The euro area bank lending survey : role, development and use in monetary policy preparation. N° 179 / September 2016.
Date: 2016-10-05
Institutions: European Central Bank
Subjects: credit, credit institution, euro area, financial market, loan, monetary policy

Occasional Paper Series 

Petra Köhler-Ulbrich, Hannah S. Hempell, 
Silvia Scopel  

The euro area bank lending survey 

Role, development and use 
in monetary policy preparation  

No 179 / September 2016 

Note: This Occasional Paper should not be reported as representing the views of the European Central Bank 
(ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB. 

 
 
Contents 

Abstract 

Non-technical summary 

1 

2 

Introduction 

The design and development of the bank lending survey 

2.1 

2.2 

2.3 

A survey on bank lending conditions in the euro area – 
changing requirements over time 

The BLS questionnaire – main objectives and enhancement in 
2015 

Extension of the standard questionnaire – ad hoc questions 

3 

Analysis of bank lending conditions in the euro area 

3.1 

3.2 

3.3 

Overview of bank lending conditions in the euro area 

Credit standards and terms and conditions on loans to 
enterprises and households and contributing factors 

Demand for loans to enterprises and households and 
contributing factors 

4 

Ad hoc questions – analysis for the euro area 

4.1 

4.2 

4.3 

4.4 

4.5 

4.6 

Banks’ access to retail and wholesale funding 

The impact of the sovereign debt tensions on bank funding 
and bank lending conditions 

Impact of the ECB’s non-standard measures on banks and on 
bank lending conditions 

The impact of the ECB’s negative deposit facility rate on 
banks’ net interest income and bank lending 

The impact of supervisory and regulatory changes on bank 
funding and bank lending conditions 

Evidence on the level of credit standards 

5 

The bank lending survey in empirical analysis 

5.1 

Model-based analysis of loan supply and its impact on loan 
growth in the euro area 

Occasional Paper Series No 179 / September 2016 

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5.2 

5.3 

5.4 

Analysis of the specific impact of the financial and the 
sovereign debt crises on euro area loan supply 

Assessment of the transmission of the ECB’s non-standard 
measures to euro area loan developments 

Relationship between monetary policy, financial stability and 
macro- or microprudential policies 

6 

Conclusions 

Annex Overview of changes in the bank lending survey questionnaire 

Glossary 

References 

Acknowledgements 

74 

76 

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Occasional Paper Series No 179 / September 2016 

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Abstract 

The euro area bank lending survey (BLS) serves as an important tool in the analysis 
of bank lending conditions in the euro area and across euro area countries, providing 
otherwise unobservable qualitative information on bank loan demand and supply 
from/to euro area enterprises and households. Since its introduction in 2003, the 
BLS has received growing attention and has become of key importance for the 
analysis and assessment of bank lending conditions in the euro area and at the 
national level. In particular in the context of the financial crisis, the BLS was used to 
gather additional information on the impact of the crisis and of the ECB’s monetary 
policy measures on banks’ funding situation and bank lending conditions. Following 
a description of the design and development of the BLS, this paper focuses on the 
analysis of bank lending supply and demand in the euro area and on their 
contributing factors. The results of the BLS are put into a wider economic 
perspective by relating them to other macroeconomic and financial variables. 
Analyses based on individual bank replies complement the picture further by 
providing more granular evidence on loan developments. In addition, an overview of 
the use of the euro area BLS as an analytical tool for investigating bank lending 
conditions in the euro area is presented. 

JEL codes: E44, E5, G21 

Keywords: euro area, bank lending conditions, loan supply, loan demand, monetary 
policy, monetary policy transmission 

Occasional Paper Series No 179 / September 2016 

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Non-technical summary 

Since its introduction in 2003, the euro area bank lending survey (BLS) has become 
an important tool in the reporting on and the analysis of bank lending conditions in 
the euro area and across euro area countries, providing otherwise unobservable 
qualitative information on bank loan demand and supply from/to euro area 
enterprises and households. In particular since the start of the financial crisis, the 
BLS has been used to gather additional information on the impact of the crisis on 
bank funding and bank lending conditions. It has received growing attention in this 
context as regards the monitoring of bank lending conditions in the euro area and 
across member countries for the purpose of monetary policy. The BLS also became 
increasingly useful as an analytical tool for investigating bank lending conditions in 
the euro area and at the national level to analyse financial fragmentation. 

Against this background, the main objectives of this paper are threefold: 

First, the conceptual design of the BLS and its development over time are described 
in order to reflect the increasing role which the BLS has assumed over time and 
especially during the financial crisis. This includes in particular the use of ad hoc 
questions in the BLS since 2006 and the introduction of an enhanced BLS 
questionnaire and compilation guide in April 2015, after taking stock of the 
interpretation of the BLS across reporting banks during 2013-14. 

Second, the results of the BLS, for both the standard questions and the ad hoc 
questions, are analysed and combined with other macroeconomic and financial 
variables. Thereby, the results of the BLS are cross-checked and put into a wider 
economic perspective. In addition to the analysis based on data for the euro area as 
a whole, evidence is also provided on the developments across the largest four euro 
area economies. Analyses based on individual bank replies complement further the 
picture by providing more granular evidence on developments. 

Third, an overview of the use of the euro area BLS for academic research 
investigating bank lending conditions in the euro area is presented. 

The analysis of euro area bank lending conditions for enterprises and households 
between 2003 and 2016 shows that bank lending conditions reflected periods of 
strong economic growth, deep recession during the financial crisis and a very 
gradual recovery in the aftermath of the crisis, supported by the ECB’s standard and 
non-standard monetary policy measures. Banks responded to the changes in the 
economic environment by adjusting their credit standards, i.e. their loan approval 
criteria, and their credit terms and conditions at which they are willing to provide new 
loans. The importance of the individual factors contributing to changes in bank 
lending conditions changed during the financial crisis. While risk perceptions 
regarding the economic situation and borrowers’ creditworthiness as well as banks’ 
cost of funds and balance sheet constraints played a dominant role in tightening 
periods, competition played a more important role in easing periods. In addition, the 

Occasional Paper Series No 179 / September 2016 

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importance of banks’ cost of funds and balance sheet constraints increased following 
the financial crisis until the end of 2011, reflecting banks’ funding stress. 

Turning to loan demand, loan demand by enterprises depends on a variety of 
factors. Financing needs for fixed investment as well as for inventories and working 
capital are the most important factors for firms’ loan demand. Demand for mergers 
and acquisitions (M&As) contributed considerably to loan demand especially in 
periods of favourable financing conditions like before the financial crisis and in the 
most recent past. Financing needs of households mainly reflected favourable 
housing market developments and positive consumer confidence, as well as, with 
respect to consumption financing, spending on durable consumer goods, such as 
cars or furniture. For all loan categories, changes in the general level of interest rates 
have an impact on loan demand. In this respect, the current low interest rate 
environment fuels loan demand. 

Banks’ qualitative answers to the BLS are closely related to quantitative data on the 
macroeconomic and financial side of the economy as well as to qualitative evidence 
from other European surveys. Specifically, changes in credit standards, terms and 
conditions and loan demand as well as contributing factors display a close 
connection to real economic growth, bank loan growth, changes in industrial and 
consumer confidence, firms’ profitability, borrowers’ balance sheet situation, M&A 
activity and the unemployment rate. In addition, developments in bank lending 
conditions are related to developments in house prices and changes in bank lending 
spreads. This confirms that bank lending conditions, as collected in the context of the 
BLS, are well anchored in actual macroeconomic and financial developments and 
contribute to explaining loan developments with a view to disentangling loan supply 
and demand factors. This is of particular interest in the analysis of monetary policy 
transmission and the design of adequate monetary policy actions. In part, BLS 
indicators lead the developments in other indicators, such as bank lending and real 
GDP growth, thereby providing particularly useful information for forward-looking 
monetary policy. 

The ad hoc questions included in the survey contribute to shedding further light on 
banks’ funding situation, on the impact of supervisory and regulatory changes as well 
as on the impact of the ECB’s standard and non-standard monetary policy measures 
taken in the context of the financial crisis on bank lending conditions. In addition, the 
ad hoc question on the level of credit standards provides evidence on the level of 
credit standards compared with the past and thereby makes it possible to cross-
check the regular BLS results on changes in credit standards. 

Finally, a literature review reflects the use of the BLS within models for analysing the 
impact of loan supply and demand factors on bank loan growth, and more broadly 
economic activity. Specifically, it provides an overview of the use of the BLS for 
analysing the impact of the financial crisis, the transmission of the ECB’s monetary 
policy measures and the relationship between monetary policy, financial stability and 
macro- or microprudential policies. 

Occasional Paper Series No 179 / September 2016 

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Overall, the analyses and assessments presented in this paper highlight the 
importance of the BLS as a tool for analysing bank lending conditions in the euro 
area and, thereby, as a key input to the Eurosystem’s monetary policy preparation. 

Occasional Paper Series No 179 / September 2016 

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1 

Introduction 

The bank lending survey (BLS) for the euro area was launched in 2003 with a 
sample of around 90 banks in 12 euro area countries and has expanded since then 
to a sample of more than 140 banks in 19 euro area countries in 2016. Its main 
objective is to enhance the Eurosystem’s knowledge of financing conditions in the 
euro area in order to provide input into the ECB Governing Council’s assessment of 
monetary, financial and economic developments, on the basis of which it takes its 
monetary policy decisions. Since 2003 the reporting on bank lending developments 
has developed substantially and analytical tools have been created to support the 
analysis of euro area bank lending with survey evidence. The BLS serves as a useful 
tool for analysing bank lending conditions in the euro area, complementing existing 
statistics on bank loans and bank lending rates with otherwise unobservable 
qualitative information on supply and demand conditions in the euro area credit 
markets and on the lending policies of euro area banks. In addition, since the 
financial crisis, which started in 2007-08, the analysis of bank lending conditions 
across euro area countries has received increasing attention in order to analyse 
dispersion in such conditions and financial fragmentation in the euro area. In April 
2015 an enhanced BLS questionnaire and an updated compilation guide were 
introduced to enhance further the information content of the survey. 

Why is it important to have a survey on bank lending conditions? 

The euro area has a largely bank-based financial system. Bank loans account for 
more than 80% of non-financial corporations’ (NFCs) outstanding amount of external 
debt financing (defined here as MFI loans and debt securities issued by NFCs; see 
Chart 1) and for the bulk of external financing for households. Therefore, banks play 
a particularly important role in the monetary policy transmission in the euro area. 
Given the asymmetric information between lenders and borrowers in credit markets, 
banks act as intermediaries to reduce the barriers to accessing credit. Thereby, they 
assume a key role in the financing of parts of the economy where information is 
opaque such as households and small firms. 

While the traditional interest rate channel focuses on the impact of changes in key 
interest rates on short-term interest rates and money, the bank lending channel 
emphasises the importance of banks in the transmission of monetary policy. 1 It 
emphasises the impact of changes in monetary policy on bank lending conditions via 
changes in banks’ retail and wholesale funding cost and in the availability of funds. 
Specifically, a hike in key interest rates by the central bank increases banks’ funding 
cost and tends to dampen banks’ profit margins (i.e. stemming from a maturity 
mismatch between short-term deposits and loans with longer-term interest rate 
fixation periods). As a consequence, banks tighten their lending conditions. 
Generally, the bank lending channel has a stronger impact on banks which have a 

1   See Bernanke and Gertler (1995), Gambacorta (2005) and Mishkin (1996). See also European Central 

Bank (2010). 

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larger maturity mismatch between assets and liabilities and are less well capitalised, 
i.e. as balance sheet constraints may become binding. 2 

Chart 1 
Importance of MFI loans versus debt securities for euro 
area NFCs 

(in percentages of the amount outstanding of MFI loans and debt securities issued by 
euro area NFCs and EUR billions for the figures in the bars) 

MFI loans
debt securities

574

768

1 033

3 334

4 714

4 426

100%

80%

60%

40%

20%

0%

Q1 2003 - Q2 2007

Q3 2007 - Q2 2012

Q3 2012 - Q2 2016

Source: ECB. 
Note: Figures in the bars indicate the average over the respective period. 

In addition, and linked to the bank lending channel, 
monetary policy is transmitted via the balance sheet 
channel (or “broad credit channel”), which focuses on 
borrowers’ balance sheet conditions. An increase in 
short-term interest rates increases borrowers’ interest 
expenses and tends to reduce borrowers’ net worth. Via 
this deterioration of their creditworthiness, financing 
conditions of borrowers generally become tighter 
following an increase in key interest rates by the central 
bank. Hence, the combination of the impact of 
monetary policy changes on banks’ funding cost and 
the impact on borrowers’ balance sheets leads to an 
overall tightening adjustment in the financing conditions 
of borrowers. 

Moreover, the development of the financial system, 
including the deepening of financial markets, has 
intensified the link between monetary policy and market 
participants’ perception of risk and the pricing of risk.3 
This channel is generally called the “risk-taking 

channel” and extends the traditional channels of monetary policy transmission to 
banks’ ability and willingness to take risk on their balance sheets and to price risk. 
Specifically, the evolution of supervisory regulation and market participants’ attention 
to the ease or difficulty of banks in fulfilling these requirements may have led to an 
increasing awareness of banks towards risk. Hence, changes in key interest rates 
and in the liquidity provision by the central bank can have consequences for banks’ 
perception of risk and for their tolerance towards taking risk on their balance sheet. 
This in turn affects banks’ credit approval and the terms and conditions at which 
banks are willing to provide loans. 

Against this background, monitoring and assessing the impact of monetary policy 
decisions on bank lending conditions and, in turn, on credit and economic growth is 
of key importance for a central bank. 

Statistical data on monetary financial institution (MFI) interest rates and MFI loans 
provide accurate and timely information about developments in lending volumes and 
prices, which allows for instance the pass-through of changes in short-term money 
market rates to bank lending rates to be assessed. At the same time, such data do 
not allow a distinction to be made between loan demand and supply. The ability of 
the BLS to disentangle credit supply and demand is valuable for complementing the 
assessment of bank loan growth and lending rates. In addition, the BLS has been 
particularly useful and proven to be a flexible tool in order to gain information on the 

2   See Gambacorta and Mistrulli (2004) and Altunbas, Fazylov and Molyneux (2002).  
3   See Borio and Zhu (2012). 

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impact of the financial crisis and of the ECB’s non-standard measures on bank 
funding and bank lending conditions as well as on the dispersion of bank funding and 
lending conditions across euro area countries. Finally, the BLS provides relevant 
information on the impact of regulatory and supervisory changes on bank lending 
conditions. 

Overall, the euro area BLS serves as a valuable tool for analysing bank lending 
conditions in the euro area as well as across euro area countries and contributes to 
improving the understanding of loan developments. The quarterly analysis of the 
BLS results for the euro area is used in the preparation of monetary policy decisions 
and, hence, forms an integral part of the monetary policy process. 

Chapter 2 of this Occasional Paper focuses on the changing requirements over time 
as regards the design and the development of the BLS, which includes among 
others the sample, the addition of ad hoc questions and the enhancement of the 
questionnaire in 2015. Chapter 3 provides an analysis of bank lending conditions for 
enterprises and households in the euro area, their relationship with other economic 
variables and developments across the four largest euro area countries. Chapter 4 
provides evidence on the main ad hoc questions introduced in the BLS, focusing in 
particular on the impact of the financial crisis on bank funding and bank lending 
conditions. Chapter 5 presents a review of the use of the BLS as an analytical tool. 
Finally, Chapter 6 concludes by providing an overall summary and an assessment of 
the use of the BLS in monetary policy preparation. 

