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.