to the financial crisis. In section 1.2, we will discuss some microeconomic causes that have led to an underpricing of risk. Last, in section 1.3, we explain how the conjunction of low interest rates and an underpricing of risk have led to a uninterrupted growing asset bubble, of which the burst has triggered the quivering of financial markets all over the world.
1.1 Macroeconomic causes
We will discuss three macroeconomic causes that contributed to the low interest rates that characterized the pre-crisis economy. A first factor was the Great Moderation that started in the mid-80’s. The reduction in volatility of output and inflation that typifies this period resulted in a greater predictability of economic and financial performance which caused firms to be less concerned about liquidity and lead to a reduction in required risk premia (Marzo, Zhoushi et al. 2011). A second factor is the accommodating course of the monetary policy succeeding the internet bubble and the terroristic attacks of September 11, 2001. Faced with threat of an upcoming recession, the Fed, under Alan Greenspan, lowered its target rate gradually to 1 percent. A last factor contributing to the low interest rates was the so-called saving-glut hypothesis (Bernanke 2007a). The rapid growth of new emerging markets, as for example China, and the accompanied increase in wealth, combined with their financial conservatism lead to a higher demand of risk-free financial assets, especially US Treasuries (Buiter 2008). As a consequence, risk-free interest rates declined.
- 5 -
1.2 Microeconomic causes
Next to these three macroeconomic causes that have led to low interest rates, there are three microeconomic factors that resulted in an under-pricing of risk. A first trend worth mentioning is securitization, which started to pick up in the US during the nineties. Loans, originated by banks, were more and more destined to the balance sheets of institutions, like asset-backed securities (ABS) issuers and government-sponsored enterprise (GSE) ABS issuers. These institutions grouped loans with similar characteristics (mortgage loans, credit card debt, student loans, …) and issued assets that were backed by these pools of loans. This portfolio diversification resulted in a reduced risk for the asset-backed securities investors and borrowers were able to access credit they otherwise would not have had. Moreover, banks were able to increase their return on equity in times of low interest rates (Boeckx 2011). This new originate-to-distribute model looked like a win-win game for all parties. This securitization trend is discussed in more detail in paragraph 2.1.2. A second microeconomic factor was weaknesses in regulation and supervision. Although loans incorporated in mortgage pools of GSEs were subject to certain requirements and the amounts of these loans were limited to a maximum value, this was not the case for the loans in the pools of alternative ABS issuers. The weak restrictions and the low monitoring of these loans has led to a deterioration of mortgage quality. Between 2001 and 2006, low quality mortgages 1 rose from 9. 7% to 33.5%, which proves the remarkable growth in the subprime mortgage market (Greenlaw, Hatzius et al. 2008). Moreover, less and less mortgage-backed securities were issued by GSE’s, with an absolute low of 10 per cent in 2004, while the alternative issuers of asset-backed securities had raised their share to more than 40 per cent (Cecchetti 2008). A last microeconomic factor was the weakness in risk management. Although theoretically, the pooling of loans in securitized assets should have reduced the overall risk of such ABS, the defaults of the underlying loans have often appeared to be positively correlated. A large contribution of this can be found in the new originate-to-distribute model, which had reduced the incentives for banks to conduct proper risk management (Purnanandam 2009). All these microeconomic factors have added up to the under-pricing of risk in the pre-crisis period.
1 By low quality mortgages, we mean Alt-A mortgages and subprime mortgages. - 6 -
1.3 Concurrence of circumstances
The above-described set of macro- and microeconomic causes has lead to a build-up of excessive leverage. On the demand side, attractive low interest rates and low lending standards tempted many US households, that otherwise would have been unable to borrow, to buy their own house. On the supply side, the originate-to-distribute model allowed banks to transfer credit risk to third parties. “By de-linking the origination of loans from funding, banks can capitalize on their comparative advantage in loan origination without requiring a large capital base” (Purnanandam 2009, p18). This excessive leverage lead to a soaring demand for houses which put an upward pressure on their prices. In 2005 and 2006 it became apparent that the ratio between home prices and annual rents, which normally amounts between 9 and 11, reached an extraordinary level of 14,5 indicating the existence of a housing bubble (Cecchetti 2008). When interest rates began to increase, many households with variable rate mortgage loans were took by surprise 2. The die was casted and the bubble began to burst. It became clear that the quality of loans in the pools wasn’t what it turned out to be. As more and more loans could not be reimbursed, the houses that served as collateral were liquidated and asset prices began to fall from their wuthering heights. While in the pre-crisis period the low risk-high return profile of ABS had attracted many investors worldwide, the complexity and insufficient transparency of the composition of the underlying pools gained the upper hand. This, together with a souring market for Collateralized Debt Obligations (CDO) and ABS, made a mark-to-market valuation to give way to a mark-to-model approach (Brunnermeier 2009). The problems in the pools of assets prompted credit-rating agencies to downgrade securities backed by these pools. As a result, many banks suffered credit losses or had to do write-downs. This resulted in great uncertainty among banks concerning the value of assets on their balance sheet which made them unsure about their lending capacity. Moreover, uncertainties about the balance sheets of counterparties raised concerns about their default risk and the fear that many banks might fail arose. This resulted in banks hoarding liquidity and being only willing to lend to one another by charging large premia. By September 2007, the Libor-OIS
2 One should keep in mind that, as stated in section 1.2, MBS are only one aspect of the securitization trend. Other loans were also recombined in pools that backed ABS, named ‘collateralized debt obligations’. - 7 - spread 3 rose to 100 basis points (bp) which is remarkable knowing that in normal times this spread fluctuates around 10 bp. These increases in risk spreads diffused over many markets, among which the commercial paper and the private asset-backed securities market. The elevated strains in many financial markets, and the threat such strains impose on the flow of credit to households and non-financial institutions, obliged central banks to step in and to provide the support they needed .
3 This Libor-OIS spread can be seen as a barometer of fears of bank insolvency - 8 -
2 A HIGH -LEVEL COMPARISON
In the previous chapter, we laid out several macro- and microeconomic causes that lead to the financial strains which could be observed since August 2007. The resulting increase in interbank money market spreads brought interbank transactions to a halt. The large demand for liquidity that many financial institutions faced, incited central banks to intervene and introduce a number of non-traditional measures. In section 2.1 , we will draft the context in which these innovative measures operated by taking a look at the differences in economic and financial structure between the euro area and the US. This is necessary in order to discuss the differences in monetary policy response of the Federal Reserve and the European Central Bank from the right perspective. This is the focus of section 2.2, where we will first go into a framework to characterize the newly introduced measures and in which we will make an elaborate assessment on the common grounds and disparities between the monetary policy response in order to make the draft complete. After this chapter, we possess all elements to present the specific measures that both central banks undertook in chapter 3.
2.1 Differences in economical and financial structure
To comprehend the rationale behind the different monetary policies and to make a useful comparison between Federal Reserve and European Central Bank, it is of great interest to have a clear understanding about the economic and financial structure in the area they both operate as different structures call for different monetary policy. In paragraph 2.1.1, we briefly discuss some differences in economic structure. In paragraph 2.1.2, we explain the channels through which both economies are mainly financed and outline why the difference in financial structure caused a different approach in combating the financial crisis.
2.1.1 Economic structure
First, the US housing market, which has as stated in chapter 1 (see above, p.7) played a major role in the arousal of the financial crisis, has undergone some evolutions that were not that manifested in Europe. Because of the attractive loan conditions, many tenants
- 9 - obtained a mortgage that allowed them to become home owners, which before had been inconceivable for them. While this evolution mainly occurred within the US borders, the consequences of the bursting bubble also hit Europe hard. A second structural difference is the share of small- and medium sized enterprises (Trichet 2009a). While in Europe the bulk of companies are of relatively small size, the United States are characterized by large firms that can obtain financing in credit markets directly. The importance of smaller companies in Europe creates a great dependence on the availability of credit offered by banks. This will be further discussed in the next paragraph. A last and important disparity between Europe and the United States is the flexibility of both economies. Macroeconomic variables, like prices and wages, typically tend to adapt decelerated in Europe relative to the United States. As Trichet (2009) notes, in normal times, this sluggishness is unwished- for as it slows down the adjustment of the economy. However, in times of crisis, this drawback is turned in to a benefit as it offers confidence and stability for private sector expectations. In Europe, such stability is offered by the mid-term orientation of the monetary policy. This difference in economic structure has impacted the response of both central banks during the financial crisis. The automatic stabilizers in Europe justify the lack of an overly activist policy, which could have destabilized expectations, and therefore could have acted counterproductive (Trichet 2009a).
2.1.2 Financial structure
Next to the differences in economic structure described in the previous paragraph, we will now take a look at structural differences between Europe and the United States in the financing of the economy. In the euro area (EA), the importance of the banking sector in supplying loans to households and non-financial organisations resulted in a design of non- standard measures that was concentrated mainly on the banking sector. In contrast, the economy in the United States relies on banking as a source of funding to a smaller extent. This caused the Federal Reserve to address several measures to specific non-banking market segments that had dried up during the financial turmoil. When we look at Figure 1, we indeed notice that the support for specific financial markets is much more elaborate for the Federal Reserve than for the European Central Bank. Whereas the Fed provided support to the ABS and commercial paper (CP) market, and to government-sponsored
- 10 - enterprises (GSE) and government securities, the ECB only directed its monetary policy to the covered bond market next to the interbank market.
Figure 1: Assets on the balance sheets of the Euro system and the Federal Reserve Notes: Percentages of average GDP during the period 2007-2009 (1) Including emergency liquidity assistance in euro. (2) Including emergency liquidity assistance in foreign currencies, the Term Auction Facility in USA dollar and swap agreements concluded with other central banks. (3) The Term Secu rities Lending Facility, repo’s with primary dealers, the Term Auction Facility, the discount window and the Primary Dealer Credit Facility. (4) Support provided for Bear Stearns and AIG. (5) The Asset-Backed Commercial Paper Money Market Mutual Fund Liquidity Facility, the Term Asset-Backed Securities Loan Facility and the Commercial Paper Funding Facility. (6) For the purpose of credit easing. Source: Annual Report 2009 of National Bank of Belgium
To clarify why the Fed intervened in a broader set of financial markets compared to the ECB, we will first take a comprehensive look at the external financing of both currency areas.
- 11 -
Next, we will talk about the entrance of financial innovations and their influence on financial markets. Securitisation, as a reaction to the tighter capital requirements and to other regulatory issues in the financial industry, has indeed changed the way financial markets were organized and thus has influenced how the Federal Reserve had to respond to the elevated strains in financial markets.
When taking a look at we can point out the first main difference in financing structure between EA and the US. In the euro area, the bulk of external financing for both households and non-financial organizations is provided via banks 4, accounting for 75 and 72 per cent respectively. By contrast, in the United States, only 30 and 21 per cent of financing is provided by credit institutions.
Figure 2: External financing of the non-financial sector in the euro area and the United States Notes: Average annual flows between 2004 and 2008, percentages of the total (1) For the United States, these are loans by commercial banks, credit unions and savings institutions Source: Annual Report 2009 of the National Bank of Belgium
4 In this context, this refers to the origination and holding of bank loans. - 12 -
Where financing in Europe is mainly bank-based, a market-based approach is far more adopted in the United States . Companies obtain funds in credit markets directly to a larger extent than in Europe. Moreover, as discussed in paragraph 2.1.1, the US is characterized by a larger share of big companies that can obtain funding in stock markets more easily (Vander Vennet 2008). This channel of funding is not displayed in Figure 2.. To be clear, in Europe as well as in the United States, banks are the main originator of financing for households. However, loans, originated by banks in the USA, are more often destined to the balance sheets of institutions that play on the secondary market of loans to households, and which use these pools of assets as collateral in the ABS they issue. These non-bank institutions, like ABS issuers and GSE ABS issuers, were created with the objective of enhancing the availability and reducing the cost of credit to certain sectors in the economy, for example the mortgage sector (Crippen 2001). This group of institutions has grown significantly across the Atlantic since 2004, in response to the tighter capital requirements, greater balance sheet controls and a desire for higher leverage ratios of banks (Verplaetse 2011). When we take a look at the grey and light blue area in Figure 2, we see that about 40 % of funds for households in the United States were provided by private ABS issuers and Government Sponsored Enterprise ABS issuers, such as Fannie Mae and Freddie Mac. Because of the rise of these unconventional institutions, an ‘originate-to-hold’ model had to make room for an ‘originate-to-distribute’ model (Berndt and Gupta 2009).
This originate-to-distribute model induced the development of a shadow banking system in the United States. The above-described securitization trend had led to the growth of institutions that each wanted a piece of the pie, among which for example asset-backed commercial paper (ABCP) conduits, structured investment vehicles, money market mutual funds and many more (Pozsar, Adrian et al. 2010). The created ABS and CDOs were in turn repackaged by these institutions, with the creation complex and opaque instruments as a result. Although these non-bank institutions perform credit intermediation, they are not subjected to the severe regulations that banks are subordinated to. They escape reserve requirements and government inspections, which meant that shadow banks could be more highly leveraged than regular banks (Adrian 2010). However, they did not have access to the support of a central bank when the situation started to deteriorate in August 2007. - 13 -
Therefore, during periods of market illiquidity, they could go bankrupt if they were unable to refinance their short-term liabilities, with the collapse of Lehman Brothers in September 2008 as the best-known example. Exactly this shadow banking system by which the majority of non-financial institutions in the US were financed, is represented by the yellow area in Figure 2..
Securitization is far more common in the US than in Europe. Nevertheless, the fact that the private sector in Europe wasn’t financed by ABS issuers doesn’t mean that little use was made of securitization operations. The covered bond market has been an important source of financing for banks in Europe (Packer, Stever et al. 2007). The covered bond market will be further discussed in section 3.3.2. Although the absence of a shadow banking system in the euro area, many European banks held ABS on their balance sheets and were therefore indirectly connected to the US shadow banking system 5. As a result, also Europe was hit by the burst of the US housing bubble.
To conclude, the structure of the financial system and the existence of the shadow banking system explain why the Federal Reserve had to set up a much broader range of facilities compared to the European Central Bank. As was shown in Figure 2, bank funding only has a small stake in the financing of the US economy. The importance of the many institutions operating in the shadow banking system, and their incapability to directly access liquidity of the central banks has driven the Federal Reserve to intervene in financial markets other than the interbank market, as for example the ABS market. This is in contrast to the ECB that mainly focused on the interbank market in its monetary policy response to the financial crisis. The specific measures both central banks have initiated will be discussed in detail in chapter 3. The above-discussed elements will be of great value for the comparison of the monetary policy stance of central banks during the financial crisis. The differences in financial structure should be considered throughout the rest of this work to discuss the response of the Fed and the ECB from a contextual point of view.
5 For further literature about the shadow banking system, we refer to Pozsar, Adrian et al. (2010)
- 14 -
2.2 Comparison between the Federal Reserve and the European Central Bank
To respond effectively to the emerging strains that appeared in financial markets after August 2007, central banks have introduced a number of non-traditional measures. In paragraph 2.2.1, we will first define a typology to characterize these non-standard measures initiated by both central banks, which will act as a valuable instrument to gain further insight in the approaches of the central banks. This framework is based on Lenza, Pill et al. (2010). Moreover, next to the structural differences discussed in the previous section (see above, p. 10), we will provide an overview of operational similarities and differences in monetary policy response of the Fed and the ECB in paragraph 2.2.2. All non- standard measures that are mentioned in this section will be discussed in detail in chapter 3.
2.2.1 A typology
In normal times, central banks respond to a decelerating economy by lowering their key interest rates. This is how monetary policy is conventionally conducted and therefore these actions are defined as the standard monetary policy measures. In this study, however, it is more interesting to look at what happens in exceptional times. During the financial crisis, elevated strains in financial markets hindered the credit creation process to households and non-financial institutions. Because of the unwished-for consequences this would have on the real economy, the Fed and the ECB decided to intervene. Taking a look at how central banks have changed course after August 2007 reveals that the standard measures were not sufficient to relieve the stress in financial markets. With key interest rates heading towards the lower bound, the Fed as well as the ECB introduced a supplementary set of non- standard measures to further ease financing conditions as the scope for conventional easing began to run out. As these non-standard measures fall outside the traditional operational framework of central banks, they are hard to characterize. Lenza, Pill et al. (2010) have developed a typology that distinguishes non-standard measures on three dimensions. We will base the following discussion on these dimensions. A first dimension is the impact of the non-standard measures on the balance sheet of central banks. The choice of counterparties is a second dimension. A third dimension is whether the non-standard
- 15 - measures were intended to complement or to substitute for interest rate cuts. As we especially aim at discussing some relevant differences between the measures undertook by the Federal Reserve and the European Central Bank based on this framework, we will only go into more detail on the first two dimensions as we consider those most relevant for this purpose. The third dimension is, although valuable in characterizing the non-standard measures, in our opinion less suitable in this discussion 6.
Qualitative and quantitative easing A first dimension is the impact that non-standard measures have on the balance sheet of central banks. Non-standard measures can have an impact on the composition of the balance sheet, the size, or both. The first is defined as qualitative easing, the second as quantitative easing and the latter is a combination of both.
Pure qualitative easing implies that the overall size of the balance sheet remains equal and only the composition is altered by superseding conventional assets by unconventional assets on the asset side of the balance sheet. In contrast, when easing quantitatively, the overall size of the balance sheet grows by increasing the shares of each asset category proportionally (this is also referred to as credit easing or credit policy). This increase on the asset side is accompanied by an increase of the monetary base, which is reflected in an increase of central bank reserves 7 (Lenza, Pill et al. 2010).
Before the bankruptcy of Lehman Brothers in September 2008, both central banks’ balance sheet sizes remained untouched 8. Liquidity provision to banks in need was offset by draining liquidity from banks with an excess of liquidity during each maintenance period (Klyuev, de Imus et al. 2009) and thereby central banks performed transactions that otherwise happen between banks in the money market directly. In Figure 1 however, a
6 For more details on this framework, we refer to Lenza, Pill et al. (2010) 7 Given that banknotes are perfectly elastic (Lenza, Pill et al. 2010) 8 The balance sheet of the ECB shows an increasing trend before September 2008. This increase is due to the annexation of several Eastern European countries to the European Union in 2004. The heightened use of Euro billets in these countries, together with the interest rate targeting of the ECB, explains this trend. As the growth of the balance size was already initiated before the beginning of the financial crisis, and because it remained stable thereafter, we do not consider this as quantitative easing.
- 16 - shift in the composition of assets on the balance sheets of both the Fed and the ECB can be observed. Therefore, the course of central banks prior September 2008 can be categorized as qualitative easing.
By looking at Figure 1 in more detail, some differences in how the composition of the balance sheets of the Fed and the ECB changed can be noticed. In the period before August 2007, it is remarkable that the liquidity provision to banks related to monetary policy occupies a much smaller share of the assets on the balance sheet of the Fed compared to the ECB 9. In normal times, the Fed adjusts the amount of liquidity in the economy by selling and purchasing government securities, which thus occupied the largest share of the balance sheet of the Fed in the pre-crisis period. A smaller amount of liquidity 10 is provided via loans to its primary dealers. In the pre-crisis period, around 15 primary dealers had the possibility to directly interact with the Federal reserve (Lenza, Pill et al. 2010). In normal times, a small liquidity shortage and the small amount of liquidity provided to the limited set of counterparties, suffices to influence short-term interest rates. However, in times of elevated strains in the money market, when there is distrust among the primary dealers, the liquidity provided to those counterparties is hardly distributed towards the rest of the economy. In contrast, the ECB provided a larger amount of liquidity to 2200 counterparties, and therefore faced these problems to a smaller extent (Boeckx 2011). After August 2007, the Federal Reserve reinforced its support to the banking system and initiated non- standard measures that provided anonymous liquidity to a broader set of counterparties (cf. the Term Auction Facility (TAF), which will be discussed in detail in paragraph 3.2.1). Also, the Federal Reserve initiated a standing credit facility for its primary dealers, the Primary Dealer Credit Facility (PDCF). This represents an extension of the ‘standing facility counterparties’, as traditionally only depository institutions had access to such a similar facility, the primary credit facility or discount window. Moreover, we can observe in Figure 1 that, in response to the elevated strains in the money market, the Fed increased the amount of liquidity provided to financial institutions and sterilized these liquidity injections by selling government securities. In contrast, at the ECB, the amount of liquidity provided
9 The ECBs weekly MROs amount around €300 billion versus around USA$30 billion in the USA 10 Represented by the blue area in Figure 1. - 17 - to banks remained rather stable and the composition of the assets on the balance sheet was merely changed by the supersedure of main refinancing operations by longer-term refinancing operations.
As can be seen in Figure 1, the collapse of Lehman Brothers has been a turning point. The heightened stress and panic in the money market forced central banks to increase the size of their balance sheets. Therefore, from September 2008 on, we can categorize the monetary policy course of both central banks as a combination of qualitative and quantitative easing, as not only the size of their balance sheet increased, but also new assets were added to the portfolio and changes in the composition of the asset side continued. Whereas at the ECB mainly an increase in the longer-term provision of liquidity bears the responsibility for the increase of the balance sheet, the Federal Reserve’s balance sheet expansion is, next to the increase in lending to financial institutions and claims in foreign currencies, attributed to more unconventional assets like asset-backed securities, commercial paper and debt securities issued or covered by GSEs. This is the result of the intervention of the Federal Reserve in other markets than the interbank market, for example the ABS market and the commercial paper market. The rationale behind these interventions was already described in 2.1.2 and will be more thoroughly discussed in section 3.2.2.
Choice of counterparties A second dimension upon which non-standard measures can be categorized is the choice of their counterparties. When evaluating a non-standard measure, the choice of counterparties gives a signal about whether the central bank wants to bypass a certain market, or rather aims at reactivating the activity in it. In paragraph 2.1.2, we have described how external financing in Europe and America significantly differs. These differences have to a large extent determined which counterparties were targeted in the non-standard measures introduced by the central banks.
In the pre-crisis period, banks were the sole counterparties of central banks. Before the collapse of Lehman Brothers in September 2008, both central banks kept their focus on the
- 18 - banking system. As stated in the previous paragraph, with the introduction of the TAF, the Fed provided depository institutions with anonymous access to liquidity. Although these institutions were already eligible to borrow at the discount window, the stigma associated with this facility (cf. paragraph 3.2.1) incited the Federal Reserve to initiate the TAF. Similarly, primary dealers were already counterparties in the refinancing operations of the Federal Reserve, but did not have access to a permanent liquidity facility yet. Therefore, this ‘expansion’ of counterparties signalled the focus on the banking system in the period before the failure of Lehman Brothers.
It was in the period that succeeding this failure, the difference in financial structure between the US and Europe played a part in the choice of counterparties. The ECB continued to operate largely via the banking sector, whilst the Fed decided to deal with a much broader set of counterparties, including non-banks. The Fed therefore supported the functioning of private credit markets and bypassed the banking system in its attempt to revive the credit creation process to households and non-financial institutions. By also providing liquidity to non-banks, they reduced the risk that the injected liquidity would be hoarded in the banking system and would not reach the rest of the economy. It is this decision to target a broader set of counterparties that explains why the Fed had to initiate a whole set of new facilities that focused on these counterparties, in contrast to the ECB of which the non-standard measures mainly included modifications to its existing framework. The only new facility the ECB initiated during the financial crisis was the covered bond purchase programme (CBPP), which performed outright purchases of covered bonds starting from May 2009. However, as will be explained in greater detail in paragraph 3.2.2, also this facility was intended to improve bank funding conditions and to promote the credit creation process through the banking system, instead of bypassing it as some of the newly introduced measures of the Fed.
We can conclude that, given the importance of the banking sector in Europe, the ECB had no other choice than focusing on the banking sector as counterparty in its operations and given the importance of the shadow banking system in the US, the Fed needed to go to greater lengths and had to create a whole new set of facilities. In paragraph 3.2.2, we will describe - 19 - the rationale behind the initiation of each of the new facilities introduced by the Federal Reserve and we will explain the choice of the particular counterparties of each facility.
2.2.2 Beyond the typology
Although the responses of both central banks seem very different at first sight, we can identify more similarities than expected by discussing them from a relative perspective. In the previous paragraph we already discussed some differences in the composition of the assets on the balance sheet of the central banks, and in the choice of counterparties in their non-standard measures. In this paragraph we continue the comparison between the Federal Reserve and the European Central Bank. Such high-level comparison is needed to put the specific measures that will be discussed in chapter 3 in a broader context. First, we will discuss obvious similarities that exist in the approach and operational framework of both central banks. Thereafter, we will take a look at what seem to be differences at first sight, but actually are similarities when looking at them from the right angle. Last, we will point out clear differences between the Fed and the ECB.
Obvious similarities A first similarity we discuss is the clear distinction both central banks made between their liquidity management and their monetary policy stance in the pre-Lehman period. For the ECB, this distinction is clearly stated in the “separation principle”(Trichet 2008). It “ensures that the specification and conduct of refinancing operations are not interpreted by market participants as signals of future changes in the monetary policy stance” (Stark 2008, p2). The monetary policy stance is determined in line with the primary objective of the ECB of maintaining price stability. The liquidity operations are employed to steer very short- term money market rates close to the ECB’s key policy rate as to assure that the monetary policy stance is effectively transmitted to the rest of the economy. This approach is consistent with the results of Poole (1970), who states that it is optimal to stabilise the very short-term interest rate in the interbank market and to let the money supply adjust endogenously when demand for central bank money is uncertain.
- 20 -
The measures that the ECB undertook between August 2007 and September 2008 were exactly designed for this purpose. The timing and maturity of liquidity supply was changed to be more aligned with the demand for liquidity within the reserve maintenance periods, and was therefore focused on stabilizing the short-term interest rate. Because the ECB was price-taker in its fine-tuning and longer-term operations, the interest rates of the latter did not contain any information about the monetary policy stance, ensuring a clear separation between both. However, communicating this separation was not straightforward as liquidity operations had to be supportive to meet the demand for liquidity of financial institutions, whereas the monetary policy stance needed to be tightened to tackle the increasing inflationary risks to meet its medium-term goals of price-stability 11 .
Keister, Martin et al. (2008) state that the Fed could have eased the liquidity shortage and reduced money market spreads by increasing the supply of bank reserves. However, this would have resulted in a market interest rate below the Federal Funds target rate and thus, the liquidity measures would have impacted the stance of the monetary policy. Therefore the Fed initiated non-standard measures like the Term Securities Lending Facility (TSLF) that liberated banks balance sheets from illiquid assets, in exchange for liquid Treasury securities. This improved the liquidity situation in the market without increasing the supply of bank reserves and therefore without impacting the monetary policy stance.
Although before September 2008 both central banks passed the test of keeping their monetary policy stance and their liquidity measures separated, their reaction to the aggravated situation thereafter, differed. This is further discussed in “Differences” (see below, p.23).
Hidden similarities Besides the clear similarities described in the previous paragraph, there are some similarities that can only be discovered when looking at central bank actions from a relative point of view.
11 On July 9, 2008, the key policy rate was increased from 4% to 4,25% - 21 -
When taking a look at Figure 1, one would tend to conclude that the Fed increased its balance sheet to a much larger extent than the ECB during the financial crisis. The total size of the Fed balance sheet has more than doubled since September 2008, in contrast to the balance sheet of the ECB, which has increased by around 60% (Lenza, Pill et al. 2010). Nevertheless, such comparison is irrelevant when taking a look at the absolute size of the balance sheets of both central banks. The initial size of the balance sheet of the ECB was much larger than that of the Fed. Therefore the required increase in liquidity to satisfy the increased demand from banks was proportionally smaller for the ECB. When again looking at Figure 1, we can observe that at the end of 2009, the difference in size between the balance sheet of the Federal Reserve and that of the ECB has diminished and became relatively similar, although the balance sheet of the ECB remains the largest in percentages of the average GDP. This indicates that what is often described as a much larger increase of the balance sheet of the Fed, actually represents a difference in starting conditions of the central banks.
Second, one could argue that the Federal Reserve went much further than the ECB in the extension of its list of eligible collateral. However, again this expansion represents a difference in starting conditions. With the TAF, for example, the Fed did not only provide liquidity to a broader set of counterparties than previously in its open market operations, but also accepted a much broader set of collateral, as for example triple-A-rated asset- backed securities on student loans, auto loans, credit card loans, and Small Business Administration loans. Many of the other newly introduced non-standard measures also accepted collateral that was previously not eligible in the refinancing operations of the Fed, as for example the Term Asset-Backed Securities Loan Facility (TALF) which accepted ABS as collateral. In contrast to the Fed, the ECB already accepted a very broad list of collateral 12 before the financial crisis had hit the financial markets, among which for example highly rated asset-backed securities. Therefore, the expansion of the list of accepted collateral of the Fed in its newly introduced facilities can be seen as an attempt to mimic the possibilities that the solid operational framework of the ECB offered to respond
12 As heritage from the pre-Monetary Union period (Lenza, Pill et al. 2010) - 22 - to the increased tensions in financial markets (Bullard 2010) without having to introduce a whole set of new facilities.
Last, one should not merely look at the absolute levels of the key policy rate of the Fed and the ECB when comparing these. Although the Federal Funds target rate was reduced to 0- 0.25 basis points, the key policy rate of the ECB has never been below 1 per cent. However, as the spreads between interbank rates and the Federal Funds target rate are larger than similar spreads in the euro area, the resulting interbank interest rates with six-month and twelve-month maturities are rather similar in both currency areas. Therefore, the monetary stance of both central banks cannot be compared by solely comparing the level of the key interest rates (Trichet 2009a).
Differences In “Obvious similarities” (see above, p.20) we already mentioned that the way central banks dealt with the separation of their liquidity management and their monetary policy stance changed after the failure of Lehman Brothers. Before, both banks succeeded in keeping these successfully separated. However, after September 2008 demand for liquidity became so elevated that both central banks adopted quantitative easing above the qualitative easing that was already in use, but had almost reached its inherent limits 13 . This quantitative easing lead to an amount of liquidity in the banking system that exceeded the required amount to fulfil minimum reserves. This has impacted the separation between liquidity operations and monetary stance in both currency areas in a different way.
