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Does Central Bank Policy Benefit the Good or the Bad? The Impact of
ECB Announcements on Bank Balance Sheets During the Financial Crisis
Katherine Hele
Faculty Sponsor: Professor Matthew Jaremski
Colgate University, Department of Economics
Hamilton, New York, 13346
April 2013
Abstract
Central bank policy has varied the size and composition of bank balance sheets in the face of the
recent global financial crisis. Usually the assumption is made that central bank behavior has the
same impact on all banks. However, given the wide heterogeneity of bank health in Europe,
sudden shifts in monetary policy at the European Central Bank could have differential effects on
each country. To examine this topic, balance sheet data have been collected on 26 countries and
47 banks in Europe on a quarterly basis from 2005-2012. The results show that banks in
countries with poor economic health responded differently to central bank announcements and
policies compared to countries with good economic health during the financial crisis. Overall,
ECB announcements helped to increase capital and cash in bad countries, but bad countries had
more volatile reactions to changes in the ECB interest rate compared to good countries.
JEL Classification: E52, E58, G21
Keywords: European Central Bank, Monetary Policy, Balance Sheets, Financial Crisis
Acknowledgements: This research paper would not have been possible without the help of
Professor Matthew Jaremski and the members of Colgate’s Economics Honors Seminar.
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I. Introduction
Banks are essential for each country’s economy, as the composition of financial balance
sheets helps to determine a country’s resilience to a range of macroeconomic shocks. Central
banks and governments intervene with monetary policy measures in order to maintain stability in
the banking system. Monetary policies and individual bank conditions support market
functioning and affect macroeconomic outcomes, such as inflation, interest rate sensitivity, and
investor confidence. In the recent financial crisis, central banks have also introduced new tools
and resources in an attempt to provide liquidity to the market. Despite different structures, the
assumption is usually made that banks react uniformly to monetary policy. However, as seen in
the recent crisis, banks do not seem to be responding to central bank monetary policy and
announcements in the same way. Portugal, Italy, Ireland, Greece, and Spain, a group of countries
known as the PIIGS, are consistently in trouble despite interventions by the European Central
Bank, while stable countries like Germany continue to experience market liquidity. Specifically,
did central bank announcements and policies by the European Central Bank have different
effects on countries and individual banks in good or bad economies? This study will look at how
the balance sheets in Europe have changed from 2005 to 2012 in response to the financial and
debt crisis at the central bank-level, aggregate country-level, and individual bank-level.
Many studies have compared balance sheets, but there are several holes in the literature.
First, very few studies of the recent financial crisis have focused on both main central banks and
individual banks. Second, in addition to policy think-tank pieces, the most common forms of
empirical analysis were the estimation of the Taylor series and reaction functions. Therefore,
most literature has focused on how central banks expanded their balance sheets during the crisis.
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Third, any work on the reaction of central banks to monetary conditions usually focuses on the
Federal Reserve and there has been little done on Europe.
Kashyap and Stein (1997) is one of the few that considers the differences between
countries and banks, and helps provide motivation for this study. Before the creation of the
European Union (EU), they argued that the banking system aspects of monetary policy under the
proposed EU system was being overlooked. They describe the conceptual differences between
the bank-centric view of monetary transmission and the conventional view, in which banks do
not play a key role. Analyzing bank balance sheet composition, size distribution of banks, bank
health, and factors affecting the lending channel, they find that monetary policy has significant
distributional effects that operate throughout the banking system. In this way a common
monetary policy in Europe could affect banks throughout Europe differently, and in turn might
influence real economic activity in different countries.
Kashyap and Stein (2000) and Hosono (2006) also suggest that the impact of monetary
policy could vary across banks depending on bank characteristics. Kashyap and Stein (2000) find
that lending by larger banks are less sensitive to changes in liquidity, which they argue suggests
that larger banks face fewer financing constraints. Hosono (2006) suggests that the effect of
monetary policy on lending is stronger for banks that are smaller, less liquid, and more abundant
with capital. Cook and Yetman (2011) developed a model to explain banking interactions in their
study, which looks at 55 individual banks in 5 emerging Asian countries from 2003-2007. Cook
and Yetman found that reserve accumulation acts to crowd out other types of assets and bank
lending, as predicted by their model. While Cook and Yetman do consider the differences
between banks (constrained versus unconstrained), they only focus on the effect of one specific
factor (reserves).
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Examination of balance sheets during the modern financial crisis has focused on central
banks: Federal Reserve (Fed), European Central Bank (ECB), and Bank of England (BOE).
Pisani-Ferry and Wolff (2012) analyzed the Fed, ECB, and BOE responses to the crisis. This
study provided a detailed assessment of the effectiveness of the long-term refinancing operations
(LTROs), by looking at banks’ stock market price indexes, loans, banks’ interest rates on loans,
and financial integration of corporate credit loans. They find that the greatest part of the ECB
liquidity ended up in the deposit facility of the ECB itself, instead of spread out across banks.
They argue that lack of confidence in the overall construction of the Economic and Monetary
Union thus impaired credit in the weaker EU countries, suggesting differences across countries.
Fahr et al. (2011) investigated the ECB’s monetary policy strategy and response to the
financial crisis in the euro area over the last fifteen years using a shock analysis model based on
structural VAR. They find that both supply side and financial developments have been important
drivers of business cycle and asset price fluctuations in the euro area, and the ECB’s monetary
policy strategy was in line with credit developments to help stabilize both inflation and output.
ECB intervention was important to avoid de-leveraging in the banking sector and in sustaining
credit creation. While Fahr et al. do not consider differences across countries or banks, they do
focus primarily on Europe and the tools used by the ECB.
We build upon previous literature to test whether European Central Bank actions have
different impacts across countries and within countries in Europe. To examine this topic, we
have collected data on central banks, aggregate country-level, and individual banks’ balance
sheets on a quarterly basis from 2005-2012. The central bank data was obtained from the Federal
Reserve, European Central Bank, and Bank of England websites, whereas country-level data was
obtained from the ECB Statistical Warehouse. Bank-level data was found listed on the Investor
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Relations section of each bank’s website. The resulting data contain 3 central banks, 26
countries, and 47 individual banks. The bank data are then linked to the major ECB
announcements found in Press Releases on the central bank’s main website and key interest
rates.
We find that the ECB was helpful at expanding liquidity, but central bank monetary
policy affected countries and individual banks to different extents. ECB announcements were
associated with an increase in assets and cash at the country-level and an increase in capital and
cash at the bank-level. At both the country-level and bank-level, however, bad countries had
more volatile reactions to ECB interest rate movements than good countries. In addition, positive
ECB announcements led to an expansion of assets, capital, and cash at the country-level,
whereas negative announcements had a harsh effect on lending at the top banks in bad countries.
Due to the varying reactions of countries, central bank leaders need to consider the diversity
among member states in the European Union and Eurozone when setting monetary policy.
II. Background
To understand long-term trends, it is important to discuss central bank policies before and
during the crisis. We therefore start by analyzing the months before August 2007 to provide a
pre-crisis perspective. Rising interest rates and a saturated housing market characterized the pre-
crisis period. Beginning in 2005, interest rates started rising, and the Federal funds rate reached
5.25% by June 2006, where it stayed until August 2007. Furthermore, during the last quarter of
2005, home prices started to fall, which led to a 40% decline in the U.S. Home Construction
Index during 2006. The bursting of the U.S. housing bubble caused the value of securities tied to
U.S. real estate to decline. The end of the pre-crisis period can be dated to August 2007, when
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BNP Paribas, France’s largest bank, terminated withdrawals on three investment funds stating
that there was a “complete evaporation of liquidity” (St. Louis Federal Reserve, 2009, 1-2).
Following August 2007, the analysis is separated into two different stages. The first stage
corresponds to the start of the financial crisis from 2007-2009, when financial institutions lost
billions of dollars from their exposure to subprime mortgage market loans. The second stage of
the crisis focuses on 2010-2012. The past few years are analyzed separately, because the
sovereign debt crisis is unique to the euro zone and therefore has required different and specific
actions from the ECB.