Occasional Paper Series No 179 / September 2016 

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2 

2.1 

The design and development of the 
bank lending survey 

A survey on bank lending conditions in the euro area – 
changing requirements over time 

The bank lending survey for the euro area was launched in 2003 with a sample of 
around 90 banks in 12 euro area countries, with the aim of analysing bank lending 
conditions in the euro area.4 It is conducted on a quarterly basis in January, April, 
July and October of each year. The information from the BLS is provided to the 
ECB’s Governing Council for its monetary policy meetings in order to support the 
timely assessment of financing conditions in the euro area for the conduct of 
monetary policy. 

Since the start of the survey, the BLS sample has expanded to above 140 banks in 
2016. First, with additional countries joining the euro area, the number of 
participating banks increased. Up to 2016 the euro area has expanded to 19 
member countries, of which all participate in the BLS. Second, some countries 
increased the size of their national sample to allow for a better representation of the 
national banking structure. The most important case for the latter was the increase of 
the German BLS sample in April 2008 from 17 banks to around 30 banks.5 

The BLS sample is constructed in a way that ensures representativeness of the euro 
area banking system and, with some limitations owing to the sample size, also of the 
national banking systems in the euro area. Preference is given to including the 
largest banks in the sample. This notwithstanding, also smaller and specialised 
banks are included in the sample if their lending behaviour represents an important 
feature of the national banking system. In addition, the sample size for each country 
should be not far from its share in the amount outstanding of bank lending to euro 
area households and non-financial corporations. The BLS sample covers around 
60% of the amount outstanding of loans to the private non-financial sector in the 
euro area. Actual coverage varies across countries, being high for countries with a 
concentrated banking system. At the same time, in countries with a low 
concentration of the banking system, small banks may be typical in their lending 
behaviour for a larger group of small banks, leading to a higher effective coverage of 
the overall BLS sample. 

The results of the individual banks participating in the BLS sample are aggregated in 
two steps, since the number of banks in the national samples differs considerably 
and does not always reflect accurately the respective share in lending to euro area 
non-financial corporations and households. In a first step, individual bank results are 

4 See Berg et al. (2005). 
5 See Deutsche Bundesbank (2009 and 2016). 

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aggregated to national results for the euro area countries, and in a second step, the 
national BLS results are aggregated to euro area BLS results. 

In the first step, banks’ replies can either be aggregated to national results by 
applying an implicit weighting through the sample selection or, alternatively, banks’ 
replies can be aggregated by applying an explicit weighting scheme. In the first case, 
while individual banks’ replies are unweighted in the aggregation to national results, 
the equal weighting of small and large banks can be appropriate if smaller banks are 
representative of the lending behaviour of a larger group of small banks forming a 
specific bank type or in a specific region. The option of an explicit weighting scheme 
was introduced in the April 2014 BLS round and is used by a small number of 
countries (France, Malta, the Netherlands and Slovakia). In this case, individual 
banks’ replies are weighted based on their share in the amounts outstanding of loans 
to non-financial corporations and households of the banks in the respective national 
samples. The common principle underlying the aggregation of national results is to 
ensure the best representativeness for the national results of the respective country. 

In the second step of the aggregation, the national survey results are aggregated to 
euro area BLS results by applying an explicit weighting scheme based on the 
national shares in the amounts outstanding of loans to euro area non-financial 
corporations and households. 

Since the start of the BLS in 2003 and in particular since the financial crisis, the 
attention paid to the results of the BLS has increased substantially. Related to this, 
the initial focus on the BLS results for the euro area as a whole has widened. Today, 
the BLS is also used for assessing lending conditions across euro area countries 
and the diversity of lending conditions across countries.  

This is also reflected in the provision of aggregate BLS data in the ECB Statistical 
Data Warehouse (SDW), which includes since 2012 the national BLS results for 
most participating countries, as well as in the BLS website report, which includes 
since April 2012 in addition to the euro area results also the BLS results for the 
largest five euro area countries (in terms of GDP, which are Germany, France, Italy, 
Spain and the Netherlands).6 

The increased importance of the BLS in monetary policy preparation during recent 
years is also reflected in the timing and adaptation of the survey in specific 
circumstances, especially in order to assess developments in financing conditions of 
enterprises7 and households during the financial crisis.  

Most prominently, since the financial crisis, the BLS has contained regularly ad hoc 
questions on specific topics of interest (see Section 2.3 and Chapter 4). 

6   See the ECB website report on the results of the bank lending survey and further information related to 

the BLS. 

7   Throughout this Occasional Paper, the term “enterprises” is used to refer to the non-financial 

corporations (NFCs) sector of the European System of Accounts. 

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2.2 

The BLS questionnaire – main objectives and 
enhancement in 2015 

2.2.1 

Main principles of the questionnaire 

The BLS questionnaire is addressed to senior loan officers at the banks and covers 
supply and demand aspects of bank lending conditions. The questionnaire is 
accompanied by a compilation guide, which is provided to survey participants to 
support a common understanding of the BLS terms and to ensure consistent 
response behaviour of the participating banks.  

Generally, in the BLS questionnaire, past developments cover the previous three-
month period, while expected developments focus on the following three-month 
period. In addition, the survey may contain ad hoc questions on specific topics of 
interest. 

The questions are classified according to the two borrower sectors that are the focus 
of the survey, i.e. enterprises and households, the latter being broken down into 
(i) loans for house purchase and (ii) consumer credit and other lending. The 
definitions and classifications used in the survey are consistent with other ECB and 
Eurostat statistics. For both enterprises and households, the questionnaire covers 
loan supply and loan demand factors. 

With regard to loan supply, the focus is on changes in credit standards that the 
banks apply when approving loans to enterprises and households and on changes in 
credit terms and conditions of new loans. In addition, banks are asked to assess how 
specific factors may have contributed to changes in credit standards and terms and 
conditions. 

For loan demand, the focus is on increases or decreases in loan demand. In this 
context, banks are asked to assess the impact of various factors on the financing 
needs of enterprises and households and the impact of the use of alternative means 
of financing on loan demand. 

2.2.2 

Enhancement of the questionnaire in 2015 

After more than ten years of existence, the BLS survey questionnaire and 
compilation guide were revised in 2015 to improve further the information content of 
the survey. The enhanced BLS questionnaire8 was launched in the April 2015 BLS 
round and contains 22 standard questions (18 backward- and 4 forward-looking 
questions) of a qualitative nature on past and expected credit market developments 
as well as one open-ended question. By comparison, when the survey was launched 
in 2003, the questionnaire consisted of 17 qualitative standard questions and one 

8   The enhanced BLS questionnaire is available in the BLS section of the ECB’s website. Previous 
versions of the questionnaire are available in the annex of the respective BLS website report. 

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open-ended question. An overview of the changes in the bank lending survey 
questionnaire is available in Annex 1 of this Occasional Paper. In addition, the 
information provided in the compilation guide is displayed as the “Glossary” at the 
end of this Occasional Paper. 

One main reason for the revision was that a survey among participants on the 
interpretation of BLS terms had revealed some heterogeneity in the understanding of 
the questionnaire. In addition, new factors and some new questions were added to 
the questionnaire, which were assessed as useful complements to the existing 
questions, while a few items were deleted because they had turned out to be less 
useful. The clarification of the definitions of some of the BLS terms in the compilation 
guide and the introduction of new factors and questions have increased overall the 
information content of the BLS. While the changes in the compilation guide have 
improved further the homogeneous understanding of BLS terms by survey 
participants, it needs to be kept in mind that the BLS is a qualitative survey and, 
hence, some divergence in banks’ answering behaviour cannot be avoided. 

The enhanced BLS compilation guide draws a clearer distinction between the terms 
“credit standards” and “credit terms and conditions”. The compilation guide defines 
“credit standards” as the internal guidelines or loan approval criteria of a bank. They 
are established prior to the negotiation on the terms and conditions of a loan and the 
actual approval or rejection of a loan application. They define the types of loan a 
bank considers desirable and undesirable, the designated sectoral or geographical 
priorities, the collateral deemed acceptable and unacceptable, etc. Credit standards 
specify the required borrower characteristics (e.g. balance sheet conditions, income 
situation, age, employment status) under which a loan can be obtained. This 
definition implies that the bank’s general approach for its lending policy is laid down 
in its credit standards. Factors which influence the determination of banks’ credit 
standards are in particular the bank’s cost of funds and balance sheet constraints, 
competitive conditions, perception of risks related to the economic environment and 
the specific creditworthiness of the borrowers as well as the bank’s tolerance 
towards taking risk on its balance sheet. From these factors, banks’ cost of funds 
and balance sheet constraints (referring to cost of capital, access to funding and the 
bank’s liquidity position) and banks’ risk tolerance mainly determine banks’ loan 
supply, i.e. their willingness and ability to provide a loan. By contrast, risk 
perceptions (referring mainly to the general economic situation and outlook as well 
as to the creditworthiness of borrowers) may not only reflect supply but also demand 
considerations. Banks’ react to the economic circumstances and determine their 
lending policy based on their assessment of the risks surrounding their lending 
policy. Hence, there is an interaction between loan demand and loan supply in risk 
perceptions. Finally, competition also includes demand aspects, as the loan demand 
side has repercussions on the bank’s positioning in the competitive environment.    

Based on the bank’s general lending policy, the bank’s credit terms and conditions 
are part of the actual implementation of its policy. “Credit terms and conditions” refer 
to the conditions of a new loan that a bank is willing to grant, i.e. to the terms and 
conditions of the loan as laid down in the loan contract between the bank (the lender) 
and the borrower. They generally consist of the agreed spread over a relevant 

Occasional Paper Series No 179 / September 2016 

13 

reference rate, the size of the loan, the access conditions and other terms and 
conditions in the form of non-interest rate charges (i.e. fees), collateral or guarantees 
which the respective borrower needs to provide, loan covenants and the agreed loan 
maturity. Typically, credit terms and conditions can be expected to change more 
frequently and to a larger extent than the internal guidelines or loan approval criteria 
of a bank. 

In addition, the definition of “loan demand” has been clarified in the context of the 
enhancement of the BLS questionnaire. According to the BLS compilation guide, 
loan demand refers to the need of enterprises and households for bank loan 
financing, irrespective of whether or not this need results in a loan being granted. 
Hence, it should reflect the entire amount of loans which was either formally or 
informally requested at a bank, even if some loans were rejected. 

Apart from the refinement of BLS definitions, the BLS questionnaire has been 
analysed with a view to revisions and useful additions to existing questions. 
Examples of additions to questions are “banks’ risk tolerance” as a factor 
contributing to changes in credit standards, the summary indicator “overall terms and 
conditions”, the “general level of interest rates” as a factor affecting loan demand, as 
well as further factors having an impact on demand for housing loans. 

Specifically, the additional factor “banks’ risk tolerance” having an impact on credit 
standards is related to banks’ willingness to supply a loan and can vary with changes 
in the bank’s underlying business strategy. It complements the factor “perception of 
risks”9, which refers to the bank’s perception of actual risks related to the economic 
environment and borrowers’ creditworthiness. From a theoretical point of view, the 
two factors make it possible to more precisely cover the risk-taking channel in the 
monetary policy transmission. 

Regarding credit terms and conditions, the addition of the summary indicator “overall 
terms and conditions” helps to provide an overall picture of the qualitative changes in 
the individual terms and conditions that are reported by banks. 

For all loan categories, the new factor “general level of interest rates” contributing to 
loan demand has been particularly important since its introduction in the first quarter 
of 2015, in relation to the low interest rate environment, which fuels loan demand.  

In addition, for loan demand by households for house purchase, a number of new 
factors provide further evidence on the underlying motivation of housing loan 
demand. For instance, “debt refinancing/restructuring and renegotiation” of a loan 
when it leads to an increase or prolongation of the amount borrowed, or changes in 
the “regulatory and fiscal regime of housing markets”, can have an impact on 

9   Related to the general economic situation and outlook, the industry or firm-specific situation and 

outlook, borrowers’ creditworthiness, as well as the collateral demanded. 

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housing loan demand. In addition, the factor “internal finance of house purchase out 
of savings/down payment” has replaced the previous factor “household savings”.10 

Moreover, for each loan category two additional standard questions were introduced 
in the context of the enhancement of the questionnaire: (i) on factors affecting banks’ 
credit terms and conditions for new loans; and (ii) on the change in the share of 
rejected loan applications. 

The factors affecting changes in terms and conditions provide additional insights into 
why such changes occurred. Compared with the factors affecting credit standards, 
the relative importance of the factors may be different, indicating their different role in 
banks’ lending policy. 

The inclusion of a question on the share of loan rejections reflects the relevance of 
this information for assessing credit supply constraints or potential credit rationing. A 
higher share of loan rejections may reflect a lower creditworthiness of borrowers or a 
lower willingness of banks to lend, for instance because of a decrease in banks’ risk 
tolerance. Therefore, changes in rejection rates should be related to changes in 
credit standards.  

Overall, the new questionnaire aims at striking a balance between on the one hand 
useful revisions and additions to the survey and on the other hand limiting the 
reporting burden of participating banks and ensuring the continuity of the survey, 
which is crucial for the economic analysis of the BLS results. 

2.3 

Extension of the standard questionnaire – ad hoc 
questions 

The BLS questionnaire puts a large emphasis on the continuity of questions to be 
able to use the survey results for analytical purposes. At the same time, when 
specific topics of interest emerge, the BLS can be complemented with dedicated ad 
hoc questions. In contrast to the standard questions for which the results for the euro 
area and for most of the euro area countries are available, the ECB publishes the 
results of the ad hoc questions only for the euro area as a whole.11 

While the economic analysis of the main ad hoc questions will be carried out in 
Chapter 4 of this Occasional Paper, the development of this conceptual extension of 
the BLS questionnaire is presented in the current section. 

10   The new factor refers more clearly to the substitution of external financing with internal financing out of 
household savings when purchasing a house. By contrast, “household savings” could have also been 
understood as a wealth effect, i.e. higher household wealth would have enabled the taking-out of a 
larger loan. 