First, we will take a look at how the separation of the liquidity management and the monetary policy stance of the ECB evolved after the fall of Lehman Brothers. In October 2008, the ECB announced that it would adapt a fixed rate full allotment (FRFA) tender procedure in its MROs. Given the high demand for liquidity due to the elevated strains in the money market and the decision of the ECB not to reabsorb excess liquidity with fine- tuning operations created a situation of ample liquidity in the banking system. The excess
13 For example, the Term Securities Lending Facility can only be operative until the quantity of Treasury that the central bank owns, is exhausted. - 23 - liquidity was reabsorbed through recourse at the marginal deposit facility (Lenza, Pill et al. 2010). Keister, Martin et al. (2008) describe in detail what happens when the supply of reserves is higher than the target supply that is necessary to achieve the target interest rate. Namely, the equilibrium overnight market interest rate, which is determined by the height of the demand for reserve balances and the level of reserve balances supplied by the central bank, will decrease 14 . Because of the use of a symmetric channel system at the ECB, the deposit rate creates a floor-limit for this overnight interest rate. In Figure 3, we can observe how the European OverNight Index Average (EONIA), which is the overnight money market interest rate in Europe, began to decrease after Lehman Brothers and the implementation of the FRFA tender procedure, until it dropped below the MRO rate begin 2009 and eventually hit the deposit facility rate. As liquidity operations after the collapse of Lehman Brothers influenced the level of the short-term money market rate, the separation between liquidity operations and the monetary policy stance was not maintained, in contrast to the pre-Lehman period. As a result, the ECB changed its official way of communicating its monetary policy stance. Instead of using the MRO rate, the stance from September 2008 on was signalled by the level of market rates at various maturities.
Figure 3: Spread between Eonia and MRO rate Note: monthly averages Source: Datastream, Fed 14 This is defined as the liquidity effect of reserve balances on the market interest rate (Keister, Martin et al. , 2008)
- 24 -
The Federal Reserve tackled the situation that arose after September 2008 in a different manner. Before the failure of Lehman Brothers, the Fed did not pay interest on reserve balances of depository institutions. In such a system, there is no floor-limit to the overnight market interest rates, as is the case at the ECB. Therefore, an increase in the supply of reserve balances in response to the large demand in the post-Lehman period would have led to a situation where the overnight market interest rate could have departed from the target rate towards zero. Moreover, the lack of interest payments on reserve balances created an opportunity cost and imposed an implicit tax for depository institutions on holding these reserves. Furthermore, a deadweight loss in the economy existed because of the effort that institutions spent on trying to get rid of their excess balances 15 . Such deadweight loss is in sharp contrast with a central banks objective of efficient financial markets and efficient allocation of resources in the economy. Especially in times of stress in financial markets, these conflicts are strong (Keister, Martin et al. 2008). On October 6, 2008, the Fed announced that it would begin to pay interest on required and excess reserve balances 16 and therefore alleviated the tensions created by these conflicts and promotes the efficiency in the banking sector. More important, with this decision, the Federal Reserve converted to a floor-system. The Fed announced that the interest rate paid on required reserve balances would be the average targeted Federal Funds rate established by the Federal Open Market Committee (FOMC) over each reserve maintenance period less 10 basis points. In contrast, at the ECB, the marginal deposit facility rate is 100 basis points below the MRO rate. This gave the Fed the possibility to use its liquidity measures to ease pressures in the money markets while at the same time maintaining the Federal Funds rate close to its target. Goodfriend already stated in 2002 that a floor-system would allow the Fed to “increase bank reserves in response to a negative shock in broad liquidity in banking or securities markets or an increase in the external finance premium that elevated spreads in credit markets” (Goodfriend 2002, p. 4).
15 For a more in-depth discussion, we refer to Keister, Martin et al. (2008) 16 This was authorized under the Financial Services Regulatory Relief Act of 2006 and was accelerated by the Emergency Economic Stabilization Act of 2008. For more information, we refer to
Although the introduction of the payment of interest on reserve balances at the Federal Reserve further increases the resemblance of the operational framework of the Fed with the framework of the ECB, the spread between the key interest rate and the deposit facility differs. Therefore, the Fed could, in contrast to the ECB, divorce its liquidity management to a larger extent from its monetary policy stance. For more details and more advantages on the introduction of a floor-system, we refer to Keister, Martin et. Al (2008).
Next to this difference in separation between liquidity operations and monetary policy stance, another difference can be found in the exposure to credit risk of both central banks. With the creation of for example the TALF and the Commercial Paper Funding Facility (CPFF) the Federal Reserve collected more risky private-sector securities compared with the European Central Bank 17 . Although the ECB also engaged in asset purchases in its Covered Bond Purchase Programme, covered bonds imply less credit risk because of their dual nature of protection (cf. paragraph 3.3.2) which ABS, for example, lack.
A last clear difference is the involvement of the central banks in the rescue of some specific financial institutions. The Fed, for example, provided loans to facilitate the rescue of AIG and it was involved in the rescue scheme of Bear Stearns (Klyuev, de Imus et al. 2009). Such an involvement was absent in the euro zone.
2.3 Conclusion
In this chapter, we have drafted a high-level context that provides us with a deeper insight in the monetary policy response of both central banks. We pointed out that especially the difference in financial structure has greatly influenced the design of the non-standard monetary policy response of the Federal Reserve. The importance of, and the elevated strains in the shadow banking system prompted the Fed to expand its set of counterparties and to also bypass the banking sector, next to its support to the interbank market. In contrast, because of the already very extended list of counterparties and accepted collateral,
17 However, as Klyuev, de Imus et al. (2009) notice, if the Fed would occur any losses, these would be borne by the US Government because of a joint Fed-Treasury statement. The supranational nature of the European Central Bank may have contributed to its reluctance to buy assets.
- 26 - the ECBs non-standard measures mainly concerned adaptations to its traditional framework.
- 27 -
3 THE TOOLBOX OF THE FEDERAL RESERVE AND THE EUROPEAN CENTRAL BANK
Provided with the draft of the economic as well as financial structure of both currency areas and keeping the discussion of some relevant similarities and differences between the Fed and the ECB in mind, the way is now paved to elaborate on the specific measures introduced by both central banks during the financial crisis. We will not dwell on the operational details of these measures, but we aim at understanding the rationale behind them as this will provide us with insights which markets these measures were intended to support. These insights are a prerequisite for the analysis of the effectiveness of the non- standard measures in the following chapter (see below, p. - 57 - ). With key interest rates heading towards the lower bound after September 2008, central banks had to address their efforts to other possibilities to provide monetary stimulus. As Bullard (2009) worded sharply: “To keep stabilization policy active and aggressive in the current global recession requires a shift in thinking relative to that of the past 15 years. ” (Bullard 2009, p. 3). Therefore, in section 3.1, we will provide a theoretical overview of four main possibilities central banks have when key policy rates are near the zero bound. After this section, the toolbox of non-standard measures introduced by both central banks is discussed. In section 3.2, we will elaborate on the toolbox the Federal Reserve created during the financial turmoil. In section 3.3, we will discuss the unconventional measures initiated by the European Central Bank. In each section, we will make a distinction between two periods, which are separated by the collapse of Lehman Brothers 18 on September 15 2008, as since then the financial turmoil evolved into a full financial crisis. The pre-Lehman and post-Lehman period differ in severity of the strains in the money market, and are therefore also characterized by a different intensity of monetary policy response.
18 However, as Trichet (2009) noted, it is hard to find out whether the failure of Lehman Brothers elicited a phase that was inevitable due to the remaining weaknesses in the banking system or whether the severed situation beginning in September 2008 caused Lehman to collapse. Moreover, Reis (2009) notes that also the bailout of American International Group (AIG) on September 16 and the vague announcement of the Troubled Asset Relief Program (TARP) on September 20 make it hard to distinguish what has lead to the second phase of the crisis. - 28 -
3.1 Theoretical introduction
In this section, we will shortly provide four main possibilities central banks have to provide monetary stimulus when key interest rates are close to the zero bound, based on Klyuev, de Imus et al. (2009). In the remaining of this chapter we will see that the Federal Reserve employed all four possibilities to the fullest, while the ECB did so to a much smaller extent.
A first possibility central banks have at their disposal when key interest rates are near the lower bound is communicating its future monetary policy course (Bernanke 2009). Even when overnight interest rates are close to zero, central banks can influence longer-term interest rates by committing to maintain policy rates low for a long period of time. Such commitment should guide long-term interest rate expectations and should therefore result in downward pressures on long-term interest rates. Moreover, with nominal interest rates at a very low level, expected inflation has a large contribution in the determination of real interest rates (Bullard 2009). Therefore, the low short-term interest rate commitment should avoid decreasing inflation expectations which would have an unwished-for increasing effect on real interest rates.
A second possibility is to provide large amounts of liquidity to financial institutions at low cost. Moreover central banks could extend their list of collateral, their set of counterparties and they could lengthen the maturities of their operations. When banks are reluctant to lend to each other, such provision of liquidity should give banks the resources they need to provide funds to households and non-financial institutions.
Third, central banks could purchase large amounts of government securities to decrease their yields. As the (risk-free) rates on government securities are an important benchmark in the determination of interest rates of a variety of private-sector assets, such a decline should be translated in decreasing long-term private borrowing rates across a wide range of financial assets (Klyuev, de Imus et al. 2009).
- 29 -
A last course open to central banks is the direct intervention in specific segments of credit markets. This could be done in a variety of manners, for example with the purchase of private assets or by providing loans that only accept particular types of assets as collateral. Such interventions could improve trading conditions, reduce liquidity premiums and support issuance in these credit markets, for example of commercial paper and asset- backed securities (Klyuev, de Imus et al. 2009). Moreover, purchases of private assets increase the monetary base more persistently than other measures introduced by the Fed (for example the TAF, the TSLF, the CPFF, the PDCF and the swap facility) and therefore Bullard (2009) argues that these should have an upward influence on inflation expectations and therefore a downward impact on real interest rates.
Now, with these four theoretical possibilities in mind, we will take a look at the specific non-standard measures of both central banks during the financial crisis.
3.2 The toolbox of the Federal Reserve
In the following section we will disentangle the toolbox of the Federal Reserve. Measures adopted during the pre-Lehman period are of a different nature than the ones implemented after the collapse of Lehman Brothers. Not only do they differ with respect to the impact on the balance sheet as mentioned in section 2.2.1, but also concerning the market segments that were being addressed by these measures, as discussed in section 2.1.2. First, in section 3.2.1, we will discuss the measures undertaken by the Federal Reserve before Lehman, which focused on supporting interbank intermediation in the money market (cf. Exhibit 1). Further, in section 3.2.2, we will disentangle the measures adopted after the collapse of the Lehman Bros according to the financial market they each addressed. These non-standard measures concentrated mainly on critical non-bank markets, such as the commercial paper or asset-backed securities market (Bernanke 2009).
3.2.1 The pre-Lehman period
In this paragraph, we will dilate upon a first set of tools, which was closely linked to the traditional role of the central bank as the lender of last resort. These measures aimed at providing short-term liquidity to financial institutions as those had become reluctant to
- 30 - lend to each other. This reluctance can be observed in Figure 4, as spreads between Libor and OIS rates began to increase during the summer of 2007, signalling an increase in credit and liquidity premiums that were demanded in interbank lending transactions, as already discussed in section 1.3.
As a first reaction, the Federal Reserve decided to cut the discount rate in August 2007. In September, the target for the Federal Funds rate was reduced with 50 basis points. These actions were initiated to soothe the effect of the financial turmoil on real economy (Bernanke 2009) as under normal circumstances, changes in policy rates are rapidly transmitted to the entire economy (Angelini, Nobili et al. 2009). However, when the severity of the turmoil became more apparent as spreads weren’t turning back to their original level, the Federal Reserve continued to lower the Federal Funds target rate resulting in a decline of 325 basis points by the spring of 2008, as can be seen from Figure 4.
Figure 4: Libor-OIS spread and Federal Funds Target rate Source: Federal Reserve, Datastream, authors’ calculations
Compared with the ECB, of which the monetary policy stance was tightening until October 2008, these reductions of the Federal Funds target rate were rather rapid and bold. However, strains in the money market remained elevated. Banks kept being confronted with a large demand for liquidity. Although banks had access to the discount window, which the Federal Reserve offers as lender of last resort, they were reluctant to borrow via this channel. Furfine (2003) states that this reluctance was caused by a stigma associated by the discount window. Informational asymmetries and adverse selection were run-of-
- 31 - the-mill starting from August 2007 (Lenza, Pill et al. 2010) and therefore banks didn’t want to give a signal of underlying problems to the market by appealing to the Fed’s standing facilities. This stigma resulted in a shortage of liquidity that continued to exist among banks (Armantier, Krieger et al. 2008). To address this continuing need and to overcome the stigma, the Fed stepped into the breach by initiating the Term Auction Facility (TAF). The TAF addressed this need by supplying liquidity anonymously to all counterparties that had access to the discount window against the broad range of collateral of the latter. The anonymous provision of funds at the regular operations of the ECB seemed to be working well and did not exhibit any stigma. Therefore, the introduction of the TAF again brings the operational frameworks of the Fed and ECB closer together. To obtain TAF liquidity, depository institutions had to bid in auctions, and therefore, the liquidity was provided to the institutions that were in the direst straits.
Next to the need for dollar liquidity in the US interbank market, more and more European financial institutions were facing problems to fund their high-levels of dollar-denominated assets. In normal times, these institutions found funding at money market funds, central banks, the interbank market and in the foreign exchange (FX) swap market (Goldberg, Kennedy et al. 2010). However, the crisis hit all these markets hard in September 2008. Especially the Eurodollar market and the FX swap market faced very elevated strains. Moreover, as conditions in the US interbank market aggravated in September 2008, also more and more American institutions shifted from the offer side to the demand side in the FX swap market. This aggregated increase on the demand side combined with a decrease on the offer side due to a higher level of caution of dollar lending institutions and a strong increase in counterparty risk, made the FX swap-implied dollar rate to move further and further from the Libor 19 . In normal situations, these two rates lie closely together as differences between them are arbitraged away. However, during the financial crisis, arbitrageurs could not access enough liquidity in strained unsecured markets to benefit from the higher FX swap-implied dollar rates, and therefore, arbitrage did not took place. When volatility in FX swap-implied dollar rates started to heighten after mid Augusts 2007,
19 For further details on the increase in counterparty risk during the financial turmoil, we refer to Baba and Packer (2009). - 32 - the Federal Reserve decided on December 12 2008, in consultation with the ECB, to offer reciprocal currency arrangements as part of the Term Auction Facility, which would provide overseas markets with dollar funding and should help the strains in the FX swap market to tranquilize. Also other central banks engaged in swap arrangements with the Federal Reserve. However, we will focus on the swap lines between the Fed and the ECB. As can be seen in Figure 1, there was a steep increase in claims in foreign currencies on the asset side of the Federal Reserve in the post-Lehman period. The coordinated effort between these central banks was directed at reducing the elevated pressures in global short-term US dollar funding markets and to maintain overall market stability (Goldberg, Kennedy et al. 2010).
In the pre-Lehman period, two other non-standard measures were announced. The Term Securities Lending Facility (TSLF) and the Primary Dealer Credit Facility (PDCF) were announced on March 11 and March 16 respectively. The TSLF and the PDCF were intended to ease liquidity strains in secured money market via primary dealers while the TAF, in contrast, provided funding to depository institutions to soothe the unsecured funding market conditions (Fleming, Keane et al. 2009). Strains in secured markets were elevated as not only credit risk had increased, but also, due to the questionably value of many hard to valuate assets, a reassessment of the risk of certain assets took place and greater hair-cuts and compensations for risk in collateral were demanded. Certain collateral was even refused for secured lending. Because of the impaired secured funding market, dealers had to find financing for their assets elsewhere. If dealers couldn’t borrow in alternative markets and if they had no capital available to fund their securities, they may have been obliged to sell them. However, as markets for these securities were facing illiquidity for the same reasons as the high compensation that was demanded for the use of these securities as collateral, such securities would have been sold at high discounts which would lead to a snowball effect. It is to overcome such spiralling effect in the secured funding market, and to promote the functioning of financial markets more generally, that the Fed had initiated the TSLF and the PDCF.
- 33 -
The TSLF allowed primary dealers to swap a broad range of collateral for Treasury which could easily be used as collateral in a broad range of funding transactions. In contrast to all other measures undertaken by the Federal Reserve and as already explained in section 2.2.2, the TSLF had no effect on the supply of bank reserves. This resulted in a large flexibility as this measure did not risk to affect the monetary policy course. In contrast to the TSLF, the PDCF is a standing facility that provides liquidity overnight and accepts a broader class of collateral. The Fed had initiated the PDCF especially because of the strains in the overnight repo-market, which had known a rapid growth prior to 2007 as more and more primary dealers had begun to rely on such repos for the rolling-over of their funding (Adrian, Burke et al. 2009). The PDCF is comparable to the discount window as it also offers backstop source of liquidity, however it addresses primary dealers instead of depository institutions. In contrast to the PDCF, the TSLF was an auction facility in which dealers could bid collectively. This approach may have helped to overcome the stigma that is typically associated with a non-anonymous standing facility. For more details on the auction mechanism of the TSLF, we refer to Fleming, Kean et al. (2009).
3.2.2 The post-Lehman period
While the functioning of the interbank market had not totally recovered against September 2008, the collapse of Lehman Brothers raised the strains in this market to a much higher level. As can be seen in Figure 4, the soaring Libor-OIS spread in September 2008 dwarfed the levels of the spread in the pre-Lehman period. As a reaction, the Federal Reserve further eased financing conditions by continuing to cut the Federal Funds target rate towards an absolute lower bound of 0 - 0.25 per cent, which was eventually hit on December 16, 2008.
As described in section 3.1, a central bank has four main possibilities when key interest rates are heading towards the lower bound. The first possibility was exercised on that December 16, as the Fed announced that the weak economic conditions were likely to warrant exceptionally low levels of the Federal Funds target rate for some time 20 . The
20 The announcement of December 16, 2008, can be found on
- 35 -
In the following we will discuss the segments of the credit market targeted by the Fed one by one, and we give an overview of the specific non-standard measures that were initiated to relieve the strains in these market segments.
3.2.2.1 Commercial paper market
A first key credit market we will take a look at, is the commercial paper market. Before the crisis, this market was a major source of funding for a variety of financial intermediaries. However during the crisis, volumes in this short-term funding market dropped, maturities shortened and interest rates climbed (Duygan-Bump, Parkinson et al. 2010) which signaled the drying up of this market. Three specific measures were launched to revive the activity in these markets and financed companies directly without going through banks (Reis 2010). However, only two will be discussed in this paragraph. The Money Market Investor Funding Facility (MMIFF) will not be elaborated on as no operations have taken place under this facility. In order to understand the rationale behind the other two measures, we will first briefly discuss some evolutions in the commercial paper market.
Evolutions in the commercial paper market Money market mutual funds (MMMF), which we further will refer to as money funds, are key investors in the (asset-backed) commercial paper market. The fall of Lehman Brothers had a major impact on these money funds, and therefore also on the commercial paper market. On September 16, the Reserve Primary Fund broke the buck 21 due to its exposure to debt securities of the Lehman Brothers. This created a fear among investors in money market funds that their fund would also break the buck, and uncertainty about the value of their investment rose. As a result, money market funds were confronted with massive redemptions. These outflows were comparable with a bank run 22 . If money funds did not have enough cash at their disposal to meet such outflows, they could be forced to sell assets to meet their redemptions 23 . Because of the low liquidity in secondary markets for these
21 The Net Asset Value fell below the value of 1 dollar per share. 22 For more information, we refer to Prescott (2010) 23 Money market mutual funds are characterized by a mismatch between the maturities of their assets ( before September 2008 the average maturity was between 35 and 55 days) and their liabilities (investors can ask redemption at any time). - 36 - assets, this could result in a sale at discount prices. Such a fire sale would further reduce the value of assets of money funds, and would theref ore reinforce the fear of investors which would in turn result in even more redemptions .
As money funds were the main investors in commercial paper 24 (Kacperczyk and Schnabl 2010), them being reluctant , or not able, to purchase newly issued commercial paper ( and other short-term investments ) resulted in an impaired short-term funding marke t. Spreads of overnight commercial paper rates over the Federal F unds target rate sharply increased after the c ollapse of Lehman Brothers and the amount of commerc ial paper outstanding declined. Because money funds were especially reluctant to buy longer -term commercial paper, the rates on the latter also soared and remained elevated for a longer period of time . Due to the poor quality of underlying assets, this was even more the case for asset -backed commercial paper. This is clearly illustrated in Figure 5.
Figure 5: Spread between ABCP and Federal Funds target rate (overnight & 3-month) Source: Federal Reserve, authors’ calculations
24 For example, money market funds held about 45% of all outstanding commercial paper in the United States (Duygan-Bump, Parkinson et al. 2010) . - 37 -
Because of the elevated strains in the commercial paper market, certain institutions that relied heavily on commercial paper for their funding were now having problems to roll over their liabilities (Adrian, Kimbrough et al. 2010). As these institutions were not being reached by the measures of the Fed introduced so far, the Fed created the Asset-backed Commercial Paper Money Market Mutual Fund Liquidity Facility (AMLF) and the Commercial Paper Funding Facility (CPFF) to address tensions in this key credit market. We will now elaborate shortly on each of these facilities.
Asset-Backed Commercial Paper Money Market Mutual Fund Liquidity Facility The AMLF was introduced on September 19, 2008 and became operational from September 22 on. The Fed offered non-recourse loans 25 to the traditional discount window borrowers at the primary credit rate in order to allow them to purchase highly rated ABCP 26 from money funds at amortized cost. This pricing provided depository institutions with an incentive to purchase ABCPs from money funds. This was because ABCP yields implied by amortized costs were, in times of market stress, higher than the primary credit rate and therefore they could earn a positive spread on such a transaction. The maturity of the loans matched the remaining maturity of the ABCP that was pledged as collateral. This design makes the AMLF one of the most unconventional measures introduced in the post-Lehman period. In contrast to the discount window, the loans were non-recourse and no hair-cut was calculated on the value of the collateral. This way, the Fed exposed itself to credit risk in case the ABCP would default. However, due to the severe restrictions on counterparties and collateral, this risk was rather modest. Moreover, the facility’s design made depository institutions take ABCP on their balance sheets, an asset which normally is not held by depository institutions. But as money funds would not be eager to lend directly from the Fed, as this could give undesired signals to its investors and as a result could reinforce the “money fund run”, the Fed was left no other choice than going through the depository institutions.
25 Because of the severe rules concerning the eligibility of the collateral, the Fed was not confronted with moral hazard problems though (Duygan-Bump, Parkinson et al. 2010) 26 Only funds that were qualified as money market mutual funds under the SEC rule 2a-7 were eligible. The ABCP- collateral had to be rated not lower than A-1, F1 or P1. For more information on the eligible collateral, we refer to the website of the Federal Reserve. - 38 -
The AMLF was initiated to prevent the flow of credit to households and firms to be harmed by the strains in the asset-backed commercial paper market (Adrian, Kimbrough et al. 2010). Therefore, the AMLF aimed at relieving such strains by increasing liquidity in ABCP markets and reducing the yields of ABCP. Moreover, by initiating the AMLF, the Fed wanted to prevent money funds that were solvent though illiquid, to fail (Duygan-Bump, Parkinson et al. 2010). This was done by helping money funds to meet the flow of redemptions by enabling them to liquefy their assets via the Fed, instead of through a fire sale. Severe restrictions on the eligibility of counterparties and collateral ascertained the Fed that such transactions would involve solvent firms and good collateral. However, as mentioned above, loans were provided at full value of the collateral, in contrast to the value minus a haircut. This was a result of the already weakened net asset value (NAV) of the money market funds, which made it impossible to make the loan at the value less a haircut (Duygan-Bump, Parkinson et al. 2010). A last objective of the AMLF was to prevent banks that acted as a sponsor of certain ABCP issues to take ABCPs on their balance sheets because money funds were reluctant to purchase them. This would be very undesirable as banks’ balance sheets were already under a lot of pressure.
Commercial Paper Funding Facility The Commercial Paper Funding Facility was announced on the 7 th of October 2008 and 20 days later the first operation took place. In contrast to the AMLF, the CPFF did not provide lending to the money funds but tackled the problem at the source by addressing issuers of commercial paper directly with the CPFF. Under the CPFF, the Fed funded the purchase of highly rated 27 unsecured and asset-backed commercial paper from eligible issuers via eligible primary dealers 28 . As stated before, money funds were faced with massive redemptions which made them reluctant, or even incapable, to invest in commercial paper, especially at the longer term. As a result, issuers of commercial paper were forced to fund themselves through overnight commercial paper to a much higher extent. Therefore, they were exposed to a larger rollover risk as they had to look for new investors every day.
27 The commercial paper had to be rated at least A-1/P-1/F-1 by a major nationally recognized statistical rating organization. Therefore, the exposure to credit risk of the Federal Reserve was limited. 28 For details, we refer to
Elevated spreads in the commercial paper market, as result of the increased liquidity and credit risk, lead to higher issuing costs and there was a large decrease in the volume of outstanding paper. The goal of the CPFF was to increase liquidity in the commercial paper market by assuring both investors and issuers of a smooth rolling over of their commercial paper 29 . This certainty should have a positive impact on the spread between commercial paper yields and the risk-free rate 30 . Such improvements in conditions in the commercial paper market should eventually result in greater availability of funds to companies and households.
To implement the CPFF, a Special Purpose Vehicle (SPV) was created to purchase eligible commercial paper with a 3-month maturity. This SPV obtained loans from the discount window with this commercial paper as collateral. Therefore, with the creation of this SPV, the extension of the discount window to the commercial paper market was made ((Adrian, Kimbrough et al. 2010). The commercial paper was held to maturity at the SPV.
3.2.2.2 Asset-backed securities market
Evolution of the asset-backed securities market While conditions in the interbank and commercial paper market started to show signs of improvement following the initiation of the above described non-standard measures, strains in the securitization market remained elevated for a longer period of time, especially in the asset-backed securities market. In chapter 1, we already described the root causes for the deterioration of the ABS market. Because of the complexity of the pools of assets that were underlying these ABS, accurate valuation of ABS became almost impossible. This turned investors reluctant to buy such securities. Moreover, because of the strains in the ABCP market, investors in ABS were having hard times themselves in rolling over their short-term funding for these investments. This further reduced their appetite to purchase ABS 31 . This lead to the precipitously decline in new issuance of ABS in September 2008 and
29 “The repayment of CP issued by a conduit depends primarily on the cash collections received from the conduit’s underlying asset portfolio and a conduit’s ability to issue new CP” (Fitch Ratings (2007) , p.1) 30 In chapter 0, we will use the Overnight Index Swap (OIS) rate for this purpose. 31 A maturity mismatch strategy where illiquid long term loans are granted by liquid short-term funding, is the daily routine in such markets (Schmaltz 2009) - 40 - to a complete halt in October. At the same time, interest rate spreads between AAA-rated tranches of ABS and Treasury soared, reflecting unusually high risk premiums. Not only primary markets for ABS suffered, also serious strains on the secondary market arose.
About half of credit loans and a third of auto loans had been funded through securitization in the years leading up to the crisis (Campbell, Covitz et al. 2011). Further constrains in this market would lead to further deterioration of the U.S. economy for which the Federal Reserve decided to intervene during November 2008. This is where the Term Asset-backed securities Lending Facility came in.
Term Asset-backed securities Lending Facility On November 25 th , the Federal Reserve announced the launch of an innovative liquidity program named the Term Asset-backed securities Lending Facility (TALF) which started its operations in March 2009. The Federal Reserve stated that this measure aimed at making credit available to consumers and business on more favorable terms by facilitating the issuance of asset-backed securities (ABS) and improving the market conditions for ABS more generally. This facility collaborated with the Troubled Asset Relief Program (TARP) set up by the US Government which, among others, aimed at restoring tranquility in the asset-backed securities market. This combination provided on the one hand liquidity provided by the Federal Reserve and capital provided by the Treasury (Bernanke 2009).
The TALF offered non-recourse loans with a maturity from 3 to 5 years to all kind of institutions which were collateralized by highly-rated asset-backed securities that these institutions purchased. Again, as with the CPFF, primary dealers were used as agents between the central bank and the borrowing institutions. Because of the non-recourse characteristic of the loan, the Federal Reserve was running more risk than otherwise but tried to protect itself by setting a haircut on these loans. Moreover, eventual losses would be borne by the US government.
- 41 -
The price of TALF loans was set well below those manifested in the late 2008 but well above the price on highly rated ABS in normal times, so that the facility would be dismantled gradually when financial conditions restored. These favorable terms in times of financial turmoil provided an incentive to investors to purchase eligible asset-backed securities and thereby earn relative high returns. This increase in activity of investors should lead to a reduction in the spread of ABS securities and therefore, the cost of issuing ABS decreases. This should eventually lead to lower borrowing costs for households and businesses (Dudley 2007).
3.2.2.3 Other key credit markets The three non-standard measures described above (the AMLF, the CPFF and the TALF) provide loans that only accept particular types of assets as collateral to support specific key credit markets. However, another way to intervene directly in specific credit markets, which corresponds to the fourth possibility central banks have for easing financing conditions once key credit rates are near the lower bound, is the purchase of private assets (cf. section 3.1). In the following, we will describe the Large-Scale Asset Purchases (LSAP) program which was announced on November 25th 2008. On this day, the Fed made public that it would purchase housing agency debt and agency mortgage-backed securities for an amount of up to $600 billion, thereby directly intervening in these credit markets. Later, in March 2009, an expansion of the purchases of agency-related securities and purchases of longer-term Treasury securities were announced. With the decision to purchase large amounts of government securities, the Fed executed the third possibility for monetary stimulus at the lower bound. This third possibility had the advantage that it concerned familiar operations and exposed the Fed to less credit risk than the other asset purchases 32. Moreover, it offered a clear signal that the Fed wanted to reduce longer-term interest rates. However, for the Treasury purchases to be effective, very large amounts had to be purchased. Moreover, the translation of the decrease in long-term risk-free interest rates to
32 If these Treasury securities are not held until maturity, losses could occur when yields start to rise in a recovering economy (Klyuev, de Imus et al. 2009) - 42 - rates of private assets could fail to come if the substitutability between these assets is low as a result of heightened risk aversion (Klyuev, de Imus et al. 2009).