The First Stage (2007-2009)
Since August 2007, the Fed, the ECB, and the BOE responded to the crisis with major
initiatives to increase their balance sheets in order to provide market liquidity. During the first
stage from 2007-2009, banks extended the scope of existing facilities, created new devices to
help financial institutions access liquidity, and cut interest rates down to zero (Figure 1: Panel
A). The Fed increased liquidity operations and opened a series of swap facilities to allow other
central banks to provide banks locally with dollars. The Bank of England swapped illiquid assets
from banks in return for Treasuries. On September 14, 2007, the Bank of England provided
liquidity support for Northern Rock, the United Kingdom’s fifth-largest mortgage lender (Gros et
al., 2012, 7; Pisani-Ferry and Wolff, 2012, 2-3; Wheelock, 2010, 89).
The financial crisis intensified following the collapse of the Lehman brothers in the Fall
of 2008, and there was a loss of confidence in the banking system. In the US, UK, and Euro area,
spreads between secured and unsecured money markets rates rose to unprecedented levels, while
interbank transactions volumes fell to low levels at longer maturities. Interest rates were also cut
significantly during the financial crisis. On October 8, 2008, the Federal Reserve, ECB, and
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Bank of England coordinated to cut their key policy rates by 50 basis points. By the spring of
2009, short-term money market rates were close to zero for all three (Lenza et al., 2010, 12-16;
Gros et al., 2012, 7).
The crisis started off primarily concentrated in the United States but quickly turned into a
global financial crisis. Banks’ demand for central bank liquidity rose significantly as there was
uncertainty of the availability of short-term financing in the money market. The Fed purchased
commercial papers, asset-backed securities and other private assets containing credit risk for
about 1 trillion USD during the year 2009. The Fed was taking on credit risk through TALF, the
Term Asset-Backed Securities Loan Facility. The European Central Bank’s Covered Bond
Purchase Program (CBPP) started in July 2009 and was equivalent to 60 billion Euros. The ECB
put in place 300 billion Euros focusing on expanding the credit to banks in the framework of an
“enhanced credit support program.” The BOE purchased medium and long-term government
bonds, at a value of 200 billion GBP between March 2009 and January 2010 (Gros et al., 2012,
7). The onset of the crisis resulted in different economic repercussions across countries and
different policy responses by the authorities.
The Second Stage (2010-2012)
The second stage of the crisis, from 2010-2012, is characterized by the sovereign debt
crisis experienced in Europe. In early 2010, fears of a sovereign debt crisis developed among
investors concerning some European countries, including Greece, Ireland, and Portugal. The
widening of bond yield spreads and credit default swaps between these weaker nations and other
EU members, most importantly Germany, led to a crisis of confidence (Blackstone et al., 2010).
The debt crisis was mainly concentrated in Greece, where the cost of financing government debt
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rose. On May 2, 2010, the Eurozone countries and the International Monetary Fund (IMF)
agreed to loan Greece 110 billion Euros. Later in May, the ECB Council intervened in the
sovereign bond market through the Securities Market Programme (SMP) and the European
Financial Stability Facility (EFSF), which was a comprehensive rescue package worth 750
billion Euros. The Greek bailout was followed by rescue package of 85 billion Euros for Ireland
in November 2010, and a bailout of 78 billion Euros for Portugal in May 2011 (Alessi, 2013). In
December 2011, the ECB implemented a new set of longer-term financing operations (LTROs)
amounting to 1,000 billion Euros. In July 2012, Spain was given a support package of 100 billion
Euros for recapitalization of its financial sector (European Commission, 2012). The ECB was
forced to become the central counterparty of the entire cross border banking market, which is a
concept known as “credit easing” (Gros et al., 2012, 9).
On the other hand, the main focus in the US after 2010 was on expanding the economy.
The Fed undertook asset purchases financed by the central bank money, known as quantitative
easing (QE), which lead to the amount of Treasuries in its balance sheet to 1.6 trillion USD. The
BOE also followed a similar approach and expanded its balance sheet to 325 billion GBP. While
the Fed and BOE experimented with asset-purchase programmes, the ECB did not. The ECB
tried to minimize its own risk whereas the Fed and BOE took on credit risk. The total assets of
the Fed and BOE almost tripled in about 5 years, while that of the ECB only doubled (Figure 1:
Panel B). The Fed took on interest-rate risk by buying government bonds, while the ECB did not
assume any maturity risk with its LTRO (Pisani-Ferry and Wolff, 2012, 3-5; Gros et al., 2012,
12).
The ECB, which lacks a unified government to back it fiscally or authoritatively, is in a
trickier position than other major central banks. The central bank hoped to increase the overall
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expansionary stance of monetary policy and improve market liquidity. The ECB intervened
forcefully in 2011 and 2012 to keep sovereign borrowing costs and banking systems under
control. Through this, the ECB prevented the periphery countries’ financial systems from
collapsing. However, even the low ECB rate has failed to bring down borrowing rates for
businesses around the periphery, such as those in the PIIGS, which are significantly above those
in Germany and France. Peripheral depositors have a strong incentive to shift funds elsewhere,
which would reduce the supply of loanable funds and raise borrowing costs in the countries with
weaker economies. The ECB needs to continue to address the “dangerous gap in borrowing costs
between the core and periphery” (R.A., 2013).
Bank-centric view of monetary policy
Most theories assume that all banks will respond to central bank actions in a similar way,
which is what this study attempts to show is not the case. Kashyap and Stein (1997) comment
that there are differences between the bank-centric view of monetary transmission and the
conventional view, in which banks do not play a role. The classic textbook treatment of
monetary policy focuses on how the central bank’s actions affect households’ portfolios.
Household portfolios are allocated between bonds, which are types of financial assets not used
for transaction purposes, and money, which is used in transactions (Kashyap and Stein, 1997, 3).
The bank-centric theory hinges on two key propositions: that monetary interventions do
something special to banks; and that once banks are affected, so are firms and consumers.
The bank centric-view asserts that the role of the banking sector is central to the
transmission of monetary policy. There are two key factors that shape the way in which
monetary policy works: first, the extent to which banks rely on reversible deposit financing and
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adjust their loan supply schedules following changes in bank reserves; and second, the extent to
which certain borrowers are bank-dependent and cannot easily offset shifts in bank loan supply
(Kashyap and Stein, 1997, 4). The key factors in determining the importance of the lending
channel are the degree of bank dependence in the economy and the extent to which central bank
actions move loan supply. Common monetary policy will affect banks throughout Europe, but
the impact will vary depending on the economic health of the country.
In light of the vast differences in institutions across Europe, this story could have
important implications for how monetary policy operates under the European Union. Kashyap
and Stein (1997) consider a uniform tightening of monetary policy and its effect on different
countries. A country with a set of mostly creditworthy banks and relatively few weak banks may
be able to offset the contraction in reserves by picking up uninsured non-deposit financing in the
capital markets, and therefore bank lending will only fall slightly. In a country with many bank-
dependent firms and a weak banking system, the impact might be quite different. Banks with
poor credit ratings may not be able to attract uninsured funds to offset their deposit outflow.
Thus, a uniform contraction in monetary policy across the two countries may lead to a very
asymmetric response, raising potentially problematic distributional issues.
The different effects of ECB policy on country-level banks in Europe can most clearly be
seen during the second stage of the crisis (Figure 1: Panel C). Some countries in the Eurozone,
such as Greece, posed risks of financial loss, whereas other affected countries, such as Ireland,
Portugal, Spain, and Italy, were financially healthy by comparison. As the US financial crisis
intensified, however, the peripheral southern European countries and Ireland appeared to have
issues of their own. Housing market and baking crises greatly affected Ireland and Spain, and
high public debts were an adverse issue in Portugal and Italy. European banks, especially French
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banks, were having difficulty getting financing. UK banks were negatively impacted by reduced
economic activity in Europe, while Germany helped to guarantee payment of some of the
sovereign debts for the rest of the Eurozone (Menéndez, 2012, 1).