11   Some selected results for the ad hoc questions are published by the national central banks (NCBs). 

Occasional Paper Series No 179 / September 2016 

15 

                                                                    
Table 1 
Overview of ad hoc questions in the euro area BLS 

Type of ad hoc question 

From 

Until 

Frequency 

Inclusion in the BLS 

Situation in housing markets 

Share of loan to households secured by real estate used for other purposes than the acquisition 
of a principal residence 

July 2006 

July 2006 

one-off question 

Impact of the financial market turmoil / situation in financial markets 

Impact of the financial market turmoil on credit standards, degree to which the access to 
wholesale funding is hampered, bank lending and banks' capital position 

October 2007 

October 2009 

quarterly 

Additional question on the effect of government announcements of recapitalisation support and 
state guarantees on banks' access to wholesale funding 

January 2009 

January 2010 

quarterly 

Modification of the ad hoc question to the impact of the financial market situation on the change 
in banks' access to wholesale funding and impact on banks' capital position and lending 

January 2010 

January 2011 

quarterly 

Modification of the ad hoc question to the impact of the financial market situation on the change 
in banks' access to wholesale funding 

April 2011 

ongoing 

quarterly 

Addition of the access to retail funding 

January 2012 

ongoing 

quarterly 

Forward-looking questions with a longer time horizon 

Forward-looking question on credit standards and contributing factors with a 12-month horizon 

January 2010 

January 2010 

one-off question 

Impact of regulatory and supervisory changes 

Impact of the Capital Requirements Regulation/Capital Requirements Directive IV (CRR/CRD 
IV) and other regulatory actions relating to capital on banks' financial situation and bank lending 
conditions 

July 2011 

ongoing 

Addition of the impact on credit margins 

January 2013 

ongoing 

Addition of the impact on bank funding conditions 

January 2014 

ongoing 

Addition of the impact of leverage or liquidity requirements and of the impact on total and liquid 
assets 

January 2015 

ongoing 

Impact of the sovereign debt crisis 

bi-annual 
(January and July) 

bi-annual 
(January and July) 

bi-annual 
(January and July) 

bi-annual 
(January and July) 

Impact of the sovereign debt crisis on bank funding and bank lending conditions 

January 2012 

October 2014 

quarterly 

Impact of the 3-year longer-term refinancing operations (LTROs) 

Impact of the 3-year longer-term refinancing operations (LTROs) on bank lending conditions 

February 2012 

February 2012 

one-off question 
(confidential) 

Level of credit standards 

Level of credit standards compared with the midpoint of a historical range of credit standards 

April 2014 

ongoing 

annual 

Impact of the targeted longer-term refinancing operations (TLTROs) 

Participation, reasons to participate or not, purposes for which funds are used and impact of the 
TLTROs on banks' financial situation and bank lending conditions 

October 2014 

ongoing 

bi-annual since January 
2015 (January and July) 

Impact of the ECB's expanded asset purchase programme (APP) 

Impact of the ECB's expanded APP on banks' financial situation, purposes for which the 
additional liquidity is used and impact on bank lending conditions 

April 2015 

ongoing 

Impact of the ECB's negative deposit facility rate 

Impact of the ECB's negative deposit facility rate on banks' net interest income and bank 
lending conditions 

April 2016 

ongoing 

bi-annual 
(April and October) 

bi-annual 
(April and October) 

Source: ECB. 

Ad hoc questions were used in the BLS for the first time in 2006 (see Table 1). In the 
July 2006 survey round, a specific question was designed to address some of the 
reasons behind the strong growth of loans to households for house purchase at that 
time, focusing in particular on whether loans to households secured by real estate 
were used for purchasing second homes or homes for investment purposes. Overall, 
it turned out that the share of such loans was relatively small in the euro area. 

Occasional Paper Series No 179 / September 2016 

16 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
For the second time in the history of the BLS, ad hoc questions were included in the 
October 2007 BLS round against the background of the US sub-prime mortgage 
crisis and the spillover to other countries and markets. The BLS served as a useful 
tool to collect timely information on the likely impact of the turmoil in credit markets 
on bank lending conditions. Specifically, the ad hoc questions asked for the impact of 
the turmoil in credit markets on banks’ credit standards, on their access to funding 
and on their capital position. In connection to this ad hoc question, the BLS also 
included (in 2009-10) evidence on the effect of government announcements of 
recapitalisation support and state guarantees on banks’ access to wholesale funding. 
Since 2010, as a follow-up to the original question on the degree to which the 
financial market turmoil had hampered banks’ access to market funding, the ad hoc 
question has focused on the change in banks’ access to retail and wholesale funding 
as a result of the situation in financial markets (see Section 4.1). This question has 
become a useful addition to the information provided by the standard BLS 
questionnaire. 

With the further evolution of the financial crisis, the BLS provided (between 2012 and 
2014) evidence on the impact of the sovereign debt crisis on bank funding and 
lending conditions (see Section 4.2). This question provided important information on 
the impact of the sovereign debt crisis as well as the diminishing impact following the 
ECB’s monetary policy measures to ease the funding and liquidity situation of banks.  

In particular, the BLS was used as an important tool to analyse the effectiveness of 
the ECB’s non-standard monetary policy measures in the transmission of monetary 
policy. In February 2012 a special confidential survey on the impact of the three-year 
longer-term refinancing operations (LTROs) was carried out among the BLS sample 
banks in most euro area countries. From October 2014 the survey contained specific 
sets of ad hoc questions focusing on the impact of the targeted longer-term 
refinancing operations (TLTROs) as well as, from April 2015, on the impact of the 
expanded asset purchase programme (APP) in order to obtain evidence on the 
impact of such measures on banks’ financial situation and bank lending conditions 
(see Section 4.3). With respect to the TLTRO ad hoc questions, the questions refer 
to both the first series of TLTROs as well as to TLTRO-II. Banks are asked whether 
and why they participated in the TLTROs or not, for the purposes for which they use 
the TLTRO funds and for the impact on lending conditions. In a broadly comparable 
manner, the ad hoc questions on the expanded APP ask for the impact of the APP 
on banks’ financial situation, the purposes for which banks use the additional APP 
liquidity, stemming either from the banks’ sales of marketable assets or from an 
increase in customer deposits, as well as for the APP impact on bank lending 
conditions. The expanded APP comprises the asset-backed securities purchase 
programme (ABSPP), the third covered bond purchase programme (CBPP3), which 
started in the fourth quarter of 2014, as well as the public sector purchase 
programme (PSPP) from March 2015 and the corporate sector purchase programme 
(CSPP) from June 2016. 12 Moreover, since the April 2016 BLS, an ad hoc question 
on the impact of the ECB’s negative deposit facility rate has been included in order 

12   The latest available data point for the APP ad hoc questions refers to the April 2016 BLS, i.e. the CSPP 

is not yet covered by the questions. 

Occasional Paper Series No 179 / September 2016 

17 

                                                                    
to collect evidence on the impact of this measure on banks’ net interest income and 
bank lending conditions (see Section 4.4). Owing to the timely availability of the 
information, these BLS ad hoc questions have proven particularly useful for 
monetary policy purposes. 

In addition, two ad hoc questions on the impact of regulatory and supervisory 
changes on banks’ balance sheets and on lending conditions were introduced in July 
2011 and have been repeated with several amendments since then in the January 
and July BLS rounds (see Section 4.5). Specifically, the questions ask for the impact 
of the regulatory changes on banks’ risk-weighted assets and capital as well as the 
impact of such adjustments on their credit standards and, since 2013, on credit 
margins. The questions were amended further several times to include for instance 
the impact on bank funding conditions as well as the impact of leverage and liquidity 
requirements referring to the introduction of the liquidity coverage ratio and the 
mandatory disclosure of the leverage ratio since January 2015. Overall, the 
questions serve as a tool to analyse banks’ balance sheet adjustments related to 
regulatory and supervisory changes and their impact on banks’ lending behaviour. 

Moreover, in April 2014 an annual ad hoc question on the level of credit standards 
was introduced (see Section 4.6). This allows putting the replies on changes in credit 
standards in the standard questionnaire into perspective. Specifically, banks are 
asked for their current level of credit standards relative to historical benchmarks. This 
allows a historical comparison even if only a few data points are available. At the 
same time, it has to be acknowledged that a long-term assessment may be difficult 
for survey participants. 

Overall, since the financial crisis, the importance of ad hoc questions has increased 
substantially. Ad hoc questions have become a regular feature of the BLS and have 
increased its importance for monetary policy preparation. 

Occasional Paper Series No 179 / September 2016 

18 

3 

Analysis of bank lending conditions in 
the euro area 

3.1 

Overview of bank lending conditions in the euro area 

Since the introduction of the BLS in 2003, the euro area economy has been through 
periods of strong economic growth, deep recession during the financial crisis and a 
very gradual recovery in the aftermath of the crisis. These periods are mirrored in the 
developments in financing conditions for euro area enterprises and households.  

Around the start of the BLS in 2003, credit standards were strongly tightened, related 
to weak economic growth at that time as well as possibly an initial period in which 
respondents needed to get used to the survey questionnaire. The net tightening of 
credit standards on loans to euro area enterprises turned into a net easing from the 
third quarter of 2004 onwards, which lasted until the second quarter of 2007 (see 
Chart 2). Similarly, for loans to households for house purchase, credit standards 
were mostly eased from the second quarter of 2004 until the first quarter of 2007 
(see Chart 3). On the one hand, strong economic growth in the euro area 
contributed to favourable financing conditions, as it implied high profitability and a 
relatively low credit risk of borrowers. On the other hand, financial innovation and 
loose financing conditions fuelled further economic growth and bank lending, and in 
fact a boom in some market segments, like in particular housing markets. In this 
environment, the ECB raised its key interest rates from December 2005 until July 
2008 in order to counteract upside risks to price stability, also against the 
background of vigorous money and credit growth. 

With the emergence of tensions in the US sub-prime mortgage market in the 
summer of 2007, which subsequently spilled over to other market segments and 
countries, euro area banks tightened significantly their credit standards on loans to 
both enterprises and households from the third quarter of 2007 onwards. The intense 
net tightening of credit standards during this period reflects the deterioration in the 
economic outlook and creditworthiness of borrowers as well as banks’ adjustment of 
their attitude towards risk, in reaction to loose credit standards in the period 
preceding the financial crisis. The net tightening of credit standards peaked in the 
third quarter of 2008 for loans to enterprises, when the investment bank Lehman 
Brothers collapsed in September 2008, and in the fourth quarter of 2008 for loans to 
households. The ECB responded with a rapid reduction in its key interest rates and 
by providing ample liquidity to the banking system. 

Following a temporary improvement in financing conditions in the euro area, the 
emergence of tensions in sovereign bond markets in some euro area countries in the 
second half of 2011 changed the scene again. The intensification of the sovereign 
debt crisis spilled over to the banking sector owing to the close nexus between the 
two sectors. This led to a second, but smaller peak in the net tightening of credit 
standards across all loan categories in the fourth quarter of 2011, when there were 

Occasional Paper Series No 179 / September 2016 

19 

intense concerns about a shortage of liquidity in the banking system, especially in 
the euro area countries that were hit hardest by the crisis. Given the heightened risks 
for economic growth and inflation prospects, the ECB reacted with its monetary 
policy to the worsening financing conditions with two consecutive key rate cuts in 
November and December 2011. 

In addition, the liquidity provision by the ECB to euro area banks through the three-
year longer-term refinancing operations (LTROs) in December 2011 and February 
2012 and the extension of eligible collateral in December 2011 alleviated banks’ 
funding constraints and led in turn to a considerable reduction in the net tightening of 
credit standards in the first quarter of 2012. Moreover, the announcement of the 
ECB’s commitment to conduct Outright Monetary Transactions (OMTs) and the 
further extension of eligible collateral to improve the access of the banking sector to 
Eurosystem operations in the summer of 2012 contributed substantially to calming 
the situation in financial markets and concerns on the part of investors about the 
reversibility of the euro. 

Chart 2 
Credit standards on loans to enterprises and real GDP 
growth in the euro area 

Chart 3 
Credit standards on loans to households for house 
purchase and real GDP growth in the euro area 

(net percentages of tightening and quarterly percentage changes; seasonally adjusted, 
current prices) 

(net percentages of tightening and quarterly percentage changes; seasonally adjusted, 
current prices) 

credit standards on loans to NFCs (lhs)
q-o-q real GDP growth, inverted (rhs)

credit standards on housing loans
q-o-q real GDP growth, inverted (rhs)

75

50

25

0

-25

-50

-75

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

50

40

30

20

10

0

-10

-20

-30

-40

-50

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Sources: ECB and Eurostat. 
Notes: Net percentages are defined as the difference between the sum of the 
percentages of banks responding “tightened considerably” and “tightened somewhat” 
and the sum of the percentages of banks responding “eased somewhat” and “eased 
considerably”. For comparability, the right-hand scale has been inverted. 

Sources: ECB and Eurostat. 
Notes: See the notes to Chart 2. For comparability, the right-hand scale has been 
inverted. 

While the monetary policy measures described above had a substantial stabilising 
effect on financial market prices and were partially passed through also to bank 
lending rates, bank lending growth remained weak up to 2014. Therefore, to 
enhance further the functioning of the monetary policy transmission channel, provide 
further monetary stimulus and bring the euro area economy back onto a path of 
inflation that is consistent with the ECB’s objective of achieving inflation rates below, 
but close to, 2% over the medium term, the ECB has introduced a number of 
additional standard and non-standard monetary policy measures since 2014. These 
have included the announcement of the targeted longer-term refinancing operations 
(TLTROs) in June 2014, the asset-backed securities purchase programme (ABSPP) 

Occasional Paper Series No 179 / September 2016 

20 

 
 
 
 
and third covered bond purchase programme (CBPP3) in October 2014, the 
announcement of the expansion of the asset purchase programme (APP) to include 
public sector securities (i.e. the public sector purchase programme, PSPP) in 
January 2015 and the announcement of the corporate sector purchase programme 
(CSPP) and TLTRO-II in March 2016. The ECB’s non-standard monetary policy 
measures were complemented by further reductions in the key ECB interest rates, 
including the reduction of the ECB’s deposit facility rate into negative territory in June 
2014 and further reductions in the following quarters. 

All these measures supported the improvement of bank lending conditions in the 
euro area (see Chapter 4 for an assessment based on the BLS ad hoc questions of 
the financial market crisis and the impact of the ECB’s measures). In combination 
with banks’ balance sheet repair and the gradual recovery of the euro area economy, 
the ECB’s standard and non-standard measures contributed to a net easing of credit 
standards from the fourth quarter of 2013 for housing loans and from the second 
quarter of 2014 for loans to enterprises until the most recent past in 2016. 

Chart 4 
Credit standards and demand for loans to enterprises 
and growth in MFI loans to NFCs in the euro area 

(net percentages of tightening, net increase in demand; quarterly percentage changes, 
seasonally adjusted) 

Developments in bank lending conditions and loan 
demand can be compared with developments in 
economic activity and bank loan growth over time. This 
underlines the importance of the BLS in assessing 
monetary policy transmission. 

net tightening of credit standards on loans to NFCs (lhs)
net demand for loans from NFCs (lhs)
q-o-q MFI loan growth to NFCs (rhs)

80

60

40

20

0

-20

-40

-60

4

3

2

1

0

-1

-2

-3

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: See the notes to Chart 2. Net percentages for the questions on demand for loans 
are defined as the difference between the sum of the percentages of banks responding 
“increased considerably” and “increased somewhat” and the sum of the percentages of 
banks responding “decreased somewhat” and “decreased considerably”. 

The graphical evidence provided in Chart 2 and Chart 
3 illustrates that changes in credit standards tend to 
lead developments in economic growth by around one 
year and can therefore be used as a leading indicator 
for explaining real GDP growth, in line with the results 
of De Bondt et al. (2010) (see Section 5.1). 

In addition, Chart 4 illustrates the fact that bank loan 
growth is a combination of loan supply and demand 
factors. While the actual MFI loan statistics do not allow 
a disentangling of loan supply and demand factors, 
banks’ qualitative answers about developments in credit 
standards and financing needs of borrowers help to 
distinguish between the two. The chart also shows 
leading indicator properties of credit standards for 
growth in bank loans to NFCs and suggests a similar 

property of NFC net loan demand. 13 Indeed, in the more recent past, net demand for 
NFC loans has become less negative since the first quarter of 2013, while the annual 
growth rate of MFI loans to NFCs reached its trough only in early 2014. The lagging 
relationship between credit standards, firms’ financing needs and actual MFI loan 

13   Different studies using BLS results as explanatory variables typically find lags of between one and four 
quarters as being econometrically significant for explaining aggregate loan growth. The lag structure 
varies with regard to the time period and countries covered and according to the methodology applied. 
For an overview of these studies, see Chapter 5. 

Occasional Paper Series No 179 / September 2016 

21 

                                                                    
 
growth may provide one explanation for the still weak loan growth of euro area NFCs 
in 2015 and 2016. 