Large-Scale Asset Purchases With the Large-Scale Asset Purchase program, the Fed purchased more than $1. 7 trillion in assets between December 2008 and March 2010. This amount was astonishing and was the largest amount of securities ever purchased in such short notice (Gagnon, Raskin et al. 2010). Therefore, the LSAP program has played a major role in the quantitative easing of the Federal Reserve in the post-Lehman period. The main objective of these asset purchases was to bring long-term private interest rates down (Rudebusch, Sack et al. 2007). This in contrast to the open market operations which aim at a minimal impact on prices. Purchases in agency-related credit markets were initiated with the goal of supporting mortgage lending and housing markets, while the purchases of Treasury securities aimed at improving conditions in private credit markets 33 .
Gagnon, Raskin et al. (2010) describe four channels via which large-scale asset purchases could have reached above-mentioned targets of reducing long-term interest rates. A first possibility is the liquidity channel. As many other markets, the agency-related and Treasury markets were facing illiquidity during the financial crisis, causing downward pressure on the prices and thus upward pressure on the yields of these assets. The fact that investors and dealers knew that they could sell their securities at all times to the Federal Reserve at market prices under the LSAP program, improved trading opportunities and made dealers and investors take larger positions in such securities again (Gagnon, Raskin et al. 2010). The resulting recovery of liquidity should have lowered liquidity premiums that investors demanded.
Another channel through which this asset program could have influenced the real economy is the portfolio balance effect. By purchasing riskier longer-term assets in agency-related
33 As announced on March 18, 2009 by the FOMC. For more information, we refer to < http://federalreserve.gov/newsevents/press/monetary/20090318a.htm> - 43 - and Treasury markets, the Fed reduced the amount of these assets held by market. Moreover, as these assets were being replaced with short-term risk-free reserves, the total amount of risk in the market was also being reduced. This should lead to a diminution in the risk premium required by investors. For investors to be willing to give up these riskier longer-term assets, the yield on these assets had to decrease 34 . For Treasuries, the most important part of the risk premium is the term premium, and therefore, as the large-scale asset purchases removed a significant amount of duration risk 35 from the market, this term premium should have declined. With the purchases of mortgage-backed securities, next to the reduction in duration risk, also a significant amount of prepayment risk was taken away from the market. Prepayment risk is the risk that a borrower may prepay the mortgage in response to a decline in interest rates (Madura 2008). This is discussed in more detail in Gagnon, Raskin et al. (2010).
A third way by which LSAPs could influence the economy is by spill-over effects. With higher prices and thus lower yields on Treasury and mortgage-backed securities in prospect, investors became also more enthusiastic to purchase other assets than those that were purchased under the LSAP, as these provided higher returns (Beirne, Dalitz et al. 2011). A higher demand for these assets should bid up their prices. Therefore, also yields of assets that were not targeted by the LSAP could decrease.
A fourth channel would be the downward influence on expectations about short-term risk- free interest rates, as long-term yields are composed of the latter over the term to maturity and a risk premium. However, this possibility was not employed by the Fed as it kept on emphasizing in its public communications that it was still able to raise short-term interest rates if this would appear to be necessary. Krishnamurthy and Vissing-Jorgensen (2011) state that the LSAP could also affect the economy via an inflation channel. Inflation expectations could be increased as such a considerable asset purchase program could signal the willingness of the Federal Reserve to stimulate the economy.
34 Or stated otherwise: the significant amount of purchases of the Fed bid up the prices of the assets and therefore lowered their yields. 35 By this we mean the reluctance of investors to bear the interest rate risk associated with holding an asset that has a long duration (Gagnon, Raskin et al. 2010) - 44 -
Gagnon, Raskin et al. (2010) state that, in the early stages of the LSAP, the liquidity channel has been the most important channel. He bases these findings on the decline in spreads between agency related securities and Treasury as before the introduction of the LSAP these were unusually high, even taking the prepayment risk associated with the mortgage- backed securities into account. Furthermore, the spread between older Treasury and newly issued Treasury was also elevated before the LSAP was introduced. This spread was signalling liquidity pressures, as this would normally be arbitraged away. After the initiation of the LSAP, the willingness to purchase these older Treasuries resumed and the spread reduced, therefore signalling an improvement in liquidity.
Once liquidity pressures started to normalize, the portfolio balance effect may have been more important (Gagnon, Raskin et al. 2010). Evidence for this is found in the fact that interest rates did not seem to be significantly impacted when, at the ending of 2009, a winding down of the Treasury purchases was announced, and neither at the end of 2009 and in early 2010 when the slowing down of the purchase of agency-related securities end was announced. Also Krishnamurthy and Vissing-Jorgensen (2011) find that the portfolio balance effect was one of the dominant channels via which the LSAP have impacted the economy 36 . A more thorough assessment of the effectiveness of the LSAP will be performed in chapter 0.
3.3 The toolbox of the European Central Bank
Since its inception in 1998, the ECB has been exposed to a variety of challenges, but these pale in light of the events that occurred since August 2007. The response designed by the policy makers of the European Central Bank was rapid and of unprecedented magnitude, nature and scope (Trichet 2009a). In contrast to the toolbox of the Federal Reserve discussed in the previous section, all measures described in this section were undertaken with the purpose of supporting the banking sector. We will first take a look at the measures initiated as a reaction to the increased strains in the money markets after August 2007.
36 Krishnamurthy and Vissing-Jorgensen (2011) present a more extended set of channels via which the quantitative easing of the Fed could have impacted interest rates. However, the paper was not published at time of publication. - 45 -
Thereafter, we will continue with a description of the measures that were undertaken in response to the severed situation after September 2008.
3.3.1 The pre-Lehman period
After the events of August 2007, the ECB faced a trilemma (Stark 2008). Monetary analysis signalled risks to the medium-term objective of price stability 37 , but at the same time, economic activity was dawdling and financial stability was being threatened. The latter two observations would entice the ECB to take actions to revive economic activity and safeguard financial stability. Nevertheless, the ECB stuck to its mandate of maintaining price stability and kept their key interest rates at prevailing levels. On July 9, 2008, the minimum bid rate was even raised by 25 basis points. The single objective of the ECB guided them in resolving the above-described trilemma. Trichet (2009b) states that this approach of maintaining a medium-term perspective on price stability, even in times of financial market tensions, provided the ECB with a steady-handedness that constituted a source of stability in this challenging period. This is in sharp contrast with the uncertainty and volatility a go-stop type of policy would have induced, as described in Goodfriend (1997)38 . All measures executed in the pre-Lehman period were undertaken in continuity of the objective of remaining price stability in the medium-term, as their design made their unwinding possible at any time, once this objective would have been threatened. In the following, we will discuss these measures.
As a first measure, the ECB performed a number of large fine-tuning operations in early August 2007 as response to the rise in money market spreads. These operations were initiated on day one of the financial turmoil after the well-known announcement 39 of BNP Paribas in which they made public that they were struggling with credit difficulties 40 . The liquidity was provided at policy rate and all demand was fully allotted. The supply of 95
37 The upside risks for price stability were driven by a significant increase in commodity prices (Klyuev, de Imus et al., 2009) 38 For more information, we refer to the Goodfriend (1997) 39 The announcement can be found on
Figure 6: Frequency of fine-tuning operations at the ECB Source: ECB
Second, the timing of the liquidity provision within the reserve maintenance period was changed. While the total amount of liquidity over an entire reserve maintenance period remained unchanged (Stark 2008), more liquidity was provided at the beginning of the maintenance period and the amount supplied at the end was reduced. This decision of frontloading liquidity came in response to the increased uncertainty for liquidity. To prevent being short on liquidity at the end of a maintenance period, banks were demanding more liquidity in the beginning of reserve maintenance periods (Lenza, Pill et al. 2010).
A third measure the ECB undertook was lengthening the average maturity of the outstanding operations. Longer-Term Refinancing Operations (LTROs), which are usually executed at the end of each calendar month, were being conducted at non-traditional dates. As discussed in paragraph 2.2.1, more LTROs were executed at the expense of Main Refinancing Operations (MROs) (cf. Figure 7). Moreover, liquidity was provided with a
41 These data can be found on < https://www.ecb.europa.eu/mopo/implement/omo/html/top_history.en.html> - 47 - maturity of 6 months. Providing this liquidity at longer maturities was intended to reduce the uncertainty about the future availability of liquidity and thereby reducing tensions in the money market.
Figure 7: Amounts of MRO and LTRO outstanding Source: ECB
Next to these three measures, the ECB also cooperated with the Fed by establishing swap lines, as already discussed in paragraph 3.2.1.
In the pre-Lehman period, no fundamental changes to the framework were needed to accommodate these measures, in contrast to the Federal Reserve. Furthermore, the measures were not intended to replace the money market, but rather to provide support and to ensure the effective functioning in this market. To return to normal conditions in the money market, it was important that market participants kept on performing their role as market makers and that they would not become reliable on the liquidity provided by the ECB (Stark 2008).
3.3.2 The post-Lehman period
After the collapse of Lehman Brothers, banks were even more reluctant to lend to one another than in the pre-Lehman period. Therefore, they relied upon the ECB’s refinancing operations for their financing (Cassola, Hortaçsu et al. 2009). While in the pre-Lehman period, the battle against the strains in the money market was fought with rather
- 48 - traditional weapons, as only adaptations to size, timing and composition of the conventional measures were needed, the post-Lehman period called for some more unconventional arms. On October 8, 2008 the ECB lowered its key policy rate with 50 basis points 42 . Further decreases lead to a policy rate of 1 per cent towards May 2009, where it has remained since then 43 (cf. Figure 7).
The European Central Bank was at the forefront to combat the severed tensions in the money market by making changes with regard to size, maturity and collateral and counterparty eligibility. These special and primarily bank-based measures that were being taken to enhance the flow of credit above and beyond what could have been achieved through policy interest rate reductions alone, constitute the enhanced credit support of the ECB (Trichet 2009a). To discuss the innovations in measures initiated at the ECB, we adopt the categorization into five building blocks of Trichet (2009a).
The first building block is composed of the transition to a Fixed Rate Full Allotment (FRFA) tender procedure in October 2008 44 . Because traffic in the interbank market had come to a halt and spreads were at staggering heights, this measure had to ascertain counterparties that the ECB would remedy any shortage of liquidity. With this measure, the central bank delegated the decision about the level of central bank intermediation in bank-to-bank transactions to the banks themselves. With the availability of credit for households and companies at stake, the ECB wanted to guarantee an effective transmission of monetary policy. However, as described in paragraph 2.2.2, such increase in liquidity provided can endanger the monetary policy stance. Therefore, with the announcement of the FRFA tender procedure, also the corridor of the standing facilities of the ECB around the MRO rate was narrowed from the traditional 100 basis points to 50 basis points. This was initiated to prevent the EONIA to diverge from the key interest rate. However, as a result of the lowered interest rate for borrowing at the marginal lending facility, activity in overnight
42 This announcement can be found on
Although endowed with a broad list of collateral as heritage from the pre-Monetary Union period, the ECB decided to expand this list to further ease the stress in the money market. This expansion of collateral constitutes the second building block, and enlarged the total value of securities that were eligible as collateral to 12.2 trillion euro, which is a 130 per cent of the GDP of the euro area (Trichet 2009a). With such an extensive list of collateral, the ECB intended to overcome market fragmentation and a shortage of high-quality collateral triggered by a flight to quality (Klyuev, de Imus et al. 2009). Moreover, even though the ECB did not provide support to credit markets directly, the acceptance of certain types of loans and private securities as collateral indirectly facilitated their issuance.
The ECB already provided liquidity to a large set of counterparties at the outset of the financial crisis. Taking the first two building blocks of the ECB’s monetary response into account, this resulted in an unlimited supply of liquidity against a very extended list of collateral to around 2200 counterparties. The ECB counted on these counterparties to distribute the provided liquidity to the whole financial system and the real economy.
A third building block of the monetary response in the post-Lehman period was the further lengthening of the average maturity of outstanding operations. Next to renewing the three- month and six-month LTROs, which were introduced in the pre-Lehman period, the ECB also announced longer-term refinancing operations with a maturity of one year on May 7, 2009. The liquidity was provided with a fixed rate full allotment tender procedure and amounted 442 billion euro. This demand, which represents 5% of the GDP of Europe, signalled that a large demand for liquidity safety endured. The response of the ECB provided evidence that the central bank was willing to step into the breach with bold measures to accommodate this remaining demand for liquidity. The ECB initiated LTROs at this unusual maturity to resolve the mismatch between the investment and the funding side of banks balance sheets. The availability of liquidity on such a long term reduced the - 50 - uncertainty banks had about their future liquidity position and should have lengthened the planning horizon of banks. In turn, this should have lead to a larger provision of credit to households and institutions (Trichet 2009a).
The swap lines that were already announced in the pre-Lehman period remained operational in the post-Lehman period. These swap operations compose the fourth building block. Rather than reducing liquidity tensions in the euro area as the first three building blocks, this block aims at improving liquidity conditions in the global money markets.
The four building blocks described so far adhere to the second possibility to provide monetary stimulus when the key interest rate is near the lower bound, as we described in section 3.1. The fifth building block in contrast, coincides with the fourth building block and targeted a specific credit market by purchasing €60 billion in the covered bond market. However, in contrast to the Federal Reserve, this measure was not intended to bypass the banking system, but to support it as before conditions in the covered bonds market began to deteriorate, these bonds composed an important part of the funding side of banks balance sheets. As covered bonds 45 were a source of liquidity that was of a longer term nature than liquidity provided by refinancing operations of the ECB, the reduction in activity in this market created a mismatch between the asset side and the liability side of banks balance sheets. The choice for covered bonds in particular was not only driven by this ability to mitigate the liquidity risk due to the increase in banks access to long-term funding, but also because of their low risk relative to other bank securities (Beirne, Dalitz et al. 2011). These favourable risk characteristics are the result of the dual-recourse feature of covered bonds 46 . The objectives of the Covered Bond Purchase Programme (CBPP) were fourfold. First of all, a further decline in money market term rates was aimed for. A second and third goal was to ease funding conditions for credit institutions and enterprises by
45 Note that these covered bonds do not imply a transfer of credit risk as the underlying assets are parked on the balance sheets of the issuer. Therefore an incentive for credit risk monitoring and evaluation remains, in contrast to the various asset-backed securities (Lenza, Pill et al. 2010) 46 Dual recourse bonds have low risk characteristics because they imply a claim on both the issuer and on the pool of assets that cover the bonds. Moreover, as the issuer is required to maintain this pool on its balance sheet, in contrast to the ABS in the United States, these assets are likely to be of higher quality compared to their overseas equivalent. - 51 - reducing the spread in covered bonds markets and to encourage credit institutions to increase the amount of credit provided to households and non-financial institutions. Last, improved market liquidity in important segments of the private debt securities market was strived for.
3.4 Conclusion
In this chapter, we have described the specific non-standard measures that were introduced by both the Federal Reserve and the European Central Bank during the financial crisis. We can conclude that both central banks have changed the way of conducting monetary policy. Next to their traditional role of lender of last resort, they became intermediaries in the interbank market when traffic froze and they became market traders for security transactions in various credit markets. However, we can notice that the Fed has gone through greater lengths in the expansion of its traditional operational framework. The Fed has exploited all four possibilities central banks have at their disposal to ease financing conditions when key interest rates were near the lower bound to the fullest. The ECB, in contrast, did so to a much smaller extent and only made use of two possibilities. Even the covered bond purchases were not intended to bypass the banking sector, but, in contrast, to increase the ECBs support to it.
- 52 -
PART II On the effectiveness
- 53 -
In the previous part, we paved the way for this part, in which we will scrutinize the effectiveness of the non-standard monetary policy measures during the financial crisis. Until now we have set the context that is necessary to look at the results we obtain in this part, which is the core of this master thesis, from the right angle. Previously, after a short refreshment of the run-up to the financial crisis, we have made a thorough comparison between the Federal Reserve and the European Central Bank. First, we have described the different economic and financial structures in which these central banks operate. Secondly, we have elaborated on a framework that helped us to make a useful comparison between the measures of the Fed and those of the ECB. We also pointed out some general similarities and differences between the approaches of both central banks. We concluded with an overview of the measures the Fed and the ECB undertook, and the rationale behind them. In this part, we will take a closer look at these measures one by one, and we will examine their effectiveness in reducing the elevated strains in a various set of markets during the financial crisis of 2007-2008. We will introduce each measure by taking a look at some graphs that visualize the reaction of the market to the introduction of the measure. From these graphs, we will draft some preliminary conclusions that we will test later on from an econometric point of view, after describing our data set. In a first chapter of this part, we will concentrate on the Federal Reserve. We will commence with the discussion of the interbank market. Although banks only compose a small part of the channels via which households and firms are financed, we include this market to complete the comparison study. In a second subsection, we will take a look at some specific markets that are important in the United States and that also experienced a significant amount of pressure during the financial turmoil. A first market is the commercial paper market. We will, in this order, elaborate on the effectiveness of the AMLF and the CPFF. A second market is the ABS market, in which the TALF was active. Third, we will discuss the impact of the LSAPs on the Treasury market. In a second chapter, we will elaborate on the effectiveness of the measures the ECB has initiated. As the ECB’s response was primarily focused on the interbank market, the first section will consist of a study of the impact that the ECB measures had on interbank money market spreads. We will also perform some simple regressions to measure the impact of the CBPP. In a third chapter, we will discuss the impact of the swap arrangements between Fed and ECB. - 54 -
Methodology Before we pass to the chapters on the effectiveness of the Federal Reserve and the European Central Bank, we will first describe the methodology which we will apply throughout our econometrical analysis. To work out the effectiveness of each non-standard measure, we will take an event-study approach. Such methodology is common in the literature on the monetary policy during the financial crisis (McAndrews, Sarkar et al. 2008; Taylor and Williams 2008). In our econometrical regressions we will mainly focus on the effects of the announcements of non-standard measures rather than on their implementation. In line with the rational expectations hypothesis, we expect that the introduction of a new measure alone has a significant and complete price impact (Beirne, Dalitz et al. 2011)47 . In contrast, we do not expect such impact from announcements concerning the implementation of the measures nor the implementation itself as in most cases, all relevant information is incorporated in the initial announcement. Moreover, Friedman states that in effect “the announcement effect has displaced the liquidity effect as the fulcrum of monetary policy implementation” (Friedman and Kuttner 2010, p. II ). To isolate the effect of these announcements, we will use daily data 48 (Andersen, Bollerslev et al. 2002; McAndrews, Sarkar et al. 2008; Wu 2008). A disadvantage of such methodology is that it is difficult to ascertain whether the effects are permanent. Especially in times of high volatility, these problems could arise (Goldberg, Kennedy et al. 2010).
Due to reasons of non-stationarity 49 , we will use the first differences of the variables in each regression, unless reported otherwise. To confirm the stationarity in our data, we have performed unit root tests on each of these first-difference variables, however the results are not reported. Moreover, we will test each regression for autocorrelation and when identified, we will compute standard errors with the Newey-West procedure. Because the first-differences of the dependent variables are used, the dummy variables that must account for the impact of the announcements, is set to one on the day of the announcement
47 We therefore assume that markets are efficient in the sense that all effects on yields occur when market participants update their expectations and not when actual implementation takes place (Gagnon, Raskin et al. 2010) 48 Weekends are excluded 49 Unit root tests confirm the non-stationarity in our data. - 55 - and to zero otherwise. Moreover, to make sure that the effect of the various announcements is captured well, we create additional dummy variables each set to one on a particular day within a time window of three days around the announcement, and to zero otherwise (Duygan-Bump, Parkinson et al. 2010), unless reported otherwise. Choosing the length of the time window is rather arbitrary as it should not be too long to prevent that it would contain the effect of other information releases, but it should also be long enough to measure the impact of the measure (Gagnon, Raskin et al. 2010). Although the time window is set up symmetrically around the day of the announcement, we do not expect significant anticipation effects as most announcements came rather unexpected. In contrast, given the unconventionality of the measures and the elevated strains in the markets, we would expect possible lagged reactions on certain announcements. The anticipation and lagged responses are calculated by taking the sum of all significant variables before and after the announcement respectively.
Every regression will be performed over a sample period ranging from January 1, 2007 until August 31, 2010, which represents a symmetrical window around the period of elevated strains in financial markets. This sample is chosen because it includes both crisis and non-crisis time periods. However, we limit our sample to this period as taking a too long sample would be too much in favor of finding significant results.
Throughout this entire part, we assume that the announcements incorporated in our regressions include all relevant announcements concerning the non-standard measures. Moreover, we assume that the effects of the announcements within the time-window are completely attributable to these announcements.
Last, one should bear in mind the inherent endogeneity of the monetary policy responses to market conditions.
- 56 -
4 THE EFFECTIVENESS OF THE NON -STANDARD MEASURES : THE FEDERAL RESERVE
In this chapter, we will examine the effectiveness of the non-standard measures of the Fed that were described in part 1. In section 4.1 we will take a look at the interbank market and the non-standard measures that were intended to relieve the strains in this market, namely the TAF, the TSLF and the PDCF. The commercial paper market and its measures, the AMLF and the CPFF, will be discussed in section 4.2. Third, in section 4.4, the asset-backed securities market with the AMLF will be disentangled. Last, we will take a look at the Treasury market and which influence the LSAP has had in this market. In each section, we will first take a look at how markets responded to the crisis and to the introduction of the measures. Thereafter, we will shortly describe the data that is used in the regressions. Last, the results will be presented and an interpretation on the effectiveness of the measures will be made.
4.1 Interbank market
4.1.1 Market response
As discussed in 2.1.2, the interbank market in the US is less substantial than in the euro area. Nevertheless, in the pre-Lehman period this is the market upon which the Fed put its focus as this market is the focal point of the traditional monetary policy. In the following, we will take a look at how this interbank market responded to the crisis and to the measures introduced with the purpose of relieving the strains in this market. For this purpose we will take a look at the Libor-OIS spread, which is plotted in Figure 8, as this spread serves as a barometer for stress in the money market (Sengupta and Tam 2008).
When agitation first arose in August 2008, the Fed eased conditions by lowering the target rate and by providing supplementary liquidity in addition to its regular operations. Moreover, on August 17 th , the Fed reduced the spread of the primary discount rate to the Federal Funds target rate and it lengthened the maturity of loans granted at the discount
- 57 - window. The combination of this set of actions could have been responsible for stopping the mounting trend of the spread at the beginning of September 2007. However, the decreasing trend of the spread that followed was short-lived. At the end of October, the Fed
Figure 8: Libor-OIS spread and amount of TAF loans outstanding Source: Datastream, Federal Reserve, authors’ calculations saw the spread curbing and reaching an even higher peak at the beginning of December. The decision to introduce the TAF and the swap lines on December 12 seemed appropriate, as after the announcement, we see the spread drop. Although no sound conclusions can be made based on this graph, this could be a first indication of the effectiveness of the facility.
However, also this time, the low levels of the Libor-OIS spread were granted a short life. The tumult round Bear Sterns in March 2008 initiated a third peak. At the same time, both the TSLF and the PDCF were announced. Albeit we cannot observe a reverse in the increasing trend, the turbulence in this period makes a judgement about these facilities difficult, as it is impossible to discover how the counterfactual would have looked like. However, we do not expect these facilities to have an as large impact on the spread as the TAF, due to their relative small size. With the failure of the Lehman Brothers in September 2008, the spread dwarfed the prevailing levels. In Figure 8 we can see that the Federal Reserve increased its amount of - 58 - liquidity provided in the Term Auction Facility after the skyrocketing of the spreads in September 2008. As normality restored gradually after this peak, this facility could have helped soothing the interbank market. We will investigate econometrically whether or not these three facilities have been successful in combating the crisis.
4.1.2 Data
As described above (cf. section 3.2.1), the TAF, the PDCF and the TSLF were initiated to support the functioning of the money market, and therefore operate as complements to interest rate cuts (Lenza, Pill et al. 2010). These non-standard measures attempted to improve the effectiveness of conventional monetary policy. Therefore, their effect can be measured by using the Libor-OIS spread as dependent variable, because reducing this spread ensures that money market interest rate decisions (standard measures) are transmitted to longer-maturity market rates and thus the real economy. This spread is also used in many other studies that measure the impact of the TAF (McAndrews, Sarkar et al. 2008; Wu 2008; Lenza, Pill et al. 2010). Analogously with this literature, we use the spread with a 3-month maturity in our regressions 50 because the 3-month Libor forms the basis for the rates of a wide variety of loans and securities, ranging from home mortgages to business loans. However, the Libor with a 1-month maturity will be applied to test the robustness of the regressions. The 3-month OIS-rate closely matches the average of the expected overnight interest rate over the contract maturity, and therefore, the 3-month OIS is a good measure for the 3-month interest rate expectations. Deducting the OIS rate from the Libor thus corrects for any expected changes in overnight rates 51 . As no principal, and only the difference in interest rates is exchanged in such a contract, and because the OIS market is very liquid, OIS transactions involve very little credit and liquidity risk. The remaining spread is therefore the premium banks pay when they borrow funds with a 3-month maturity, relative to the expected cost from repeatedly rolling over that funding in the overnight market (Gorton and Metrick 2009). This premium exists of both a liquidity risk
50 McAndrews, Sarkar et al. (2008) notices that there is a suspicion that banks in the LIBOR-panel may have underreported their borrowing costs during the period of recent credit crunch. However, the authors point out that this doesn’t cause problems for the regressions. For more detail, we refer to McAndrews, Sarkar et al. (2008) 51 Mathematically the Libor-OIS spread is calculated as Y t = LIBOR t+1 – OIS t, as the Libor is published daily by 11 AM (London time)and therefore contains information about the previous day - 59 - and a credit risk compensation 52 . Various authors that performed research about the effectiveness of the Term Auction Facility do not seem to agree which of both the TAF has influenced. While Wu (2008) is convinced that the TAF could have influenced both credit and liquidity risk premiums, McAndrews, Sarkar et al. (2008) and Christensen, Lopez et al. (2009) are of the opinion that the TAF should only influence the liquidity risk premium. In contrast, Taylor and Williams (2008) take the view that only the credit risk premium should be impacted. Although both liquidity risk and default risk lead to an increased unwillingness to lend and to a rise in borrowing costs, it is interesting to make a distinction in these premiums. In this study, we take the view of Wu(2008) and we will test the impact of the TAF both on liquidity risk and credit risk premiums.
A set of variables is constructed to capture the impact of the TAF, the PDCF and the TSLF. For a first series of regressions, which will solely measure the announcement effect, three variables, to account for the announcement of the TAF on December 12, 2007 (TAF INITIAL ), the PDCF on March 11, 2008 (PDCF INITIAL ) and the TSLF on March 16, 2008 (TSLF INITIAL ) respectively, are created with the methodology earlier described (see above, p. 55). For a second series of more elaborate regressions, we create a set of variables applying a similar methodology as McAndrews, Sarkar et al. (2008). For the TAF, six variables are created. A first variable is set to one on each day an important general announcement concerning the
TAF was made, and to zero otherwise (TAF GENERAL ). A second variable is set to one each day an operation-related announcement was made and to zero otherwise (TAF OPERATION ). Furthermore, three variables are created that go into more detail on these operation- related announcements. These variables are set to one on each day an announcement is made concerning the auction conditions (TAF CONDITION ), the auction execution (TAF AUCTION ) and the results of the auction (TAF NOTIFICATION ) respectively, and to zero otherwise 53 . These announcements can reduce the uncertainty that banks face regarding their expected liquidity needs and can put the banks’ mind at rest about the distribution of the funds
52 Schwarz (2009) estimates that two-thirds of the spread increase in the money market is due to liquidity risk and the remaining third due to counterparty risk 53 Settlement dates and dates on which the loans end are not included in any variable because in efficient markets there should be no reaction on these days as all information has been announced previously.
- 60 - allocated in the auction. Therefore they can influence the liquidity risk, and thus the Libor- OIS spread. Last, a variable that is composed of the amounts of TAF loans outstanding is created. To depict the PDCF, we create PDCF GENERAL which is set to 1 on each day a general announcement is made. A second variable is PDCF OPERATIONS , which is a variable that is set to 1 each Thursday, as then a weekly report on the loans under the PDCF was published.
For the TSLF we compose two variables. TSLF GENERAL is set to 1 on each day a general announcement is made. TSLF COND is set to one on each day conditions for a TSLF auctions were announced. TSLF OPERATIONS is set to one on each day an operation-specific announcement was made. Last, we create a variable that is set to one on each day a general announcements on the swap lines between the Federal Reserve and the European Central Bank is made, as these are part of the TAF program.
Next to these independent variables, we also create a set of control variables. First, we set up a variable to control for the credit risk premium in the spread. Ideally, a Credit Default Swap index for the banking sector would be used. However, due to the restricted time- period for which we have this variable available, we instead use the first-differences of the
54 55 CDS of the Bank of America (CDS BOA ), as in Taylor and Williams (2008) , . Furthermore, we create a variable to represent the uncertainty in the stock market, as changes in this uncertainty may cause changes in credit risk premiums and therefore may also cause the Libor to change . For this purpose, we use the Chicago Board of Options Exchange Volatility Index (CBOEVIX), which is a measure of implied volatility in the S&P 500 index (SPX). Moreover, a variable is created which is composed of the changes in the Merrill Lynch Option Volatility Estimate (MOVE) index. This variable is comparable to the VIX-index, but is a measure of implied volatility of Treasury options. Last, a variable that controls for the general state of the banking system is included (S&P BANKS ). This variable is composed of the changes in the variable S&P Banks. Furthermore, we include a control variable for quarter ends. Typically short-term interest rates spike on quarter ends, as institutions have to report their balance sheets. Analogously with McAndrews, Sarkar et al. (2008), the
54 In addition, Taylor and Williams (2008) also use the CDS of Citigroup . 55 Wu (2008) reports that, when replacing his self-created CDS variable by the CDS rates for Bank of America, his estimated TAF coefficient is still significantly negative. This confirms that the CDS of the Bank of America is a decent replacer for the CDS of the banking system. - 61 - variable QENDS is set to 1 from three days before a quarter end and is set back to 0 three days after a quarter end. Last, a variable that controls for the effect of the failure of Lehman Brothers is created. For more information on the variables and the sources of our data, we refer to Exhibit 2.