III. Data
To study the impact of central bank policy, we collected data at the central bank-level,
country-level, and individual bank-levels. The central bank balance sheet data were obtained for
the Fed, ECB, and BOE from their main websites for the background section. The Federal
Reserve Board releases weekly balance sheet updates in the report: “Credit and Liquidity
Programs and the Balance Sheet H.4.1.” ECB balance sheet items were obtained from the ECB
Statistical Warehouse website. Bank of England data were downloaded from “Table B1.1.1 –
Total liabilities and total assets.” Because we only focus on Europe at the country-level, country-
level data were obtained from the ECB Statistical Warehouse website. We collected information
on the 27 member states of the European Union. Estonia was the only excluded country because
it did not have available data for all seven years. Total assets, loans, deposits, capital, and cash
were downloaded for each country on a monthly basis from January 2005 to December 2012.
In order to determine if there are differential effects, it is necessary to divide the countries
between those with strong and weak economies. The 26 countries were divided into those with a
“good” or healthy banking sector, and those with “bad” economic health, based on the European
Sovereign Credit Rating of each country by Moody’s Investors Service at the end of 2012Q3
(Table 1). The good countries are judged to be of the high quality, with minimal to very low
credit risk (Rating Aaa-A3), whereas the bad countries possess speculative characteristics and
are subject to credit risk (Rating Baa and below). The ratings do a good job of creating the
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division between good and bad countries. For instance, the PIIGS countries are included in the
bad group, as their ratings are below investment grade. We will test sensitivity of the marginal
countries later in the paper.
There is no existing freely available micro dataset on European banks. The most
comprehensive database is Bankscope, which was used in study by Vazquez and Federico
(2012), but the price quote for a subscription was unfortunately too high. Therefore for the bank-
level analysis, we collected bank-level data for the top five largest banks in ten European
countries from each bank’s website in the Investor Relations section (Table 2). Five countries
were chosen with good economic health (Germany, The Netherlands, United Kingdom, Sweden,
and France) and five countries with bad economic health (the PIIGS). The frequency of the data
depended on what was available. Information was collected on a quarterly or half-yearly level
from 2005-2012. Three banks were dropped from the individual level due to the data only being
available at an annual frequency, resulting in a total of 47 banks.
It is important to note that each country has different market composition of the total
banking system, as shown in Table 3. In Sweden, the Netherlands, and the UK, the large banks
appear to hold a dominant position. The financial sectors of these countries are sizeable and
dominated by the largest institutions. On the other hand, in Ireland, Portugal, Germany, and Italy,
the smaller banks appear to control a significant fraction of the assets. The Herfindahl Index (HI)
for each country is also shown in Table 3. The index ranges from 0 to 1.0, moving from a large
number of small firms to a single firm with monopolistic power. A decrease in the index number
indicates a loss in pricing power and increased competition. The Netherlands and Sweden have a
concentrated HI index of 0.28 and 0.20, respectively, indicating the top three banks in the
country have more market power relative to the other countries in the sample. Conversely,
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Portugal and Ireland have a HI index of 0.03, indicating a competitive banking industry with few
dominant players. These different compositions of the countries’ banking systems need to be
controlled for and taken into consideration at both the macro and micro level analysis.
The ECB could have affected countries through two different ways: interest rate
movements and announcements. The ECB key interest rate was from the ECB Statistical
Warehouse, and ECB announcements were located on the European Central Bank Website.
There are shock factors for central bank announcements available for FOMC Statements in the
United States, but no such rating system has been developed for Europe. Therefore the major
announcements were coded as +1 or -1 based on an overall positive or negative shock (Table 4).
An event is included if it is a key date of the financial crisis (since 2005) as reported on the ECB
website. Announcements about changes to the key interest rate were not included as they are
separately controlled for. ECB announcements that were about the Bank of England or the
Federal Reserve were also included due to the interconnected nature of the global economies.
Macroeconomic factors are needed as control variables when considering differences
across countries because bank health should be closely correlated with economic activity.
Following changes in monetary policy, there is a strong correlation between bank loans and
unemployment, GNP, and other key macroeconomic indicators (Kashyap and Stein, 1997;
Bernanke and Blinder, 1992). Controls include average real GDP, the unemployment rate,
central bank key interest rates for BOE and the Fed, the inflation rate, the LIBOR rate, housing
prices, inflation, and the Euronext 100 Index. GDP, unemployment, and central bank key interest
rates were found on the ECB Statistical Warehouse site. The LIBOR rate is the 12-Month
Interbank Offered Rate, based on the U.S. Dollar taken from the British Bankers’ Association.
The rate is taken at a quarterly frequency and is aggregated from the end of the period. Housing
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prices were also from the ECB Statistical Warehouse as an index (2007=100), representing
residential property valuation for the whole country taken at a quarterly frequency. Inflation data
are from Eurostat and is the monthly data index of the HICP (2005=100). Historical Euronext
100 Index data are from Yahoo! Finance. The Euronext 100 Index is the blue chip index of the
European stock exchange and comprises the largest and most liquid traded stocks.
Summary statistics for various balance sheet items can be seen in Table 5. The resulting
data contains 26 countries and 47 individual banks from 2005-2012Q2. Banks at both the
country-level and bank-level have fairly high mean value of loan to asset and deposit to asset
ratios. The greatest difference between the country-level and bank-level is seen in the cash to
asset ratio, at 16.90% and 2.62% respectively. Mean values for the macroeconomic control
variables can also be found in Table 5.
IV. Empirical Specification
We will examine the different effect of ECB policy at both the country and bank-level. In
each case, we will use an OLS Fixed Effects model to help control for macroeconomic of
financial developments that might affect balance sheet characteristics across countries and banks
but that are the same across time. In order to capture balance sheet size and composition, balance
sheet levels and fractions of total assets are both analyzed. The main balance sheet variables are
assets, loans, deposits, capital and cash. They are either logged, similar to Kashyap and Stein
(1995), or divided by assets, similar to Cook and Yetman (2011). Explanatory variables include
the lagged value of each dependent variable, to capture the initial size in the previous quarter.
The lagged terms of each dependent variable should be included to mitigate the serial correlation
(Bowman et al., 2011), because the current level of the balance sheet item should be heavily
influenced by its past level.
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The key explanatory variables are the ECB announcement and the ECB key interest rate,
which will be interacted with the main dependent variables. indicates if there was
either a positive or negative central bank announcement during the time period t. is the log
of the key interest rate set by the European Central Bank, in order to capture monetary policy at
the time. As discussed previously, we created a dummy variable taking a value of 1 if the
country has poor economic health (Table 1). The good group of countries is used as a reference
group to the bad. The dummy variable is not in the regression due to the fixed effects, but
we capture the differential effects through the separate interaction of the ECB announcement and
the ECB interest rate with the bad dummy. Separating interest rate movements and
announcements (not related to interest rates) is important to determine what is actually driving
the differences. A positive coefficient on the interaction indicates that an announcement or
increase in the interest rate is associated with an increase in the balance sheet item for bad
countries compared to good countries, whereas a negative indicates a decrease in the balance
sheet item for bad countries compared to good countries.
is a series of variables made up of macroeconomic factors in country or bank i
in time period t to act as a control. This vector includes GDP, unemployment rate, Bank of
England key interest rate, Federal Reserve key interest rate, the inflation rate, the LIBOR rate,
the log of house prices, and the Euronext 100 Index. The term captures individual fixed
effects, and the error term accounts for unobservable factors in the model.
The following equation is used for our main specification:
(1)
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where is either the natural log of each balance sheet item of the country or bank i in time
period t or the each balance sheet ratio for a particular country or bank i in time t. At the country-
level model, i represents each individual country, whereas at the bank-level, i represents the
individual bank. The bank-level regression is run at a half-yearly frequency to be consistent
across time since not all the bank data was available at a quarterly level. 2012Q4 is also dropped
from both levels of the model due to lack of data for some banks.
V. Results
Country-Level
Panel A of Table 6 reports the country-level results. Focusing on the interaction terms,
ECB*Bad is significant when the log of assets is the dependent variable. A 1% increase in the
ECB key interest rate is associated with a 0.084% decrease in the log of assets for bad countries
compared to good countries, on average, holding all else constant. Therefore, changes in the key
ECB interest rate will lead to a decrease in overall bank size for banks in bad countries.