The analysis in the remaining sections of this chapter focuses on the developments 
in banks’ credit standards, credit terms and conditions and their factors, as well as 
on bank loan demand and its factors in the euro area as a whole and in the largest 
four euro area countries. In addition to the presentation of the survey evidence itself, 
the evidence from the BLS will be related to other macroeconomic and financial data 
to analyse and cross-check the results of the BLS. Thereby, the BLS results are put 
into a broader macroeconomic context, underlining the important role which the BLS 
plays in assessing bank loan supply and demand conditions in the euro area. 

3.2 

Credit standards and terms and conditions on loans to 
enterprises and households and contributing factors  

Based on the presentation of the overall developments in credit standards in 
Section 3.1, this section focuses on the factors contributing to changes in credit 
standards and credit terms and conditions. It further relates the developments in 
bank lending conditions to quantitative data on the macroeconomic and financial side 
of the euro area economy as well as to other survey data (see Chart 5 for a 
schematic overview of the selected indicators presented throughout the section). 

Chart 5 illustrates the relationship between loan supply, represented in the BLS 
mainly by credit standards, and loan demand (displayed by the big gears) with their 
contributing factors (shown in the outer circle of these gears) as covered in the BLS 
questionnaire. Going beyond the direct content of the survey, the chart also shows 
the connection with selected other macroeconomic and financial indicators, for which 
the relationship with the BLS is analysed in this chapter (upper small gears). At the 
same time, it is important to note that the BLS may be connected with further 
indicators which are not covered here. As illustrated in the chart, loan supply and 
demand, as well as the contributing factors, have an impact on bank lending 
conditions and spreads which are negotiated between lenders and borrowers. Actual 
loan growth is the outcome of the interplay of loan supply and demand, having 
ultimately an impact on real economic growth and inflation (displayed in the bottom 
two gears). 

Indeed, when analysing the relationship of the BLS with quantitative and other 
survey data in the remainder of this chapter, it turns out that the BLS results have a 
close relationship with, and in part leading indicator properties for, other 
macroeconomic and financial indicators. This cross-check confirms the information 
content of the BLS with regard to analysing economic developments in the euro 
area. In particular, taking into account the unique value of such a survey among 
banks in disentangling loan supply and demand effects, it allows an assessment of 
bank lending supply and demand conditions and their impact on loan growth and, 
more broadly, economic growth and inflation. 

Occasional Paper Series No 179 / September 2016 

22 

Chart 5 
Graphical illustration of the interaction of selected macroeconomic and financial indicators with bank loan supply 
and demand 

ECONOMIC CONDITIONS

Borrowers' 
balance sheet 
situation

House 
prices

Unemployment 
rate

M&A activity

Firm 
profitability

Confidence 
indicators

Cost of funds and
balance sheet constraints

Bank lending 
conditions and 
spreads

Financing cost of 
borrowers

Risk
perceptions

BANK LOAN 
SUPPLY

Competition

Risk
tolerance

LOAN GROWTH

Financing 
needs

LOAN
DEMAND

Alternative
finance

GDP GROWTH AND
INFLATION

Note: The factors surrounding bank loan supply and demand refer to the BLS factors contributing to changes in credit standards and loan demand respectively. 

3.2.1 

Loans to enterprises 

The net tightening or net easing of credit standards14, i.e. of the internal guidelines or 
loan approval criteria, is influenced by some key factors, like banks’ cost of funds 
and balance sheet constraints, risk perceptions, competition and banks’ risk 
tolerance (see Chart 6). The former three factors have been included in the BLS 
since its start in 2003, whereas the last factor, which refers to the bank’s risk 
tolerance in its lending policy, was introduced in April 2015 in the enhanced BLS 

14   See Section 2.2.2 and the Glossary at the end of this Occasional Paper for an explanation of the BLS 

terms. 

Occasional Paper Series No 179 / September 2016 

23 

 
                                                                    
questionnaire. Among the factors, banks’ cost of funds and balance sheet 
constraints and banks’ risk tolerance refer mainly to banks’ ability and willingness to 
provide loans and, hence, to loan supply. Risk perceptions with respect to economic 
developments and the creditworthiness of borrowers also refer to loan supply, but 
they also contain demand considerations having an impact on credit standards. This 
shows the interaction between loan supply and demand. Compared with credit 
standards, credit terms and conditions refer to the actual lending conditions on new 
loans, which are negotiated between the lender and the borrower, such as loan 
margins and, for instance, collateral requirements (see also Section 2.2.2 for the 
definition of credit standards and terms and conditions as well as the specific role of 
the factors in explaining credit supply and demand). 

Generally, the importance of the factors having an impact on credit standards on 
loans to enterprises is distributed asymmetrically during periods of net tightening and 
net easing of credit standards and has changed over time (see Chart 7). 

Chart 6 
Euro area banks’ credit standards on loans to 
enterprises and contributing factors 

Chart 7 
Relative importance of factors having an impact on 
credit standards on loans to NFCs 

(net percentages of tightening and contributing factors) 

(in percentages of the sum of the factors) 

credit standards on loans to NFCs
banks' risk tolerance
risk perceptions
competition
cost of funds and balance sheet constraints

bank's risk tolerance
risk perceptions
competition
cost of funds and balance sheet constraints

125

100

75

50

25

0

-25

1.0

0.8

0.6

0.4

0.2

0.0

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: The net percentages for responses to questions related to the factors are defined 
as the difference between the percentage of banks reporting that the given factor 
contributed to a tightening and the percentage reporting that it contributed to an easing. 
“Cost of funds and balance sheet constraints” are an unweighted average of “cost 
related to capital position”, “access to market financing” and “liquidity position”; “risk 
perceptions” are an unweighted average of “general economic situation and outlook”, 
“industry or firm-specific situation and outlook/borrower’s creditworthiness” and “risk on 
collateral demanded”; “competition” is an unweighted average of “bank competition”, 
“non-bank competition” and “competition from market financing”. “Risk tolerance” was 
introduced in Q1 2015. 

Source: ECB. 
Notes: See the notes to Chart 6. Percentages are calculated based on the net 
percentages of the factors, relative to the sum of the net percentages of all factors. 

Risk perceptions generally play an important role in the net tightening of credit 
standards when current and expected economic activity is weak. The latter is for 
instance reflected in the industrial confidence indicator of the European Commission 
(see Chart 8). 15 In periods of weak economic activity, like in 2003, in 2007-08 and in 
2012-13, banks’ typically tighten their credit standards to take account of the 

15   See European Commission (2016). 

Occasional Paper Series No 179 / September 2016 

24 

 
 
 
 
 
 
 
 
                                                                    
 
declining creditworthiness of borrowers, related to lower profitability of firms, and a 
higher likelihood of non-performing loans. 

While banks’ cost of funds and balance sheet constraints played a less important 
role before the financial crisis, when financing conditions were very favourable, they 
gained importance during the crisis (see Chart 7 and Chart 9). First, banks were 
concerned about the availability and cost of short-term funding when the US sub-
prime crisis hit the euro area money markets in August 2007, and passed this on to 
their credit standards. In addition, banks’ cost of funds and balance sheet constraints 
were a major factor in the net tightening of credit standards following the insolvency 
of the investment bank Lehman Brothers in September 2008, related to the drying-up 
of interbank markets. The relative importance of banks’ cost of funds and balance 
sheet constraints in the net tightening of credit standards peaked in the fourth 
quarter of 2011, when in particular banks in the vulnerable euro area countries were 
concerned about their access to retail and wholesale funding (see also the ad hoc 
question on banks’ access to retail and wholesale funding in Section 4.1). Following 
the ECB’s liquidity provision via the two three-year LTROs, the importance of this 
factor declined during 2012, reflecting banks’ alleviated funding concerns. 

Chart 8 
Euro area banks’ risk perception and industrial 
confidence 

Chart 9 
Euro area banks’ cost of funds and balance sheet 
constraints and banks’ funding cost 

(net percentages of factors contributing to a tightening of credit standards and 
percentage balances) 

(net percentages of factors contributing to a tightening of credit standards and 
percentages p.a.) 

general economic situation and outlook (lhs)
industry and firm-specific outlook (lhs)
risk on collateral demanded (lhs)
industrial confidence, inverted (rhs)

capital position (lhs)
market financing (lhs)
liquidity position (lhs)

banks' funding cost (rhs)
bank bond yields (rhs)

250

200

150

100

50

0

-50

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

-50

-40

-30

-20

-10

0

10

100

75

50

25

0

-25

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

8

6

4

2

0

-2

Sources: ECB and European Commission. 
Notes: Risk perception factors refer to the factors having an impact on credit standards 
for loans to enterprises. See the notes to Chart 6. For comparability, the right-hand 
scale has been inverted. The industrial confidence indicator refers to the European 
Commission DG-ECFIN opinion survey. Balances are constructed as the difference 
between the percentages of respondents giving positive and negative replies. The 
Commission calculates the euro area aggregates on the basis of the national results and 
seasonally adjusts the balance series. 

Sources: ECB, Bloomberg (Merrill Lynch Global Index) and ECB calculations. 
Notes: Cost of funds and balance sheet constraints refer to the factors having an impact 
on credit standards for loans to enterprises. Banks’ funding cost is a composite indicator 
of the average of banks’ deposit rates on new business and banks’ cost of market debt 
funding weighted with their corresponding outstanding amounts. Bank bond yields refer 
to unsecured investment-grade euro area bank bond yields, based on the Merrill Lynch 
Global Index. 

The peaks of the impact of banks’ cost of funds and balance sheet constraints on the 
net tightening of credit standards, as indicated by the BLS, are closely related to the 
peaks in banks’ actual funding cost, as reflected in a composite indicator of banks’ 
retail and wholesale funding cost (see Chart 9). Specifically, during the financial 
crisis, the market debt funding cost (i.e. bank bond yields) played a crucial role for 
the importance of banks’ cost of funds and balance sheet constraints (see Chart 7). 

Occasional Paper Series No 179 / September 2016 

25 

 
 
 
 
 
Competition between banks16, with non-banks and with market financing typically 
has an easing impact on credit standards, especially in periods when banks’ 
concerns about their cost of funds and balance sheet situation as well as risk 
perceptions are declining (see Chart 6 and Chart 7). This was the case in the period 
ahead of the financial crisis, from 2004 until the second quarter of 2007, as well as 
since 2013. 

Chart 10 
Differences in lending conditions and competitive 
pressures by interest rate sensitivity of loan demand 

Chart 11 
Dispersion of the net tightening of credit standards on 
loans across euro area countries 

(unweighted percentages (left chart) and unweighted net percentages (right chart)) 

(standard deviation across euro area countries) 

credit standards 
margins on average loans

banking competition as factor 
contributing to changes in credit 
standards
banking competition as factor 
contributing to changes in margins

enterprises
house purchase
consumer credit

10

0

-10

-20

-30

-40

-50

-60

-70

10

0

-10

-20

-30

-40

-50

-60

-70

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

loan demand responsiveness to
current interest rate level

other banks

Source: ECB. 
Notes: Based on unweighted individual data. Interest rate sensitivity is proxied by banks 
indicating the relevance of the “general level of interest rates” for an increase in loan 
demand. Banks are grouped into those for which this factor is relevant (left chart) and 
other reporting banks (right chart). “Competition from other banks” indicates the factor 
contributing to changes in credit standards and margins on average NFC loans, 
respectively. 

50

40

30

20

10

0

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Note: The standard deviation is calculated based on the net percentages across all euro 
area countries. 

An assessment of more recent changes in competition, more precisely of changes in 
the sub-factor “competition among banks”, moreover, indicates a strong relationship 
between competitive pressures and the interest rate sensitivity of demand for NFC 
loans (see Chart 10). The comparison of replies by individual BLS banks indicating 
the “general level of interest rates” as an important factor for an increase in loan 
demand with the remaining BLS banks may serve as a proxy for the interest rate 
sensitivity of the demand for loans. In the current low interest rate environment, such 
a grouping of individual replies suggests that competitive pressures contribute 
strongly to an easing in credit standards and particularly to a narrowing of margins 
for average loans when the interest rate sensitivity of demand is high, i.e. when the 
“general level of interest rates” is regarded as an important positive factor for loan 
demand (see Chart 10, left-hand side vs. right-hand side). 

16   For a description of the different types of competitive pressures contributing to changes in credit 

standards for loans to enterprises over time and the resurgence of banking competition in the aftermath 
of the crises, see Hempell (2015). 

Occasional Paper Series No 179 / September 2016 

26 

 
 
 
 
 
                                                                    
 
Chart 12 
Credit standards on loans to NFCs across euro area 
countries 

Chart 13 
Impact of cost of funds and balance sheet constraints 
on NFC loans across euro area countries 

(net percentages of tightening) 

(net percentages of factors contributing to a tightening of credit standards) 

euro area (rhs)
Germany
Spain

France
Italy
dummy

euro area (rhs)
Germany
Spain

France
Italy
dummy

300

250

200

150

100

50

0

-50

90

75

60

45

30

15

0

-15

125

100

75

50

25

0

-25

-50

30

24

18

12

6

0

-6

-12

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Note: Net percentages are defined as the difference between the sum of the 
percentages of banks responding “tightened considerably” and “tightened somewhat” 
and the sum of the percentages of banks responding “eased somewhat” and “eased 
considerably”. 

Source: ECB. 
Note: “Cost of funds and balance sheet constraints” are an unweighted average of “cost 
related to capital position”, “access to market financing” and “liquidity position”. 

The different importance of contributing factors is also reflected in the heterogeneous 
developments in credit standards across euro area countries. Overall, the dispersion 
of bank replies increased across euro area countries with the start of the financial 
crisis in 2007 and 2008 (see Chart 11). In particular in the vulnerable euro area 
countries, banks tightened credit standards on loans to NFCs significantly during the 
crisis. In Spain, the net tightening took place predominantly at the beginning of the 
crisis, in mid-2007, partly compensating for loose credit standards before the crisis 
(see Chart 12). In Italy, the intense net tightening of credit standards started 
somewhat later, in the third quarter of 2008, and reached a second peak during the 
sovereign debt crisis in the second half of 2011. During the latter period, banks in 
Italy suffered in particular from difficulties in their access to market funding and in 
their liquidity position, as summarised in the combined factors “cost of funds and 
balance sheet constraints” (see Chart 13). To a smaller extent, banks in France 
were also affected by liquidity problems during the second half of 2011. By contrast, 
the net tightening of credit standards was more limited in Germany and occurred 
mostly in 2008-09. This reflected risk concerns of banks regarding the economic 
situation and outlook against the background of the deep economic recession, as 
well as concerns by some German banks regarding their balance sheet situation 
related to investments in US sub-prime mortgages. By contrast, German banks’ cost 
of funds and balance sheet situation remained largely unaffected by the sovereign 
debt crisis.17 

17 See Deutsche Bundesbank (2016). 

Occasional Paper Series No 179 / September 2016 

27 

 
 
                                                                    
 
Chart 14 
Credit terms and conditions and credit standards on 
loans to euro area NFCs 

Chart 15 
Margins on loans to euro area NFCs and composite 
bank lending rate 

(net percentages of tightening) 

(net percentages of tightening and percentages p.a.) 

margins on average NFC loans
margins on riskier NFC loans
non-interest terms and conditions
credit standards on loans to NFCs

composite bank lending rate for NFCs (rhs)
loan margins (lhs)

100

80

60

40

20

0

-20

-40

7

6

5

4

3

2

1

0

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

100

75

50

25

0

-25

-50

Source: ECB. 
Notes: Margins are defined as the spread over a relevant market reference rate. “Non-
interest terms and conditions” are an unweighted average of non-interest rate charges, 
the size of the loan or credit line, collateral requirements, loan covenants and loan 
maturity. 