4.1.3 Econometrical analysis
Literature on the Term Auction Facility is more elaborate than that of other measures undertook by the Federal Reserve. Although most authors seem to agree upon the effectiveness of the TAF, no consensus is reached. McAndrews, Sarkar et al. (2008) identify a cumulative reduction of more than 50 basis points as a result of TAF announcements and operations undertook before April 24, 2008. Also Wu (2008) reports a strong effect of the TAF in soothing liquidity concerns in the inter-bank money market. Moreover, he finds a less discernible effect of the PDCF and the TSLF in reducing financial strains in the Libor market. He ascribes this to the weaker interest from primary dealers in the TSLF compared with the interest that banks showed for the TAF. Hooper and Slock (2009) find that the announcement effect of the TAF was most important. Furthermore, they do not find a significant impact from the TSLF in narrowing the Libor-OIS spread. Christensen, Lopez et al. (2009) analysed the counterfactual three-month Libor and found that the Libor-OIS spread would have been higher if the Fed wouldn’t have initiated the liquidity operations. In contrast, Taylor and Williams (2008) find that the TAF has neither affected liquidity premiums, expectations of future overnight rates nor counterparty risk premiums. They thus could not detect an impact of the TAF on the Libor-OIS spread. All four studies are performed in a sample that does not include the post-Lehman period.
The TAF could have influenced the Libor-OIS spread in various ways (Wu 2008). First of all, the TAF could have provided an additional source of funding. In the pre-Lehman period, the balance sheet of the Fed did not expand, however, the TAF could have had an impact on the liquidity in the interbank market. Because banks were reluctant to lend to one another, the Fed could have improved liquidity conditions by reallocating liquidity by absorbing liquidity from those banks that had a surplus and by providing funds via the TAF to those banks that had a shortage. This additional funding source could have relieved financial
- 62 - stress. As Wu (2008) notices, the TAF could also have helped in reducing credit risk, as the facility reduced the pressure of banks to liquidate assets at low prices to obtain liquidity. Moreover, the premium that investors demand for a unit of credit risk could have declined due to an increase in confidence that arose because of the introduction of the facility. Finally, banks could have been less eager to hoard liquidity out of precaution as the TAF provided them with a certain, anonymous source of liquidity, and therefore the premium they demanded for lending their liquidity for a longer period of time could have reduced. As the TAF is a liquidity measure, the impact of the TAF on the liquidity risk premium should be considerable. Therefore, we will first test the impact of the TAF on this premium. Later, we will measure the impact of the TAF on the credit risk premium.
To test the effectiveness of the Term Auction Facility on the liquidity risk premium of the Libor-OIS spread with a 3-month maturity, we perform two series of regressions. A first series measures solely the announcement effect. A first regression is the following:
Δ ∑ _ Δ (1) with Yt = LIBOR 3M – OIS 3M . TAF WINDOW_i is the set of dummy variables within the time window around the initial TAF announcement, as described earlier (see above, p. 55). For the specific composition of these dummies, we refer to Exhibit 2. We include the lag of the dependent variable as control variable in case the change in the spread is dependent on its level. The changes in the CDS rates are included to control for credit risk. Therefore, this regression tests the impact of the TAF on the liquidity risk premium. We would expect the initial announcement to have a significant negative impact.
The results of this regression are displayed in Table 1. As expected, the changes in CDS seem to be significantly positive, thereby confirming that credit risk contributes to the Libor-OIS spread. The results confirm a significant negative impact of the initial
- 63 - announcement of the TAF, amounting 5 basis points on the day of the announcement 56 . Moreover, as expected, we find a noticeable lagged response 57 of around 10 basis points. Furthermore, in contrast in our prospects, we also see a significant anticipation effect of about 8 basis points. However, this effect could be attributed to information that was revealed at a speech of Bernanke at November 29, 2007, or a testimony from Kroszner at December 6, 2007 58 . Both state that the Federal Reserve was exceptionally alert and flexible, and actively working to respond to the challenges that had manifested since August 2007.
To test the robustness of these results, we perform the following regression:
Δ _ Δ ∆
∆ & (2) with the variables defined as described in section 4.1.2.
The results are shown in Table 1. The announcement effect of the TAF remains significant at the 1% level. The VIX variable shows significance, but this seems to come at the expense of the CDS variable. Both variables are risk-indicators. Apparently, during the financial crisis, the effect of the implied volatility in the S&P 500 index on the Libor-OIS spread seems to dominate over the impact of the CDS. As another test for the robustness of our results, we have performed regression (2) with longer and shorter time windows around the initial TAF announcement and comparable results were found.
In the previous regressions we have not controlled for the impact of the PDCF and the TSLF. It is very difficult to separate the impact of these two facilities, as they were announced
56 As part of the TAF program, also the swap arrangements between the Federal Reserve and other central banks were announced. The impact of the TAF variables therefore includes the impact of both announcements. 57 To calculate the anticipation and lagged effects we take the sum of the significant coefficients in the window. 58 This testimony can be found on
Δ _
_ _
Δ ∆ ∆ &
(3) with the variables defined as described in section 4.1.2. We would expect the announcement of the PDCF and the TSLF to have a significant negative impact.
The results are displayed in Table 1. For the TSLF, these expectations are confirmed and, in contrast to Wu (2008), a significant negative impact of around 12 basis points can be found. Moreover, a significant lagged effect of around 17 basis points can be noticed. However, due to the overlap of the time windows of the TSLF and the PDCF variable, this coefficient has to be taken with a pinch of salt, as it could partially include an anticipation effect for the PDCF. The impact of the initial announcement of the PDCF should be displayed in the estimates for the lagged response, as the initial announcement took place on a Sunday and weekends are excluded from our dataset. However, a significant positive effect can be found in the three days after the PDCF announcement, signalling that this announcement has not been effective in lowering the Libor-OIS spread. These results of the announcements of the TSLF and the PDCF must be interpreted with care. Given the very turbulent period around Bear Stearns, we cannot ascertain that our estimates do not include the effect of other events. Moreover, when we go back to Figure 8, we notice that the declines after the initial announcement are only short-lived.
- 65 -
Dependent variable First differences of LIBOR-OIS spread (3 month maturity) Regression model (1) (2) (3) DayAnt. Lag Day Ant. LagDay Ant. Lag Independent variables Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Intercept C 0.14 0.31 0.05 0.12 0.04 0.10 Lag of LIBOR-OIS spread LAG_SPREAD -0.36 -0.31 -0.42 -0.38 -0.39 -0.36 Lehman LEHMAN 12.57 2.96 *** 12.83 3.15 *** 12.95 3.17 *** First differences of CDS ∆CDS_BOA 0.08 2.79 *** 0.04 1.50 0.03 1.13 First differences of VIX ∆CBOEVIX 0.30 2.39 ** 0.31 2.50 ** First differences of S&P Banks ∆S&P_BANKS -0.06 -1.41 -0.05 -1.14 Quarter ends Q_ENDS 1.19 1.49 1.20 1.49 Term Auction Facility Initial announcement TAF_INITIAL -5.01 -8.02 *** -8.31 -9.55 -5.09 -6.88 *** -9.55 -9.71 -5.05 -6.74 *** -9.77 -9.61 Term Securities Lending Facility Initial announcement TSLF_INITIAL -11.70 -14.05 *** 4.90 -16.96 Primary Dealer Credit Facility Initial announcement PDCF_INITIAL - - 24.54 Adjusted R² 7% 7% 7% 11% 11% 11% 19% 19% 19%
Table 1: Announcement effects of the TAF, the PDCF and the TSLF on the Libor-OIS spread (a) Note that, consistent with the methodology that McAndrews, Sarkar et al. apply, we use the changes in the dependent variable. If we would use levels, than we would assume that the spread decreases on an announcement day, but than returns to its previous level immediately after. When we would use the level of the Libor-OIS spread in combination with a TAF variable that is a step function, we would assume the impact of the TAF to be permanent. It is clear that both assumptions are unrealistic. Moreover, we have found that the level of Libor-OIS has unit root. (b) Although the term premium component of the 3-month Libor is believed to be small 59, it is important to create a variable to control for this premium in the regressions. We used the changes in the 3-year term premium based on Kim and Wright (2005), as made available by the Federal Reserve Board 60. However, this variable was insignificant in all regressions and the null hypothesis of the omitted variables test could not be rejected. (c) Ant. Est = Anticipation effect estimate = sum of the significant estimates in the time window before the announcement. Lag Est = Lagged effect estimate = sum of the significant estimates in the time window after the announcement (d) The results are expressed in basis points (e) Newey-West standard errors (d) The time window overlap between TSLF and PDCF is displayed in the lagged effect estimate of the TSLF (d) In regression model (3) the estimates for the PDCF are empty for the initial announcement as this was a Sunday. The impact of the TSLF should thus be interpreted by looking at the lagged effect estimate. (e) * significant at 10%; ** significant at 5%; *** significant at 1%.
59 Michaud and Upper (2008) 60 The data can be found on
The TAF was initiated in the pre-Lehman period. However, when strains in the interbank market sharply rose with the collapse of Lehman Brothers, the amount of liquidity provided in TAF loans was also increased, as can be seen in Figure 8 (see above, p. 58). Therefore, the impact of the TAF cannot be captured by solely looking at the announcement effect. To measure the effect of the TAF throughout its entire life cycle, we perform a second set of regressions.
First, the following regression is performed:
Δ Δ (4) Because announcements and operations can have a different effect, we include both variables separately. As described earlier (see above, p. 55), normally we do not expect any effect from the implementation of the program. However, given the heightened amounts of liquidity provided after Lehman Brothers, in these regressions we would expect the announcements on the operations to show a significant negative impact on the Libor-OIS spread.
The results of this regression are displayed in Table 2. In contrast to our previous set of regressions, the announcement effect is not validated. However, in these regressions the announcement variable includes all general announcements over the life-time of the TAF, in contrast to only including the initial announcement as in the previous regressions. Therefore we can conclude that, although the initial announcement was effective, the whole set of general announcements wasn’t. However, we can find a significant negative impact of the TAF operation-related announcements at a 10% significance level. This confirms our expectations that, due to the considerable changes in the amounts of liquidity provided in TAF loans, the announcements on the TAF operations revealed supplementary information to the market. A cumulative effect 61 of around 107 basis points is found. However, as stated
61 The cumulative effect is calculated by multiplying the coefficient of the variable with the sum of the values of this variable. For more information, and for the drawbacks of such methodology, we refer to McAndrews, Sarkar et al. (2008) - 67 - by McAndrews, Sarkar et al. (2008), these estimations only have an illustrating purpose and therefore should be interpreted carefully. When we compare this cumulative effect with the cumulative increase as result of the failure of Lehman Brothers with around 63 basis points, the effect of the TAF seems relatively large. However, the cumulative effect of Lehman Brothers represents the average increase in the Libor-OIS spread within a two-day time- window around the announcement. As the Libor-OIS spread reaches its peak later, in the beginning of October 2008, these huge increases are not incorporated in this variable. However, also in comparison with the largest value of the spread of around 350 basis points in the beginning of October, a decrease of around 107 basis points is quite considerable, thereby confirming the effectiveness of the TAF in reducing the Libor-OIS spread.
Next, the set of control variables is added to test the robustness of these results:
Δ Δ ∆ ∆ &
` (5) The results are displayed in Table 2 and comparable results are found, confirming the robustness of our model.
To test which of the announcements on the operations of the TAF have been especially significant, we perform the following regression, in which we refine our operation-related announcement variable in three more specific variables which were described in section 4.1.2:
Δ
Δ ∆ ∆ & (6) The results of this regression are displayed in Table 2. We again find similar results as the previous regressions and find that only the announcements on the conditions of the TAF auctions seem to have had a significant negative impact, with a cumulative effect of 160 basis points. These findings are in line with the results of McAndrews, Sarkar et al. (2008) - 68 - as a similar impact of the announcements of the TAF auction conditions are discovered in the pre-Lehman period. However, McAndrews, Sarkar et al. (2008) also find a significant negative impact of the general announcement variable. These contrary results could be due to the shorter sample in which the regressions are performed, as the collapse of Lehman Brothers and thus the second phase of the TAF facility are not included.
Next, as in our first set of regressions, the variables with the general announcements of the PDCF, the TSLF and the swap lines are added to regression (5):
Δ
Δ ∆ ∆ &
(7) The results of this regression can be found in Table 2. None of the added variables seems to have a significant impact in relieving strains in the Libor-OIS spread. However in our previous set of regressions a significant impact of the initial announcement of the TSLF could be found. This effect stays away in the results of this regression. This confirms what we had expected when looking at Figure 8, namely that this impact was short-lived. These results are in line with various other authors that could not find a significant impact of the TSLF and the PDCF in the pre-Lehman period (Wu 2008; Hooper and Slock 2009). Wu (2008) ascribes this to the weaker interest from primary dealers in the TSLF compared with the interest that banks showed for the TAF. We also performed regression (7) with the
PDCF OPERATIONS and TSLF OPERATIONS variables. Again, we could not find a significant effect. The results are not displayed in the table.
As the impact of the operation-related operations seems to be significantly negative in every of the previous regressions, we perform a regression with the variable that accounts for the amount of TAF loans outstanding as independent variable to take a further look at the TAF operations. However, as stated when describing our methodology (see above, p. 55), we would not expect a significant effect of these operations, as all information is
- 69 - already provided in the operation-related announcements. We will perform the following regression:
Δ Δ
∆ ∆ & ` (8) The results are displayed in Table 2 and bear out our expectations that the amount of TAF loans outstanding would not have a significant impact on the Libor-OIS spread, as the announcements on the operations reveal all relevant information. In effect, the impact of the operation-related announcements remains significant in this regression and, therefore, again confirms the robustness of our results.
The previous regressions measured the impact of the TAF on the liquidity risk premium in the Libor-OIS spread. As Wu (2008) notices, the TAF could also help to reduce the credit risk premium. Therefore we perform a regression on the changes in the CDS rates, as these are a proxy for credit risk:
∆
SWAPS ∆ ∆ & ∆
(9) The results are displayed in Table 2. None of the variables shows a significant effect. Therefore, we can conclude that the TAF has only been effective in reducing the liquidity premium part of the Libor–OIS spread. These results are in line with the results of Wu (2008) and confirm the vision of McAndrews, Sarkar et al. (2008) and Christensen, Lopez et al. (2009) that the TAF should only influence the liquidity risk premium.
- 70 -
Dependent variable First differences of LIBOR-OIS spread First differences of CDS index Regression model (4) (5) (6) (7) (8) (9) Independent variables NOT Est. t-stat Est. t-stat Est. t-stat Est. t-stat Est. t-stat Est. t-stat Intercept C 0.19 0.41 0.10 0.21 0.09 0.19 0.11 0.25 0.10 0.22 127.82 1.88 Lag of LIBOR-OIS spread LAG_SPREAD -0.34 -0.30 -0.40 -0.38 -0.41 -0.38 -0.43 -0.41 -0.42 -0.38 Lehman LEHMAN 12.51 2.95 *** 12.74 3.13 *** 12.76 3.13 *** 13.44 3.27 *** 12.79 3.15 *** First differences of CDS ∆CDS 0.08 2.78 *** 0.04 1.56 0.04 1.56 0.04 1.53 0.04 1.56 First differences of VIX ∆CDS 0.30 2.43 ** 0.30 2.48 ** 0.29 2.39 ** 0.30 2.42 ** -17.05 -0.22 First differences of S&P Banks ∆S&P_BANKS -0.05 -1.23 -0.05 -1.28 -0.05 -1.19 -0.05 -1.20 Quarter ends Q_ENDS 1.00 1.50 1.16 1.51 1.00 1.55 1.16 1.50 First differences of Move index ∆MOVE -38.49 -1.39 Lag of CDS index LAG_CDS -1.06 -1.28 Term Auction Facility General announcements TAF_GEN 1.45 1.01 1.15 1.04 1.11 1.01 0.72 0.78 1.17 1.05 34.94 0.22 Operation-related announcement TAF_OPERATIONS -0.87 -1.89 * -0.73 -1.78 * -0.69 -1.67 * -0.73 -1.77 * -38.40 -0.32 Conditions TAF_CONDITIONS -2.67 -1.90 * Auctions TAF_AUCTIONS 1.75 1.25 Notification TAF_NOTIFICATIONS -0.41 -0.56 First differences TAF outstanding ∆TAF_OUTSTANDING 0.00 0.33 Term Securities Lending Facility General announcements TSLF_GEN -2.09 -1.28 417.67 0.72 Primary Dealer Credit Facility General announcements PDCF_GEN 0.73 0.26 -114.42 -0.39 Swap lines General announcements SWAP_GEN 1.82 0.66 -232.80 -0.52 Adjusted R² 8% 11% 11% 11% 7% 4% Estimates of cumulative effects ( of the significant variables at a 10 % significance level) Independent variables NOT Est. St. Err. Est. St. Err Est. St. Err Est. St. Err Est. St. Erd Lehman LEHMAN 62.55 14.73 63.72 15.63 63.78 15.65 67.18 16.36 63.94 15.73 Term Auction Facility Operation-related announcement TAF_OPERATIONS -107.17 56.60 -89.57 50.28 -85.09 51.03 Conditions TAF_CONDITIONS -160.31 84.40 -89.24 -100.05 Table 2: Extended regressions of the TAF, the PDCF and the TSLF on the Libor-OIS spread (a) Although the term premium component of the 3-month Libor is believed to be small 62, it is important to create a variable to control for this premium in the regressions. We used the changes in the 3-year term premium based on Kim and Wright (2005), as made available by the Federal Reserve Board 63. However, this variable was insignificant in all regressions and the null hypothesis of the omitted variables test could not be rejected. (b) The results are expressed in basis points (c) Newey-West standard errors (d) * significant at 10%; ** significant at 5%; *** significant at 1%.
62 Michaud and Upper (2008) 63 The data can be found on
As a last test for the robustness of our results, we performed the same regressions on the total spread between three-month Libor and three-month OIS, thus without controlling for the credit risk, because possibly credit premiums and liquidity premiums are correlated 64 . Again we obtain significant negative effects of TAF operation-related variables. The results are not displayed in the table. We also performed all-above regressions on the spread between the 1-month Libor and the 1-month OIS. We obtained very comparable results. This again confirms the robustness of these regressions.
From all above results we can conclude that the TAF has been effective in reducing the liquidity premium in the Libor-OIS spread. Next to a significant effect of the initial announcement of the TAF, also the operation-related announcements were found to be effective in soothing the financial turmoil. This can be explained by the fact that after the collapse of Lehman Brothers, the TAF evolved into a second phase and increased its amounts of TAF loans considerably. Such increases were made public via announcements on the conditions of the TAF auctions. Therefore, these announcements revealed new information to the market. Our results confirm that, in effect, these announcements on the conditions of TAF loans in particular have had a significant negative impact on the liquidity premium. Our findings are in line with the results of many authors that have examined the effectiveness of the TAF in the pre-Lehman period and who found a significant impact of the TAF in relieving financial strains in the interbank market (McAndrews, Sarkar et al. 2008; Wu 2008; Christensen, Lopez et al. 2009; Hooper and Slock 2009). Furthermore, our results suggest that the PDCF and the TSLF have not been effective in reducing the Libor- OIS spread.
64 For example Sarkar (2009) and Abbassi and Linzert (2011) argue that liquidity and credit risk cannot be separated as both measures mutually affect each other - 72 -
4.2 The asset-backed commercial paper market
4.2.1 Market response
The AMLF and its rationale were described in paragraph 3.2.2.1. In this part, we will take a first look at the response of the asset-backed commercial paper market to the introduction of the AMLF. In Figure 9, we illustrate the spread between Asset-Backed and Financial Commercial Paper yields of outstanding paper. Since this facility is only targeting asset- backed commercial paper, this spread should visualize the impact of the AMLF, while cancelling out general movements in the commercial paper market. Such a general movement could for example be the result of the temporary insurance offered by the Treasury Department to existing balances on MMMFs, and thus including both asset-backed and financial commercial paper, which was also announced on September 19, 2008.
Figure 9: Amount of AMLF loans outstanding Source: Federal Reserve, authors’ calculations
As in many other financial markets, the strains in the asset-backed commercial paper market started around the period of the Lehman Brothers’ failure. As described in paragraph 3.2.2.1, money market mutual funds, which are the main investors of (asset- backed) commercial paper, experienced heavy redemptions after September 15 th , which lead to the drying up of the commercial paper market. However, on September 19 th , the
- 73 -
AMLF was announced. In Figure 9, we can see that in the days after the announcement, overnight spreads started to drop, signalling a clear announcement effect. Whether this decline was significant, will be tested in paragraph 4.2.3. The amount of AMLF loans granted to depository institutions kept on rising, reaching an absolute peak on October 1 st 2008, while the spread continued to decline. Although no sound conclusions can be drawn from a graph, this figure insinuates that the AMLF helped the overnight asset-backed commercial paper market to restore to liquidity. The more spreads returned to normality, the less the facility was used. Although the decline was set in immediately after the announcement and implementation of the AMLF, it took until January 2009 for the spreads to return to pre-Lehman levels.
Furthermore, on October 7 th , the CPFF was announced. Although this facility focuses both on asset-backed commercial paper as on financial commercial paper, the spread between asset-backed and financial commercial paper seems to decline following the announcement. This signals that also the CPFF could have helped in reducing the spread.
In Figure 9, we see that the spread between asset-backed and financial commercial paper has been reduced from 300 basis points prior to the introduction of AMLF and CPFF, towards somewhere between 10 and 20 basis points at the end of 2009. Therefore, we would expect that the measures of the Fed have helped to return the spread between overnight asset-backed and financial commercial paper to normality.
The effect on longer maturities is less pronounced, as can be seen in Figure 10. Although we see a decline after the announcement on September 19 th , this decrease is short-lived and turbulence in the spread is observable. From mid-September till mid-October, longer-term yields seem to increase. We expect that such delay was a result of the fact that the announcement of the AMLF did not restore liquidity and trust immediately, rather than the AMLF being ineffective in reducing the spreads on these maturities. This is in line with the results of Duygan-Bump, Parkinson et al. 2010, who notices that money funds only resumed purchases of ABCP after redemptions subsided. Adrian, Kimbrough et al. (2010) notice that, after the Reserve Primary Fund broke the buck on September 16th , money - 74 - market investors allocated their investments to funds that solely held government securities, at the expense of those allocated to prime money market funds. This flight to quality of investors made 2a-7 money market mutual funds unwilling or even unable to purchase commercial paper, especially on the longer-term. The flight to quality after September 16 th and the gradual reallocation of investments towards prime money market funds, which Adrian, Kimbrough et al. (2010) notice from October 21 st on , could therefore also help to understand the delay in reaction of longer-term commercial paper to the introduction of the facilities of the Federal Reserve.
Figure 10 Spreads between asset-backed and financial commercial paper (overnight, 1-month and 3-month maturities) Source: Federal Reserve, authors’ calculations
Moreover, when we behold the evolution of the asset-backed and financial commercial paper rates separately (figure not included), we notice a delay in increase of both asset- backed and financial commercial paper compared with their overnight counterpart after the collapse of Lehman Brothers. This could be caused by the fact that longer-term rates do not begin to increase until the market expects the turmoil to be of a more persistent
- 75 - duration 65 . A similar mechanism could have been in effect when overnight rates began to decrease. This could therefore also help to explain the delayed decrease in the spread on longer-maturities when compared to the overnight spreads.
4.2.2 Data
Before testing whether the above-illustrated impact of the AMLF is significant, we first describe the data we will use in the regressions. For the dependent variable we use the spread between secured (asset-backed) and unsecured (financial) rates of commercial paper at the overnight, 1-month and 3-month maturity. This spread is used from the point of view that the AMLF was only focused on asset-backed commercial paper. Influences on the commercial paper market in general are cancelled out by taking this spread. For example, as the temporary guarantee, that the Treasury Department announced on September 19th, the same day the AMLF was announced, should have an impact on both asset-backed as financial commercial paper, the spread should not be influenced by this. For similar reasons, we use the rates of A2P2 commercial paper instead of financial commercial paper to test the robustness of our regressions. It would be more correct to take the spread between asset-backed commercial paper and unsecured commercial paper issued by its own sponsor as these are from similar credit quality, and therefore we would be able to control for the CDS of this sponsor (Bump (2010)). However, as we do not dispose of this micro-data, we content ourselves by plotting the average rates. This simplification can lead to an underestimation of our results. Moreover, due to this lack of micro data, we cannot control for the CDS of each sponsor individually either. We had the intention to create a CDS index including the CDS of several sponsors of asset-backed commercial paper. Unfortunately, we do not dispose over this data either and therefore we cannot control for this possible impact. However, the results from Bump(2010) comfort us as the CDS per sponsor is insignificant in the majority of their regressions.
The effect of the AMLF will be measured by creating a series of dummy-variables based on the methodology earlier described (see above, p. 55). Moreover, we introduce variables to
65 Cfr. the weak form of the expectation hypothesis of the term structure which states that there is an equality between current longer-term rates and the average expected overnight rate plus a constant maturity specific risk premium (Hamilton and Kim 2002) - 76 - control for the impact of Lehman Brothers’ failure and for the turbulent quarter-end in September.
Ideally, we should have to be able to distinct the impact on asset-backed commercial paper that was perceived as potential collateral for the facility and from ABCP that was not (Bump 2010). However, the lack of micro-data prevents us from accounting for this factor. This could lead to a further underestimation of the impact of the AMLF in our regressions, as rates of asset-backed commercial paper that was not eligible for the facility are also included in the rate as calculated by the Federal Reserve.
More information on these data and their source can be found in Exhibit 3.
4.2.3 Econometrical analysis
Literature on the effectiveness of the AMLF is very scarce. Duygan-Bump, Parkinson et al. (2010) discuss various aspects of the impact of the AMLF. The authors rely heavily on micro-data in the design of their analysis. They find that the AMLF helped to stabilize net asset flows to mutual money market funds. Moreover, the authors perform a regression on the spread between overnight asset-backed and financial commercial paper from the same sponsor and notice a significant improve in liquidity, with a 78 basis points decrease in the overnight spread as a result. Furthermore, they observe that money funds resumed ABCP purchases once redemptions had subsided.
To test whether the effect of the announcement of the AMLF on the overnight spread between asset-backed and financial commercial paper is significant, we perform the following regression, in which we assume that the change in the spread between asset- backed and financial commercial paper is linearly associated with the variables representing the measures of the Fed:
∆
(1)
- 77 - with Y t = . The lag of the asset-backed CP – financial CP overnight spread is included as a control variable in case the change of the spread depends on its level. Moreover, we incorporate a set of dummy variables representing the end of the third quarter in September 2008 as the search for liquidity at the end of a quarter could have an upwards effects on commercial paper rates and thus on the spread between asset-backed and financial commercial paper. The other variables are composed as defined in paragraph 4.2.2 and Exhibit 3.
Based on the description in paragraph 4.2.1, and assuming that the announcement of the AMLF had an immediate effect on the overnight asset-backed commercial paper rate, we would expect coefficients of the AMLF variable to be significantly negative throughout the regressions performed in this paragraph. Moreover, effects of the CPFF would be expected to have a less discernable effect. In contrast, we do not expect the initial operation to have a significant negative impact as most of the information concerning the AMLF program was already incorporated in the initial announcement.
The results of regression (1) can be found in Table 3. When taking a glance at these results, we do not find a significant negative impact on the day of the announcement of the AMLF. However, we do find a significant negative lagged response after the announcement on September 19 th , for which the reasons are explained in paragraph 4.2.1. . Moreover, when taking a look at the CPFF, we see a large significant increase on the day of the announcement. This could be explained by a difference in impact on both the asset-backed and financial commercial paper rates. Moreover, on October 8 th , the Federal Funds rate was lowered from 2 to 1.50 per cent, which could also have influenced this spread 66 .
To examine the possible impact of the initial operations of both measures, we perform regression (2a). Furthermore, to test the robustness of the time window, we expand our range of dummy variables as long as possible so that it would not interfere with other variables, as this would result in multi-collinearity (2b).
66 Due to reasons of multi-collinearity we cannot add a regressor to control for this impact. - 78 -
∆
(2) with Y t = . The results of both regressions can be found in Table 3. When comparing both regressions, we find similar which provides us with evidence in favor of the robustness of our time window.
Table 3 confirms our expectations about the AMLF having a significant negative impact on the ABCP Financial CP spread. Although the impact on the day of the announcement of the AMLF is not significant, we do find a significant negative impact on the day of the first operation which indicates that the change of the spread is significantly more negative in this period than in other time periods. However, as the first operation takes place immediately after the announcement of the AMLF, it is very difficult to distinguish the effect of both events. As we expect that most of the impact of the AMLF occurs at the initial announcement, we contribute this significant negative impact to the initial announcement rather than to the first operation. The results indicate a total decrease of 54 basis points in the spread between asset-backed and financial commercial paper between September 22 th and September 26 th . As expected, we find less discernible effects of the CPFF. Although the announcement and the implementation of the AMLF seem to have a significant negative effect on the spread between asset-backed and financial commercial paper, this effect is relatively small when it is compared to the considerable rise of the spread caused by the
th failure of Lehman Brothers, amounting 158 basis points on September 15 , 2008. This verifies our expectations that the recovery began immediately after the announcement and implementation of the AMLF, but that the spread did not fall promptly to its pre-Lehman level.
- 79 -
To compare our results to the outcome in Duygan-Bump, Parkinson et al. (2010), we calculate the impact of the AMLF in the time window between September 19 th and 24 th . This results in a decline of 12 basis points, compared to 78 basis points reported by Duygan-Bump, Parkinson et al. (2010). This illustrates that our results could actually underestimate the impact of the AMLF, due to the reasons described in the previous section (cf. paragraph 4.2.2. ).
To further check the robustness, we performed the same regression on the spread between asset-backed and A2/P2 non-financial commercial paper (regression (3)) . This should result in a similar outcome, with an increase in the spread. As A2/P2 is not included in the AMLF, but is, as the AMLF, impacted by the temporary guarantee of the Treasury Department, initiated on the same day as the AMLF, the change in spread should reflect solely the impact of the AMLF announcement. Table 3 shows the results of this regression and reports a significant increase of the spread after the announcement and implementation of the AMLF, confirming the robustness of our results. Moreover, although one could suggest that the CPFF had a significant negative impact on this spread, we do find a positive lagged response which is relatively higher.