Announce*Bad is also positive and significant, meaning that an ECB announcement leads to an
increase in bank size for banks in bad countries. The presence of an ECB announcement is
associated with a 1.4% increase in the log of assets in the bad countries compared to the good
countries, on average, holding all else constant. Furthermore, both interaction terms are positive
and significant in Panel B of Table 6. Therefore we would expect the ECB announcements with
a positive impact to be driving the increase in bank size.
The presence of an ECB announcement is associated with a decrease in both the size and
composition of loans in bad countries. An ECB announcement is associated with a 3.6%
decrease in loans, and the presence of an announcement is associated with a 0.3% decrease in the
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loan to asset ratio, for bad countries compared to good countries, on average, holding all else
constant. The majority of the announcements are related to the bad countries, and in times of
economic distress, nervous investors shift their funds back to good safe-haven countries, such as
Germany. There is less lending to low net-worth borrowers after ECB announcements, implying
that announcements have a greater negative shock factor for bad countries.
Changes in the level and composition of deposits are being driven by ECB key interest
rates. A 1% increase in the ECB key interest rate leads to a 0.32% decrease in deposits for bad
countries compared to good countries, on average, holding all else constant. Similarly, a 1%
increase in the ECB key interest also leads to a decrease in the deposit to asset ratio, by 0.01%
for bad countries compared to good countries, on average, holding all else constant. However,
the linear combination of the Announce variable in Panel B has a significant and positive effect
on the log of loans. Therefore it is contractionary monetary policy, such as an increase in the
ECB key interest rate, which has a net negative effect for bad countries relative to good
countries.
Lastly, the presence of an ECB announcement is associated with 2.4% increase in cash,
for the bad countries compared to the good countries, on average, holding all else constant. The
combined linear effect in Panel B is associated with a 2.9% increase in cash. This influx of cash
into the bad countries could be a cautionary response, indicating that the ECB policies were
helpful to some extent at increasing liquidity in the weaker countries. Overall, the varying impact
of ECB monetary policy on different countries is evident in both balance sheet size and
composition of banks at the country-level. Both balance sheet composition and balance sheet size
of bad countries are negatively affected by increases in the ECB interest rate, whereas ECB
announcements resulted in an increase in assets, deposits, and cash, but a decrease in loans and
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the loan to asset ratio, suggesting that negative announcements may be driving the effect on
loans.
Bank-Level
When estimating the models at the bank-level, the number of observations drops due to
the half-yearly frequency instead of quarterly frequency. First, it is interesting to note that the
bank-level model only has significant results on the interaction terms for the size of capital and
cash, whereas the country-level picked up significance for the size of assets, deposits, and cash.
In Table 7, significance is found on the Announce*Bad interaction term when capital and capital
to assets are the dependent variable. An ECB announcement is associated with a 4.1% increase
in capital for bad countries compared to good countries, on average, holding all else constant. In
line with an increase in capital in terms of balance sheet size, an ECB announcement was
significant and associated with a 0.8% increase in the capital to asset ratio. The increased level of
capital and capital to asset ratio could be a sign that the bad countries are following the Basel
accords, which have attempted to raise the capital ratios of banks in Europe, in order to be better
protected against operating losses.
ECB*Bad is positive and significant when the log of cash is the dependent variable, and
and Announce*Bad is positive and significant for the cash to asset ratio. A 1% increase in the
ECB interest rate is associated with a 0.436% increase in cash, for the bad countries compared to
the good countries, on average, holding all else constant. The combined linear effect in Panel B
of a 1% increase in the ECB rate and interaction term is associated with a 0.667% increase in
cash. In addition, an ECB announcement is associated with a 0.6% increase in the cash to asset
ratio for bad countries compared to good countries, on average, holding all else constant. The
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similar result at the country-level in Table 6 supports the claim that the influx of cash into the
PIIGS and other bad countries is a cautionary response to prepare the weaker economies for the
unstable economic conditions.
Also in Table 7, the deposit to asset ratio was significant but negative, which is similar to
the result found at the country-level in Table 6. Thus a 1% increase in the ECB key interest rate
leads to a 0.045% decrease in the deposit to asset ratio for bad countries compared to good
countries, on average, holding all else constant. The ECB key interest rate movement seems to be
a primary driver for negative changes in the deposit to asset ratio for the top banks in bad
countries compared to the top banks in good countries.
Overall, ECB announcements were successful at increasing capital and cash ratios, but
interest rates drove down the deposit to asset ratio, decreasing the funding base for the top banks
in bad countries. ECB policies have a more prominent and positive impact on the micro
individual bank-level than at the macro country-level perspective, but the ECB interest rate had a
negative effect at both the country-level and bank-level. These results suggest that the ECB was
successful at spreading liquidity to the top banks in bad countries compared to the top banks in
good countries, but the bad countries had more volatile reactions to the interest rate. Because the
capital to asset ratio and cash to asset ratio were not significant at the country-level, however, a
different story could be going on with the small banks.
Additional Specifications
Table 8 and 9 show the results at the country-level and bank-level when ECB*Bad is
dropped from the models. In Table 8, Announce*Bad remains significant and positive when the
log of assets and log of cash are the dependent variables, indicating that the ECB key interest rate
20
is also an important driver of change. In addition, Announce*Bad becomes significant and
positive when deposits is the dependent variable, for both the log and ratio, whereas it had no
significance in Table 6. This indicates that the significance on ECB announcement in bad
countries is being driven by changes in the ECB key interest rate with a net negative effect. At
the bank-level, the significant results in Table 9 are also significant in Table 7, indicating that
ECB announcements help increase the ratios of capital to assets and cash to assets. ECB interest
rates, however, help drive the change in the log of capital due to the loss of significance in Table
9. The results indicate that the ECB announcements and ECB key interest rate should be
considered together.
Next, we divide the Announce variable into either a positive or negative announcement,
in order to see which specific movement is picked up in the country. The results for the country-
level can be seen in Table 10. Announcements with a positive impact were the main drivers of
change in balance sheet size in bad countries compared to good countries. An announcement
with a positive impact was associated with an increase in the log of assets, capital, and cash. The
ECB was helpful in promoting liquidity in the bad countries, with the exception of the size of
loans. A positive announcement is associated with a 1.1% decrease in the size of loans, on
average, holding all else constant. Even following a positive announcement, investors may want
loans from the safest countries, given the unstable economic conditions in this time period.
Both positive and negative announcements have significant impacts on the loans to assets
ratio of the bad countries. Positive announcements have a negative impact on the loan to asset
ratio in bad countries, whereas negative announcements have a positive impact. Since the size of
assets increases with a positive announcement, and the size of loans decreases with a positive
announcement, this leads to a decrease in the loan to asset ratio for bad countries compared to
21
good countries. Following a negative announcement, bad countries may see a reduction in the
level of loans, while the size of assets remains constant, which would lead to an increase in the
loan to asset ratio. ECB key interest rate changes, instead of positive versus negative
announcements, still seem to be the main drivers of change for the deposit to asset ratio, as an
increase in the ECB key interest rate is associated with a decrease in the deposit to asset ratio, for
bad countries compared to good countries, on average, holding all else constant.
As seen in Table 11, negative ECB announcements seem to drive changes in balance
sheet size for bad countries at the bank-level. Negative announcements had more of an effect at
the bank-level, while positive announcements had more of an impact for the country-level. This
could indicate that the negative announcements, which are usually about the bad countries, are
more strongly felt by the top banks in the top banks in the weak countries. Negative
announcements at the bank-level lead to a 7.8% decrease in the size and loans of the bank in bad
countries compared to good countries, on average, holding all else constant.
According to economic theory, this phenomenon can be described as the “flight to
quality.” The “flight to quality” corresponds to the reallocation of loans from the highest risk
firms to the safest ones after a macroeconomic shock (Lang and Nakamura, 1995). Bernanke,
Gertler, and Gilchrist (1996) describe how borrowers who face significant agency costs of
borrowing in credit markets, such as firms or countries with weak balance sheets, are likely to
bear the brunt of an economic downturn. In particular, following a macroeconomic shock, such
as a negative announcement, “these borrowers should experience reduced access to credit,
relative to other borrowers” (Bernanke, Gertler, and Gilchrist, 1996, 6). Thus a negative ECB
announcement is associated with banks in bad countries seeing a relative decline in their size and
loans compared to banks in good countries.