Source: ECB. 
Notes: The indicator for the composite bank lending rate for NFC loans is calculated by 
aggregating short and long-term MFI lending rates using a 24-month moving average of 
new business volumes. “Loan margins” are an unweighted average of margins on 
average and riskier loans to NFCs and are defined as the spread over a relevant market 
reference rate. 

Beyond the internal guidelines and loan approval criteria, banks decide in their 
lending policy on the terms and conditions at which they are willing to provide a loan. 
The terms and conditions of a loan are conditional on the borrower’s characteristics, 
in particular on the creditworthiness, the collateral and the related riskiness of the 
loan. Credit standards and terms and conditions are generally closely related, in 
particular in net tightening periods, reflecting the close relationship between the loan 
approval decision and the conditions granted in the actual loan negotiations between 
the bank and the borrower (see Chart 14). At the same time, banks tend to change 
more intensively their price terms and conditions (i.e. loan margins, defined as the 
spread of bank lending rates over a relevant market reference rate) than their credit 
standards. Specifically, margins on riskier loans tend to tighten more than credit 
standards in tightening periods, reflecting an increased borrower risk, the impact of 
asymmetric information between the borrower and lender as well as the risk aversion 
of banks. In addition, in net easing periods, banks’ narrowing of margins on average 
loans has been considerably stronger than the net easing of credit standards. 

Changes in non-interest terms and conditions, like collateral requirements or non-
interest rate charges, tend to move in the same direction as the changes in loan 
margins (see Chart 14). However, non-interest terms and conditions appear to move 
overall less than price terms and conditions. It also seems that banks mostly do not 
use non-interest terms and conditions as a compensatory tool for declining loan 
margins. 

Developments in bank loan margins as reported by BLS banks are related to 
developments in actual bank lending rates, as indicated by the composite bank 
lending rate for loans to NFCs (see Chart 15). A higher lending rate typically also 

Occasional Paper Series No 179 / September 2016 

28 

 
 
 
implies wider margins. In particular, both the net widening of margins on average 
loans and the composite lending rate on loans to NFCs peaked in the third quarter of 
2008, at the time of the Lehman collapse, as well as in the fourth quarter of 2011. In 
addition, the decline in composite bank lending rates since 2014 has been 
accompanied by a considerable narrowing of margins. 

Chart 16 
Margins on loans to euro area NFCs and bank lending 
spreads 

Chart 17 
Margins on loans to NFCs and changes in bank lending 
spreads – country evidence 

(net percentages of tightening and basis points) 

(net percentages of tightening and two-quarter moving average in basis points) 

margins on average NFC loans (lhs)
margins on riskier NFC loans (lhs)
bank lending spread (comp. BLR for NFCs - 3m EURIBOR) (rhs)
change in bank lending spread (lhs)

IT, margins on average NFC loans (lhs)
DE, margins on average NFC loans (lhs)
IT, change in bank lending spread (comp. BLR - 3m EURIBOR) (rhs)
DE, change in bank lending spread (comp. BLR - 3m EURIBOR) (rhs)

100

75

50

25

0

-25

-50

300

250

200

150

100

50

0

-50

-100

-150

100

75

50

25

0

-25

-50

-75

-100

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Sources: ECB and Thomson Reuters. 
Notes: Margins are defined as the spread over a relevant market reference rate. “Comp. 
BLR for NFCs” denotes the composite bank lending rate for NFCs. It is calculated by 
aggregating short and long-term MFI lending rates using a 24-month moving average of 
new business volumes. The change in bank lending spread is a two-quarter moving 
average in basis points. 

Sources: ECB and Thomson Reuters. 
Note: See the notes to Chart 16. 

60

40

20

0

-20

-40

-60

Moreover, developments in BLS bank loan margins are closely associated with 
developments in actual bank lending spreads, calculated as the difference between 
the composite lending rate for NFCs and a relevant market reference rate (see 
Chart 16 for the euro area and Chart 17 at the country level). While banks use a 
range of various market reference rates across bank products for setting their 
lending rates, the three-month EURIBOR can be used as a typical market reference 
rate for the comparison. 

The considerable increase in bank loan margins, as indicated by BLS banks, and in 
bank lending spreads during 2008 and 2009 reflects a reassessment of risk by euro 
area banks in the context of the financial crisis. Bank lending spreads and loan 
margins stabilised and declined slightly in 2010 and the first half of 2011, but rose 
again between the fourth quarter of 2011 and 2012 in the context of the sovereign 
debt crisis (see also the ad hoc question on the sovereign debt crisis in Section 4.2). 
Spreads rose particularly strongly in the vulnerable euro area countries, which were 
more affected by the sovereign debt crisis than the less vulnerable euro area 
countries. In particular, in Italy, the peak of the spread increase in 2011-12 in the 
context of the sovereign debt crisis was as pronounced as the first peak in 2008-09, 
whereas the peak in 2011-12 was much lower for the euro area as a whole and 
especially for Germany compared with 2008-09. 

Occasional Paper Series No 179 / September 2016 

29 

 
 
 
 
 
The differences in bank spread developments in part reflect disturbances in the 
transmission of monetary policy, in particular in the vulnerable euro area countries. 
Funding costs of some banks, especially in the vulnerable euro area countries, did 
not decline in parallel with the key ECB rate cuts, implying that such banks deviated 
from their historical pattern of the pass-through of key ECB rate cuts to bank 
borrowers. Following further standard and non-standard monetary policy measures, 
bank lending spreads have declined considerably since 2014 and bank loan margins 
have narrowed markedly. This applies in particular also to the more vulnerable euro 
area countries, where banks were catching up in the transmission of lower key ECB 
rates to bank lending rates compared with the less vulnerable euro area countries. 

With respect to the driving forces of loan margins, risk perceptions play an important 
role for changes in loan margins (see Chart 18). Specifically, the steep fall in firm 
profitability during the financial crisis led to more stringent terms and conditions 
applied by banks to compensate for firms’ declining creditworthiness. This is 
indicated by the inverse relationship between banks’ margins for loans to enterprises 
and firm profitability, measured here as the annual growth rate of NFCs’ gross 
operating surplus. 

Chart 18 
Terms and conditions for loans to NFCs, risk 
perceptions and firm profitability 

Chart 19 
Terms and conditions for loans to NFCs and 
contributing factors 

(net percentages of tightening and annual percentage changes) 

(net percentages of tightening and contributing factors) 

loan margins (lhs)
banks' risk perceptions (lhs)
annual growth of NFC gross operating surplus (rhs)

cost of funds and balance sheet constraints
competition
risk perception
risk tolerance
margin average loans 
margin riskier loans 

80

60

40

20

0

-20

-40

40

30

20

10

0

-10

-20

10

0

-10

-20

-30

-40

-50

-60

average loans

10

0

-10

-20

-30

-40

-50

-60

riskier loans

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Sources: ECB and Eurostat.  
Notes: “Loan margins” are an unweighted average of margins on average and riskier 
loans to NFCs. Risk perceptions refer to the factors having an impact on credit 
standards for loans to enterprises. See the notes to Chart 6. The gross operating 
surplus of NFCs refers to the operating income of NFCs, before taxation and 
depreciation. 

Source: ECB. 
Note: The factors having an impact on terms and conditions were introduced in Q1 
2015. 

Moreover, in line with the evidence for credit standards, competition has been the 
most important factor contributing to an easing of credit terms and conditions on 
loans to enterprises since the first quarter of 2015, when the factors contributing to 
changes in terms and conditions were introduced in the BLS questionnaire. This has 
been the case for both average and riskier loans, but to different degrees (see 
Chart 19). In particular, the substantial narrowing of margins for average loans in 

Occasional Paper Series No 179 / September 2016 

30 

 
 
 
 
2015 and the first half of 2016 was to a large extent on account of competition. By 
contrast, banks were more cautious in narrowing margins on riskier loans. 

Chart 20 
Changes in rejection rates and in credit standards and 
conditions 

(unweighted percentages (left chart) and unweighted net percentages (right chart)) 

declined
increased

credit standards
terms & conditions

25

20

15

10

5

0

50

25

0

-25

-50

-75

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q1
2015

Q3
2015

Q1
2016

Q1
2015

Q3
2015

Q1
2016

rejection rate
declined

rejection rate
increased

When banks set their credit standards (i.e. their internal 
guidelines or loan approval criteria), they implicitly also 
set their standards for the loans which they do not want 
to grant. A question on the share of loan rejections 
(relative to the total volume of loan applications or 
requests) was introduced in the questionnaire in the 
first quarter of 2015. It complements the information on 
bank lending conditions for the overall assessment of 
the lending situation of potential and actual borrowers. 
As can be seen from Chart 20, an overall small net 
percentage of banks have changed their rejection rates 
on loans to NFCs since the first quarter of 2015. 
Specifically, the comparison of replies by individual BLS 
banks suggests that banks indicating a decline in 
rejection rates for loans to NFCs tend to ease bank 
lending conditions. By contrast, banks that reported an 
increase in rejection rates were more inclined to tighten 
bank lending conditions. 

Source: ECB. 
Notes: Based on unweighted individual replies. The chart on the left-hand side presents 
unweighted percentages of replies regarding the changes in rejection rates for loans to 
enterprises. The chart on the right-hand side presents unweighted net percentages of 
changes in credit standards and in terms and conditions of banks indicating either a 
decline or an increase in their rejection rates. 

Evidence on bank lending conditions from the 
perspective of banks can also be related to survey-
based evidence on bank loan availability from the 
perspective of euro area firms, as available from the 
“Survey on the access to finance of enterprises” (SAFE).18 The evidence from the 
SAFE confirms that bank loan availability has improved considerably for NFCs since 
the first half of 2014 (see Chart 21). At the same time, bank loan availability started 
to improve already in 2013 for large firms according to the SAFE, while it improved 
only since the second half of 2014 and overall less for small and medium-sized 
enterprises (SMEs). 

In addition, in line with banks’ indications of a narrowing of loan margins, euro area 
firms reported a net decrease in the level of bank lending rates since the first half of 
2014 (see Chart 22). According to the SAFE, this decrease was considerably 
stronger for interest rates on loans to large firms than for those on loans to SMEs. 
This should be related to a generally higher riskiness of loans to SMEs, owing for 
example to less detailed reporting requirements compared with large firms implying a 
higher uncertainty in the assessment of SMEs’ creditworthiness. 

18 See the SAFE section of the ECB’s website.  

Occasional Paper Series No 179 / September 2016 

31 

                                                                    
 
Chart 21 
Bank loan availability for euro area NFCs from the 
perspective of banks and firms 

Chart 22 
Bank lending conditions for euro area NFCs from the 
perspective of banks and firms 

(net percentages of tightening and net percentages of deterioration) 

(net percentages of tightening and net increase in rates) 

NFC bank loan availability to firms, inverted (SAFE)
net tightening of credit standards on NFC loans (BLS) 

net increase in interest rates (SAFE)
net widening of loan margins (BLS) 

all NFCs

SMEs

large firms

50

40

30

20

10

0

-10

-20

-30

-40

all NFCs

SMEs

large firms

80

60

40

20

0

-20

-40

-60

Q2
2009

Q2
2011

Q2
2013

Q2
2015

Q2
2009

Q2
2011

Q2
2013

Q2
2015

Q2
2009

Q2
2011

Q2
2013

Q2
2015

Q2
2009

Q2
2011

Q2
2013

Q2
2015

Q2
2009

Q2
2011

Q2
2013

Q2
2015

Q2
2009

Q2
2011

Q2
2013

Q2
2015

Sources: ECB (BLS, SAFE) and European Commission (SAFE). 
Notes: Bank loan availability is defined as the difference between the percentage of euro 
area firms responding “improved” and the percentage of euro area firms responding 
“deteriorated”. For comparability, the net percentage has been inverted. 

Sources: ECB (BLS, SAFE) and European Commission (SAFE). 
Notes: “Net increase in interest rates” is defined as the difference between the 
percentage of euro area firms reporting an “increase” and the percentage of euro area 
firms reporting a “decrease” in the level of interest rates of bank financing. “Loan 
margins” are an unweighted average of margins on average and riskier loans. 

3.2.2 

Loans to households for house purchase 

Loans to households for house purchase account for around 75% of all outstanding 
MFI loans to euro area households, whereas consumer credit and other lending to 
households amount to around one-quarter. Against this background, the analysis of 
loans to households puts a larger emphasis on housing loans. 

During the first phase of the financial crisis, the net tightening of credit standards on 
euro area housing loans was less pronounced than for NFC loans (see Chart 23 and 
Section 3.2.3 on consumer credit and other lending to households). This is related to 
the fact that banks in some countries, in particular Germany, tightened their credit 
standards on housing loans only a little (see Chart 24), whereas the net tightening 
for loans to enterprises was considerable and widespread at the beginning of the 
financial crisis across the large euro area countries (see Chart 12 above). In some 
euro area countries where housing markets were booming before the crisis, spillover 
effects from the US sub-prime crisis contributed to a substantial net tightening of 
credit standards on housing loans. Of the larger euro area countries, BLS banks in 
Spain tightened their credit standards on housing loans the most in net terms in 
2007-08. These developments led to an increase in the dispersion of the net 
tightening of credit standards for housing loans across euro area countries in 2007 
(see Chart 11 above). 

Hence, the overall less intense net tightening of credit standards on housing loans is 
related on the one hand to the heterogeneity of housing market developments 
across euro area countries. On the other hand, the less pronounced net tightening 

Occasional Paper Series No 179 / September 2016 

32 

 
 
 
pattern for housing loans reflects the higher collateralisation of housing loans 
compared with business loans. 

Chart 23 
Euro area banks’ credit standards on NFC loans and 
loans to households 

Chart 24 
Credit standards on housing loans across euro area 
countries 

(net percentages of tightening) 

(net percentages of tightening) 

credit standards on NFC loans
credit standards on housing loans
credit standards on consumer credit and other lending to households

euro area (rhs)
Germany
Spain

France
Italy
dummy

75

50

25

0

-25

200

150

100

50

0

-50

-100

40

30

20

10

0

-10

-20

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB.   
Notes: Net percentages are defined as the difference between the sum of the 
percentages of banks responding “tightened considerably” and “tightened somewhat” 
and the sum of the percentages of banks responding “eased somewhat” and “eased 
considerably”. 

Source: ECB. 
Note: See the notes to Chart 23. 

Chart 25 
Euro area banks’ credit standards on housing loans and 
contributing factors 

Chart 26 
Relative importance of factors having an impact on 
credit standards on housing loans 

(net percentages of tightening and contributing factors) 

(in percentages of the sum of the factors) 

credit standards on housing loans
banks' risk tolerance
risk perceptions
competition
cost of funds and balance sheet constraints

bank's risk tolerance
risk perceptions
competition
cost of funds and balance sheet constraints

100

75

50

25

0

-25

1.0

0.8

0.6

0.4

0.2

0.0

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: The net percentages for responses to questions related to the factors are defined 
as the difference between the percentage of banks reporting that the given factor 
contributed to a tightening and the percentage reporting that it contributed to an easing. 
“Risk perceptions” are an unweighted average of “general economic situation and 
outlook”, “housing market prospects including expected house price developments” and 
“borrower’s creditworthiness” (the latter from Q1 2015 onwards); “competition” is an 
unweighted average of “competition from other banks” and “competition from non-
banks”. “Risk tolerance” was introduced in Q1 2015. 