Last, in order to see the impact of this facility on the longer term commercial paper, we perform a similar regression on the spread of asset-backed and financial commercial paper with a maturity of both 1 month and 3 month. The effects on longer-maturity spreads are less pronounced. As can be seen in Table 3, the one-month and three-month spreads do not show a significant decrease on the day of the first announcement. However, when looking at the one-month maturity, we find a significant negative impact on the day of the first operation. However, this decline, as could be seen already from the graph in paragraph 4.2.1, was short-lived and started to increase again soon after. As stated before, this decline could be due to a lagged response of the initial announcement which was announced shortly before. When comparing regression (4) and (5) , we can conclude that the longer the maturity, the more slackened the response. .
- 80 -
Dependent variable First differences of ABCP-FIN CP overnight Regression model (1)* (2a)* (2b)* Day Ant. LagDay Ant. LagDay Ant. Lag Independent variables Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Intercept C 2,32 3,55 *** 2,15 3,46 *** 2,07 3,13 *** Quarter end Q_ENDS 208,03 54,40 *** 67,92 -195,19 207,17 57,51 *** 67,39 -197,10 206,58 52,92 *** 67,01 -198,38 Lehman LEHMAN 157,62 574,79 *** 3,36 115,20 157,60 605,64 *** 3,36 114,33 157,56 582,83 *** 3,33 113,73 Lag of ABCP-FIN CP (overnight) ABCP-FIN(-1) OV -8,65 -3,68 *** -8,11 -3,66 *** -7,75 -3,23 *** Lag of ABCP-A2P2 CP (overnight) A2P2-ABCP(-1) OV Lag of ABCP-FIN CP (1 month) ABCP-FIN(-1) 1M ABCP-FIN(-1) 3M AMLF Initial announcement AMLF_ANNOUNCEMENT 2,68 0,43 38,94 -8,04 1,28 0,22 37,52 0,33 0,05 36,56 Initial operation AMLF_OPERATION -15,34 -2,86 *** -38,10 -16,22 -2,79 *** -47,10 CPFF Initial announcement CPFF_ANNOUNCEMENT 120,40 52,32 *** -0,17 -10,54 119,90 55,34 *** -2,16 -9,84 119,54 50,88 *** -3,56 -11,33 Initial operation CPFF_OPERATION -3,48 -1,94 * 20,56 36,07 -3,78 -1,94 * 19,98 27,28 Adjusted R² 70% 71% 71% Dependent variable First differences of A2P2 - ABCP overnight First differences of ABCP-FIN CP (1 month) First differences of ABCP-FIN CP (3 month) Regression model (3)* (4)* (5)* Day Ant. LagDay Ant. LagDay Ant. Lag Independent variables Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Intercept C 0,41 1,97 ** 3,51 5,44 *** 6,10 3,94 *** Quarter end Q_ENDS -163,29 -109,06 *** -0,32 1,16 81,46 13,64 *** -0,13 -1,62 26,63 5,44 *** -0,45 -0,15 Lehman LEHMAN -22,61 -123,52 *** -0,02 0,26 -9,66 -19,85 *** 0,00 0,35 3,79 3,09 *** -0,09 0,06 Lag of ABCP-Fin. CP (overnight) ABCP-FIN(-1) OV Lag of ABCP-A2P2 CP (overnight) A2P2-ABCP(-1) OV -3,46 -3,13 *** Lag of ABCP-Fin. CP (1 month) ABCP-FIN(-1) 1M -14,78 -4,46 *** Lag of ABCP-Fin. CP (3 month) ABCP-FIN(-1) 3M -14,86 -2,85 *** AMLF Initial announcement AMLF_ANNOUNCEMENT 21,01 61,52 *** 16,20 109,21 74,53 *** 26,30 65,44 9,37 *** -85,57 Initial operation AMLF_OPERATION 48,71 88,67 *** 99,24 -23,42 -4,80 *** -38,56 16,99 13,30 *** 95,72 CPFF Initial announcement CPFF_ANNOUNCEMENT -81,73 -48,85 *** 80,63 147,57 150,67 42,34 *** 96,83 2,32 80,84 86,76 *** 17,65 63,19 Initial operation CPFF_OPERATION 25,86 11,86 *** 7,96 17,04 79,83 67,25 *** -92,14 52,21 133,23 50,42 *** -77,00 41,98 Adjusted R² 56% 45% 25%
Table 3: Asset-backed commercial paper market Notes: (a) Newey-West standard errors are used in regression models signaled with a ()* (b) Ant. Est = Anticipation effect estimate = sum of the significant estimates in the time window before the announcement. (c) Lag Est = Lagged effect estimate = sum of the significant estimates in the time window after the announcement (d) The results are expressed in basis points (e) * significant at 10%; ** significant at 5%; *** significant at 1%.
- 81 -
4.3 The commercial paper market
4.3.1 Market response
Figure 11 plots the spread of different kinds of commercial paper yields over the OIS rate on the three-month maturity. This spread eliminates the risk-free interest rate from the commercial paper rate, and leaves over a risk premium.
Figure 11: 3-month commercial paper rates Source: Federal Reserve, authors’ calculations
In Figure 12, we can see that after the launch of the Commercial Paper Funding Facility on the 7 th of October 2008, the outstanding volume of commercial paper funding immediately skyrocketed which an absolute high of $350 billion by the end of January 2009. Initially, the CPFF was set to expire on April 30, 2009 but as we can see in figure 3, the need for this liquidity measure hadn’t relieved at that time.
Figure 12: Commercial Paper Funding Facility loans outstanding Source: Federal Reserve, authors’ calculations - 82 -
When comparing Figure 11 and Figure 12, we see a similar evolution. The initiation of the CPFF went with significant reductions in the spread between commercial paper yields and the OIS rate (3 month), which gives a first indication about the effectiveness of this facility. Starting from the initiation to the end of December 2008, the financial spread declined from 220 till 20 basis points. The ABCP spread made a similar descent moving from 320 to 70 basis points. In contrast, the A2/P2 CP spread went up with 30 basis points during this period. In general, this spread fluctuated around a value of 500 basis points while other spreads where situated round 200 basis points. In contrast to AA Financial and ABCP, AA A2/P2 commercial paper wasn’t eligible as collateral for the Commercial Paper Liquidity Facility by which the combination of an increase in liquidity and default risk manifested a during longer period of time. This provides us with further signals on the effectiveness of this facility.
Further, in Figure 12, we see that the share of the ABCP to the total outstanding volume of CPFF kept on rising during 2009. Probably, ABCP had more difficulties re-entering the market, as the housing boom and subsequently the bursting bubble lead to heavy deterioration and distrust against asset-backed commercial paper. However, the amount of ABCP at the Federal Reserve started to decline gradually from May 2009, signalling an improvement in the ABCP market which could have been ascribed to changes in capital regulatory requirements and accounting rules (Adrian, Kimbrough et al. 2010).
For the same reasons stated in paragraph 4.2.1, we expect a slower reaction in longer- maturities commercial paper rates relative to overnight rates.
4.3.2 Data
To test whether the announcement of the CPFF had a significant impact on the commercial paper rates, we calculate the spread between commercial paper rates and the Federal Funds rate. This spread gives an indication of the risk premium in the market, as the Federal Funds rate represents the risk-free interest rate. We perform regressions on different maturities (overnight, 1-month and 3-month) and we take the spread of both asset-backed and financial commercial paper over the Federal Funds target rate. As these
- 83 - data are aggregated commercial paper rates, a lot of detail about rates of specific institutions and their respective credit risk is averaged out. However, our average rates do give a general overview of the market, and are therefore useful. The CPFF variables are created as described earlier (see above, p. 55). For more information on the data and their source, we refer to Exhibit 3.
4.3.3 Econometrical analysis
Just as for the AMLF, literature on the CPFF is rather confined and so far, to our knowledge, no econometrical research has been published. Adrian, Kimbrough et al. (2010) however provide some empirical evidence that the CPFF soothed the strains in the commercial paper market. The authors notice that the one-month AA financial commercial paper - OIS spread declined from 188 basis points on October 27 to 38 basis points during the month of December while the ABCP spread declined from 256 basis points to 86.
We first examine the effect of the announcement of the CPFF on the overnight spread between the financial commercial paper and the Federal Funds target rate. For doing so, we perform the following regression, in which we assume that the change in the spread is linearly associated with the variables of the measures of the Fed:
Δ
(1) with Y t = . The variables are composed as defined in paragraph 4.3.2 and Exhibit 7. The control variables are similar to the ones in paragraph 4.2.2. The discussion in the previous section suggests that an immediate significant negative impact of the announcement of the CPFF should be found.
The results can be found in Table 4. At first sight, the results seem to contradict our expectations. On October 7 th , we notice a significant increase of 80 basis points in the spread between overnight financial commercial paper rate and the Federal Funds target rate. However, when looking at the rates separately (figure not illustrated), we see both
- 84 - rates are declining, with the Federal Funds target rate taking a leap of 50 basis points on October 8 th . Therefore the increases in the spread could be the result of an anticipation effect on October 7 th and a slow adaptation of the financial commercial paper rate to the changed Federal Funds target rate on October 8 67 . Due to reasons of multi-collinearity, however, we cannot control for this impact. On the days following,, we do notice a significant decrease in the spread amounting 73 basis points thus resulting in a net decrease of 20 basis points since the announcement of October 8. However, this amount could be overestimating the impact of the CPFF and should be interpreted carefully as, building on assumption that the increase in the spread was caused due to a lagged reaction, part of this decrease probably incorporates an adaptation to the decrease in the Federal Funds target rate. However, the size of the coefficient leads one to suspect that at least part of this decline is the result of the announcement of the CPFF.
Next, to examine the impact of the first operation of the CPFF, we perform the following regression in which we include the operation variables.
∆
(2) with Y t = . The variables are composed as defined in Exhibit 7. As described earlier (see above, p.55), we would not expect a significant impact of the operations. The results can be found in Table 4. According to our expectations, we see that the first operation does not impact the spread in significant way.
To check the robustness of our results, we performed the same regressions on the spread between overnight A2P2 non-financial commercial paper rates and overnight financial commercial paper. This allows us to correct for the limitations of the previous regressions
67 Abbassi and Linzert (2011) notice a higher persistence of the Euribor, a more lasting impact of shocks in the expected short-term interest path and a lower predictability of Euribor rates on basis of market expectations of future overnight rates (an anticipated policy rate of 25 basis points was accompanied by a contemporaneous increase of the 3M Euribor with 3 basis points during the crisis period.) These results are for the European interbank market, nevertheless, we suspect similar mechanisms to be active here. - 85 - as we filter the impact of the delayed adaptation to the lowering of the Federal Funds target rate. As A2P2 non-financial commercial paper is not eligible under the CPFF, we would expect the spread to increase after the announcement of the CPFF. The results of this regression confirm these expectations and show a significant increase in the spread on October 7 th (these results are not displayed in Table 4). Therefore we can conclude that the announcement of the CPFF has been effective in lowering overnight financial commercial paper rates.
When we perform equation (1) on the spread between one-month financial commercial paper and the Federal Funds rate (regression (3) in Table 4), we do not find any significant negative. This could again signal the turbulence during this period and the slower adaptation of longer-term rates to the new measure. Also performing the regression on the three-month maturity spread does not give any significant impact of the CPFF (results are not displayed).
Second, we perform similar regressions for asset-backed commercial paper spread over the Federal Funds target rate (regression model (4) en (5)). The AMLF is incorporated as this facility also influences this spread. Based on the description in paragraph 4.3.1, we would expect an immediate significant negative impact of both the AMLF and the CPFF on this spread. The results of the regression are reported in Table 4, in which we can see the insignificance of the announcement of the AMLF and a large positive significant impact of the CPFF announcement. The first operation however of both AMLF as CPFF show a significant negative impact. It is not clear whether this result is caused by a lagged response to the announcement of by the operation itself, and therefore it is very difficult to draw a conclusion on the effect of the CPFF on the ABCP commercial paper yields..
Regressions on the on-month maturity spreads (regression (6)) show rather similar results as the financial commercial paper spreads as no significant negative impact can be found.
- 86 -
Dependent variable ∆( FIN CP-FED FUND TARGET RATE) OV ∆(FIN CP-FED FUND TARGET RATE) 1M Regression model (1) (2) (3)* Day Ant. LagDay Ant. Lag Day Ant. Lag Independent variables Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Intercept C -1,00 -4,00 *** 0,25 -4,11 *** 0,29 2,61 *** Quarter end Q_ENDS 121,19 17,92 *** 1,47 -81,73 120,77 17,98 *** 0,99 -81,15 128,65 142,92 *** -73,38 28,54 Lehman LEHMAN 85,94 12,76 *** 10,00 -16,35 86,03 12,87 *** 10,03 -15,58 12,16 9,25 *** 12,03 9,17 Lag of FIN CP-FED TARGET (overnight) FIN CP-FED(-1) OV -10,38 -7,45 *** -11,17 -7,78 *** Lag of FIN CP-FED TARGET (1 month) FIN CP-FED (-1) 1M -12,62 -3,54 *** CPFF Initial announcement CPFF_ANNOUNCEMENT 80,10 11,89 *** -33,11 -72,89 79,90 11,95 *** -35,20 -71,36 15,34 5,56 *** -39,86 93,01 Initial operation CPFF_OPERATION 6,71 -0,98 13,42 5,78 -2,58 *** 10,56 10,25 Adjusted R² 64% 65% 44% Dependent variable ∆(ABCP CP-FED FUND TARGET RATE) OV ∆(ABCP CP-FED FUND TARGET RATE) 1M Regression model (4)* (5)* (6)* Day Ant. LagDay Ant. LagDay Ant. Lag Independent variables Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Intercept C 2,61 3,99 *** 2,33 3,79 *** 1,53 2,83 *** Quarter end Q_ENDS 335,68 93,55 *** 72,60 -256,31 -262,65 -21,17 *** 72 -262 192,90 37,52 *** -113,74 164,96 Lehman LEHMAN 244,30 300,11 *** 13,65 110,45 243,95 332,33 *** 13,48 107 0,10 0,08 10,59 42 Lag of ABCP CP -FED TARGET (overnight) ABCP-FED(-1) OV -13,75 -4,39 *** -12,29 -4,30 *** Lag of ABCP CP - FED TARGET (1 month) ABCP-FED(-1) 1M -5,57 -2,22 ** AMLF Initial announcement AMLF_ANNOUNCEMENT 12,36 1,28 57,62 -39,08 7,86 0,89 52,67 148,27 56,81 *** 31,77 Initial operation AMLF_OPERATION -20,82 -2,62 *** -76,31 5,24 0,85 -62,37 CPFF Initial announcement CPFF_ANNOUNCEMENT 204,59 83,98 *** -22,84 -44,89 203,47 91,95 *** -24,77 -57,10 151,79 32,72 *** 8,06 23,94 Initial operation CPFF_OPERATION -7,33 -6,57025 *** 24,3495 9,81 57,67 17,82 *** -29,71 41,28 Adjusted R² 81% 81% 50% Table 4 Commercial paper market Notes: (a) Newey-West standard errors are used in regression models signaled with a ()* (b) Ant. Est = Anticipation effect estimate = sum of the significant estimates in the time window before the announcement. (c) Lag Est = Lagged effect estimate = sum of the significant estimates in the time window after the announcement (d) The results are expressed in basis points (e) * significant at 10%; ** significant at 5%; *** significant at 1%.
- 87 -
By bringing previous sections together, we can conclude that the AMLF and the CPFF have been effective in reducing tensions in the commercial paper market. Especially the effects of the announcements on the overnight rates have been significant. The impact on longer-term maturities was slackened. We expect that this delay was caused because expectations about future short-term interest rates were only adjusted downwards when the market was convinced about the strength of the newly announced measures. Moreover, we believe that liquidity and trust did not restore immediately after the announcement of the new facilities in longer-term markets. Also the flight-to-quality can help in understanding this delay. In the ABCP-market, we notice an even slower amelioration of the spreads, signalling deeper penetrated strains in this market, and therefore a more toilsome recovery. However, due to lack of micro-data, we were unable to perform more thorough research on these suppositions.
4.4 The asset-backed securities market
This section proceeds on the description of the TALF in paragraph 3.2.2.2. Due to a lack of micro data, we will not measure the effectiveness of the TALF measure by means of econometrical analysis. Moreover, a thorough and extensive study has already been performed by Campbell, Covitz et al. (2011). With the data of the asset-backed securities market that we have at our disposal, it would be difficult to add value to this research. However, analogously to the previous sections, we will try to divulge the effectiveness of the TALF on the basis of empirical observations. Although we cannot draw any firm conclusions from a figure at first sight, our observations seem to be in line with the existing literature. The TALF program was directed to both consumer asset-backed securities as well as commercial mortgage-backed securities, although the latter was only accepted as eligible collateral in May 2009. We will discuss them separately with the aid of a visual representation.
When looking at Figure 13, we see that just like in all other markets, strains soared at the outset of Lehman Brothers. This increase reflected a rise in credit risk, a loss in confidence and an accompanying increase in risk aversion as stated in Dudley (2009). The spreads of
- 88 - the auto and credit card ABS yields68 over the two year Treasury yield, displayed in Figure 13, went up to reach almost 800 basis points. Given these high yields, issuing ABS became so costly that ABS issuance came to a standstill. The amount of issuance decreased with $46 billion and thus reached a level of $4 billion in the fourth quarter of 2008 (Dudley 2009).
Figure 13: Asset-Backed Securities yield Source: Datastream
On November 25th, the Federal Reserve announced the creation of the Term Asset-Backed Securities Loan Facility. While one could suspect that the TALF was ineffective as spreads remained high after the initial announcement, a finely tuned judgment has to be made and other factors have to be taken into account. As was the case in the commercial paper market, we expect that the high level of innovativeness of the measure combined with an elevated level of mistrust could be contributing to the decelerated reaction of the spreads. An additional contribution could be done by a stigma associated with the TARP as investors could be worried “that the use of TARP funds in TALF could restrict their ability to conduct their business activities more broadly” (Dudley 2009). Moreover, we expect that the difficult year end of 2008 we brought up already several times has added to the remaining high levels. The plummeting on January 1 st 2009 could be providing proof of this. Although
68 These yields are Bank of America-Merrill Lynch AAA-rated reduced yields on Auto ABS and Credit Card ABS. - 89 - this plummet was probably not caused by the TALF, the further decreasing from January on potentially did. Campbell, Covitz et al. (2011) demonstrate that ABS spreads were falling at times when the market-wide price and level of risk appeared to rise, as can be seen in the figure in Exhibit 4. Moreover, the authors find econometrical proof for this as the spread between AAA Auto ABS and CDX (which is a measure for the market-wide price and level of risk) significantly drops with 63 basis points on March 3, 2009, when the Fed announced that the first TALF subscription would take place on March 17. Also the announcement of March 19 on the successful completion of this first subscription added to a decline of 40 basis points. In contrast, Campbell, Covitz et al. (2011) cannot find significant results for the AAA credit card and private student loan ABS. When we take a look at Figure 13 we notice that the declining trend in the spreads that was noticeable since January 2009, reinforced once TALF operations took off. However, at the same time, we observe a gradual increase in S&P 500 which could indicate that part of the decline in spreads could be attributed to a more general improvement in market conditions. However it is unclear whether the improved market conditions were caused by a decreased cost of borrowing as a result of the TALF or whether it was the other way around.
Next to the decreases in spread, Dudley (2009) also finds proof of the effectiveness of the TALF in the gradual revival of consumer ABS securities issuances from March 2008 on. Moreover, he finds that these new issues were only financed slightly more than half by TALF loans. “This means that the TALF is helping to restart the market, rather than the TALF being the market” (Dudley 2009, p.1).
The effectiveness could also be regarded at from a point of view in which we compare the ABS market from Europe with the United States. Both central banks accepted ABS as collateral, the ECB in its refinancing operations and the Federal Reserve in its discount window. However, the ECB accepted ABS collateral from issuers directly, while the TALF program involved investors in ABS collateral. Campbell, Covitz et al. (2011) find that the Fed was more effective in reducing the ABS spread more rapidly. The lack of investor involvement seems to have put the ECB at a disadvantage in the recovery of ABS market.
- 90 -
After a short elaboration on the response of the consumer ABS market to the introduction of the TALF, and based on a short summary of the relevant literature about its effectiveness, we now take a look at the commercial mortgage backed securities market. As can be seen in Figure 14, strains in the commercial mortgage backed securities market remained elevated for a long time and therefore the Fed also decided to interfere in this market. Although the
Figure 14: Spread on accepted and rejected Commercial Mortgage-Backed Securities Source: Campbell, Covitz et al. (2011) confirmation of the eligibility of the CMBS as collateral in the TALF program was only made on May 1st, we consider the announcements in March about the first TALF subscription and its successful completion as a turning point in the course of CMBS spreads. These first signals of success together with a previous announcement on February 10 that had raised a corner of the veil that CMBS could be accepted as collateral in the future, could have led to the curbing of the soaring spreads. Campbell, Covitz et al. (2011) indeed find that the two March announcements have had a significant statistical impact on the CMBS spreads.
Comparing the spread on the CMBS that was accepted as collateral for TALF loans and CMBS that was rejected, we see that, before the announcement on May 1st about the terms and conditions of the TALF new-issue CMBS program, both were improving and also the spreads between these spreads was declining. However, from this announcement on, the
- 91 - declining trend of the spread between rejected and accepted securities reversed, signaling the potential effectiveness of the TALF in reducing the spread of the accepted collateral.
The graphs we have discussed in this section show improvements both in the consumer and the commercial ABS market after the announcement of the TALF program. Moreover, although we have not performed an econometrical analysis ourselves, we conclude that the TALF has been effective in its purpose as various authors have shown that the TALF has significantly reduced the yields of consumer and commercial ABS markets.
4.5 Other key markets
The rationale behind the large-scale asset purchase program was discussed in paragraph 3.2.2.3. While various authors seem to agree on the effectiveness of the LSAP in reducing yields of agency debt and agency mortgage-backed securities (D’Amico and King 2010; Doh 2010; Gagnon, Raskin et al. 2010; Krishnamurthy and Vissing-Jorgensen 2011), more scepticism exists on the effectiveness of the LSAP in the Treasury market. Thornton (2009) for example argues that the LSAP were ineffective in reducing interest rates of Treasury as in October 2008, yields even surpassed pre-LSAP levels. Moreover, it was doubted that, even taking the considerable intervention size into account, purchases of Treasury could have significant effects, as there is a broad range of substitutes for Treasury securities (D’Amico and King 2010). Next to these arguments, scepticism also arose from a theoretical point of view as for example the expectations theory assumes that a shift in the supply of bonds does not matter in determining prices (Doh 2010). Yellen (2011) 69 , however, states that preferred-habitat models were the underlying theory for the LSAP and that, therefore, the term structure of interest rates can be influenced by exogenous supply shocks 70 . Moreover, D’Amico and King (2010) point out the importance of a potential decrease in Treasury yields for the cost of credit across a range of markets, and thus also the borrowing for businesses and households, in contrast to agency-debt and MBS programs that were mainly focused on the stimulation of the housing market. Given the large consensus in literature on the effectiveness of the LSAP on agency debt and agency mortgage-backed
69 This speech can be found on
4.5.1 Market response
In Figure 15, market yields of Treasury Securities on different maturities are plotted. As a first indicator of the potential effectiveness of the LSAP on these Treasury Securities, we take a look at how market yields evolved in two important periods. The first period is around November 25th and December 1 st , 2008, respectively when the LSAP program was announced 71 and when potential purchases of longer-term Treasury were first mentioned 72 . After these announcements, we can notice a decline in market yields. A second period is after March 18th, 2009, when the FOMC announced that it had decided to purchase up to $300 billion of longer-term Treasury securities 73. Although the possibility of this event was already announced on December 1 st , 2008, a noticeable decrease can be observed, ranging between 20 and 50 basis points on the different maturities. The effect on the Treasury securities with a maturity of 2 years is smaller, probably as a result of the focus on longer-maturities in the purchase of Treasuries under the LSAP. Moreover, we notice that the 10-year term premium (Kim and Wright 2005) shows a similar course as the
percentages
Figure 15: Market yields on 2-year, 10-year and 20-year Treasury securities Source: Datastream, Federal Reserve
71 This announcement can be found on
Treasury yields. Therefore, we would expect that the possible impact of the LSAP has reduced the term premium and not the expectations about the future short-term interest rates. Whether or not these declines were significant will be tested in paragraph 4.5.3.
%
Figure 16: BAA Corporate Bond Yields Source: Datastream
Although these declines signal that the LSAP announcements potentially have been effective in lowering yields on Treasury securities, these decreases were short-lived. In May 2009, market yields even hit higher rates than before the LSAP was announced. As stated above, this fostered criticism from various authors and from a theoretical point of view. However, some reasons exist to expect that these increases were driven by other factors, and therefore we do not immediately reject the possibility that the LSAP has been effective in reducing Treasury yields. One of these reasons is the improved economic outlook that arose which made expectations about future short-term interest rates increase, and therefore also had an upward effect on longer-term interest rates (Doh 2010). Moreover, an increase in policy uncertainty and rising mortgage rates that encouraged investors to shake off duration, and therefore reversed the flight-to-quality, may have contributed to these increases in Treasury yields (D’Amico and King 2010). Gagnon, Raskin et al. (2010) argue that also a very large increase in the expected future fiscal deficit could have led to an increase in Treasury yields.
- 94 -
Next to the direct goals of the LSAP to reduce interest rates of Treasury, agency debt and mortgage-backed securities, more broadly, the goal was to reduce longer-term interest rates on a range of securities, including securities that were not part of the LSAP, via spill- over effects. In Figure 16, BAA corporate bond yields and 7 important LSAP announcements are plotted. BAA corporate bonds were not purchased under the LSAP, however, we notice declines on several days on which LSAP announcements were made. Moreover, we notice a declining trend during the lifetime of the LSAP. This gives a first signal that the large-scale asset purchase program could also have impacted securities that were not purchased by the Fed. In section 4.5.3, we will test if these declines were significant.
4.5.2 Data
As stated above, our focus mainly lies on the effect of the LSAP on the Treasury market yields. The method we will use is analogous with Meyer (2010). As dependent variable we apply the first differences of the market yield of Treasury Securities with a maturity of 10 year. To check the robustness of our results and to measure the effect of the LSAP program on other maturities, we will incorporate the market yield on Treasuries with maturities of 2 and 20 years as well. However, we need to control for changes in the market expectations about the future short-term interest rates, as these are a component of the Treasury yields. We will use the OIS 1 year as proxy for the future short-term interest rate expectations 74 . Moreover, S&P 500 is also included in the dataset as this reflects the changing economic outlook.
As independent variable we consider 4 relevant announcements concerning the LSAP program, including the initial announcement of the LSAP on November 25 2008, the speech of Bernanke (2008) on December 1 which stated that potentially substantial quantities of Treasury securities would be purchased, the announcement on December 16 th in which the Fed announced it was evaluating the potential benefits of purchasing longer-term Treasury
74 An OIS variable with a longer maturity would be more appropriate, however, our dataset is limited to the OIS with a 1-year maturity. - 95 - securities and last, the announcement of March 18, in which the purchases of Treasury securities were confirmed. The announcement-variables and the time-window variables are defined as earlier described (see above, p. 55). Moreover, 4 dummies are created to measure the impact of the FOMC statements of January 28, August 12, September 23 and November 4, 2009, as these could have revealed additional relevant information on the LSAP program. As the objective of the LSAP program was to reduce the term premium, we will also perform a regression on the 10-year term premium (Kim and Wright 2005) to further check whether the Fed succeeded in its purpose. To check whether the LSAP also had effects on securities that were not purchased under the LSAP, we perform a set of regressions on BAA corporate bond yields. For more information and for the source of these variables, we refer to Exhibit 5.
4.5.3 Econometrical analysis
Literature on the large-scale asset purchases is rather extensive. Many authors agree on the effectiveness of the LSAP in reducing interest rates in agency debt and mortgage-backed securities markets (Stroebel and Taylor 2009; D’Amico and King 2010; Doh 2010; Fuster and Willen 2010; Gagnon, Raskin et al. 2010). Also on the impact of the LSAP program on Treasury securities, quite some research has been performed. Gagnon, Raskin et al. (2010), for example, utilize two different methods to measure the impact on the 10-year term premium. Although the methods and the used data are completely different in both methods, the authors find similar results, with the decline in the 10-year term premium ranging between 38 and 82 basis points. Moreover, Gagnon, Raskin et al. (2010) measure the cumulative changes on eight days on which relevant announcement were made and finds a cumulative decrease of 91 basis points in the 10-year Treasury interest rates. The authors conclude that the reductions in Treasury rates reflect reductions in risk premiums, rather than declines in the expectations of future short-term interest rates. Doh (2010) finds a significant reduction in 10-year Treasury yields as a result of the announcement of March 18 th , when the initiation of the Treasury purchase program was confirmed. Further, various authors have performed research on the effect of the LSAP operations and all find a decrease in 10-year Treasury yields between 13 and 15 basis points (Gagnon, Raskin et al. 2010; Meyer 2010; Hamilton and Wu 2011). Next to the significant decline in Treasury
- 96 - yields, Gagnon, Raskin et al. (2010) find a long-lasting reduction in interest rates of securities that were not purchased in the LSAP program. In contrast to all these authors that find significant declines in agency debt, agency MBS and Treasury yields as a consequence of the LSAP program, Thornton (2009) states that the LSAP has been ineffective. As stated in paragraph 4.5.1, we will only measure whether the LSAP program has been effective in reducing Treasury yields.
Our methodology to test whether the LSAP has been effective in reducing market yields of 10-year Treasury securities is based on the methodologies of Gagnon,Raskin et al. (2010), Meyer (2010) and Doh (2010). To test whether or not the LSAP program has been effective in reducing market yields on longer term Treasury Securities, we will commence with the following regression:
Δ
Δ ∆ & (1) with which is the market yield of 10-year Treasury securities. The other variables are composed as described previously (cf. paragraph 4.5.2 and Exhibit 5). . Analogously with previous regressions, we include the lag of the dependent variable in case changes in the yields are influenced by the level. We expect all four announcements to have a significant negative impact on the 10-year Treasury yields, and anticipate especially a large reduction as a result of the announcement of March 18 th , as then the Treasury purchases were confirmed.