22
Interestingly, the results that are significant at the bank-level for the interaction term
PosAnnounce*Bad in Table 11 are opposite those found at the country-level in Table 10. At the
bank-level, PosAnnounce*Bad is positive and significant when the log of loans is the dependent
variable, whereas is it negative and significant at the country-level. The country-level regression
includes both the top banks and small banks, so small banks could have different results than the
ones found at the bank-level analysis. This result indicates that the top banks in bad countries are
lending more than top banks in good countries, but not by enough to offset the net negative
result, as the small banks in bad countries are doing worse than the small banks in good
countries. The switch in the signs of the coefficients indicates that differences not only exist
across countries but also within countries.
In order to perform a sensitivity analysis on the results, we drop the marginal countries
out of the Good and Bad groups. First, we drop the countries with low investment credit ratings
out of the Bad dummy variable group at the country-level regression, except for Italy and Spain
as they are part of the PIIGS. The countries we drop include Bulgaria, Latvia, Lithuania,
Romania, and Slovenia. When Bulgaria and Latvia are dropped out of the model, the coefficient
on Announce*Bad becomes less significant. There is no change when Lithuania and Romania are
dropped out next. Once Slovenia is dropped and all five marginal countries are not included,
Announce*Bad loses significance completely on the size of assets and loans. This indicates that
the story in the PIIGS (in addition to Hungary and Cyprus) at the country-level is one that is
reliant on deposits and cash. There is no change on ECB*Bad without the five marginal countries
in the model.
Next, we drop the UK and Sweden to reduce the sample to Eurozone countries in both
the country-level and bank-level models. The aftermath of the LIBOR scandal in the summer of
23
2012 is another reason to check the results without the UK included in the sample of countries.
However, the LIBOR scandal could be controlled for by including the LIBOR rate in the
macroeconomic variables. When the UK and Sweden are not included, the interaction term
Announce*Bad loses significance when the log of cash is the dependent variable. Deposits is still
significant on Announce*Bad and ECB*Bad at the 5% level without all of the marginal
countries. The results are thus primarily driven by the countries in the Eurozone, such as
Germany.
When the marginal countries are all included in the Good group, and only the PIIGS,
Cyprus, and Hungary are in the Bad dummy variable, the country-level results are significant for
deposits on Announce*Bad and ECB*Bad and significant when assets are the dependent variable
on ECB*Bad. The marginal countries are still low investment grade, so they could have been
included in either dummy variable. Due to heightened uncertainty in Europe, there is still
moderate credit risk associated with a Baa3 and Baa2 rating by Moody’s, which is why
ultimately these countries are included in the Bad group, since it provides a more equal division
between good and bad countries.
VI. Conclusion
Banks have varied both their size and composition in the wake of the recent global
financial crisis. Central bank policies have attempted to help alter bank balance sheets, however,
due to the heterogeneity of bank health, there may have been varying effects on each country.
Conventional monetary economic theory usually assumes that central bank policy has a uniform
effect across all banks. However, a growing focus on the bank-centric view of monetary
transmission and the recent events in the modern banking sector during the financial crisis has
illustrated that this is not the case. This study examined if these differences existed across
24
countries and within countries, especially in those with bad economic health, such as the PIIGS,
compared to those with good economic health, such as Germany.
The results confirm that differences did exist between countries in Europe during the
financial crisis. The ECB was helpful at increasing liquidity in the bad countries, but only to a
certain extent. At the country-level, bad countries experienced an increase in assets, loans, and
cash. However, the bad countries had much more volatile reactions to changes in the ECB
interest rate. At the bank-level, announcements and key interest rate changes only had significant
effects on capital and cash for bad countries compared to the good countries. This influx of cash
into the PIIGS and other weak economies could have been a result of precautionary measures
taken by the ECB and other large central banks. Positive announcements had strong, positive
effects at the country-level, whereas negative announcements seemed to affect the largest banks
in the bad countries at the bank-level. Bad announcements hit the big banks in weak countries
harshly, compared to big banks in good countries, as both balance sheet size and composition
contracted as a result.
It is important to note that the bank-level results only capture movements at the top banks
in each country. When there is a switch in a sign of a coefficient in a balance sheet value at the
bank-level model compared to the country-level model, we would expect to see a large opposite
sign on that value in a sample of small banks in that country. Kashyap and Stein (1997) explain
how only looking at the top three firms may be misleading. Countries with equally sized-banks
are different than countries with three main banks and hundreds of small banks. Depending on
the size of the large banks, small banks might appear to be more or less important, even though
there may be no small banks (Kashyap and Stein, 1997). In relation to Kashyap and Stein (1997),
25
future research could analyze small banks in European countries to determine the effects of
central bank policies picked up there.
In conclusion, the findings in this study support the claim that shifts in monetary policy
have differing powerful effects on each country at both the aggregate country-level and bank-
level. Many economists and politicians criticize the ECB for its monetary decision-making,
which affects various member states differently and could drive their economies out of alignment
(Salvatore, 2002). In the future, policy makers should consider the diversity among the member
states in European Union and the Eurozone, as this study has established that monetary policy
decisions and announcements have differential impacts on member states.
26
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28
Figure 1. Key Interest Rates and Balance Sheet Assets
Notes: See Section III for sources.
0
1
2
3
4
5
62
00
5-0
1
20
05
-05
20
05
-09
20
06
-01
20
06
-05
20
06
-09
20
07
-01
20
07
-05
20
07
-09
20
08
-01
20
08
-05
20
08
-09
20
09
-01
20
09
-05
20
09
-09
20
10
-01
20
10
-05
20
10
-09
20
11
-01
20
11
-05
20
11
-09
20
12
-01
20
12
-05
20
12
-09
Key
In
tere
st R
ates
(%
) Panel A: Central Bank Key Interest Rates
FED ECB BOE
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
450,000
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
4,500,000
5/2
4/2
00
6
8/2
4/2
00
6
11
/24
/20
06
2/2
4/2
00
7
5/2
4/2
00
7
8/2
4/2
00
7
11
/24
/20
07
2/2
4/2
00
8
5/2
4/2
00
8
8/2
4/2
00
8
11
/24
/20
08
2/2
4/2
00
9
5/2
4/2
00
9
8/2
4/2
00
9
11
/24
/20
09
2/2
4/2
01
0
5/2
4/2
01
0
8/2
4/2
01
0
11
/24
/20
10
2/2
4/2
01
1
5/2
4/2
01
1
8/2
4/2
01
1
11
/24
/20
11
2/2
4/2
01
2
5/2
4/2
01
2
8/2
4/2
01
2
Mil
lio
n G
BP
Mil
lio
n E
UR
Panel B: Total Assets of Central Banks
Fed ECB BOE
0%
200%
400%
600%
800%
1000%
1200%
Panel C: Total Assets by Country (% of GDP)
Germany Spain France UK Greece Ireland Italy Netherlands Portugal
29
Table 1. Description of Good-Bad Dummy
Good Bad
Country Moody’s Country Moody’s
Austria Aaa Bulgaria Baa2
Belgium Aa3 Cyprus B3
Czech Republic A1 Greece* C
Denmark Aaa Hungary Ba1
Finland Aaa Ireland* Ba1
France* Aaa Italy* Baa2
Germany* Aaa Latvia Baa3
Luxembourg Aaa Lithuania Baa1
Malta A3 Portugal* Ba3
Netherlands* Aaa Romania Baa3
Poland A2 Slovenia Baa2
Sweden* Aaa Spain* Baa3
Slovakia A2
United Kingdom* Aaa Notes: * means that data is available at the bank-level. Moody’s Ratings as of October 15, 2012.