Source: ECB. 
Notes: See the notes to Chart 25. Percentages are calculated based on the net 
percentages of the factors, relative to the sum of the net percentages of all factors. 

Occasional Paper Series No 179 / September 2016 

33 

 
 
 
 
 
 
 
 
 
 
 
 
In line with loans to enterprises, risk perceptions have been the most important factor 
in periods of net tightening of credit standards on housing loans (see Chart 25 and 
Chart 26). The contribution of housing market prospects to the net tightening of 
banks’ credit standards on housing loans tends to have a negative relationship with 
developments in house prices (see Chart 27). In particular in the early phase of the 
financial crisis, in 2008-09, the steep decline in house prices contributed to banks’ 
net tightening of credit standards owing to worsening housing market prospects. In 
turn, during house price recovery periods, like in 2014-16, housing market prospects 
(and risk perceptions) played only a small role in changes in credit standards. This 
indicates an asymmetric relationship between the tightening and easing impact of 
housing market prospects on credit standards, possibly related to a tightening bias of 
banks in the survey replies. 

Cost of funds and balance sheet constraints as a factor contributing to the net 
tightening of housing loans became very important in the course of the crisis, 
especially during the sovereign debt crisis in 2011 (see Chart 26). It was particularly 
relevant in Italy, signalling liquidity problems of the Italian banking sector at that time 
(see Chart 28). By contrast, this factor was basically not relevant for banks in 
Germany. The importance of banks’ cost of funds and balance sheet constraints 
diminished substantially with the ECB’s liquidity provision via its non-standard 
monetary policy measures (see also Chapter 4). 

Chart 27 
Housing market prospects and annual growth of house 
prices in the euro area 

Chart 28 
Impact of cost of funds and balance sheet constraints 
on housing loans across euro area countries 

(net percentages of factors contributing to a tightening of credit standards and annual 
percentage changes) 

(net percentages of factors contributing to a tightening of credit standards) 

housing market prospects (lhs)
annual growth rate of house prices (rhs)

euro area (rhs)
Germany
Spain

France
Italy
dummy

50

40

30

20

10

0

-10

-20

-30

10

8

6

4

2

0

-2

-4

-6

150

125

100

75

50

25

0

-25

30

25

20

15

10

5

0

-5

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: “Housing market prospects” refer to the factor contributing to the net tightening of 
credit standards on loans to households for house purchase. Euro area house prices 
refer to new and existing dwellings; neither seasonally nor working day adjusted, 
2007=100. 

Source: ECB. 
Note: See the notes to Chart 25. 

Developments in banks’ credit terms and conditions are highly correlated with the net 
tightening of credit standards on housing loans (see Chart 29), in line with the 
evidence presented in Section 3.2.1 for loans to enterprises. In addition, 
developments in banks’ loan margins (defined as the spread of bank lending rates 
over a relevant market reference rate) are closely related to the change in actual 

Occasional Paper Series No 179 / September 2016 

34 

 
 
 
 
 
bank lending spreads (defined as the difference between the composite lending rate 
for housing loans and the three-month EURIBOR) (see Chart 30). The surge in bank 
lending spreads in the second half of 2008 and 2009 and the net widening of banks’ 
loan margins on housing loans reflect the intensification of the financial crisis at that 
time and the disturbance in the pass-through of key ECB interest rate cuts to bank 
lending rates, in particular in some euro area countries. At the same time, the 
increase in bank lending spreads and in loan margins also reflects the correction of 
previously loose credit terms and conditions in an environment of deteriorating 
housing market prospects. Bank lending spreads and loan margins, which had 
declined considerably before the financial crisis, increased dramatically and 
remained overall at elevated levels, before declining from 2013 to 2015 across euro 
area countries and in particular in the vulnerable euro area countries. 

Chart 29 
Credit terms and conditions and credit standards on 
euro area housing loans 

Chart 30 
Loan margins on euro area housing loans and change 
in bank lending spreads 

(net percentages of tightening) 

(net percentages of tightening and two-quarter moving average in basis points) 

loan margins (lhs)
change in bank lending spread (comp. BLR - 3m EURIBOR) (rhs)

loan margins
non-interest terms and conditions
credit standards on housing loans

60

40

20

0

-20

-40

60

50

40

30

20

10

0

-10

-20

-30

120

100

80

60

40

20

0

-20

-40

-60

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: “Loan margins” are defined as the spread over a relevant market reference rate. 
They are an unweighted average of margins on average and on riskier loans. 

Sources: ECB and Thomson Reuters. 
Notes: “Loan margins” are defined as the spread over a relevant market reference rate. 
They are an unweighted average of margins on average and on riskier loans. “Comp. 
BLR” denotes the composite bank lending rate for loans to households for house 
purchase. It is calculated by aggregating short and long-term MFI lending rates using a 
24-month moving average of new business volumes. The change in the bank lending 
spread is a two-quarter moving average in basis points. 

Besides a close correlation with loan margins, the net tightening of non-interest 
terms and conditions for housing loans like loan-to-value (LTV) ratios and collateral 
requirements is also closely correlated with developments in house prices (see 
Chart 31). The negative correlation reflects that banks tend to ease LTV conditions, 
i.e. banks increase the loan volume they are willing to grant relative to the value of 
the house, when house prices increase and housing wealth grows. Such looser 
terms and conditions fuel the increase in house prices and housing loan growth 
further, which has led in the past to housing market boom-bust episodes. In the euro 
area, the annual growth rate of house prices declined steeply from the second half of 
2007 onwards, when the US sub-prime crisis spilled over to the euro area, and 
reached its trough in mid-2009. This development went hand in hand with a 
tightening of LTV ratios, i.e. banks reduced the loan volume they were willing to 

Occasional Paper Series No 179 / September 2016 

35 

 
 
Chart 31 
Loan-to-value ratios on euro area housing loans and 
house prices 

grant relative to the value of the house, which peaked in 
the fourth quarter of 2008 and reflected banks’ 
scepticism regarding housing market prospects. 

(net percentages of tightening and annual percentage changes) 

loan-to-value ratio (lhs)
collateral requirements (lhs)
annual growth of house prices (rhs)

40

30

20

10

0

-10

-20

12

9

6

3

0

-3

-6

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: Euro area house prices refer to new and existing dwellings; neither seasonally 
nor working day adjusted, 2007=100. 

Of the four largest euro area countries, LTV ratios were 
tightened most in Spain, reflecting the steep decline in 
prices in the Spanish housing market as well as loose 
conditions before the crisis. With the recovery of euro 
area house prices, the net tightening impact of LTV 
ratios and collateral requirements on housing loans 
declined. At the same time, banks hardly eased LTV 
ratios in net terms. This may imply that banks apply a 
more prudent approach, possibly partly related to 
regulatory changes in housing markets 19, compared 
with the period before the crisis, which may be 
beneficial from a macroprudential and financial stability 
perspective. 

3.2.3 

Consumer credit and other lending to households 

Consumer credit and other lending to households (hereafter referred to as simply 
“consumer credit”) accounts for about one-quarter of MFI lending to euro area 
households. It includes loans granted mainly for personal consumption, such as for 
the financing of motor vehicles, furniture and other consumer durables. Overdrafts 
and credit card loans also typically belong in this category as well as loans to sole 
proprietors and partnerships. Bank lending conditions for consumer credit are 
therefore closely related to the general economic and employment situation and its 
implications for consumer creditworthiness. 

Compared with loans to enterprises and housing loans, the net tightening of credit 
standards at the beginning of the financial crisis started somewhat later and was 
overall less intense for consumer credit, in particular when compared with loans to 
enterprises (see Chart 23 above). Risk perceptions were the main contributor to 
banks’ net tightening of credit standards on consumer credit during the crisis, while 
competition has been the most important factor in the easing periods before the 
crisis and since the second quarter of 2014, in line with the pattern of the relative 
importance of factors for the other loan categories (see Chart 32 and Chart 33). The 
relative importance of banks’ cost of funds and balance sheet constraints for the net 
tightening of credit standards on consumer credit increased during the financial 
crisis, in particular during the sovereign debt crisis. 

19 See the European Commission’s website regarding the implementation of the EU Mortgage Credit 

Directive 2014/17/EU. 

Occasional Paper Series No 179 / September 2016 

36 

 
                                                                    
 
Chart 32 
Euro area banks’ credit standards on consumer credit 
and other lending to households 

Chart 33 
Relative importance of factors having an impact on 
credit standards on consumer credit and other lending 
to households 

(net percentages of tightening and contributing factors) 

(in percentages of the sum of the factors) 

credit standards on consumer credit and other lending
banks' risk tolerance
risk perceptions
competition
cost of funds and balance sheet constraints

bank's risk tolerance
risk perceptions
competition
cost of funds and balance sheet constraints

60

45

30

15

0

-15

-30

1.0

0.8

0.6

0.4

0.2

0.0

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: The net percentages for responses to questions related to the factors are defined 
as the difference between the percentage of banks reporting that the given factor 
contributed to a tightening and the percentage reporting that it contributed to an easing. 
“Risk perceptions” are an unweighted average of “general economic situation and 
outlook”, “creditworthiness of consumers” and “risk on collateral demanded”; 
“competition” is an unweighted average of “competition from other banks” and 
“competition from non-banks”. “Risk tolerance” was introduced in Q1 2015. 

Chart 34 
Credit standards for consumer credit and other lending 
to households across countries 

(net percentages of tightening) 

euro area (rhs)
Germany
Spain

France
Italy
dummy

Source: ECB. 
Notes: See the notes to Chart 32. Percentages are calculated based on the net 
percentages of the factors, relative to the sum of the net percentages of all factors. 

Chart 35 
Change in the unemployment rate and bank lending 
conditions for consumer credit and other lending to 
households 

(net percentages of tightening, factors contributing to the net tightening and 
percentages) 

margin on average loans (lhs)
margin on riskier loans (lhs)
creditworthiness of consumers (lhs)
change in unemployment rate (rhs)

250

200

150

100

50

0

-50

50

40

30

20

10

0

-10

50

40

30

20

10

0

-10

-20

-30

1.0

0.8

0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Note: Net percentages are defined as the difference between the sum of the 
percentages of banks responding “tightened considerably” and “tightened somewhat” 
and the sum of the percentages of banks responding “eased somewhat” and “eased 
considerably”. 

Sources: ECB and Eurostat. 
Notes: “Creditworthiness of consumers” is a factor having an impact on the net 
tightening of credit standards on consumer credit and is a component of “risk 
perceptions”. The unemployment rate is given as a percentage of the labour force.  

Occasional Paper Series No 179 / September 2016 

37 

 
 
 
 
 
 
 
 
 
 
 
Across the large euro area countries, credit standards on consumer credit were 
tightened most in Spain at the beginning of the financial crisis, reflecting the spillover 
of the deterioration in housing markets to consumers’ creditworthiness (see 
Chart 34). The net tightening of credit standards in Italy was also intense, but started 
slightly later and was more distributed over the quarters. By contrast, credit 
standards were tightened only a little or even eased in Germany and France, partly 
related to competitive pressures. These developments led to an increase in the 
heterogeneity of the net tightening of credit standards for consumer credit across 
euro area countries during 2007-08 (see Chart 11 above). 

Banks’ loan margins on consumer credit are closely related to changes in 
consumers’ creditworthiness (see Chart 35). Banks demand higher margins on 
average and especially riskier loans when the creditworthiness of consumers is 
deteriorating. One important factor for deteriorating creditworthiness is 
unemployment, as reflected in the positive correlation between changes in 
unemployment rates and changes in loan margins. 

3.3 

Demand for loans to enterprises and households and 
contributing factors 

In addition to credit supply, banks also report on loan demand developments in the 
BLS and on factors contributing to changes in loan demand. In this context, loan 
demand refers to the bank loan financing need of enterprises and households, 
independent of whether this need will result in a loan or not. 

Loan demand depends on a variety of factors, like in particular financing needs of 
enterprises for fixed investment, working capital or M&As. Financing needs of 
households mainly relate to housing market developments, consumer confidence 
and spending on durable consumer goods. For all loan categories, changes in the 
general level of interest rates have an impact on loan demand. In line with the 
approach for loan supply in Section 3.2, loan demand is related in this section to 
quantitative and other survey data. The close relationship of the qualitative 
information from the BLS on loan demand with these indicators confirms the valuable 
role of the BLS in the overall assessment of economic developments in the euro 
area (see Chart 5 above for a schematic overview of the interaction of selected 
macroeconomic and financial indicators with bank loan supply and demand). 

3.3.1 

Loans to enterprises 

Following strong loan demand by enterprises in the period from 2003 until the 
second quarter of 2007, NFC loan demand dropped dramatically with the beginning 
of the financial crisis and remained negative until the first quarter of 2010 (see 
Chart 36). Following a short recovery period, net demand for NFC loans became 
negative again from the third quarter of 2011 until the last quarter of 2013, but has 
recovered considerably since 2014. 

Occasional Paper Series No 179 / September 2016 

38 

Across the large euro area countries, loan demand contracted strongly during the 
financial crisis in Spain, Italy and France, whereas it remained rather resilient in 
Germany (see Chart 37). While it declined in Spain most strongly at the beginning of 
the crisis, along with the intense net tightening of credit standards at that time, the 
largest contraction in Italy occurred during the sovereign debt crisis. All in all, 
heterogeneous country developments led to an increase in the dispersion of NFC 
loan demand in 2007 and 2008 (see Chart 38). 

Chart 36 
Net demand for loans to euro area enterprises and 
contributing factors 

Chart 37 
Net demand for loans to enterprises across selected 
euro area countries 

(net percentages of banks reporting an increase in demand and contributing factors) 

(net percentages of banks reporting an increase in demand) 

demand for NFC loans (rhs)
fixed investment (lhs)
inventories and working capital (lhs)
general level of interest rates (lhs)
other financing needs (lhs)
use of alternative finance (lhs)

euro area (rhs)
Germany
Spain

France
Italy
dummy

75

50

25

0

-25

-50

-75

-100

45

30

15

0

-15

-30

-45

-60

200

150

100

50

0

-50

-100

-150

-200

-250

40

30

20

10

0

-10

-20

-30

-40

-50

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: Net percentages for the questions on demand for loans are defined as the 
difference between the sum of the percentages of banks responding “increased 
considerably” and “increased somewhat” and the sum of the percentages of banks 
responding “decreased somewhat” and “decreased considerably”. The net percentages 
for responses to questions related to each factor are defined as the difference between 
the percentage of banks reporting that the given factor contributed to increasing demand 
and the percentage reporting that it contributed to decreasing demand. “Other financing 
needs” are an unweighted average of “M&A and corporate restructuring” and “debt 
refinancing/restructuring and renegotiation”; “use of alternative finance” is an unweighted 
average of “internal financing”, “loans from other banks”, “loans from non-banks”, 
“issuance/redemption of debt securities” and “issuance/redemption of equity”. “General 
level of interest rates” was introduced in Q1 2015. 

Source: ECB. 
Notes: See the notes to Chart 36. Percentages are calculated based on the net 
percentages of the factors, relative to the sum of the net percentages of all factors. 

Demand for loans to euro area enterprises has been largely driven by firms’ 
financing needs for fixed investment, which is the dominant factor contributing to 
NFC loan demand (see Chart 36 and Chart 39). Given the long-term nature of fixed 
investment, the relationship is close to firms’ demand for long-term loans (see 
Chart 40). In addition, “inventories and working capital” reflect the financing need for 
firms’ daily business. In recovery periods, financing needs for inventories and 
working capital generally recover earlier than those for fixed investment. 