The results are shown in Table 5 and as can be seen, all announcements concerning the LSAP program contributed significantly to the decline in the Treasury market yield. In total, a reduction of more than 100 basis points can be noticed, with the largest contribution coming from a reduction of around 50 basis points on the day of the announcement of March 18 th , as expected. Moreover, from almost all variables we can observe both significant negative anticipation and lagged effects. The lagged effects are in line with our general expectations described earlier (see above, p. 55). In contrast, usually we do not
- 97 - expect anticipation effects. However, the fact that already on December 1, 2008, the possibility that Treasuries would be purchased in the LSAP was announced could have contributed to such anticipation effects. The announcement of March 18 shows significant positive anticipation and lagged effects. However, these are small compared to the coefficient on the day of the announcement.
Although the results have to be interpreted with care as they can include the impact of other events, our results are highly comparable with the findings of Gagnon, Raskin et al. (2010), who finds a cumulative decrease in Treasury rates of 91 basis points on days of announcements, and a cumulative decrease of more than 100 basis points when expanding the time window around the announcements.
Next we will perform a regression in which we add the supplementary dummy variables to measure the effect of the 4 FOMC announcements:
Δ
Δ ∆ &
(2) with . Although these announcements could reveal relevant information on the LSAP program, we do not expect these variables to have an impact of similar magnitude as the first four announcements. The results are displayed in Table 5 and confirm our expectations as three out of the four added announcements are insignificant, and the fourth only shows a small significant decrease. This could be explained by the fact that these announcements did not contain supplementary information or did not concern the Treasury market.
Next, we perform regression (1) on different maturities, namely the 20-year (regression model (3)) and the 2-year (regression model (4)) Treasury yields. The results are shown in Table 5. We notice very similar results as for the 10-year Treasury yields. However, we see
- 98 - that the coefficients are lower for the 2 year (a decrease of around 50 basis points) and 20- year maturities (a decrease of 83 basis points) than for the 10-year maturities. This is consistent with D’Amico and King (2010) as they argue that the yields in the 5-to-10-year range declined the most because in this sector the majority of the purchases was conducted.
The regressions above confirm our expectations that the LSAP were effective in lowering Treasury yields. However, the question remains whether these declines were caused by declines in the term premium, which was the main goal of the LSAP program. The lower coefficients in the regression performed on the 2-year maturities already gives a first signal of this, but to test this more thoroughly, we will perform the basic regression (1) on the 10- year maturity term-premium. The results can be found in Table 5 and show a significant reduction of in total 83 basis points in the term-premium. When comparing this reduction with the decline of around 100 basis points in the 10-year Treasury yields, we can conclude that most of the reduction can be attributed to a reduction in the term premium. Therefore, the LSAP has reached its goal of reducing longer-term interest rates by reducing risk premiums. Again, these results are comparable with the results of Gagnon, Raskin et al. (2010).
As a last regression, we perform equation (1) on the changes in BAA corporate bond yields. If the effectiveness of the LSAP in reducing the 10-year Treasury yields (and agency debt and agency mortgage-backed securities yields) would have spilled over to other markets, we would expect significant negative coefficients for the LSAP announcements. The results are displayed in Table 5. and again we find significant negative effects of the LSAP on the yields, with a total decrease of around 60 basis points. . This signals that spillover effects took place and that also securities that were not included in the LSAP, have benefited from this program.
From these regressions, we can conclude that the Federal Reserve has reached its objectives to reduce yields of Treasury securities, and more broadly, to reduce the cost of credit in a range of private markets. Although the yields quickly returned to their pre- announcement levels, we described above that there were other factors at play that caused - 99 - yields to increase again. Therefore, no doubt can exist about the reduction in the term premium as a result of the LSAP.
- 100 -
Dependent variable ∆ of Treasury yields (10 year maturity) ∆ of Treasury yields (20 year maturity) Regression model (1)* (2)* (3)* Day Ant. Lag Day Ant. Lag Day Ant. Lag Independent variables Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Intercept C 4,17 3,60 *** 4,00 3,50 ** 8,64 3,89 *** First differences of OIS rate ∆OIS 58,31 12,92 *** 58,66 12,83 *** 43,90 9,92 *** First differences of S&P 500 ∆S_P 0,10 6,31 *** 0,10 6,17 *** 0,09 5,77 *** Lag of Treasury 10 year TRSY_10Y(-1) -0,98 -3,48 *** -0,94 -3,38 *** Lag of Treasury 20 year TRSY_20Y(-1) -1,84 -3,83 *** LSAP November 25 2008 NOVEMBER_25 -20,39 -43,46 *** -9,83 -27,11 -20,31 -42,75 *** -9,63 -26,91 -13,93 -29,47 *** -22,87 -23,60 December 1 2008 DECEMBER_1 -10,77 -7,95 *** -24,34 -10,82 -7,97 *** -24,10 -12,06 -9,00 *** -25,12 December 16 2008 DECEMBER_16 -24,58 -32,34 *** -18,13 -23,75 -24,45 -32,02 *** -17,98 -23,82 -21,34 -24,48 *** -14,79 -31,45 March 18 2009 MARCH_18 -52,75 -130,31 *** 6,71 11,95 -52,67 -129,43 *** 6,00 12,22 -35,90 -92,82 *** 9,64 -1,19 January 28 2009 JANUARY_28 8,93 14,54 *** August 12 2009 AUGUST_12 2,91 7,53 *** September 23 2009 SEPTEMBER_23 -2,00 -5,88 *** November 4 2009 NOVEMBER_04 5,89 25,33 *** Adjusted R² 43% 42% 32% Dependent variable ∆ of Treasury yields (2 year maturity) ∆ of Term Premium (5 year maturity) ∆ of Baa Corporate bond yields Regression model (4)* (5)* (6) Day Ant. Lag Day Ant. Lag Day Ant. Lag Independent variables Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Intercept C 0,39 1,76 * 1,46 4,91 *** -2,62 -0,90 First differences of OIS rate ∆OIS 89,52 13,95 *** 28,85 7,51 *** 38,29 2,95 *** First differences of S&P 500 ∆S_P 0,12 8,23 *** 0,07 4,65 *** 0,07 3,10 *** Lag of Treasury 2 year TRSY_2Y(-1) -0,14 -2,11 ** Lag of Term Premium 5Y TERMPREMIUM(-1) -1,89 -3,86 *** Lag of Baa Corporate Bond BAA_CORP(-1) 0,35 0,88 LSAP November 25 2008 NOVEMBER_25 -9,08 -15,46 *** 17,154 -22,64 -14,72 -37,09 *** 3,1059 -13,27 -6,67 -0,84 December 1 2008 DECEMBER_1 4,44 3,91 *** 0,00 -11,88 -10,97 -9,47 *** 0,00 -13,34 -11,88 -1,47 December 16 2008 DECEMBER_16 -19,17 -30,37 *** -9,1788 16,31 -17,08 -27,07 *** -12,2973 -16,05 -20,00 -2,51 ** -20,64 March 18 2009 MARCH_18 -23,45 -73,73 *** -2,72 11,05 -41,00 -145,49 *** 5,10 0,97 -23,79 -3,01 *** Adjusted R² 64% 30% 9%
Table 5: Treasury market Notes: (a) Newey-West standard errors are used in regression models signaled with a ()* (b) Ant. Est = Anticipation effect estimate = sum of the significant estimates in the time window before the announcement. (c) Lag Est = Lagged effect estimate = sum of the significant estimates in the time window after the announcement (d) The results are expressed in basis points (e) * significant at 10%; ** significant at 5%; *** significant at 1%.
- 101 -
5 THE EFFECTIVENESS OF THE NON -STANDARD MEASURES : THE EUROPEAN CENTRAL BANK
In the previous chapter, we have measured the effectiveness of the various non-standard measures introduced at the Federal Reserve. In this chapter, we will measure the effectiveness of the non-standard measures introduced at the European Central Bank.
5.1 Interbank market
5.1.1 Market response
As a first indicator for the effectiveness of the monetary response during the financial crisis, we take a look at Figure 17 . Although the turbulence in this crisis-period makes it impossible to draw conclusions with certainty from this graph, we can see some interesting moves in the spread between secured and unsecured interbank lending on certain dates. `
Figure 17: Euribor-OIS spread (3-month maturity) Source: Datastream, authors’ calculations
The period following August 2007 was characterized by the emergence of strains in the money market. The contamination from the problems in the asset-backed securities market caused spreads to rise. The ECB was in the vanguard to respond and performed several fine-tuning operations to meet the rising demand for liquidity caused by the increased uncertainty for short-term financing in the money market. Furthermore supplementary and - 102 - special LTROs were organized to provide banks with certainty about their liquidity position for a longer period of time (3 months), but the declines in spread following these operations were most of the time neutralized by an increase in the following days. However, we do not have the counterfactual for the spread in this period of crisis, and therefore it is impossible to make firm conclusions based on this graph.
Although in mid-October 2007 interbank market conditions seemed to be improving, it only took until mid-November before spreads started to increase again to even higher levels than the first peak. It is until the announcement of the joint action with the Federal Reserve to offer US dollar funding to Euro system counterparties on December 12, 2007, that the rise of the spread seemed to come to a halt and spreads were starting to move in the opposite direction.
But again, this decline was short-lived. In March 2008, the period in which uncertainties about Bear Stearns arose and in which it was taken over by JP Morgan, tensions in the money market started to climb again. It is in this period that the ECB renewed its supplementary 3-month LTROs and introduced 6-month LTROs. The growth of the spread curbed and the spread began to decrease.
Also this time, the decrease came to an end quickly as in September 2008, the collapse of Lehman Bros caused the spread to hit even higher levels than the peaks in the pre-Lehman period. Announcements about the significant increases in TAF amounts and the introduction of special LTROs slowed the rocketing spreads on the days of their announcements (September 18 and September 29) but could not stop the soaring spreads. It is not until October 8 th , the day on which the fixed rate full allotment tender procedure in its MROs, a 50 bp decline of the key interest rate and the narrowing of the corridor of the interest rates of the marginal facilities relative to the MRO-rate was announced, that this rising trend could be reversed. On October 15, the ECB announced the expansion of accepted collateral 75 and the renewal of LTROs and SLTROs, and introduced FRFA in its
75 To include securities (other than ABS) rated BBB or higher - 103 -
LTROs. It is also in early October 2008 that European fiscal authorities interfered, for example by stepping into the breach to rescue Fortis and Dexia banking groups. Also the UK banking sector was restructured and overseas, the Troubled Asset Relief Program was introduced. Together, these measures seemed to have a great impact on the spreads and a decline was set in.
The expansions of the swap arrangements with the Fed in June 2009, the introduction of LTROs with a maturity of one year on May 7, 2009, and the announcement about the initiation of the covered bonds program, on June 4, were followed by a further decline of the spread.
The combination of these innovations lead to a situation of ample liquidity 76 and therefore provided significant comfort and support to the banking sector. Although the level of the spread had not been restored to its pre-crisis level, a stabilization and normalization of the conditions seems to have been emerged since the autumn of 2009.
%
Figure 18: Euribor-MRO spread (3-month maturity) Source: ECB, Datastream, authors’ calculations
76 As excess liquidity was absorbed via the deposit facility, in stead of via draining operations - 104 -
The situation of ample liquidity can also be noticed in Figure 17 . The Euribor 3M started to move away from the MRO-rate towards the interest rate of the deposit facility, by which the excess of liquidity was absorbed. This was already described earlier (cf. 2.2.2).
In the following, we will measure whether the non-standard measures of the Fed have been effective in relieving strains in the interbank market.
5.1.2 Data
For analogue reasons as described in paragraph 4.1.2, and consistent with the literature (Lenza, Pill et al. 2010; Abbassi and Linzert 2011), we use the changes in the Euribor-OIS spread 77 with a 3-month maturity as dependent variable in the regressions 78 . Many financial contracts are priced using Euribor rates and therefore, the Euribor is a major link in the transmission of the monetary policy to the economy (Abbassi and Linzert 2011).
To test whether the actions of the ECB have been effective, we compose a set of independent variables. First, we make a set of variables that must account for important initial announcements. We include the initial announcement that SLTROs would be performed, on August 22, 2007, the initial announcement on the introduction of swap lines with the Federal Reserve on December 12, 2007, the sets of important announcements (cf. paragraph 5.1.1) made on October 8 and October 15, 2008 and the initial announcements of 6-month and 1-year LTROs, respectively on March 28, 2008 and May 7, 2009.
Next to these dummy variables, we compose a set of variables that takes a value 1 on days with certain announcements, and 0 otherwise, based on Abbassi and Linzert (2011).
LTRO_6M ANNOUNCEMENTS is one on each day a 6-month LTRO operation is announced.
77 On March 3 2008, the announcements of the OIS-rates were changed from 4:30 p.m. to 11 a.m. when also the Euribor rate is announced. This means that these announced rates reflect the impact of announcements of the day before. We take this into account in the composition of our Euribor-OIS variable. Before March 3, 2008, the spread is calculated as: EURIBOR-OIS t = EURIBOR t+1 – OIS t . Thereafter, the spread is calculated as: EURIBOR-OIS t = EURIBOR t+1 – OIS t+1 . 78 By taking this spread, we control for the implicit path of the expected future short term interest rate, which is a component of the Euribor and is cancelled out by taking the spread with the OIS-rate. For more information on how the effect of expected future short-term interest rates on the Euribor has changed during the financial crisis, we refer Abbassi and Linzert (2011) - 105 -
Furthermore, SLTRO ANNOUNCEMENTS is set to one on each day a special LTRO is announced, and SWAP ANNOUNCEMENTS is set to one on each day an announcement is made about a liquidity swap transaction with the Federal Reserve. All three variables exclude the initial announcement. For the announcements on 1-year operations such a variable is not created because of the lack of sufficient announcements. Moreover, no variables are created that include the announcements of regular MROs and 3-month LTROs, as an indicative calendar is published and therefore these announcements do not contain any new information.
Moreover, we create a variable to account for the amount of Open Market Operations (OMOs) outstanding (OUTSTANDING). During the crisis these operations became a policy instrument to steer interest rates (Abbassi and Linzert 2011) and therefore, these variables could have an impact on the Euribor-OIS spread. The variable is composed as the amount of OMOs outstanding scaled back to take the liquidity need of the banking sector into account. The latter is calculated as the sum of the reserve requirements and the autonomous liquidity factors. The OUTSTANDING variable is than calculated by dividing the total amount of OMOs outstanding by the total liquidity need of the banking system. Therefore, this variable is an indication for the amount of liquidity that is provided to the banking system above what they need to fulfill their reserve requirements and the autonomous liquidity factors.
Next to these independent variables, we also create a set of control variables. First, we set up a variable (CDS) with changes in the CDS to control for the credit risk premium in the spread. Moreover, to control for general banking sector conditions, we include the Euro Stoxx Banks (EUROSTOXX). Furthermore, we include a control variable for quarter ends, because typically, short-term interest rates spike on quarter ends, as institutions have to report balance sheets. The variable QEND is composed similarly to the variable we used for the US interbank market (cf. paragraph 4.1.2. ) Last, a variable to measure the impact of the collapse of Lehman Brothers is created. For more information, and for the source of these data, we refer to Exhibit 1.
- 106 -
5.1.3 Econometrical analysis
Literature on the effectiveness of the measures of the European Central Bank in relieving financial strains in the interbank market is scarcer than the literature on its overseas counterpart. Lenza, Pill et al. (2010) construct a counterfactual path for the Euribor under a no policy scenario and compare this scenario with the observed money market rates. They find that the non-standard measures introduced by the ECB have reduced the spread between the Euribor and OIS rates and that they have helped to avoid a financial meltdown. Abbassi and Linzer(2011) find that the net increase of 60% in outstanding volumes associated with open market operations between August 2007 and June 2009 have reduced the Euribor rates with more than 100 basis points. Moreover, they find a weak significant effect of the announcements of supplementary 3-month LTROs. In the following we perform an econometrical analysis to test which non-standard measures have been effective in reducing the Euribor-OIS spread.
We apply a methodology similar to Abbassi and Linzer (2011), but instead of decomposing the Euribor rates into its different components, we will perform the regressions on the spread between Euribor and OIS rates, consistent with our regressions for the US interbank market. Similar to these regressions, we will first take a look at the impact of some important announcements. For this purpose, we perform the following regression:
∆
_ _ _6
0_6 _ _1 _1 _
_
_ (1) with Y t = - and the announcement variables and their time windows as defined earlier (cf. paragraph 5.1.2 and Exhibit 6). In this regression, the CDS variable is not
- 107 - included and therefore, we measure the impact of the announcements on the total spread between Euribor and OIS.
Although we expect all announcements to have a significant negative impact on the Euribor-OIS spread, we would especially expect strong effects from the swap announcement, the announcements of October 8 th and October 15 th and the announcement on the 1-year LTRO, given their highly unconventional nature. Earlier (see above, p. 55) we have described that, given this unconventionality of many of the newly introduced measures, we expect significant lagged responses to the announcements. For the same reasons, we do not expect anticipation effects.
The results of this regression are displayed in Table 6. We notice that most of our expectations are confirmed. Although both the swap announcement and the announcement about the introduction of FRFA in the main-refinancing operations lack a significant negative effect on the day of their announcement (the swap announcement even shows a significant increase), we can observe a lagged decrease with around 4 and 10 basis points respectively. Moreover, when we perform this regression with expanded time windows around the announcement days, we can observe that the lagged response of the swap announcement keeps on growing 79 . This confirms our expectation that in times of elevated strains in the market, innovative announcements know lagged responses.
Moreover, as anticipated, the announcement of October 15 th about, among others, the introduction of FRFA in longer-term refinancing operations, shows a significant negative impact of around 2 basis points on the Euribor-OIS spread. Furthermore, a lagged response of 6 basis points can be noticed. Similar results are obtained for the announcement of the 1- year longer-term refinancing operation, with a significant decrease of around two basis points on the announcement day. However, this announcement seems to have had a smaller lagged response. This could be caused by the fact that market conditions were already more relieved in the beginning of 2009, compared with October 2008. Therefore, it could be
79 Due to the overlap of time windows with the announcement of October 15, 2008, we could not expand the time window of the announcement of October 8. - 108 - possible that the market incorporated the information revealed in the 1-year LTRO announcement more quickly.
Last, when we take a look at the effect of the announcements about the first SLTRO announcement in August 2007 and the first 6-month LTRO announcement in March 2008, we can only observe a significant decrease on the day of the announcements, amounting respectively around 3 and 1 basis points. These small decreases and the lack of a lagged response can probably be explained by the highly turbulent periods in which these announcements took place, respectively the beginning of the financial turmoil and the strains caused by Bear Stearns.
In a second regression, we add our set of control variables.
∆
_6
0_6 _1 _1
∆ ∆
(2) with Y t = - and the control variables as described in paragraph 5.1.2 and Exhibit 6.
The results are displayed in Table 6. We notice very comparable results and in this regression, also the impact of the announcement of October 18, 2008 is significantly negative on the day itself. Moreover, as in this regression the CDS-variable is included, the impact of the measures on the liquidity premium are measured. As most coefficients remain rather unchanged when comparing with the results of regression (1), we could conclude that the non-standard measures of the ECB have especially been effective in reducing the liquidity premium of the Euribor-OIS spread. However, this has to be
- 109 - interpreted with care. As the Euribor-OIS spread is generally believed to be composed of both a credit risk premium and a liquidity premium, we would expect a significant impact of the CDS. However, we cannot observe such impact. This could be the result of the Euribor-OIS premium being mainly consisted of a liquidity premium. However, it is also possible that the used CDS-variable is not appropriate. Due to a lack of an alternative CDS- variable, we cannot test the robustness of our CDS-variable. For this reason, we do not interpret the results of the regression we performed with the CDS variable as dependent variable to test the impact of the non-standard measures on the credit risk premium.
In a third regression, we want to measure whether the general announcements that followed the initial announcements of certain measures have had an impact on the Euribor-OIS spread. Therefore, we perform the following regression:
∆
_6
0_6 _6 _1
_1 ∑
∆
∆ (3) with Y t = - . The added variables were already described in paragraph 5.1.2 and Exhibit 6. Although the general announcements on the 6-month LTROs, the SLROs and the swap lines between the Federal Reserve and the European Central Bank can reveal new information to the market, we would expect that most of the impact of the non- standard measures occurs at the initial announcement. The results of this regression are displayed in Table 6 and confirm our expectations as none of the added variables shows a significant impact. In a fourth regression, we measure the impact of the amounts of Open Market Operations outstanding, as these were considerably increased during the financial crisis. Abbassi and
- 110 -
Linzer (2011) find that these amounts of liquidity outstanding have been effective in reducing the 3-month Euribor during the financial crisis. We perform the following regression:
∆
_6
0_6 _1 _1
∑
∆
∆ (4) with Y t = - and the OUTSTANDING-variable as described in paragraph 5.1.2 and Exhibit 6. The results of this regression are displayed in Table 6. In contrast to Abbassi and Linzer (2011) we cannot find a significant impact of the amounts of OMO liquidity outstanding. Abbassi and Linzer (2011) perform rather similar regressions, but use the changes in the 3-month Euribor as dependent variable and the level of MRO and LTRO liquidity outstanding, in contrast to regression (4), in which we use the changes in OMO liquidity outstanding. When we perform regression (4) by using the levels instead of the changes in OMO liquidity outstanding, we also find a significant effect. However, the levels of OMO liquidity outstanding appear to have unit root and thus a non-stationary variable is regressed on a stationary variable. Therefore, the results of this regression are not valid.
We can conclude that the initial announcements of several non-standard measures the ECB has undertook during the financial crisis, have been effective in reducing the Euribor-OIS spread and thereby in relieving strains in the European interbank market.
- 111 -
Dependent variable ∆ EURIBOR - OIS (3 month maturity) Regression model (1)* (2)* (3)* (4)* Day Ant. LagDay Ant. LagDay Ant. LagDay Ant. Lag Independent variables Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Intercept C 0,24 1,41 0,22 1,19 0,22 1,20 0,22 1,20 Lag of EURIBOR-OIS (3 month) EURIBOR-OIS(-1) -0,48 -1,12 -0,52 -1,24 -0,54 -1,31 -0,52 -1,25 ∆ CDS banks ∆ CDS 0,01 0,66 0,01 0,63 0,01 0,59 ∆ EUROSTOXX Banks ∆ EUROSTOXX -0,04 -1,83 * -0,04 -1,82 * -0,04 -1,87 * Lehman LEHMAN 3,01 3,05 *** 3,04 3,08 *** 3,09 3,18 *** Quarter ends QUARTER_END 0,17 0,29 0,16 0,29 0,17 0,30 FRFA MRO Initial announcement OCTOBER_8 -0,87 -1,39 44,28 -9,34 -1,29 -2,17 ** 44,24 -8,95 -1,26 -2,12 ** 44,07 -8,87 -0,98 -1,62 44,27 -8,93 FRFA LTRO Initial announcement OCTOBER_15 -1,21 -2,01 ** 6,36 -5,83 -1,65 -2,78 *** 6,70 -6,16 -1,57 -2,93 *** 6,72 -6,09 -1,58 -2,71 *** 6,68 -6,21 LTRO 6M Initial announcement FRFA_6M_INITIAL -1,14 -6,17 *** 4,53 1,59 -1,28 -1,98 ** 4,86 2,43 -1,46 -2,20 ** 4,91 2,47 -1,28 -1,99 ** 4,90 2,30 General announcements FRFA_6M_ANN -0,25 -0,47 LTRO 1Y Initial announcement LTRO_1Y_INITIAL -2,08 -13,65 *** 0,80 -0,34 -1,86 -5,19 *** 1,46 -0,05 -1,86 -5,23 *** 1,47 -0,03 -1,88 -5,22 *** 1,45 -0,19 SLTRO Initial announcement SLTRO_INITIAL -3,22 -25,64 *** 4,45 4,43 -3,00 -23,46 *** 5,12 4,76 -2,99 -23,30 *** 5,15 4,58 -3,06 -21,48 *** 5,14 4,81 General announcements SLTRO_ANN 0,20 0,39 SWAP lines Initial announcement FRFA_MRO_INITIAL 3,92 16,64 *** 2,14 -3,96 3,99 20,83 *** 2,55 -4,55 4,00 20,87 *** 2,39 -4,51 4,11 20,25 *** 2,49 -4,61 General announcements FRFA_MRO_ANN 0,49 0,32 OMO outstanding OUTSTANDING -0,85 -105,05 Adjusted R² 25% 26% 26% 26%
Table 6: European interbank market Notes: (a) Newey-West standard errors are used in regression models signaled with a ()* (b) Ant. Est = Anticipation effect estimate = sum of the significant estimates in the time window before the announcement. (c) Lag Est = Lagged effect estimate = sum of the significant estimates in the time window after the announcement (d) The results are expressed in basis points (e) * significant at 10%; ** significant at 5%; *** significant at 1%.
- 112 -
5.2 Covered bond market
The Covered Bond Purchase Program me shows resemblanc es with the TALF and the LSAP programs of the Fed, as one of the pur poses (as described in paragraph 3.3.2) is to ameliorate lending conditions for, and expand the provision of credit to , households and non-financial institutio ns, and as its implementation implies o utright purchases of securities. However, it cannot be compared completely with the programs of the Fed . The CBPP was initiated to support the functioning of the banking sector, in contrast to many of the innovative measures of the Fed, which bypassed the banking sector . To get a complete view on the effectiveness of the ECB in battling the crisis, also the effectiveness of this CBPP has to be discussed. In this section, we will take a look at the course of covered bond spreads and we will perform some simple regressions.
Figure 19 : Covered bond yield spread with sovereign yields (France, Germany, Spain) Source: Datastream, authors’ calculations
In Figure 19 we have plotted the spread between covered bond yields of different countries and their sovereign yields . In Figure 20, we visualized the spread between the covered bond index for the euro area and the Ge rman sovereign yields to take a more aggregated view. All rates are obtained from Datastream . Like all other markets that have passed in review , also in the covered bond market we notice a troubled progress of covered bond spreads following the collapse of Lehman Brothers . In May 2009, the ECB decided to intervene in this market as part of its support to the banking sector . We notice that from
- 113 - that day on, spreads begin to decline. Although Beirne, Dalitz et al. (2011) notice that there was some uncertainty on which types and maturities of covered bonds would be eligible after the initial announcement, we do notice a sharp and rapid reaction of the covered bond market. However, one should keep in mind that on the same day as the CBPP, May 7 th , also the first long-term refinancing operation with a maturity of one year was announced. Nevertheless, it seems more likely that the CBPP had the major contribution in the reduction of spreads from May 2009 on. On June 4 th , when the Terms and Conditions of the CBPP were announced, there seems to be no effect at first sight. This could indicate that the uncertainty after the initial announcement was not of such level that it hindered the effect of the announcement.
%
Figure 20: Covered bond spread (euro area) Source: Datastream, authors’ calculations
On these graphs only spreads of covered bonds are visualized. Beirne, Dalitz et al. (2011) notice a substitution effect between covered bonds and banks’ uncovered bonds as yields on the latter were higher because of a flight-to-quality and because of the government- guarantee feature. Therefore issuance of uncovered bond decreased at the expense of issuance of covered bonds and an effect on the issuance of the bank bond market as a whole
- 114 - failed to come. However, we do not know the counterfactual, and therefore the CBPP could have prevented a decrease of the issuance in the bank bond market as a whole, which would have seriously impeded the refinancing possibilities of banks.
The operations of the program were initiated on July 6 th . Between July 6 th 2009 and June 10 2010 442 different bonds were purchased, with a nominal value of €60 billion. From July 6th on, we notice a reinforced decline of the spreads. However, Beirne, Dalitz et al. (2011) cannot find a significant impact of the CBPP operations. They argue that this is in line with the rational expectations hypothesis and therefore they expect that the introduction of the program had a complete price impact, “while purchases were only seen as the execution of the previously announced commitment” (Beirne, Dalitz et al. (2011), p. 6). One should also keep in mind that market conditions generally improved in 2009, which could also have contributed to the declines in covered bond spreads.
Overall, Beirne, Dalitz et al. (2011) find that the CBPP has decreased euro area covered bond yields with approximately 12 basis points. Moreover, they find that the issuance of covered bonds in the primary market was stimulated and therefore, funding conditions for banks were improved. Above, they notice improved covered bond market liquidity and find evidence of positive real economy effects. Therefore, all four goals of the CBPP (cf. paragraph 3.3.2) seem to be achieved. From April 2010 on, however, we notice that spreads curb and begin to increase again. These increases can be attributed to the sovereign debt crisis that commenced following the downgrade of Greece on 24 April 2010, and therefore these should not raise doubts about the effectiveness of the CBPP.
Due to a lack of accurate control variables, we could not perform elaborate econometrical research on this subject. However, as we do have data on yields on covered bonds at our disposal, we performed a small econometrical study in which we examined the announcement effect of the CBPP. We will not draw strong conclusions from these regressions, nor will they be reported. However, based on these regressions, we did obtain a first indication of the effectiveness of the CBPP program.
- 115 -
As the Covered Bond Purchase Programme was rather innovative in its existence, we did not expect a significant negative effect prior to the announcement. In contrast, we did expect the impact of the announcement of this program to mark only sometime after. This lagged response was confirmed by our basic regressions.
Although the program was only focused on longer-term covered bonds, we found similar results when performing this regression on longer and shorter maturities. Also if we regressed on spreads of covered bond yield of Germany and Spain and their respective sovereign yields, we found similar results.
In paragraph 3.2.2.3., we described four channels via which asset purchases programs can be transmitted to the real economy. Throughout all our regressions, we find that the announcement of the CBPP had a significant negative impact. The announcement proclaiming the first operation and the first operation itself however did not. These results are in line with the finding of Beirne, Dalitz et al. (2011) that mainly the announcement channel was effective in transmitting the asset purchases program to the real economy
- 116 -
6 JOINT EFFORT BETWEEN FEDERAL RESERVE AND EUROPEAN CENTRAL BANK : SWAP LINES
Before, we have discussed the effectiveness of non-standard measures undertook by the Federal Reserve and the European Central Bank separately. In this section, we will take a look at the liquidity swap lines, the joint measure that the central banks have initiated. The TAF auctions of US Dollars to the euro area have already been discussed in paragraph 3.2.1. Now we will take a look at their effectiveness. We will only discuss the swap lines between the Fed and the ECB, as these central banks are the focus of this work.