30
Table 2. Description of Bank-Level Data (2005Q1-2012Q2) Bank Frequency Data Holes
Germany Deutsche Bank Quarterly -
Commerzbank Quarterly -
Deutsche Postbank Quarterly - Landesbank Berlin Quarterly -
Hypo Real Estate Group Quarterly 2012 all quarters
The Netherlands ING Quarterly -
ABN AMRO Half Yearly -
Rabobank Half Yearly - SNS REAAL Half Yearly -
Italy
UniCredit Group Quarterly - Intesa SanPaolo Quarterly 2012Q4, 2005Q3, 2005Q2, 2005Q1;
Missing cash from 2008-2012 Banca MPS Quarterly -
UBI Banca Quarterly 2005Q3, 2005Q2, 2005Q1
Banco Popolare Quarterly 2006Q3, 2006Q2, 2006Q1, and 2005 all quarters
Spain
Banco Santander Quarterly - Banco Bilbao Vizcaya Quarterly -
Banco Popular Espanol Quarterly - Banco de Sabadell Quarterly -
La Caixa Half Yearly 2012Q4, 2012Q3
United Kingdom Barclays Half Yearly -
Royal Bank of Scotland Quarterly -
Lloyds Banking Group Quarterly - HSBC Holdings Half Yearly -
Standard Charter Group Half Yearly -
Greece Alpha Bank Group Quarterly -
National Bank of Greece Quarterly -
EFG Eurobank S.A. Quarterly - Piraeus Bank Group Quarterly -
Attica Bank Quarterly -
Portugal Banco Comercial Português Quarterly -
Banco Internacional de Credito Quarterly -
Banco Espirito Santo Quarterly - Banco Santander Totta Half Yearly -
Caixa Geral de Depositos Quarterly -
France BNP Paribas Half Yearly -
Societe Generale Group Half Yearly 2006Q2 2005Q4 2005Q2
Banque Fédérative du Crédit Mutuel
Half Yearly -
Groupe BPCE Half Yearly 2005Q2
Ireland
Allied Irish Banks Half Yearly -
Permanent TSB Half Yearly -
National Irish Bank Quarterly -
Bank of Ireland Half Yearly -
Sweden
Nordea Bank AB Quarterly -
Skandinaviska Enskilda Banken AB
Quarterly -
Svenska Handelsbanken AB Quarterly -
Swedbank AB Quarterly - Forex Bank Half Yearly 2005Q2
Notes: See Section III for sources. Data taken from individual bank’s website.
31
Table 3. Market Composition of Top 3 Banks
Country % of Total
Country Assets
Herfindahl
Index
France 59.8 0.12
Germany 36.0 0.07
Greece 53.2 0.10
Ireland 26.3 0.03
Italy 44.0 0.08
Netherlands 72.1 0.28
Portugal 24.7 0.03
Spain 55.6 0.15
Sweden 74.9 0.20
United Kingdom 58.1 0.11 Notes: See Section III for sources.
32
Table 4. Description of Central Bank Press Releases (2005Q1-2012Q2)
Year Quarter Date Effect Description
2005 Q4 December 8 -1 ECB warns on financial imbalances
2006 Q4 December 11 -1 ECB sees euro area financial system as potentially vulnerable
2007 Q2 June 15 -1 Markets increasingly vulnerable 2007 Q3 August 9 +1 Interbank lending slows down
2007 Q4 December 12 +1 Central banks seek to ease pressures in short-term funding markets
2008 Q1 March 28 +1 ECB offers refinancing operations with longer maturities 2008 Q1 March 5 +1 US Fed, BofE quantitative easing
2008 Q3 September 15 -1 Lehman brothers files for bankruptcy
2008 Q3 September 29 +1 ECB and Fed step up efforts to alleviate tension in short-term funding markets 2008 Q3 October 15 +1 EC aims to improve protection for bank deposits
2009 Q2 June 4 +1 ECB launches first covered bonds programme 2009 Q4 December 2 +1 EU to create new supervisory authorities
2010 Q1 January 27 +1 ECB to end US dollar/euro swaps
2010 Q2 April 23 -1 Greece seeks financial support
2010 Q2 May 10 +1 ECB introduces Securities Market Programme
2010 Q2 May 10 +1 Loan package for Greece agreed
2010 Q2 June 7 +1 The European Financial Stability Facility is established 2010 Q4 November 3 +1 US Fed QE second round
2010 Q4 November 21 -1 Ireland seeks financial support
2010 Q4 December 4 +1 EU-IMF package for Ireland agreed 2011 Q1 January 1 +1 New EU supervisory bodies are created
2011 Q2 April 6 -1 Portugal requests activation of aid mechanism
2011 Q3 August 12 +1 Bailout of Portugal 2011 Q3 September 15 +1 ECB announces additional US dollar liquidity-providing operations
2011 Q4 October 13 +1 Enhanced European Financial Stability Facility becomes fully operational
2011 Q4 December 22 +1 ECB allots €489 billion to 523 banks in first 36-month longer-term refinancing operation 2012 Q1 February 21 +1 Eurogroup agrees on second financial aid package for Greece
2012 Q1 March 1 +1 European leaders sign fiscal compact
2012 Q1 March 1 +1 ECB allots €530 billion to 800 banks in second 36-month refinancing operation 2012 Q1 March 8 +1 ECB reactivates eligibility of Greek bonds as collateral
2012 Q2 June 27 -1 Cyprus seeks financial support
2012 Q2 June 27 -1 Spain seeks financial support
Notes: An announcement is coded as +1 for a positive impact and -1 for a negative impact. Quarters with no major announcement are coded as 0.
33
Table 5. Summary Statistics (2005-2012)
Variable
Country-Level
(Quarterly)
Bank-Level
(Half-Yearly)
Assets €1,598,562 mil €674.02 mil
Loans €253,753 mil €52.46 mil
Deposits €259,939 mil €74.64 mil
Capital €101,892 mil €27.62 mil
Cash €31,296 mil €13.67 mil
Loans/Assets 11.51% 8.51%
Deposits/Assets 15.37% 13.69%
Capital/Assets 8.10% 5.52%
Cash/Assets 16.90% 2.62%
Unemployment Rate 8.37% 9.12%
GDP €400,531 mil €304,732 mil
House Price Index 97.64 96.38
Announce 0.23
ECB Rate 2.15%
Fed Rate 1.92%
BOE Rate 2.71%
LIBOR Rate 2.69%
Inflation Index 111.55
Euronext 100 Index 744.39
Notes: Mean values of each variable. See Section III for sources.
34
Table 6. Country-Level: Balance Sheet Size and Composition (2005Q1-2012Q2)
Panel A: Results
Assets Loans Deposits Capital Cash
Log
(1)
Log
(2)
Ratio
(3)
Log
(4)
Ratio
(5)
Log
(6)
Ratio
(7)
Log
(8)
Ratio
(9)
L. Dep. Var. 0.010
[0.014]
0.174***
[0.057]
0.536***
[0.141]
0.142**
[0.053]
0.683***
[0.075]
0.059
[0.036]
0.559***
[0.143]
-0.017***
[0.006]
0.161***
[0.041]
Announce 0.006*
[0.003]
0.028***
[0.006]
0.003***
[0.001]
0.011
[0.007]
0.001
[0.001]
0.003
[0.005]
-0.000
[0.000]
0.005
[0.004]
0.002
[0.002]
ECB Rate 0.244***
[0.039]
0.173
[0.102]
-0.004
[0.005]
0.425***
[0.110]
0.014**
[0.006]
0.170***
[0.056]
-0.002
[0.002]
0.093*
[0.045]
-0.038
[0.025]
Announce*Bad 0.014**
[0.006]
-0.036*
[0.021]
-0.003***
[0.001]
0.019
[0.015]
0.001
[0.002]
0.011
[0.009]
-0.000
[0.001]
0.024**
[0.010]
-0.002
[0.004]
ECB*Bad -0.084** [0.039]
-0.079 [0.116]
-0.000 [0.006]
-0.320*** [0.095]
-0.010* [0.005]
-0.078 [0.047]
0.000 [0.003]
0.008 [0.043]
0.029 [0.027]
Country Fixed Effects & Macroeconomic Variables
Yes
Yes Yes
Yes Yes
Yes Yes
Yes Yes
Observations 796
787 796
787 796
796 796
805 796
R-squared 0.803
0.254 0.470
0.521 0.686
0.798 0.646
0.495 0.177
Panel B: Linear Combinations
Assets Loans Deposits Capital Cash
Log (1)
Log (2)
Ratio (3)
Log (4)
Ratio (5)
Log (6)
Ratio (7)
Log (8)
Ratio (9)
Announce +
Announce*Bad
0.020***
[0.004]
-0.008
[0.018]
-0.001
[0.001]
0.031***
[0.10]
0.002
[0.002]
0.139**
[0.001]
-0.001*
[0.001]
0.029***
[0.007]
-0.000
[0.002]
ECB Rate +
ECB*Bad
0.160***
[0.052]
0.094
[0.103]
-0.004
[0.006]
0.105
[0.133]
0.004
[0.007]
0.093*
[0.053]
-0.002
[0.003]
0.100
[0.072]
-0.009
[0.038]
Notes: Panel A displays the results of the OLS Fixed Effects model. Panel B displays the results of the linear combinations of the interaction terms. Robust Standard Errors in Parentheses. * denotes significance at 10%; ** at 5% level; and *** at 1% level.