Related to the considerable importance of financing for fixed investment, inventories 
and working capital for firms’ business, NFC loan demand is closely connected to the 
stage of the business cycle and to the economic sentiment of the industrial sector 
(see Chart 41). 

Occasional Paper Series No 179 / September 2016 

39 

 
 
 
 
 
 
 
 
 
 
 
 
Chart 38 
Dispersion of the net increase in loan demand across 
euro area countries 

(standard deviation across euro area countries) 

enterprises
house purchase
consumer credit

60

50

40

30

20

10

0

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Note: The standard deviation is calculated based on the net percentages across all euro 
area countries. 

At the same time, net demand for NFC loans has 
increased considerably more than indicated by NFCs’ 
financing needs for fixed investment and for their daily 
business in some periods. 

In the period from the fourth quarter of 2003 until the 
second quarter of 2007, i.e. until the start of the 
financial crisis, the relative importance of firms’ 
financing needs for M&As and corporate restructuring 
increased considerably (included in the BLS factor 
“Other financing needs” contributing to NFC demand; 
see Chart 39). This reflects strong M&A activity during 
this period and the related additional financing need of 
firms for acquiring other companies (see Chart 42), a 
development which had been fuelled by the favourable 
financing conditions for borrowers at that time. The drop 
in M&A activity between the second half of 2007 and 
the first half of 2010 is mirrored by the steep fall in 
financing needs for this type of activity. In addition, the 
modest recovery of M&A activity since the second half 
of 2014 has led to a corresponding increase in 
financing needs of firms. 

Chart 39 
Relative importance of factors having an impact on 
demand for NFC loans 

Chart 40 
Demand for loans to NFCs across maturities and NFC 
financing needs 

(in percentages of the sum of the factors) 

(net percentages of banks reporting an increase in demand and contributing factors) 

fixed investment
inventories and working capital
general level of interest rates
other financing needs
use of alternative finance

demand for long-term NFC loans
demand for short-term NFC loans
financing need for fixed investment
financing need for inventories and working capital

1.0

0.8

0.6

0.4

0.2

0.0

60

40

20

0

-20

-40

-60

-80

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: See the notes to Chart 36. Percentages are calculated based on the net 
percentages of the factors, relative to the sum of the net percentages of all factors. 

Source: ECB. 
Notes: See the notes to Chart 36. 

Occasional Paper Series No 179 / September 2016 

40 

 
 
 
 
 
 
Chart 41 
Net demand for loans to NFCs and industrial 
confidence in the euro area 

Chart 42 
Financing need for M&As and corporate restructuring in 
the euro area 

(net percentages of banks reporting an increase in demand and percentage balances) 

(net percentages contributing to an increase in demand and quarter-on-quarter 
percentage change of 12-month sum of deal value) 

demand for NFC loans (lhs)
industrial confidence (rhs)

financing needs for M&As and corporate restructuring
change in M&As in the euro area NFC sector

30

15

0

-15

-30

-45

-60

20

10

0

-10

-20

-30

-40

80

60

40

20

0

-20

-40

-60

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Sources: ECB and European Commission. 
Notes: See the notes to Chart 36. The industrial confidence indicator refers to the 
European Commission DG-ECFIN opinion survey. Balances are constructed as the 
difference between the percentages of respondents giving positive and negative replies. 
The Commission calculates the euro area aggregates on the basis of the national results 
and seasonally adjusts the balance series. 

Chart 43 
Loan demand and debt-to-GDP ratio of euro area NFCs 

(net percentages and annual percentage changes) 

demand for NFC loans (lhs)
annual growth in debt-to-GDP ratio (rhs)

30

20

10

0

-10

-20

-30

-40

-50

6

4

2

0

-2

-4

-6

-8

-10

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Sources: ECB and Eurostat. 
Note: NFC debt includes loans, debt securities issued by NFCs and pension fund 
reserves. 

Sources: ECB and Dealogic. 
Notes: See the notes to Chart 36. M&A activity, involving euro area corporates as the 
acquirer, is displayed as the percentage change in the deal value (cash and borrowing) 
according to the completion date. 

High loan demand during the period up to the start of 
the financial crisis led to a significant increase in the 
debt-to-GDP ratio of euro area NFCs, which continued 
to build up until the third quarter of 2009, partly related 
to the weakness in economic activity as well as owing 
to the lagged relationship between loan demand and 
MFI loan growth (see Chart 43 and Chart 4 above). 
The increase in firms’ indebtedness was followed by 
rising concerns on the part of lenders regarding the 
balance sheet situation of borrowers and the 
consequent need of borrowers to consolidate their 
balance sheets. This dampened loan demand following 
the financial crisis. 

Turning to financial factors, demand for NFC loans has 
increased strongly in periods of favourable financing 
costs for firms, as indicated by low lending rates and 
spreads. As can be seen from Chart 44, there is a 
negative relationship between demand for NFC loans 

and the change in bank lending spreads (defined as the difference between 
composite lending rates for NFCs and a relevant market reference rate) as well as 
margins on NFC loans. Specifically, loan demand declined when bank lending 
spreads increased during the financial crisis. In the more recent period since 2014, 
favourable financing costs have fuelled NFC loan demand. This is also confirmed by 
the factor “general level of interest rates”, which has contributed positively to NFC 

Occasional Paper Series No 179 / September 2016 

41 

 
 
 
 
 
 
 
loan demand since its introduction in the first quarter of 2015 (see Chart 39 and 
Chart 45). 

Chart 44 
Relationship between demand for NFC loans and bank 
lending spreads 

Chart 45 
Interest rate sensitivity of demand for loans to 
enterprises and banks’ changes in loan margins 

(net percentages of banks reporting an increase in demand, net percentage of tightening 
and two-quarter moving average in basis points) 

(unweighted net percentages of banks reporting an increase in demand) 

demand for NFC loans (lhs)
change in bank lending spread (comp. BLR for NFCs - 3m EURIBOR) (rhs)
margin on average NFC loans (rhs)

fixed investment
margin average loans
margin riskier loans

working capital
mergers & acquisitions
dummy

50

40

30

20

10

0

-10

-20

-30

-40

-50

75

50

25

0

-25

-50

-75

80

60

40

20

0

-20

-40

-60

-80

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Loan demand responsiveness to
current interest rate level

Other banks

Sources: ECB and Thomson Reuters. 
Notes: See the notes to Chart 36. “Comp. BLR” denotes the composite bank lending 
rate for NFCs. It is calculated by aggregating short and long-term MFI lending rates 
using a 24-month moving average of new business volumes. The change in the bank 
lending spread is a two-quarter moving average in basis points. 

Source: ECB. 
Notes: Based on unweighted individual data. Interest rate sensitivity is proxied by net 
percentages for banks indicating the relevance of the “general level of interest rates” for 
an increase in loan demand. Banks are grouped into those for which this factor is 
relevant and other reporting banks. “Fixed investment”, “working capital” and “mergers & 
acquisitions” are selected factors contributing to changes in demand for loans by NFCs; 
changes in margins refer to loans to NFCs by the respective banks. 

Looking at the interest rate sensitivity of demand for NFC loans more closely, the 
differences in the importance of the interest rate level for loan demand across euro 
area BLS banks seems to have a strong impact not only on loan demand but also on 
changes in banks’ lending margins (Chart 45). In this regard, the comparison of 
replies by individual BLS banks indicating the “general level of interest rates” as an 
important factor for an increase in loan demand with the remaining banks may serve 
as a proxy for the interest rate sensitivity of loan demand. Indeed, the results 
suggest that a higher interest rate sensitivity of loan demand goes along with higher 
increases in loan demand and stronger reductions in lending margins in a period of 
low and declining market rates.20 The latter may point to a higher degree of 
competition associated with a higher price elasticity of demand (see also Chart 10 in 
Section 3.2 for the observed relationship with banking competition). 

3.3.2 

Loans to households 

After a period of high demand for housing loans, households’ financing needs for 
house purchase dropped strongly between 2006 and 2008 (see Chart 46). 
Compared with NFC loan demand, housing loan demand had already peaked at the 

20   These findings also hold when assessing countries more and less exposed to sovereign risks 

separately.  

Occasional Paper Series No 179 / September 2016 

42 

 
 
                                                                    
 
end of 2005 at high levels and turned negative in the third quarter of 2006, signalling 
the high valuation of housing markets in some euro area countries and deteriorating 
housing market prospects (see Chart 47). With the outbreak of the US sub-prime 
crisis in the summer of 2007, net demand for euro area housing loans dropped 
further and reached its trough in the second half of 2008. 

Chart 46 
Net demand for loans to euro area households and 
NFCs 

Chart 47 
Net demand for housing loans and contributing factors 

(net percentages of banks reporting an increase in demand) 

(net percentages of banks reporting an increase in demand and contributing factors) 

net demand for housing loans
net demand for consumer credit and other lending to households
net demand for NFC loans

demand for housing loans (rhs)
housing market prospects (lhs)
consumer confidence (lhs)
general level of interest rates (lhs)
other financing needs (lhs)
use of alternative finance (lhs)

60

40

20

0

-20

-40

-60

-80

120

80

40

0

-40

-80

-120

-160

-200

60

40

20

0

-20

-40

-60

-80

-100

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: Net percentages for the questions on demand for loans are defined as the 
difference between the sum of the percentages of banks responding “increased 
considerably” and “increased somewhat” and the sum of the percentages of banks 
responding “decreased somewhat” and “decreased considerably”. 

Source: ECB. 
Notes: See the notes to Chart 46. The net percentages for responses to questions 
related to each factor are defined as the difference between the percentage of banks 
reporting that the given factor contributed to increasing demand and the percentage 
reporting that it contributed to decreasing demand. “Other financing needs” are an 
unweighted average of “non-housing-related consumption expenditure” (discontinued in 
Q1 2015), “debt refinancing/restructuring and renegotiation” and “regulatory and fiscal 
regime of housing markets” (both from Q1 2015 onwards); “use of alternative finance” is 
an unweighted average of “internal financing out of savings/down payment” (from Q1 
2015 onwards), “household savings” (until Q4 2014), “loans from other banks” and 
“other sources of external finance”. “General level of interest rates” was introduced in Q1 
2015. 

Housing loan demand declined in particular in Spain, Italy and France, whereas it 
developed in a more stable manner in Germany (see Chart 48). Following a 
temporary recovery, net demand for housing loans became negative again during 
2011-12, in the context of the sovereign debt crisis and liquidity problems in the 
banking sector, in particular in some euro area countries, as well as debt 
consolidation needs of households. From a trough in euro area housing loan 
demand in the first quarter of 2012, the ECB’s monetary policy measures supported 
its recovery. In particular, the low interest rate environment has fuelled housing loan 
demand in the more recent past. The periods of negative housing loan demand from 
the third quarter of 2006 until the second quarter of 2009 and from the first quarter of 
2011 until the second quarter of 2013 broadly correspond to periods of increased 
dispersion in housing loan demand across all euro area countries (see Chart 38 
above). 

Housing market prospects and consumer confidence are the most important factors 
for housing loan demand (see Chart 47 and Chart 49). In addition, the general level 

Occasional Paper Series No 179 / September 2016 

43 

 
 
 
of interest rates has been an important factor for housing loan demand more 
recently. The factor “other financing needs”21 has covered since the first quarter of 
2015 effects related to debt refinancing/restructuring and renegotiation as well as 
any specific impact of changes in the regulatory and fiscal regime of housing 
markets, which can have a relevant impact on housing loan demand in the 
respective countries where changes in the regime have occurred. At the euro area 
level, the impact has been minor however. 

Chart 48 
Net demand for housing loans across selected euro 
area countries 

Chart 49 
Relative importance of factors having an impact on 
demand for housing loans  

(net percentages of banks reporting an increase in demand) 

(in percentages of the sum of the factors) 

euro area (rhs)
Germany
Spain

France
Italy
dummy

300

200

100

0

-100

-200

-300

-400

housing market prospects
consumer confidence
general level of interest rates
other financing needs
use of alternative finance
dummy

60

40

20

0

-20

-40

-60

-80

1.0

0.8

0.6

0.4

0.2

0.0

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Note: See the notes to Chart 46. 

Source: ECB. 
Note: See the notes to Chart 47. Percentages are calculated based on the net 
percentages of the factors, relative to the sum of the net percentages of all factors. 

The availability of alternative sources of finance refers to the internal financing of 
house purchase from household savings and to external financing from other banks 
or other sources of external finance. These financing sources have been an overall 
small but steady factor contributing negatively to housing loan demand in the euro 
area. 

Demand for housing loans is positively related to house price developments (see 
Chart 50). This reflects, on the one hand, the increasing financing needs for house 
purchases in an environment of rising house prices and, on the other hand, positive 
housing market prospects and increasing household wealth fuelling housing loan 
demand. Housing loan demand is also positively related to developments in 
consumer confidence, reflecting the high importance of consumer confidence as a 
contributing factor to housing loan demand (see Chart 51). 

21   “Other financing needs” referred until the fourth quarter of 2014 to non-housing-related consumption 
expenditure, contributing predominantly negatively to housing loan demand. This factor indicated 
mainly a cost of living-related decision between housing loan demand and consumer credit demand. In 
part, it also related to real estate-guaranteed loans for consumption. A modified version of this factor 
was shifted to consumer credit in the first quarter of 2015. 

Occasional Paper Series No 179 / September 2016 

44 

 
                                                                    
 
Moreover, financing costs are an important factor for households’ demand for 
housing loans (see Chart 52). An increase in bank loan margins on housing loans as 
reported in the BLS and an increase in bank lending spreads, calculated as the 
difference between the composite bank lending rate for housing loans and a relevant 
market reference rate, have a dampening impact on housing loan demand. In turn, 
declining spreads fuel housing loan demand, as they did in the most recent period. 

Chart 50 
Demand for housing loans, housing market prospects 
and house prices 

Chart 51 
Demand for housing loans and consumer confidence 

(net percentages of banks reporting an increase in loan demand, contributing factors 
and annual percentage changes) 

(net percentages of banks reporting an increase in demand, contributing factors and 
percentage balances) 

demand for housing loans (lhs)
housing market prospects (lhs)
house prices (y-o-y %, rhs)

demand for housing loans (lhs)
consumer confidence (factor for loan demand) (lhs)
European Commission consumer confidence (rhs)

80

60

40

20

0

-20

-40

-60

-80

8

6

4

2

0

-2

-4

-6

-8

60

40

20

0

-20

-40

-60

-80

-100

0

-5

-10

-15

-20

-25

-30

-35

-40

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Note: See the notes to Chart 47. 

Sources: ECB and European Commission. 
Notes: See the notes to Chart 47. The consumer confidence indicator refers to the 
European Commission DG-ECFIN opinion survey. Balances are constructed as the 
difference between the percentages of respondents giving positive and negative replies. 
The Commission calculates the euro area aggregates on the basis of the national results 
and seasonally adjusts the balance series. 

As regards the interest rate sensitivity of the demand for housing loans more 
specifically, Chart 53 highlights strong differences in the importance of the level of 
interest rates across euro area BLS banks using individual bank replies, which is 
similar to the evidence for loans to enterprises (see Chart 45 for comparison). As 
before, contrasting replies by banks indicating the “general level of interest rates” as 
a factor contributing positively to an increase in loan demand with the remaining 
bank replies serves as a proxy for the differences in the interest rate sensitivity of 
demand. As for loans to enterprises, the results suggest that in an environment of 
low and declining market rates a higher interest rate sensitivity of demand for 
housing loans corresponds to a higher increase in loan demand and a stronger 
reduction in margins for average loans.22 By contrast, no differences can be 
observed with regard to changes in margins for riskier loans. 