6.1 FX swap market
6.1.1 Market response
In normal times, there is parity between the cost that non-US financial institutions face to borrow directly in the dollar cash market, and the total cost of borrowing in the domestic currency and then exchanging this domestic currency into dollars via a FX swap. This parity is called the covered interest parity (CIP). Deviations from this parity are typically arbitraged away, but because of the strains in unsecured lending markets, this arbitrage didn’t took place during the financial crisis. Therefore, during the financial turmoil and crisis, we notice a deviation from the CIP. When we take a look at Figure 21, rom August 2007 on, we notice a higher volatility in deviations from the CIP from August 2007 on.
The announcement of the establishment of swap lines between the Federal Reserve and the European Central Bank on December 12 2007 did not seem to have an immediate or radical impact as the deviation and volatility seem to increase in the period after the announcement. Albeit, the counterfactual is not known, and therefore we do not know how high deviations would have been otherwise. At the end of February 2008, deviations seem to have returned to their pre-crisis value. However, together with the turmoil around Bear Stearns, deviations and volatility increased again. The gradual expansion of the amount of dollars made available through the swap facilities since December 2007 does not seem to
- 117 - totally return deviations to normal levels, an d even the announcement on July 30, 2008, that swaps with a maturity of 84 days would be introduced, does not seem to restore normality in the FX swap market .
Figure 21 : Covered Interest Parity Deviation Source: Datastream, authors’ calculations
With the failure of Lehman Brothers on September 15th and the announcement of the bailout p ackage for AIG on September 16 th , earlier deviations were dwarfed . This major climb was the result of a further increase in counterparty risk and a soaring demand for liquidity, as now US banks were using FX swaps to obtain dollar liquidity as well . The CIP deviation of three-month rates even hit the 2 percentage point level . As reaction to increased strains, on October 13, 2008, the Fed and the ECB jointly decided to switch to an unlimited provision of liquidity through the swap facilities. We notice a drop in the devations from CIP , bringing 1 -month and 3-month deviations back below 1 percentage point levels. After these sharp declines, we see rates bouncing back . However, Goldberg, Kennedy et al. (2010) notice that this could be the result of an ap proaching critical year end. The first two announcements following the announcement about the unlimited provision were the largest performed in the swap facility with a peak of $600 billion outstanding dollars, probably signaling both the high demand for dollar -liquidity and the approaching year end. Goldber, Kennedy et al . (2010) find proof that at least part of the increased strains were caused by the hoarding behaviour around the year end by observing - 118 - the decrease in outstanding balances in January 2009. Also in Figure 21, we notice a decrease in the deviation from the CIP at the beginning of January 2009.
The critical year end of 2008 makes it very difficult to draw any firm conclusions on the effectiveness of the swap facility in the post-Lehman period. However, we do notice that once the year end has passed, the 3-month rates devation of the CIP remain below 0.5 percentage points. This could give an indication that the dollar provision has ameliorated the dollar shortage problem in the euro area. However, Goldberg, Kennedy et al. (2010) mention that also other factors could have helped to reduce the deviations from the CIP. Many banks had written down their dollar-denominated credit-related assets and therefore their dollar funding needs were reduced. Also the biggest suppliers of dollars in FX swaps became more willing to lend dollars to foreign banks as their acces to dollars also had improved. Last, as a result of a return to more conservative liquidity management practices at global financial institutions and a tightened regulation, the reliance on short-term cross- currency funding had reduced. In paragraph 6.1.3, we will test whether the swap lines have been effective in relieving strains in the FX swap market.
6.1.2 Data
In our regressions, we will use the changes in deviation from CIP as the dependent variable. The FX swap-implied three-month dollar rates (which is “the total cost of raising dollars using euro as a funding currency through the FX swap market” (Baba and Packer 2009, p. 1353)) are calculated with spot and forward rates taken from Thomas Reuters, and with the 3-month uncollateralized euro interest rate as published by the British Bankers’ Association. The calculations of the deviation from the CIP, are based on the formula Baba and Packer (2009), and are performed as follows 80 :
, 1 , 1 ,
80 For the calculations, we expressed the funding schemes in 3 month and 1 month maturities respectively. Subsequently, we expressed both FX swap deviations from CIP in the 3-month maturity to make a useful comparison in the graph. - 119 - with the deviation from the CIP on day t and the USD Libor as published by the BBA , on day t with a maturity of s. is the FX forward rate contracted at time t for exchange , at time t+s. is the FX spot rate at time t. For our basis regressions we will set s to 3 months, but we will test the robustness of our regressions with s equalling 1 month 81 .
To test the impact of the measures that the Fed and the ECB jointly initiated, we create the following set of variables. First, three dummy variables are set to one on important announcement days. SWAP INITIAL is set to one on December 12 th 2007, as then the first TAF auction of US Dollars in the euro area was announced. SWAP_LONG INITIAL is set to one on July 30 th 2008, because on that day TAF-auctions with a maturity of 84 days were announced. Last, FRFA INITIAL is set to one on October 13 th , 2008 as then an unlimited swap line between Fed and ECB was announced. Furthermore, we compose a variable,
SWAP EXTENSION which is set to one on each day that the Fed and ECB announced jointly that the swap lines would be extended to a certain future date. Furthermore, time window variables are created with the methodology earlier described (see above, p. 55). We also create four variables to measure the impact of the swap operations that took place between the Federal Reserve and the European Central Bank. SWAP OVERNIGHT is set to one on each day an operation with an overnight maturity performed, SWAP MEDIUM is set to one on each day an operation with a maturity between overnight and 9 days is performed, SWAP LONG is set to one on each day an operation with a maturity between 10 and 28 days is performed and SWAP VERYLONG is set to one on each day an operation with a maturity longer than 28 days is performed. We would expect that the three above-mentioned important announcements had a significant negative impact on the FX swap deviations from CIP. Moreover, announcements on the extension of the facility could reveal new information to the market and therefore we would also expect a significant negative impact of these announcements. However, as described earlier (see above, p. 55), we would not expect the operations to have a significant impact.
81 As Libor rates are published by the BBA at 11 a.m., these rates contain more information about the day before. Baba 2008 noticed that this could lead to a higher volatility in FX swap deviations than otherwise. We have performed all our regressions by using the Libor rate of day t+1 on day t and found similar results. - 120 -
The composition of our set of control variables is based on Baba and Packer (2009). Libor rates are derived from a set of Libor panel banks, while FX swap-implied dollar rates reflect funding costs of a wider range of financial institutions. Therefore we add the changes in the 3-month Eurodollar deposit rate – OIS spread to control for these differences. For these variables, we expect to find a positive impact on the deviations from CIP 82 . Moreover, we add the changes in CDS-rates of both the United States and Europe to control for the asymmetry of counterparty risk, as this could influence the FX swap deviations from the covered interest parity. Baba and Packer (2009) state that in the pre-Lehman period, the CDS of European institutions would have a positive impact on deviations from CIP, and the CDS of American institutions would have a negative impact, as American institutions were on the lending side in these transactions 83 . In the post-Lehman period however, Baba and Packer (2009) expect both CDS rates to have a positive effect on the deviations from CIP as then both sides of the ocean are on the demanding side for dollar liquidity. For the United States, we use the CDS rate of the Bank of America. Although this CDS is not ideal as measure for counterparty risk of US financial institutions, a lack of data prohibits the use of a more appropriate CDS. For Europe, we use the senior CDS spread for European financial institutions. Last, we include the changes in the Libor-OIS spread to control for funding liquidity conditions in the US dollar cash market. We refer to Baba and Packer et al. (2009) for more details on these control variables.
For more information and for the source of our data, we refer to Exhibit 7.
6.1.3 Econometrical analysis
When we take a look at the literature on the swap facilities between the Federal Reserve and the European Central Bank, various authors seem to agree on the effectiveness (Baba and Packer 2009; Goldberg, Kennedy et al. 2010). Only Baba and Packer (2009) perform econometrical regressions. The authors find that in the pre-Lehman period, the announcements nor the operations executed a significant impact on FX swap deviations. For the post-Lehman period, they find that the announcement of October 13th reduced FX
82 For more details, we refer to Baba and Packer (2009) 83 For more information on the rationale behind this, we refer to Baba and Packer (2009) - 121 - swap deviations from CIP conditions with around 30 basis points. Moreover, the authors find that especially swap facility operations at longer maturities (28+ days) were effective in ameliorating the problems of dollar shortage in FX swap markets and in reducing FX swap deviation volatility (-69 bp).
First we perform the following regression in which we test the effect of three important announcements, concerning the initiation, maturity and full rate full allotment. For further details on these variables, we refer to paragraph 6.1.2 and Exhibit 7.
∆ _ _
_ _ _
(1) with Y t the FX swap deviation from the CIP condition 3 month. We include the lag of the dependent variable for the case that the changes in the deviation are dependent on the level. The Fed together with the ECB announced on October 13 th that unlimited dollar liquidity would be provided in the swap operations. This gave a strong signal to the market of the willingness of the central banks to go through great lengths in combating the strains in the FX swap market. It is therefore that we expect this announcement to be the most effective of all three announcements.
The results are shown in Table 7. As expected in section 6.1.1, the announcement of both July 30 and December 12 do not significantly influence the deviations from the covered interest parity. In contrast, the radical announcement of October 13 th does appear to have a significant negative impact of 28 basis points. This is consistent with Baba and Packer (2009), who find a reduction in FX swap deviations of 30 basis points as a result of this announcement. Moreover these results are consistent with the view of many market observes who argue that the swap lines between the Federal Reserve and the European Central Bank were especially effective from mid-October 2008 on (Baba and Packer 2009). If we look in the days following this regressions, we notice a further decline of 54 basis - 122 - points. However, in begin October 2008 many other innovative measures were announced at both central banks. This could lead to an overestimation of the impact of the announcement of October 13 th .
Next, we add our set of control variables, and perform the following regression:
∆ _ _
_ _ _
∆ ∆
∆ _ ∆ _ (2) with Y t the 3-month FX swap deviation from the CIP condition.
The results are shown in Table 7. We can observe similar results, with a decline in the deviation from CIP of 23 basis points and a lagged decline of 34 basis points. Next, we add the variables that must measure the impact of the operations on the deviation from CIP. We perform the following regression:
∆
∆
∆ ∆ ∆
(3) with Y t the 3-month FX swap deviation from the CIP condition. Analogously to other regressions, we do not expect operations to have a significant negative impact.
These results can be found in Table 7 from which we can observe that the operations did not have any negative significant impact and thus confirms our expectations. This is in contrast with Baba and Packer (2009). The insignificant impact could be explained by the fact that all information was already incorporated immediately after the announcements or
- 123 - by the choice/limitation of our data. The announcement of October 13 th however keeps it significant negative impact.
To uncover the cause for this difference in results, we adapt our dataset to perform similar regressions as Baba and Packer (2009). We use the levels of the deviations from CIP and apply the same variables to measure the impact of the operations as published in Baba and Packer (2009). When we perform these regressions, we do not succeed in finding similar results. We expect that these differences are the result of the CDS variables we use in our regressions. In paragraph 6.1.2, we already noticed that our CDS variables are not ideal. These results show that the impact we found of the announcement of October 13 th could be underestimated. Also the insignificant impacts of the operation variables we found in our earlier regressions could be caused by our inappropriate CDS variables.
To check the robustness of our results, we performed regression (2) on the 1-month FX swap deviations from CIP. The results of regression (4) are displayed in Table 7.
We can conclude that the announcement of unlimited swap lines between the Federal Reserve and the European Central Bank has reduced the deviation from CIP and therefore has had an ameliorating impact on the conditions in the FX swap market. Consistent to Baba and Packer (2009), we find a decreasing impact of 23 basis points as a result of the announcement of unlimited swap lines on October 13 th . From the graph in paragraph 6.1.1, we can observe that this decrease was short-lived. However, various authors argued a very turbulent course in the build-up to the year end of 2008 which could have caused the resurgence of the basis swap spread at the end of October 2008. Albeit our lack of appropriate CDS variables prohibits us to accurately measure the impact of the operations under the swap facility, different authors (Baba and Packer 2009; Goldberg, Kennedy et al. 2010) seem to agree that these operations, and especially those US dollar auctions at longer maturities, have ameliorated the problems of dollar shortage in FX swap markets.
- 124 -
First differences of CIP deviation 3 month maturity First differences of CIP deviation 1 month maturity (1) (2) (3) (4)* DayAnt. Lag Day Ant. Lag Day Ant. Lag Day Ant. Lag Not. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. Est. t-stat Est. Est. C 1,33 3,82 *** 2,04 4,28 *** 2,37 4,89 *** 4,62 3,87 *** CIP_DEV_3M(-1) -5,98 -5,08 *** -7,90 -5,48 *** -11,89 -6,90 *** ∆ EURODOLLAR-OIS_3M 27,37 7,12 *** 28,14 7,40 *** 56,53 1,54 ∆ LIBOR-OIS_3M -12,15 -1,70 * -9,22 -1,29 -38,35 -0,81 ∆ CDS_BANKS 0,07 1,17 0,05 0,79 -0,11 -0,41 ∆ CDS_BOA 0,08 2,30 ** 0,06 1,94 * 0,12 1,23 CIP_DEV_1M(-1) -20,83 -4,16 ***
SWAP_INITIAL -3,77 -0,52 -3,19 -0,41 -2,75 -0,35 -1,89 -1,05 -12,74 31,65 SWAP_LONG -4,55 -0,63 -4,12 -0,52 -3,98 -0,51 -21,77 -24,03 *** 10,22 -15,71 FRFA_INITIAL -28,61 -3,91 *** 40,65 -54,17 -23,29 -2,88 *** 47,12 -34,03 -20,02 -2,49 *** 46,12 -50,33 -53,89 -4,39 *** 143,02 -57,36 OPERATION_OVERNIGHT 4,67 4,45 *** OPERATION_MEDIUM 0,43 0,47 OPERATION_LONG -1,39 -0,68 OPERATION_VERYLONG 0,23 0,15 13% 21% 23% 19%
Table 7: FX swap market Notes: (a) Newey-West standard errors are used in regression models signaled with a ()* (b) Ant. Est = Anticipation effect estimate = sum of the significant estimates in the time window before the announcement. (c) Lag Est = Lagged effect estimate = sum of the significant estimates in the time window after the announcement (d) The results are expressed in basis points (e) * significant at 10%; ** significant at 5%; *** significant at 1%.
- 125 -
7 CONCLUSION
The financial turmoil that began in August 2007 has made financial markets quiver all over the world. Strains in financial markets got more and more elevated as a result of the distrust that arose among financial institutions and their unwillingness to lend to one another. In September 2008, after the collapse of Lehman Brothers, the turmoil evolved into a full financial crisis that lashed out hard to financial markets and institutions. These highly exceptional times have enticed central banks to interfere and to initiate as exceptional measures. With key interest rates evolving towards the lower bound, central banks were forced to initiate innovative and unconventional measures. The monetary policy response of central banks all over the world has been very distinct. The goal of this work is to make a comparison between the policy responses of the Federal Reserve and the European Central Bank, and to measure whether the non-standard measures these central banks initiated have been able to relieve the strains in financial markets.
The considerable differences in economic and financial structure that exist between the United States and the euro area have played a major role in shaping the monetary policy response. Where in the euro area the banking system is of major importance for the financing of households and non-financial institutions, in the United States, this is much less the case. Given this importance of banks in the euro area, the European Central Bank was left no other choice than provide support to the interbank market. All non-standard measures that have been initiated at the ECB have been focused on relieving strains in this interbank market. Even the Covered Bond Purchase Program served this purpose, as covered bonds had been a major source of funding for banks in the pre-crisis period. The Federal Reserve, in contrast, had to go through much greater lengths. Although the measures initiated in the pre-Lehman period, namely the Term Auction Facility, the Treasury Securities Lending Facility and the Primary Dealer Credit Facility, had been focusing on the interbank market, the seism that hit financial markets after September 2008 incited the Federal Reserve to initiate facilities for a broader range of financial markets. Given the importance of the shadow banking system for the financing of households and
- 126 - non-financial institutions in the United States, the Federal Reserve decided to intervene in the commercial paper market and the asset-backed securities market (by initiating the AMLF, the CPFF and the TALF). Moreover, a large-scale asset purchase (LSAP) program that would purchase up to $1.75 trillion in agency debt, agency mortgage-backed securities and Treasury securities was introduced.
The initiation of a whole toolbox of innovative measures created an interesting opportunity for research to academics and central bankers and has led to a rather extended literature on the specific measures introduced at both central banks. However, in this work we take a more holistic view and we apply one similar methodology to measure the impact of the non-standard measures introduced during the financial crisis. In particular, we focus on the impact of announcements of non-standard measures in soothing financial strains, as these announcements make public the most relevant information to the markets, whereas the operations are solely an implementation of these announcements. Therefore, the market response to the announcements of the various newly introduced measures should give a clear indication on the effectiveness. For the purpose of measuring this impact, we have assembled a very extensive dataset. However, in some regressions, we have not been able to access the most appropriate variables. Although such lack of appropriate variables could lead to under- or overestimations of the effect of the non-standard measures in relieving financial strains, we have performed extensive robustness checks and in almost all regressions, we have found results that were in line with the existing literature.
In general, we can conclude that, albeit the considerable differences in monetary policy response, both central banks have been effective in relieving financial strains. Our results suggest that the ECB has been effective in reducing the strains in the European interbank market. We find a significant negative impact on the Euribor-OIS spread of many of the announcements concerning the introduction of non-standard measures. Moreover, some very basic regressions show signs of the success of the Covered Bond Purchase Programme. For the Fed, the econometrical analysis imposed a greater effort. In all of the financial markets discussed throughout this work, namely the interbank market, the commercial paper market and the asset-backed securities market, we find significant improvements - 127 - that could be attributed to the measures initiated by the Federal Reserve. Also the Large- Scale Asset Purchase program, of which we focus on the Treasury purchases, proves to have had significant impacts, not only in reducing Treasury yields but also by spill over effects to securities that were not included in the purchase program, as for example Baa corporate bond yields. Last, we examined the joint measure initiated by the Federal Reserve and the European Central Bank to provide dollar liquidity to the euro area via swap lines and we find significant improvements in FX swap market conditions.
Although we will never know how market conditions would have evolved without central bank intervention and although it is still too early to shout victory, as many financial experts state that the financial crisis has not yet totally ebbed away, we can conclude that the monetary response to the financial crisis of both the Federal Reserve and the European Central Bank has been effective. We find that especially by responding to the financial crisis with non-standard measures that were tailored to the economical and financial structure of the United States and the euro area respectively, the Fed and the ECB have successfully soothed the strains in financial markets.
- 128 -
REFERENCES
Abbassi, P. and T. Linzert (2011). "The Effectiveness of Monetary Policy in Steering Money Market Rates during the Recent Financial Crisis." Working Paper Series.
Abbassi, P. and D. Nautz (2010). “Monetary transmission right from the start the (dis)connection between the money market and the ECB’s main refinancing rates”. Berlin, Freie Univ. Berlin
Acharya, V. V. and O. Merrouche (2010). “Precautionary hoarding of liquidity and inter-bank markets: Evidence from the sub-prime crisis”, National Bureau of Economic Research.
Adrian, T. (2010). “Shadow Banking System: Implications for Financial Regulation”, DIANE Publishing.
Adrian, T., C. R. Burke, et al. (2009). "The Federal Reserve s Primary Dealer Credit Facility." Current Issues in Economics and Finance, Vol. 15, No. 4, August 2009.
Adrian, T., K. J. Kimbrough, et al. (2010). "The Federal Reserve s Commercial Paper Funding Facility." SSRN eLibrary.
Allen, F. and D. Gale (2000). “Comparing financial systems.” Cambridge (Mass.), MIT press.
Andersen, T. G., T. Bollerslev, et al. (2002). “Micro effects of macro announcements: Real- time price discovery in foreign exchange”, National Bureau of Economic Research Cambridge, Mass., USA.
Angelini, P., A. Nobili, et al. (2009). “The Interbank Market after August 2007: What has changed, and why?” The CEPR/ESI 13th Annual Conference on ‘Financial Supervision in an Uncertain World’ Venice.
Armantier, O., E. Ghysels, et al. (2010). "Stigma in Financial Markets: Evidence from liquidity auctions and discount window borrowing during the crisis." Unpublished paper, Federal Reserve Bank of New York.
Armantier, O., S. Krieger, et al. (2008). "The Federal Reserve’s Term Auction Facility." Federal Reserve Bank of New York Current Issues in Economics and Finance 14(5).
Aucremanne, L., J. Boeckx, et al. (2007). "Het liquiditeitsbeheer van het Eurosysteem tijdens de periode van financiële beroering." Economisch Tijdschrift: 29.
Aucremanne, L., J. Boeckx, et al. (2007). "Rentebeleid versus geldbasisbeleid: gevolgen voor de centrale-bankbalans." Economisch Tijdschrift: 19.
VI
Baba, N. and F. Packer (2009). "From turmoil to crisis: dislocations in the FX swap market before and after the failure of Lehman Brothers." Journal of International Money and Finance 28(8): 1350-1374.
Beirne, J., L. Dalitz, et al. (2011). "The impact of the Eurosystem's covered bond purchase programme on the primary and secondary markets." Occasional Paper Series.
Bernanke, B. (2007a). "Global Imbalances: Recent Developments and Prospects." Bundesbank Lecture speech, September.
Bernanke, B. (2007b). "National and regional economic overview: a speech at the presentation of the Citizen of the Carolinas Award, Charlotte Chamber of Commerce”, Charlotte, North Carolina, November 29, 2007.
Bernanke, B. (2008). "Federal Reserve policies in the financial crisis." Speech to the Greater Austin Chamber of Commerce, Austin, Texas 1.
Bernanke, B. (2009). "The crisis and the policy response: a speech at the Stamp Lecture, London School of Economics, London, England, January 13, 2009."
Berndt, A. and A. Gupta (2009). "Moral hazard and adverse selection in the originate-to- distribute model of bank credit." Journal of Monetary Economics 56(5): 725-743.
Boeckx, J. (2011), Personal communication with Boeckx J., February 12, 2010, National Bank of Belgium.
Borio, C. E. and P. Disyatat (2009). "Unconventional Monetary Policies: An Appraisal." SSRN eLibrary.
Brunetti, C., M. Di Filippo, et al. (2009). "Effects of Central Bank Intervention on the Interbank Market during the Sub-Prime Crisis." SSRN eLibrary.
Brunnermeier, M. K. (2009). "Deciphering the Liquidity and Credit Crunch 2007-2008." Journal of Economic Perspectives 23(1): 77-100.
Buiter, W. H. (2008). "Lessons from the North Atlantic financial crisis." The First Global Financial Crisis of the 21st Century: 129.
Bullard, J. (2009). "Effective monetary policy in a low interest rate environment." Speech(Mar 24).
Bullard, J. (2010). "Three lessons for monetary policy from the panic of 2008." Federal Reserve Bank of St. Louis Review 92(3): 155-163.
VII
Campbell, S., D. Covitz, et al. (2011). "Securitization Markets and Central Banking: An Evaluation of the Term Asset-Backed Securities Loan Facility." Finance and Economics Discussion Series.
Cassola, N., C. Holthausen, et al. (2009). "Liquidity management under market turmoil: experience of the European Central Bank in the first year of the 2007-2008 financial market crisis." The First Credit Market Turmoil of the 21st Century: Implications for Public Policy 10: 195.
Cassola, N., A. Hortaçsu, et al. (2009). The 2007 Subprime Market Crisis Through the Lens of European Central Bank Auctions for Short-Term Funds, National Bureau of Economic Research Cambridge, Mass., USA.
Cecchetti, S. G. (2008). "Monetary policy and the financial crisis of 2007-2008." CEPR Policy Insight.
Christensen, J. H. E., J. A. Lopez, et al. (2009). "Do central bank liquidity facilities affect interbank lending rates?" Federal Reserve Bank of San Francisco Working Paper 13.
Covitz, D. M., N. Liang, et al. (2009). "The Evolution of a Financial Crisis: Panic in the Asset- Backed Commercial Paper Market." SSRN eLibrary.
Crippen, D. L. (2001). "Federal Subsidies for the Housing GSEs." Testimony before the Subcommittee on Capital Markets, Insurance and Government Sponsored Enterprises of the House Committee on Financial Services, 107th Cong., 1st sess.
D’Amico, S. and T. B. King (2010). "Flow and stock effects of large-scale Treasury purchases." Finance and Economics Discussion Series 52.
Doh, T. (2010). "The efficacy of large-scale asset purchases at the zero lower bound." Federal Reserve Bank of Kansas City Economic Review: 5—34.
Dudley, W. (2009). "A preliminary assessment of the TALF." Speech(Jun 4).
Dudley, W. C. (2007). "May you live in interesting times." Remarks at the Federal Reserve Bank of Philadelphia, October 17.
Duygan-Bump, B., P. M. Parkinson, et al. (2010). "How Effective Were the Federal Reserve Emergency Liquidity Facilities? Evidence from the Asset-Backed Commercial Paper Money Market Mutual Fund Liquidity Facility." FRB of Boston Quantitative Analysis Unit Working Paper No. 10-3.
ECB (2006). "The predictability of the ECB's monetary policy." Monthly Bulletin October
ECB (2009). "Monthly Bulletin October." (October 2009). VIII
Fleming, M. J., F. Keane, et al. (2009). "The Term Securities Lending Facility: Origin, Design, and Effects." Current Issues in Economics and Finance, Vol. 15, No. 2, February 2009.
Friedman, B. M. and K. N. Kuttner (2010). “Implementation of monetary policy: How do central banks set interest rates?”, National Bureau of Economic Research.
Furfine, C. (2001). "The reluctance to borrow from the Fed." Economics Letters 72(2): 209- 213.
Furfine, C. (2003). "Standing Facilities and Interbank Borrowing: Evidence from the Federal Reserve's New Discount Window." International Finance 6(3): 329-347.
Fuster, A. and P. Willen (2010). "$1.25 Trillion is Still Real Money: Some Facts about the Effects of the Fed’s Mortgage Market Investments." Federal Reserve Bank of Boston Public Policy Discussion Papers, No. 10-4.
Gagnon, J. E., M. Raskin, et al. (2010). "Large-Scale Asset Purchases by the Federal Reserve: Did They Work?" SSRN eLibrary.
Goldberg, L. S., C. Kennedy, et al. (2010). “Central bank dollar swap lines and overseas dollar funding costs”, National Bureau of Economic Research Cambridge, Mass., USA.
González-Hermosillo, B. (2008). “Investors' risk appetite and global financial market conditions”, International Monetary Fund.
Goodfriend, M. (1997). "Monetary policy comes of age: a 20th century odyssey." Federal Reserve Bank of Richmond Economic Quarterly 83(1): 1.
Goodfriend, M. (2002). "Interest on reserves and monetary policy." Federal Reserve Bank of New York Economic Policy Review 8(1): 13-29.
Gorton, G. and A. Metrick (2009). “ The Run on Repo and the Panic of 2007-2008”, Yale working paper.
Greenlaw, D., J. Hatzius, et al. (2008). “Leveraged losses: lessons from the mortgage market meltdown”, Citeseer.
Greenwood, R. and D. Vayanos (2010). "Price pressure in the government bond market." American Economic Review 100(2): 585-590.
Hamilton, J. D. and D. H. Kim (2002). "A reexamination of the predictability of economic activity using the yield spread." Journal of Money, Credit, and Banking 34(2): 340-360.
Hamilton, J. D. and J. C. Wu (2011). “The Effectiveness of alternative monetary policy tools in a zero lower bound environment”, National Bureau of Economic Research.
IX
Hauck, A. and U. Neyer (2010). "The euro area interbank market and the liquidity management of the eurosystem in the financial crisis." DICE Discussion Papers.
Hooper, P. and T. Slock (2009). "Are the Fed’s Programs Working?." Deutsche Bank Global Economic Perspectives.
Kacperczyk, M. and P. Schnabl (2010). "Does Organizational Form Affect Risk Taking? Evidence from Money Market Mutual Funds."
Kamps, A. (2009). "What drives international money market rates? Lessons from a Cointegration VAR Approach."
Keister, T., A. Martin, et al. (2008). "Divorcing Money from Monetary Policy." SSRN eLibrary.
Kim, D. H. and J. H. Wright (2005). “An arbitrage-free three-factor term structure model and the recent behavior of long-term yields and distant-horizon forward rates”, Federal Reserve Board, Divisions of Research & Statistics and Monetary Affairs.
Klyuev, V., P. de Imus, et al. (2009). "Unconventional Choices for Unconventional Times."
KPMG (1993). “Banking and finance in the United States”. New York, KPMG Peat Marwick.
Krishnamurthy, A. and A. Vissing-Jorgensen (2011). “The effects of Quantitative Easing on Interest Rates. Macroeconomic impact of non-standard monetary policy measures.” Conference ‘Macroeconomic impact of non-standard monetary policy measures’, Frankfurt Am Main.
Lemmen, J. J. G. (1993). “An introduction to the Diamond-Dybvig model”: (1983).
Lenza, M., H. Pill, et al. (2010). "Monetary policy in exceptional times." Economic Policy(62): 295-339.
Madura, J. (2008).” Financial markets and institutions”, Cengage Learning.
Marzo, M., L. Zhoushi, et al. (2011). "The Relationship Between Financial Risk Premia and Macroeconomic Volatility: Issues and Perspectives on the Run-Up to the Turmoil." Working Papers.
McAndrews, J., A. Sarkar, et al. (2008). "The Effect of the Term Auction Facility on the London Inter-Bank Offered Rate." SSRN eLibrary.
Meyer, L. H. (2010). “Some Empirical Evidence on the Effectiveness of Monetary Policy at the Zero Bound. Revisiting Monetary Policy in a Low Inflation Environment”. Federal Reserve Bank of Boston.
X
Michaud, F. L. and C. Upper (2008). "What drives interbank rates? Evidence from the Libor panel." BIS Quarterly Review 3: 47–58.
Mishkin, F. S. (2006). “The economics of money, banking, and financial markets.” Boston, Pearson/Addison Wesley.