35
Table 7. Bank-Level: Balance Sheet Size and Composition (2005Q1-2012Q2)
Panel A: Results
Assets Loans Deposits Capital Cash
Log
(1)
Log
(2)
Ratio
(3)
Log
(4)
Ratio
(5)
Log
(6)
Ratio
(7)
Log
(8)
Ratio
(9)
L. Dep. Var. 0.073
[0.044]*
0.106***
[0.037]
-0.031
[0.059]
0.165**
[0.067]
0.035
[0.106]
0.136***
[0.036]
-0.024
[0.042]
0.227***
[0.057]
-0.042
[0.051]
Announce 0.044**
[0.018]
0.022
[0.017]
-0.014
[0.011]
0.034
[0.022]
-0.003
[0.010]
0.003
[0.016]
0.002
[0.003]
0.002
[0.042]
-0.003*
[0.001]
ECB Rate 0.217
[0.138]
0.332***
[0.087]
0.106
[0.088]
0.354**
[0.146]
0.052
[0.070]
0.199
[0.131]
-0.009
[0.013]
0.265
[0.230]
-0.010
[0.011]
Announce*Bad -0.019
[0.016]
-0.003
[0.017]
0.014
[0.010]
-0.020
[0.025]
0.001
[0.010]
0.041**
[0.019]
0.008**
[0.003]
0.079
[0.061]
0.006**
[0.002]
ECB*Bad -0.018 [0.056]
0.011 [0.052]
0.009 [0.023]
-0.092 [0.070]
-0.045* [0.027]
0.047 [0.068]
-0.001 [0.006]
0.436*** [0.154]
0.001 [0.009]
Bank Fixed Effects & Macroeconomic Variables
Yes
Yes Yes
Yes Yes
Yes Yes
Yes Yes
Observations 688
688 688
688 688
678 688
676 676
R-squared 0.461
0.516 0.184
0.449 0.076
0.420 0.042
0.364 0.060
Panel B: Linear Combinations
Assets Loans Deposits Capital Cash
Log (1)
Log (2)
Ratio (3)
Log (4)
Ratio (5)
Log (6)
Ratio (7)
Log (8)
Ratio (9)
Announce +
Announce*Bad
0.023*
[0.012]
0.018*
[0.010]
0.001
[0.006]
0.019
[0.019]
-0.002
[0.009]
0.043
[0.031]
0.010*
[0.005]
0.080
[0.070]
0.003
[0.003]
ECB Rate +
ECB*Bad
0.199*
[0.133]
0.342***
[0.088]
0.115*
[0.076]
0.262*
[0.164]
0.007
[0.064]
0.246*
[0.149]
-0.009
[0.016]
0.667**
[0.257]
-0.009
[0.013]
Notes: Panel A displays the results of the OLS Fixed Effects model. Panel B displays the results of the linear combinations of the interaction terms. Robust Standard Errors in Parentheses. * denotes significance at 10%; ** at 5% level; and *** at 1% level.
36
Table 8. Additional Specifications - Country-Level: Balance Sheet Size and Composition (2005Q1-2012Q2)
Panel A: Results
Assets Loans Deposits Capital Cash
Log
(1)
Log
(2)
Ratio
(3)
Log
(4)
Ratio
(5)
Log
(6)
Ratio
(7)
Log
(8)
Ratio
(9)
L. Dep. Var. 0.012
[0.014]
0.175*** [0.058]
0.536*** [0.141]
0.163** [0.060]
0.699*** [0.076]
0.061* [0.034]
0.559*** [0.143]
-0.017***
[0.006] 0.166*** [0.036]
Announce -0.001
[0.006]
0.021
[0.014]
0.003***
[0.001]
-0.016
[0.015]
-0.000
[0.001]
-0.004
[0.008]
-0.000
[0.000]
0.006
[0.005]
0.005
[0.005]
ECB Rate 0.220***
[0.035]
0.152
[0.091]
-0.004
[0.004]
0.330***
[0.094]
0.011**
[0.005]
0.149***
[0.047]
-0.002
[0.002]
0.095*
[0.051]
-0.030
[0.026]
Announce*Bad 0.032**
[0.012]
-0.019
[0.033]
-0.003*
[0.002]
0.087***
[0.028]
0.003*
[0.002]
0.028
[0.017]
-0.001
[0.001]
0.022**
[0.009]
-0.009
[0.010]
ECB*Bad
Country Fixed Effects & Macroeconomic Variables
Yes
Yes Yes
Yes Yes
Yes Yes
Yes Yes
Observations 796
787 796
787 796
796 796
805 796
R-squared 0.795
0.254 0.470
0.521 0.686
0.798 0.646
0.495 0.169
Panel B: Linear Combinations
Assets Loans Deposits Capital Cash
Log (1)
Log (2)
Ratio (3)
Log (4)
Ratio (5)
Log (6)
Ratio (7)
Log (8)
Ratio (9)
Announce +
Announce*Bad
0.031***
[0.010]
0.002
[0.021]
-0.000
[0.001]
0.071***
[0.019]
0.003*
[0.001]
0.024**
[0.010]
-0.001
[0.001]
0.028***
[0.005]
-0.004
[0.005]
Notes: Panel A displays the results of the OLS Fixed Effects model. Panel B displays the results of the linear combinations of the interaction terms. Robust Standard Errors in Parentheses.
* denotes significance at 10%; ** at 5% level; and *** at 1% level.
37
Table 9. Additional Specifications - Bank-Level: Balance Sheet Size and Composition (2005Q1-2012Q2)
Panel A: Results
Assets Loans Deposits Capital Cash
Log
(1)
Log
(2)
Ratio
(3)
Log
(4)
Ratio
(5)
Log
(6)
Ratio
(7)
Log
(8)
Ratio
(9)
L. Dep. Var. 0.073
[0.044]
0.106*** [0.037]
-0.031 [0.059]
0.166** [0.066]
0.038 [0.107]
0.136*** [0.036]
-0.024 [0.042]
0.245*** [0.058]
-0.042 [0.051]
Announce 0.042**
[0.018]
0.023
[0.016]
-0.013
[0.012]
0.026
[0.021]
-0.007
[0.012]
0.007
[0.017]
0.002
[0.003]
0.040
[0.044]
-0.003*
[0.001]
ECB Rate 0.216
[0.137]
0.332***
[0.086]
0.107
[0.087]
0.350**
[0.147]
0.050
[0.069]
0.201
[0.131]
-0.009
[0.013]
0.265
[0.230]
-0.010
[0.011]
Announce*Bad -0.015
[0.019]
-0.006
[0.019]
0.012
[0.014]
0.001
[0.022]
0.011
[0.011]
0.030
[0.023]
0.008**
[0.004]
-0.019
[0.064]
0.005*
[0.004]
ECB*Bad
Bank Fixed Effects & Macroeconomic Variables
Yes
Yes Yes
Yes Yes
Yes Yes
Yes Yes
Observations 688
688 688
688 688
678 688
676 676
R-squared 0.461
0.516 0.173
0.444 0.076
0.419 0.042
0.349 0.060
Panel B: Linear Combinations
Assets Loans Deposits Capital Cash
Log (1)
Log (2)
Ratio (3)
Log (4)
Ratio (5)
Log (6)
Ratio (7)
Log (8)
Ratio (9)
Announce +
Announce*Bad
0.027**
[0.014]
0.017
[0.130]
-0.001
[0.007]
0.027
[0.019]
0.004
[0.007]
0.040
[0.032]
0.010**
[0.005]
0.021
[0.074]
0.002
[0.004]
Notes: Panel A displays the results of the OLS Fixed Effects model. Panel B displays the results of the linear combinations of the interaction terms. Robust Standard Errors in Parentheses.
* denotes significance at 10%; ** at 5% level; and *** at 1% level.
38
Table 10. Country-Level: Balance Sheet Size and Composition with Positive versus Negative Announcements (2005Q1-2012Q2)
Panel A: Results
Assets Loans Deposits Capital Cash
Log
(1)
Log
(2)
Ratio
(3)
Log
(4)
Ratio
(5)
Log
(6)
Ratio
(7)
Log
(8)
Ratio
(9)
L. Dep. Var. 0.011
[0.013]
0.171*** [0.057]
0.535*** [0.142]
0.142** [0.053]
0.684*** [0.076]
0.060 [0.035]
0.559*** [0.143]
-0.016** [0.006]
0.163*** [0.040]
PosAnnounce -0.008
[0.012]
0.101***
[0.035]
0.008***
[0.002]
-0.030
[0.026]
0.001
[0.003]
-0.013
[0.012]
0.000
[0.001]
-0.049***
[0.011]
-0.010
[0.013]
NegAnnounce 0.024**
[0.010]
-0.058
[0.034]
-0.004
[0.003]
0.061**
[0.024]
-0.000
[0.003]
0.022*
[0.011]
-0.001
[0.001]
0.068***
[0.011]
0.016
[0.013]
ECB Rate 0.241*** [0.038]
0.190* [0.099]
-0.003 [0.005]
0.417*** [0.110]
0.014** [0.006]
0.167*** [0.056]
-0.002 [0.002]
0.080* [0.045]
-0.041 [0.027]
PosAnnounce*Bad 0.039*
[0.021]
-0.117*
[0.063]
-0.011***
[0.003]
0.074
[0.053]
-0.000
[0.004]
0.047*
[0.027]
-0.001
[0.002]
0.052*
[0.029]
-0.011
[0.026]
NegAnnounce*Bad -0.018 [0.015]
0.065
[0.054] 0.007* [0.003]
-0.049 [0.043]
0.002 [0.003]
-0.034 [0.021]
0.000 [0.001]
-0.012 [0.019]
0.008 [0.024]
ECB*Bad -0.081**
[0.038]
-0.088
[0.114]
-0.001
[0.006]
-0.315***
[0.094]
-0.011*
[0.005]
-0.074
[0.045]
0.000
[0.003]
0.012
[0.045]
0.029
[0.025]
Country Fixed Effects &
Macroeconomic Variables Yes
Yes Yes
Yes Yes
Yes Yes
Yes Yes
Observations 796
787 796
787 796
796 796
805 796
R-squared 0.804
0.260 0.477
0.522 0.690
0.799 0.647
0.509 0.183
Panel B: Linear Combinations
Assets Loans Deposits Capital Cash
Log
(1)
Log
(2)
Ratio
(3)
Log
(4)
Ratio
(5)
Log
(6)
Ratio
(7)
Log
(8)
Ratio
(9)
PosAnnounce +
PosAnnounce*Bad
0.031**
[0.012]
-0.016
[0.043]
-0.002
[0.002]
0.046
[0.036]
0.001
[0.002]
0.034*
[0.018]
-0.001
[0.001]
0.003
[0.021
-0.021
[0.015
NegAnnounce +
NegAnnounce*Bad
0.006
[0.009]
0.007
[0.033]
0.002
[0.002]
0.012
[0.033]
0.002
[0.003]
-0.012
[0.016]
-0.001
[0.001]
0.056***
[0.014]
0.024*
[0.016]
ECB Rate + ECB*Bad
0.160*** [0.052]
0.102 [0.107]
-0.003 [0.006]
0.102 [0.135]
0.004 [0.007]
0.093* [0.052]
-0.002 [0.003]
0.091 [0.074]
-0.012 [0.038]
Notes: Panel A displays the results of the OLS Fixed Effects model. Panel B displays the results of the linear combinations of the interaction terms. Robust Standard Errors in Parentheses. * denotes significance at 10%; ** at 5% level; and *** at 1% level.
39
Table 11. Bank-Level: Balance Sheet Size and Composition with Positive versus Negative Announcements (2005Q1-2012Q2)
Panel A: Results
Assets Loans Deposits Capital Cash
Log
(1)
Log
(2)
Ratio
(3)
Log
(4)
Ratio
(5)
Log
(6)
Ratio
(7)
Log
(8)
Ratio
(9)
L. Dep. Var. 0.076
[0.046]
0.109*** [0.038]
-0.031 [0.059]
0.169** [0.068]
0.035 [0.106]
0.138*** [0.037]
-0.024 [0.042]
0.240*** [0.058]
-0.041 [0.051]
PosAnnounce 0.080***
[0.029]
0.031
[0.039]
-0.008
[0.015]
0.128**
[0.053]
0.024
[0.015]
0.085
[0.065]
0.004
[0.011]
0.434**
[0.167]
0.000
[0.008]
NegAnnounce 0.024
[0.028]
0.024
[0.030]
-0.016
[0.017]
-0.026
[0.027]
-0.022
[0.017]
-0.054
[0.039]
0.000
[0.005]
-0.302***
[0.098]
-0.004
[0.005]
ECB Rate 0.187
[0.132]
0.297*** [0.085]
0.097 [0.080]
0.313** [0.142]
0.046 [0.065]
0.182 [0.130]
-0.008 [0.016]
0.154 [0.238]
-0.013 [0.013]
PosAnnounce*Bad 0.036
[0.034]
0.083***
[0.030]
0.033
[0.024]
0.015
[0.047]
-0.005
[0.018]
0.030
[0.044]
0.005
[0.008]
-0.028
[0.147]
0.010*
[0.006]
NegAnnounce*Bad -0.065** [0.025]
-0.078** [0.037]
-0.002 [0.013]
-0.049 [0.036]
0.006 [0.014]
0.052
[0.043] 0.010
[0.009]
0.181* [0.099]
0.002 [0.002]
ECB*Bad 0.000
[0.054]
0.039
[0.051]
0.015
[0.020]
-0.079
[0.072]
-0.047*
[0.026]
0.045
[0.062]
-0.002
[0.004]
0.401**
[0.154]
0.003
[0.008]
Bank Fixed Effects &
Macroeconomic Variables Yes
Yes Yes
Yes Yes
Yes Yes
Yes Yes
Observations 688 688 688 688 688 678 688 676 676
R-squared 0.465
0.522 0.173
0.454 0.077
0.421 0.042
0.372 0.061
Panel B: Linear Combinations
Assets Loans Deposits Capital Cash
Log
(1)
Log
(2)
Ratio
(3)
Log
(4)
Ratio
(5)
Log
(6)
Ratio
(7)
Log
(8)
Ratio
(9)
PosAnnounce +
PosAnnounce*Bad
0.116***
[0.039]
0.113***
[0.033]
0.026
[0.025]
0.143**
[0.056]
0.019
[0.022]
0.115*
[0.074]
0.010
[0.170]
0.406]**
[0.163
0.010
[0.010]
NegAnnounce + NegAnnounce*Bad
-0.042 [0.031]
-0.054** [0.021]
-0.018 [0.019]
-0.075** [0.036]
-0.016 [0.019]
-0.002 [0.049]
0.010 [0.012]
-0.121* [0.079]
-0.003 [0.004]
ECB Rate +
ECB*Bad
0.187
[0.132]
0.336***
[0.087]
0.112*
[0.072]
0.235
[0.163]
-0.001
[0.062]
0.226*
[0.146]
-0.010
[0.019]
0.555**
[0.257]
-0.010
[0.015]
Notes: Panel A displays the results of the OLS Fixed Effects model. Panel B displays the results of the linear combinations of the interaction terms. Robust Standard Errors in Parentheses. * denotes significance at 10%; ** at 5% level; and *** at 1% level.