Mizen, P. (2008). "The credit crunch of 2007-2008: A discussion of the background, market reactions, and policy responses." Federal Reserve Bank of St Louis Review 90(5): 531-567.
Murphy, E. (2009). “Money Market Fund Reform. Securities and Exchange Commission: Proposed Rules, Securities and Exchange Commission”. Release No. IC-28807; File No. S7- 11-09.
N.B.B. (2010). “Economische en financiële ontwikkeling” jaarverslag 2009, NBB, Brussel.
Packer, F., R. Stever, et al. (2007). "The covered bond market." BIS Quarterly Review 34(3): 43-55.
Pelizzon, L., D. Sartore, et al. "Deciphering the Libor and Euribor Spreads during the Subprime crisis
Poole, W. (1970). "Optimal choice of monetary policy instruments in a simple stochastic macro model." The Quarterly Journal of Economics 84(2): 197.
Pozsar, Z., T. Adrian, et al. (2010). "Shadow banking." Federal Reserve Bank of New York Staff Report 458.
Prescott, E. S. (2010). "Introduction to the special issue on the Diamond-Dybvig model." Economic Quarterly: 1-9.
Purnanandam, A. (2009). "Originate-to-distribute model and the subprime mortgage crisis."
Ratings, F. (2007). "Asset-Backed Commercial Paper explained." Structured Finance Asset- Backed Criteria Report 8.
Reis, R. (2010). “Interpreting the unconventional US monetary policy of 2007-09”, National Bureau of Economic Research Cambridge, Mass., USA.
Rudebusch, G. D., B. P. Sack, et al. (2007). "Macroeconomic implications of changes in the term premium." Review-Federal Reserve Bank of Saint Louis 89(4): 241.
Sarkar, A. (2009). "Liquidity risk, credit risk, and the federal reserve’s responses to the crisis." Financial Markets and Portfolio Management 23(4): 335-348.
Schmaltz, C. (2009). “A Quantitative Liquidity Model for Banks”.
XI
Schwarz, K. (2009). "Mind the gap: disentangling credit and liquidity in risk spreads." Unpublished manuscript.
Sengupta, R. and Y. M. Tam (2008). "The LIBOR-OIS spread as a summary indicator." Monetary Trends(Nov).
Stark, J. (2008). "Monetary policy during the financial turmoil - what have we learned? : a speech at the conference "The ECB and its Watchers X", Frankfurt am Main, Germany, 5 September 2008."
Stroebel, J. C. and J. B. Taylor (2009). “Estimated impact of the Fed’s mortgage-backed securities purchase program”, National Bureau of Economic Research Cambridge, Mass., USA.
Taylor, J. B. (2009). “The financial crisis and the policy responses: An empirical analysis of what went wrong”, National Bureau of Economic Research Cambridge, Mass., USA.
Taylor, J. B. and J. C. Williams (2008). "A Black Swan in the Money Market." National Bureau of Economic Research Working Paper Series No. 13943
Taylor, J. B. and J. C. Williams (2008). "Further results on a black swan in the money market." Federal Reserve Bank of San Francisco, working paper.
Thornton, D. L. (2009). "What the Libor-OIS spread says." Economic Synopses.
Trichet, J. C. (2008). "Some lessons from the financial market correction." Speech delivered at the “European Banker of the Year 2007".
Trichet, J.-C. (2009a). The ECB's enhanced credit support. Munich, CESifo.
Trichet, J. C. (2009b). Credible alertness revisited.
Tucker, P. (2009). "The Repertoire of Official Sector Interventions in the Financial System: Last Resort Lending, Market-Making, and Capital: a speech at the Bank of Japan's 2009 International Conference in Tokyo, Japan on 28 May 2009.
Vander Vennet, R. (2008). “Bank- en Financiewezen”, University of Ghent.
Verplaetse, A. (2011). Personal communication with Verplaetse, A, National Bank of Belgium, Brussels.
Whaley, R. E. (2009). "Understanding the VIX." Journal of Portfolio Management 3: 98-105.
Wu, T. (2008). "On the Effectiveness of the Federal Reserve's New Liquidity Facilities." SSRN eLibrary.
XII
Yellen, J. (2011). “The Federal Reserve’s Asset Purchase Program.”
XIII
Exhibits
VII
Exhibit 1 Balance sheet policy during the crisis
Source: Borio and Disyatat (2009)
VIII
Exhibit 2 Data description US interbank market
Variable Source Unit Description
Libor stands for London InterBank Offered Rate and is published by Thomson Reuters British on behalf of the British Bankers’ Association (BBA)84 . The Libor rates are published Bankers’ daily by 12 noon UK time. Because the contributor panel is chosen by the Foreign Association Exchange and Money Markets Committee (FX&MM Committee) to give the best LIBOR 3M (BBA) Percentages representation of activity within the London money market, the rates represent the (obtained lowest real-world cost of unsecured funding in a certain currency with maturities from ranging from overnight to one year. Rather then being a tradable rate, the Libor is a datastream) reference rate in financial instruments and serves as a benchmark for short-term interest rates globally.
OIS stands for Overnight Indexed Swap, which is a contract in which two parties agree to swap fixed rate interest payments against a floating rate interest payments, whereby this floating leg is tied to a published index of a daily overnight rate benchmark. For swaps based on the United States dollar (USD), this is the daily effective federal funds rate. At maturity, the two parties exchange the difference between the interest that would be accrued at the agreed fixed rate and interest that OIS Datastream Percentages 3M would be accrued from repeatedly rolling over an investment in the overnight market at the floating rate, which is calculated as the geometric average of the overnight benchmark, in particular the effective federal funds rate. As no principal, and only the difference in interest rates is exchanged, and because the OIS market is very liquid, OIS transactions involve very little credit and liquidity risk. The rate is quoted at 4:30 pm EST.
84 Under supervision of the BBA and using the definitions provided by the FX&MM Committee, Thomson Reuters assembles the rates at which the panel of 16 contributors could borrow funds by asking and then accepting inter-bank offers in a reasonable market size just prior to 11 am UK time (which equals 6 am EST). To increase the accuracy, bottom and top quartiles are discarded and the average of the middle two quartiles is averaged IX
1 on December 12, 2007 Federal TAF Dummy 0 otherwise INITIAL Reserve Initial announcement
TAF WINDOW_1 is 1 on December 7, 2007 and 0 otherwise TAF WINDOW_2 is 1 on December 10, 2007 and 0 otherwise TAF WINDOW_3 is 1 on December 11, 2007 and 0 otherwise TAF WINDOW_i Dummy TAF WINDOW_4 is 1 on December 13, 2007 and 0 otherwise TAF WINDOW_5 is 1 on December 14, 2007 and 0 otherwise TAF WINDOW_6 is 1 on December 17, 2007 and 0 otherwise Time window dummies
1 if general announcement 0 otherwise Federal These general announcements are not related to specific operations, but concern TAF Dummy GENERAL Reserve changes in the amounts offered in the TAF auctions, and about the expected future frequency 85 of them. Also the initial announcement of the program and the announcement regarding the final auction of the TAF are included.
1 if announcement on auction conditions Federal 0 otherwise TAF Dummy CONDITION Reserve As a first step in a TAF operation, the Fed announces the TAF auction conditions, with the minimum bid rate as most important element.
1 if announcement on auction execution Federal TAF Dummy 0 otherwise AUCTION Reserve On these days, banks make a bid for the offered funds.
85 Although the announcements, starting on June 25, 2009, that the amounts auctioned in the TAF would be reduced seem opposite to the previous announcements, we consider them as positive signals and assign these a positive value on the corresponding dates. We find supportive arguments for this in the mentioned announcement (
1 if announcement on notification of auction results Federal TAF Dummy 0 otherwise NOTIFICATION Reserve On these days, the results of the TAF auctions are notified.
Federal 1 if TAF TAF or TAF TAF Dummy CONDITION, AUCTION NOTIFICATION OPERATIONS Reserve 0 otherwise
Federal This variable is calculated as: Reserve, Millions of TAF TAF (t) = TAF (t-1) + TAF loans issued at day t – TAF OUTSTANDING authors’ dollars OUTSTANDING OUTSTANDING calculations loans maturing at day t
1 on March 11, 2008 Federal PDCF Dummy 0 otherwise INITIAL Reserve Initial announcement
PDCF WINDOW_1 is 1 on March 6, 2008 and 0 otherwise PDCF WINDOW_2 is 1 on March 7, 2008 and 0 otherwise PDCF WINDOW_i Dummy PDCF WINDOW_3 is 1 on March 10, 2008 and 0 otherwise Time window dummies
PDCF_TSLF WINDOW_1 is 1 on March 12, 2008 and 0 otherwise PDCF_TSLF WINDOW_2 is 1 on March 13, 2008 and 0 otherwise PDCF_TSLF WINDOW_i Dummy PDCF_TSLF WINDOW_3 is 1 on March 14, 2008 and 0 otherwise These dummies represent the overlapping time windows between the PDCF and the TSLF.
1 if general announcement Federal 0 otherwise PDCF Dummy GENERAL Reserve These general announcements include the initial announcement, and announcements on the extension of the facility.
XI
1 each Thursday since initial announcement 0 otherwise Federal PDCF Dummy Each Thurday, generally at 4:30 p.m. a report was published that contained OPERATIONS Reserve the total amount of PDCF credit outstanding at the close of business on the prior business day and the average daily amounts for each week
Federal
Reserve/ SWAP Dummy 1 on each day a general announcement is made European 0 otherwise Central Bank
TSLF WINDOW_1 is 1 on March 17, 2008 and 0 otherwise TSLF WINDOW_2 is 1 on March 18, 2008 and 0 otherwise TSLF is 1 on March 19, 2008 and 0 otherwise Federal WINDOW_3 TSLF Dummy The TSLF was announced on March 16, 2008. However, this was a Sunday WINDOW_i Reserve and weekends are not included in our dataset. Therefore, the initial announcement is not included. The impact of the TSLF should be captured with these three time window dummies.
Credit Default Swap of the Bank of America with a 5-year maturity. In a Credit Default Swap (CDS) contract, which is comparable to an insurance policy for a corporate bond, the buyer hedges against the risk of default of the bank issuing the corporate bond, by paying a regular fee to the seller of the contract who makes the promise to pay the difference between CDS Datastream BOA the par value and the market value of the corporate bond concerned, in the event of bankruptcy or default 86 . The higher the probability that banks might default, the higher the fee that the seller will demand to guarantee the creditworthiness of the underlying corporate bond. Therefore, the CDS is a measure for counterparty risk.
86 More information about CDS can be found on the website of the Federal Reserve Bank of Atlanta
Chicago Board of Options Exchange Volatility Index. This a measure of implied volatility in the S&P 500 index (SPX) over the next 30-day period, which is then annualized. In literature, it is often referred to as the fear gauge 87 . Because the calculation of the VIX is based on the SPX option prices, it reflects the price of portfolio insurance 88 . The more volatility investors expect, the more portfolio insurance they will demand, the higher CBOEVIX Datastream Basis points the price of the insurance will be, and thus the higher the prices of the options. Therefore, a higher VIX index reflects a higher risk-aversion. Moreover, volatility leads to higher option prices because there is a greater probability that the options will expire in the money. Especially in periods of financial turmoil, when investors risk appetite is low due to expectations about a widespread re-pricing of risk 89 , the VIX typically reaches its highest levels.
Merrill Lynch Option Volatility Estimate index This index is comparable to the VIX-index, but it is a measure of implied MOVE Datastream Basis points volatility of Treasury options, in contrast to the VIX-index, which is a measure for the implied volatility of the SPX. Therefore, the MOVE-index is the bond market’s equivalent of the VIX-index.
S&P BANKS Datastream Index S&P Banks
1 on September 11,12, 15, 16 and 17, 2008 LEHMAN Dummy 0 otherwise
1 from three days before a quarter end Q Dummy ENDS set back to 0 three days after a quarter end.
87 For more information about the VIX, we refer to Whaley (2009). 88 For more details about the calculation of the VIX index, we refer to the VIX White paper:
Exhibit 3 Data description commercial paper market
Variable Source Unit Description
AA interest rates interpolated from data on certain commercial paper Federal trades settled by The Depository Trust Company. The trades represent sales Reserve’s of commercial paper by dealers or direct issuers to investors (that is, the ABCP Data Percentages offer side).For more information, we refer to Download
AA interest rates interpolated from data on certain commercial paper Federal trades settled by The Depository Trust Company. The trades represent sales Reserve’s of commercial paper by dealers or direct issuers to investors (that is, the CP Data Percentages offer side).For more information, we refer to Download
Interest rates interpolated from data on certain commercial paper trades Federal settled by The Depository Trust Company. The trades represent sales of Reserve’s commercial paper by dealers or direct issuers to investors (that is, the offer A2P2 Data Percentages side).For more information, we refer to Download
Federal 1 on September 19, 2008 AMLF Dummy ANNOUNCEMENT Reserve 0 otherwise Initial announcement XIV
AMLF ANNOUNCEMENT_1 is 1 on September 17, 2008 and 0 otherwise AMLF ANNOUNCEMENT_2 is 1 on September 18, 2008 and 0 otherwise Time window dummies. Normally, dummies are created for a time window of three AMLF Dummy ANNOUNCEMENT_i days. However, for this announcement, our time window is constricted due to the overlap with the time window of the Lehman variable (see below) and the AMLF OPERATION variable (see next)
Federal 1 on September 22, 2008 AMLF Dummy OPERATION Reserve 0 otherwise First operation.
AMLF OPERATION _1 is 1 on September 23, 2008 and 0 otherwise AMLF OPERATION _2 is 1 on September 24, 2008 and 0 otherwise AMLF OPERATION _3 is 1 on September 25, 2008 and 0 otherwise AMLF OPERATION_i Dummy AMLF OPERATION_4 is 1 on September 26, 2008 and 0 otherwise Time window dummies. Usually, a time window of three days is used. However, we define a four day window to perform robustness checks. The time window before the announcement is restricted by the time window of the initial announcement.
1 on October 7, 2008 Federal CPFF Dummy 0 otherwise ANNOUNCEMENT Reserve Initial announcement.
CPFF ANNOUNCEMENT_1 is 1 on October 2, 2008 and 0 otherwise CPFF ANNOUNCEMENT_2 is 1 on October 3, 2008 and 0 otherwise CPFF ANNOUNCEMENT_3 is 1 on October 6, 2008 and 0 otherwise CPFF ANNOUNCEMENT_i Dummy CPFF ANNOUNCEMENT_4 is 1 on October 8, 2008 and 0 otherwise CPFF ANNOUNCEMENT_5 is 1 on October 9, 2008 and 0 otherwise CPFF ANNOUNCEMENT_6 is 1 on October 10, 2008 and 0 otherwise CPFF ANNOUNCEMENT_7 is 1 on October 13, 2008 and 0 otherwise
XV
Time window dummies. We define a time window of 4 days (we add an extra dummy to test the robustness of our results). However, this time window overlaps with the control variables for the quarter end (see below), and therefore September 1, 2008 is not included.
Federal 1 on October 27, 2008 CPFF Dummy OPERATION Reserve 0 otherwise First operation.
CPFF ANNOUNCEMENT_1 is 1 on October 21, 2008 and 0 otherwise CPFF ANNOUNCEMENT_2 is 1 on October 22, 2008 and 0 otherwise CPFF ANNOUNCEMENT_3 is 1 on October 23, 2008 and 0 otherwise CPFF ANNOUNCEMENT_4 is 1 on October 24, 2008 and 0 otherwise CPFF OPERATION_i Dummy CPFF ANNOUNCEMENT_5 is 1 on October 28, 2008 and 0 otherwise CPFF ANNOUNCEMENT_6 is 1 on October 29, 2008 and 0 otherwise CPFF ANNOUNCEMENT_7 is 1 on October 30, 2008 and 0 otherwise CPFF ANNOUNCEMENT_8 is 1 on October 31, 2008 and 0 otherwise Time window dummies.
QEND_1 is 1 on September 29, 2008 and 0 otherwise QEND_2 is 1 on September 30, 2008 and 0 otherwise QEND_3 is 1 on October 1, 2008 and 0 otherwise QEND_i Dummy This variable controls for the difficult quarter end of September 2008. A time window of 1 day is used because otherwise an overlap with other time windows would occur.
LEHMAN 1 is 1 on September 12, 2008 and 0 otherwise LEHMAN i Dummy LEHMAN 2 is 1 on September 15, 2008 and 0 otherwise LEHMAN 3 is 1 on September 16, 2008 and 0 otherwise
Federal Funds Federal The Federal Funds target rate as can be obtained from the website of the Federal Percentages target rate Reserve Reserve. The obtained data was transformed to a daily variable.
XVI
Exhibit 4: Comparison of spreads on auto ABS issued in the US and Europe
`
XVII
Exhibit 5 Data description Large-Scale Asset Purchases
Variable Source Unit Description
Federal TREASURY 10Y / Reserve’s Yields on actively traded non-inflation-indexed issues adjusted to constant TREASURY 20Y / Data Percentages maturities. For more information, we refer to TREASURY 2Y Download
Federal Reserve’s The term premiums can be downloaded are from Kim and Wright (2005) from < TERMPREMIUM Data Percentages http://www.federalreserve.gov/econresdata/researchdata.htm> Download Program
Federal Reserve’s Moody's Baa rates. For more information, we refer to BAA_CORPORATE Data Percentages Download < http://www.federalreserve.gov/releases/h15/update/> Program
OIS 1Y Datastream Percentages cf. Exhibit 2
1 on November 25, 2008 NOVEMBER_25 Dummy 0 otherwise Initial LSAP announcement.
NOVEMBER_25 1 is 1 on November 20, 2008 and 0 otherwise NOVEMBER_25 i Dummy NOVEMBER_25 2 is 1 on November 21, 2008 and 0 otherwise NOVEMBER_25 3 is 1 on November 24, 2008 and 0 otherwise
XVIII
NOVEMBER_25 4 is 1 on November 26, 2008 and 0 otherw ise NOVEMBER_25 5 is 1 on November 27, 2008 and 0 otherwise NOVEMBER_25 6 is 1 on November 28, 2008 and 0 otherwise Time window variables.
1 on December 1, 2008 0 otherwise DECEMBER_1 Dummy Speech Bernanke: potentially substantial quantities of Treasury securities sill be purchased
DECEMBER_1 1 is 1 on December 2, 2008 DECEMBER_1 2 is 1 on December 3, 2008 DECEMBER_1 is 1 on December 4, 2008 DECEMBER_1 Dummy 3 i Time-window variables. Due to an overlap of time windows with the announcement of November 25, 2008, no dummies are created before the announcement of December 1, 2008
1 on December 16, 2008 0 otherwise DECEMBER_16 Dummy The Fed announced it was evaluating the potential benefits of purchasing longer- term Treasury securities.
DECEMBER_16 1 is 1 on December 11, 2008 and 0 otherwise DECEMBER_16 2 is 1 on December 12, 2008 and 0 otherwise DECEMBER_16 3 is 1 on December 15, 2008 and 0 otherwise DECEMBER_16 i Dummy DECEMBER_16 4 is 1 on December 17, 2008 and 0 otherwise DECEMBER_16 5 is 1 on December 18, 2008 and 0 otherwise DECEMBER_16 6 is 1 on December 19, 2008 and 0 otherwise Time window variables.
MARCH_18 Dummy 1 on March 18, 2009 0 otherwise
XIX
Treasury purchases under the LSAP are confirmed
MARCH_18 i is 1 on March 13, 2009 and 0 otherwise MARCH_18 2 is 1 on March 16, 2009 and 0 otherwise MARCH_18 3 is 1 on March 17, 2009 and 0 otherwise MARCH_18 i Dummy MARCH_18 4 is 1 on March 19, 2009 and 0 otherwise MARCH_18 5 is 1 on March 20, 2009 and 0 otherwise MARCH_18 6 is 1 on March 23, 2009 and 0 otherwise
FOMC 1 is 1 on January 28, 2009 and 0 otherwise FOMC 2 is 1 on August 12, 2009 and 0 otherwise FOMC i Dummy FOMC 3 is 1 on September 23, 2009 and 0 otherwise FOMC 4 is 1 on November 4, 2009 and 0 otherwise
S&P_500 Datastream Index S&P_500
XX
Exhibit 6 Data description European interbank market
Variable Source Unit Description
Euribor stands for Euro Interbank Offered Rate. The Euribor rates are based on the average interest rates at which a panel of more than 50 European
banks borrow funds from one another. In the calculation, the highest and EURIBOR 3M Datastream Percentages lowest 15% of all the quotes collected are eliminated. The remaining rates are averaged and rounded to three decimal places. Euribor is determined and published at about 11:00 am each day, Central European Time.
OIS 3M Datastream Percentages Overnight Indexed Swap with the floating leg tied to the overnight Eonia
ECB 1 on August 22, 2007 SLTRO INITIAL Press Dummy 0 otherwise Releases Initial special LTRO announcement .
SLTRO INITIAL_1 is 1 on August 17, 2007 and 0 otherwise SLTRO INITIAL_2 is 1 on August 20, 2007 and 0 otherwise SLTRO INITIAL_3 is 1 on August 21, 2007 and 0 otherwise SLTRO INITIAL_i Dummy SLTRO INITIAL_4 is 1 on August 23, 2007 and 0 otherwise SLTRO INITIAL_5 is 1 on August 24, 2007 and 0 otherwise SLTRO INITIAL_6 is 1 on August 27, 2007 and 0 otherwise Time window dummies.
ECB 1 on each day a SLTRO is announced SLTRO Press Dummy ANNOUNCEMENTS 0 otherwise Releases
ECB 1 on December 12, 2007 SWAP INITIAL Press Dummy 0 otherwise Releases Initial announcement on swap lines with Federal Reserve.
XXI
SWAP INITIAL_1 is 1 on December 7, 2007 and 0 otherwise SWAP INITIAL_2 is 1 on December 10, 2007 and 0 otherwise SWAP INITIAL_3 is 1 on December 11, 2007 and 0 otherwise SWAP INITIAL_i Dummy SWAP INITIAL_4 is 1 on December 13, 2007 and 0 otherwise SWAP INITIAL_5 is 1 on December 14, 2007 and 0 otherwise SWAP INITIAL_6 is 1 on December 17, 2007 and 0 otherwise Time window dummies.
ECB 1 on each day a swap operation is announced SWAP Press Dummy ANNOUNCEMENTS 0 otherwise Releases
ECB 1 on March 28, 2008 LTRO_6M INITIAL Press Dummy 0 otherwise Releases Initial announcement of LTRO with 6-month maturity
LTRO_6M INITIAL_1 is 1 on March 25, 2008 and 0 otherwise LTRO_6M INITIAL_2 is 1 on March 26, 2008 and 0 otherwise LTRO_6M INITIAL_3 is 1 on March 27, 2008 and 0 otherwise LTRO_6M INITIAL_i Dummy LTRO_6M INITIAL_4 is 1 on March 31, 2008 and 0 otherwise LTRO_6M INITIAL_5 is 1 on April 1, 2008 and 0 otherwise LTRO_6M INITIAL_6 is 1 on April 2, 2008 and 0 otherwise Time window dummies.
ECB 1 on each day a 6-month LTRO is announced LTRO_6M Press Dummy ANNOUNCEMENTS 0 otherwise Releases
1 on October 8, 2008 ECB 0 otherwise th OCTOBER_8 INITIAL Press Dummy On October 8 , an important set of announcements was made. For the Releases specific announcements, we refer to < https://www.ecb.europa.eu/press/pr/date/2008/html/pr081008.en.html
XXII
>
OCTOBER_8 INITIAL_1 is 1 on October 3, 2008 and 0 otherwise OCTOBER_8 INITIAL_2 is 1 on October 6, 2008 and 0 otherwise OCTOBER_8 INITIAL_3 is 1 on October 7, 2008 and 0 otherwise OCTOBER_8 INITIAL_i Dummy OCTOBER_8 INITIAL_4 is 1 on October 9, 2008 and 0 otherwise OCTOBER_8 INITIAL_5 is 1 on October 10, 2008 and 0 otherwise OCTOBER_8 INITIAL_6 is 1 on October 13, 2008 and 0 otherwise Time window dummies.
1 on October 15, 2008 ECB 0 otherwise OCTOBER_15 INITIAL Press Dummy On October 15 th , an important set of announcements was made. For the Releases specific announcements, we refer to < https://www.ecb.europa.eu/press/pr/date/2008/html/pr081015.en.html>
OCTOBER_15 INITIAL_1 is 1 on October 14, 2008 and 0 otherwise OCTOBER_15 INITIAL_2 is 1 on October 16 2008 and 0 otherwise OCTOBER_15 INITIAL_3 is 1 on October 17, 2008 and 0 otherwise OCTOBER_15 INITIAL_i Dummy OCTOBER_15 INITIAL_4 is 1 on October 20, 2008 and 0 otherwise Time window dummies. Due to an overlap in time window with the OCTOBER_8 INITIAL variable, we cannot create dummy variables for the full three-day time-window.
ECB 1 on May 7, 2009 LTRO_1Y INITIAL Press Dummy 0 otherwise Release Initial announcement on the LTROs with a maturity of 1 year.
LTRO_1Y INITIAL_1 is 1 on May 4, 2009 and 0 otherwise LTRO_1Y INITIAL_2 is 1 on May 5, 2009 and 0 otherwise LTRO_1Y INITIAL_i Dummy LTRO_1Y INITIAL_3 is 1 on May 6, 2009 and 0 otherwise LTRO_1Y INITIAL_4 is 1 on May 8, 2009 and 0 otherwise LTRO_1Y INITIAL_5 is 1 on May 11, 2009 and 0 otherwise
XXIII
LTRO_1Y INITIAL_6 is 1 on May 12, 2009 and 0 otherwise Time window dummies.
OMO_OUTSTANDING – (AUTONOMOUS_LIQUIDITY_FACTORS + RESERVE_REQUIREMENTS) Website Millions of OUTSTANDING All these data can be downloaded from ECB Euros
CMA (Credit Market Analysis CDS Credit Default Swap for the European bank sector with a 5-year maturity. Ltd) Obtained from Datastream
EUROSTOXX BANKS Datastream Euro Stoxx Banks
1 from three days before a quarter end Q Dummy ENDS set back to 0 three days after a quarter end.
XXIV
Exhibit 7 FX swap market
Variable Source Unit Description
FX_SPOT Datastream Percentages Thomson Reuters US$ to euro spot rates with a three-month maturity . One-month maturities are used to check the robustness of our results.
Thomson Reuters US$ to euro forward rates with a three-month maturity . FX_FORWARD Datastream Percentages One-month maturities are used to check the robustness of our results.
British Bankers’ Association Euro interbank interest rates with a three-month maturity . EURO_LIBOR 3M (BBA) Percentages (obtained One-month maturities are used to check the robustness of our results. from Datastream)
1 on December 12, 2007 Federal 0 otherwise SWAP Dummy INITIAL Reserve Initial announcement of TAF swap operations that would provide US dollar to the euro area.
SWAP INITIAL_1 is 1 on December 7, 2007 and 0 otherwise SWAP INITIAL_2 is 1 on December 10, 2007 and 0 otherwise SWAP INITIAL_3 is 1 on December 11, 2007 and 0 otherwise SWAP INITIAL_i Dummy SWAP INITIAL_4 is 1 on December 13, 2007 and 0 otherwise SWAP INITIAL_5 is 1 on December 14, 2007 and 0 otherwise SWAP INITIAL_6 is 1 on December 17, 2007 and 0 otherwise Time window dummies.
Federal SWAP_LONG Dummy INITIAL Reserve 1 on July 30, 2008 XXV
0 otherwise Announcement that swap operations with a 84-day maturity would be performed.
SWAP_LONG INITIAL_1 is 1 on July 25, 2008 and 0 otherwise SWAP_LONG INITIAL_2 is 1 on July 28, 2008 and 0 otherwise SWAP_LONG INITIAL_3 is 1 on July 29, 2008 and 0 otherwise SWAP_LONG INITIAL_i Dummy SWAP_LONG INITIAL_4 is 1 on July 31, 2008 and 0 otherwise SWAP_LONG INITIAL_5 is 1 on August 1, 2008 and 0 otherwise SWAP_LONG INITIAL_6 is 1 on August 4, 2008 and 0 otherwise Time window dummies.
1 on October 13, 2008 Federal 0 otherwise FRFA Dummy INITIAL Reserve Announcement that the central banks would switch to an unlimited provision of liquidity through the swap lines.
FRFA INITIAL_1 is 1 on October 8, 2008 and 0 otherwise FRFA INITIAL_2 is 1 on October 9, 2008 and 0 otherwise FRFA INITIAL_3 is 1 on October 10, 2008 and 0 otherwise FRFA INITIAL_i Dummy FRFA INITIAL_4 is 1 on October 14, 2008 and 0 otherwise FRFA INITIAL_5 is 1 on October 15, 2008 and 0 otherwise FRFA INITIAL_6 is 1 on October 16, 2008 and 0 otherwise Time window dummies.
1 on each day an announcement was made that the swap lines would be Federal SWAP Dummy extended EXTENSION Reserve 0 otherwise
Federal 1 on each day a swap operation with an overnight maturity was performed SWAP Dummy OVERNIGHT Reserve 0 otherwise
XXVI
1 on each day a swap operation with a maturity between overnight and 9 Federal SWAP Dummy days was performed MEDIUM Reserve 0 otherwise
1 on each day a swap operation with a maturity between 10 and 28 days Federal SWAP Dummy was performed LONG Reserve 0 otherwise
1 on each day a swap operation with a maturity longer than 28 days was Federal SWAP Dummy performed VERYLONG Reserve 0 otherwise
Federal
Reserve Eurodollar deposit rate with a maturity of 3-months . EURODOLLAR 3M Data Percentages Source Federal Reserve: Bloomberg and CTRB ICAP Fixed Income & Money Market Download Products. Program
CDS BOA_AM Datastream Credit Default Swap of the Bank of America with a 5-year maturity
iTraxx (obtained CDS Credit Default Swap European financial institutions with a 5-year maturity; FINANCIAL_EU from Datastream)
LIBOR 3M Datastream Percentages cf . Exhibit 2
OIS 3M Datastream Percentages cf. Exhibit 2
XXVII
XX VIII
XXIX