22   These findings also hold when assessing countries more and less exposed to sovereign risks 

separately. 

Occasional Paper Series No 179 / September 2016 

45 

 
 
                                                                    
 
Chart 52 
Relationship between demand for housing loans and 
bank lending spreads 

Chart 53 
Interest rate sensitivity of demand for housing loans 
and banks’ changes in loan margins 

(net percentages of banks reporting an increase in loan demand, net percentages of 
tightening and two-quarter moving average in basis points) 

(unweighted net percentages) 

demand for housing loans (lhs)

change in bank lending spread (comp. BLR for housing loans -
3m EURIBOR) (rhs)
margin on average housing loans (rhs)

loan demand
margin average loans
margin riskier loans

60

40

20

0

-20

-40

-60

-80

80

60

40

20

0

-20

-40

120

80

40

0

-40

-80

-120

-160

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

loan demand responsiveness to current
interest rate level

other banks

Sources: ECB and Thomson Reuters. 
Notes: See the notes to Chart 46. “Comp. BLR” denotes the composite bank lending 
rate for loans to households for house purchase. It is calculated by aggregating short 
and long-term MFI lending rates using a 24-month moving average of new business 
volumes. The change in the bank lending spread is a two-quarter moving average in 
basis points. 

Source: ECB. 
Notes: Based on unweighted individual data. Interest rate sensitivity is proxied by net 
percentages for banks indicating the relevance of the “general level of interest rates” for 
an increase in loan demand. Banks are grouped into those for which this factor is 
relevant and other reporting banks. Changes in margins refer to housing loans for the 
respective banks. 

3.3.3 

Consumer credit and other lending to households 

Net demand for consumer credit and other lending to households (hereafter referred 
to as simply “consumer credit”) developed broadly in line with net demand for NFC 
loans and, during the more recent past, also with housing loan demand (see 
Chart 46 above). The most important factors determining developments in consumer 
credit are consumer confidence and spending on durable consumer goods, such as 
cars or furniture (see Chart 54 and Chart 55). Related to this, the European 
Commission’s consumer confidence indicator displays a close relationship with net 
demand for consumer credit and its respective contributing factor (see Chart 56). 

In addition, since the introduction of the factor “general level of interest rates” in the 
first quarter of 2015, this factor has accounted for a relevant share contributing to net 
demand for consumer credit. 

By contrast, “other financing needs” were overall of modest importance for consumer 
credit demand, with the exception of a few periods. Up to the fourth quarter of 2014 
“other financing needs” included financing needs for securities purchases. In 
particular in the period from end-2007 until mid-2009, this factor had a relevant 
dampening impact on the demand for consumer credit, as households were less 
willing and able to take out a loan to purchase securities during the financial crisis. 
From the first quarter of 2015 (when the factor “securities purchases” was 
discontinued), “other financing needs” includes consumption expenditure financed 

Occasional Paper Series No 179 / September 2016 

46 

 
 
 
through real estate-guaranteed loans, the importance of which has been low overall 
in the euro area. 

Chart 54 
Net demand for consumer credit and other lending to 
households and contributing factors 

Chart 55 
Relative importance of factors having an impact on 
demand for consumer credit and other lending to 
households 

(net percentages of banks reporting an increase in demand and contributing factors) 

(in percentages of the sum of the factors) 

demand for consumer credit and other lending (rhs)
spending on durable goods (lhs)
consumer confidence (lhs)
general level of interest rates (lhs)
other financing needs (lhs)
use of alternative finance (lhs)

spending on durable goods
consumer confidence
general level of interest rates
other financing needs
use of alternative finance
dummy

75

50

25

0

-25

-50

-75

-100

-125

-150

-175

60

40

20

0

-20

-40

-60

-80

-100

-120

-140

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: Net percentages for the questions on demand for loans are defined as the 
difference between the sum of the percentages of banks responding “increased 
considerably” and “increased somewhat” and the sum of the percentages of banks 
responding “decreased somewhat” and “decreased considerably”. The net percentages 
for responses to questions related to each factor are defined as the difference between 
the percentage of banks reporting that the given factor contributed to increasing demand 
and the percentage reporting that it contributed to decreasing demand. “Other financing 
needs” refer to “securities purchases” (until Q4 2014) and to “consumption expenditure 
financed through real estate-guaranteed loans” (from Q1 2015 onwards). “Use of 
alternative finance” is an unweighted average of “internal financing out of savings” (from 
Q1 2015 onwards), “household savings” (until Q4 2014), “loans from other banks” and 
“other sources of external finance”. “General level of interest rates” and “consumption 
expenditure financed through real estate-guaranteed loans” were introduced in Q1 2015. 

1.0

0.8

0.6

0.4

0.2

0.0

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: See the notes to Chart 54. Percentages are calculated based on the net 
percentages of the factors, relative to the sum of the net percentages of all factors. 

The use of alternative finance such as loans from other banks or households’ 
internal financing out of savings was of small overall importance for consumer credit 
demand. Nonetheless, an inverse relationship between the factor “household internal 
financing out of savings”, which has a dampening impact on loan demand, and an 
increase in the unemployment rate can be detected (see Chart 57). This indicates 
that households tend to use their savings rather than applying for a loan in times of 
high or increasing unemployment. During the financial crisis and in particular in 2012 
and 2013, the dampening impact of household internal financing out of savings on 
consumer credit increased. Households appear to have used their internal funds for 
financing consumption instead of taking out new loans in an economic environment 
of high and rising unemployment, in particular in some euro area countries, and 
uncertainty about household income prospects. 

Occasional Paper Series No 179 / September 2016 

47 

 
 
 
 
 
 
 
 
 
 
 
 
 
Chart 56 
Net demand for consumer credit and other lending to 
households and consumer confidence 

Chart 57 
Impact of internal financing out of savings on consumer 
credit and other lending to households and the 
unemployment rate 

(net percentages of banks reporting an increase in demand, contributing factors and 
percentage balances) 

(two-quarter average of net percentages of banks reporting an increased contribution to 
loan demand and changes in percentage points) 

demand for consumer credit and other lending (lhs)
consumer confidence (factor for loan demand) (lhs)
European Commission consumer confidence (rhs)

demand contribution of internal finance out of saving (lhs)
change in unemployment rate (rhs)

60

40

20

0

-20

-40

-60

-80

0

-5

-10

-15

-20

-25

-30

-35

15

10

5

0

-5

-10

-15

-20

1.2

0.8

0.4

0.0

-0.4

-0.8

-1.2

-1.6

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Sources: ECB and European Commission. 
Notes: See the notes to Chart 54. The consumer confidence indicator refers to the 
European Commission DG-ECFIN opinion survey. Balances are constructed as the 
difference between the percentages of respondents giving positive and negative replies. 
The Commission calculates the euro area aggregates on the basis of the national results 
and seasonally adjusts the balance series. 

Chart 58 
Net demand for consumer credit and other lending to 
households across selected euro area countries 

(net percentages of banks reporting an increase in demand) 

euro area (rhs)
Germany
Spain

France
Italy
dummy

250

200

150

100

50

0

-50

-100

-150

-200

-250

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Source: ECB. 
Notes: See the notes to Chart 54. 

60

45

30

15

0

-15

-30

-45

-60

Sources: ECB and Eurostat. 
Notes: See the notes to Chart 54. The unemployment rate is given as a percentage of 
the labour force; changes in percentage points. 

Across the largest euro area countries, the drop in net 
demand for consumer credit at the beginning of the 
financial crisis was deepest in Spain, possibly related to 
high and rising unemployment as a result of the crisis 
(see Chart 58). In Italy, demand for consumer credit 
declined strongly during the intensification of the 
sovereign debt crisis and the related uncertainty, which 
had a strong negative impact on consumer confidence. 
The increased dispersion of net demand for consumer 
credit across all euro area countries in particular in 
2008-09 indicates the heterogeneity of the impact of the 
financial crisis across countries (see Chart 38 above). 
Net demand for euro area consumer credit has 
recovered markedly from a trough in the first quarter of 
2012, in particular in the vulnerable euro area countries, 
with overall decreased heterogeneity across countries. 

The ECB’s standard and non-standard monetary policy 
measures have helped the recovery. Chart 59 shows 

the positive impact of the low interest rate environment and specifically the narrowing 
of loan margins on the demand for consumer credit. 

Occasional Paper Series No 179 / September 2016 

48 

 
 
 
 
 
 
 
Chart 59 
Demand for consumer credit and other lending to 
households and loan margins 

Chart 60 
Interest rate sensitivity of loan demand for durable 
consumer goods and banks’ changes in loan margins 

(net percentages of banks reporting an increase in demand or a widening of margins) 

(unweighted net percentages) 

demand for consumer credit and other lending (lhs)
margin on consumer credit and other lending (rhs)

60

40

20

0

-20

-40

-60

75

50

25

0

-25

-50

-75

50

40

30

20

10

0

-10

-20

-30

-40

-50

durable consumer goods
margin average loans
margin riskier loans

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q1
2015

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2016

Q4
2002

Q4
2003

Q4
2004

Q4
2005

Q4
2006

Q4
2007

Q4
2008

Q4
2009

Q4
2010

Q4
2011

Q4
2012

Q4
2013

Q4
2014

Q4
2015

Loan demand responsiveness to
current interest rate level

Other banks

Source: ECB. 
Notes: See the notes to Chart 54. Margins are defined as the spread of bank lending 
rates over a relevant market reference rate. They are an unweighted average of margins 
on average loans and margins on riskier loans. 

Source: ECB. 
Notes: Based on unweighted individual data. Interest rate sensitivity is proxied by net 
percentages of banks indicating the relevance of the “general level of interest rates” for 
an increase in loan demand. Banks are grouped into those for which this factor is 
relevant and other reporting banks. Loan demand related to durable consumer goods is 
a selected factor contributing to changes in demand for consumer loans; changes in 
margins refer to consumer loans by the respective banks. 

Looking at the interest rate sensitivity of demand for consumer loans more closely, 
Chart 60 focuses on the differences associated with the importance of interest rates 
for demand using individual BLS replies. To proxy for the interest rate sensitivity of 
demand, replies by banks indicating the “general level of interest rates” as an 
important contributing factor for an increase in demand for consumer loans are again 
contrasted with the remaining replies. The results suggest also for consumer loans 
that a higher interest rate sensitivity of demand corresponds to a higher increase in 
loan demand for financing durable consumer goods and a stronger reduction in 
lending margins for average loans in an environment of low and declining market 
rates.23 By contrast, similar to the case of housing loans (see Chart 53), no notable 
differences can be observed with regard to changes in margins for riskier loans. 

23   These findings also hold when assessing countries more and less exposed to sovereign risks 

separately. 

Occasional Paper Series No 179 / September 2016 

49 

 
                                                                    
 
4 

Ad hoc questions – analysis for the euro 
area 

The standard questions in the BLS questionnaire are complemented with ad hoc 
questions on specific topics of interest. This option has been regularly used since the 
financial crisis to assess the impact of the crisis on bank funding and lending 
conditions and specifically the impact of the ECB’s non-standard monetary policy 
measures. An overview of the ad hoc questions and their development has been 
presented in Section 2 of this Occasional Paper. In the current section, an economic 
assessment of the euro area evidence on the main ad hoc questions is presented 
(see also Section 3.1 for an overview of developments in bank lending conditions in 
the euro area). 

4.1 

Banks’ access to retail and wholesale funding 

Banks’ access to funding deteriorated substantially with the start of the financial 
crisis in the late summer of 2007. In the period from the third quarter of 2007 until the 
third quarter of 2009 (i.e. from the October 2007 BLS until the October 2009 BLS), 
the BLS ad hoc question on banks’ access to wholesale funding asked for the 
degree to which banks’ access to wholesale markets was hampered (see Chart 61). 

Chart 61 
Hampered access of euro area banks to wholesale 
funding 

(percentages of banks reporting hampered market access; net percentages of 
tightening) 

access to money markets
access to debt securities
access to securitisation
credit standards on NFC loans 

100

80

60

40

20

0

-20

Q1
2008

Q2
2008

Q3
2008

Q4
2008

Q1
2009

Q2
2009

Q3
2009

Q4
2009

Q1
2010

Source: ECB. 
Notes: The percentages are defined as the sum of the percentages for “hampered 
considerably” and “hampered somewhat”. The results shown are calculated as a 
percentage of the number of banks which did not reply “not applicable”. 

At the beginning of the financial crisis, in particular 
asset-backed securities (ABS) markets were affected. 
In line with this, a high percentage of euro area banks, 
for which the securitisation business was relevant, 
indicated hindered access to securitisation. At the same 
time, it needs to be kept in mind that securitisation was 
only relevant for around 50% of the euro area BLS 
banks. In addition, banks’ access to money markets 
and debt securities markets became particular 
hampered in the third and fourth quarters of 2008, in 
the context of the collapse of the investment bank 
Lehman Brothers and the related extraordinary 
uncertainty in financial markets. In the course of 2009, 
when the situation in financial markets improved, as 
also indicated by the decrease in the net tightening of 
credit standards, banks indicated a considerably lower 
degree to which their wholesale funding access was 
impeded, with the exception of the securitisation 
market. 

In order to capture also an improvement of banks’ 
access to funding, the ad hoc question was adjusted in 

Occasional Paper Series No 179 / September 2016 

50 

 
the January 2010 BLS round and has asked since then for changes in banks’ access 
to funding as a result of the situation in financial markets. 

With the emergence of the sovereign debt crisis and related to the close link 
between government bonds and bank bonds, euro area banks’ access to wholesale 
funding deteriorated dramatically in the second half of 2011 (see also Section 4.2). 
The deterioration of banks’ access to debt securities issuance is indicated by the 
considerable increase in unsecured bank bond yields (see Chart 62). The ECB 
reacted with its monetary policy to the worsening in financing conditions (see also 
the overview in Section 3.1 as well as Section 4.3). This has substantially improved 
banks’ access to funding and reduced funding costs since the first quarter of 2012. 

Chart 62 
Change in banks’ access to wholesale funding and 
banks’ wholesale funding cost 

Chart 63 
Change in banks’ access to wholesale funding and 
developments in bank liabilities 

(net percentages of banks reporting deteriorated market access; percentages p.a.) 

(net percentages of banks reporting deteriorated market access; annual percentage 
changes) 

access to money markets (lhs) 
access to debt securities (lhs) 
access to securitisation (lhs) 
unsecured bank bond yields (rhs) 
3m Euribor (rhs) 

access to money markets (lhs) 
access to debt securities (lhs) 
access to securitisation (lhs) 
debt securities issued by MFIs (rhs) 
money market fund shares (rhs) 

200

150

100

50

0

-50

-100

6

5

3

2

0

-2

-3

200

150

100

50

0

-50

-100

40

30

20

10

0

-10

-20

Q2
2010

Q4
2010

Q2
2011

Q4
2011

Q2
2012

Q4
2012

Q2
2013

Q4
2013

Q2
2014

Q4
2014

Q2
2015

Q4
2015

Q2
2016

Q2
2010

Q4
2010

Q2
2011

Q4
2011

Q2
2012

Q4
2012

Q2
2013

Q4
2013

Q2
2014

Q4
2014

Q2
2015

Q4
2015

Q2
2016

Sources: ECB, Bloomberg (Merrill Lynch Global Index) and ECB calculations.  
Notes: The net percentages are defined as the difference between the sum of the 
percentages for “deteriorated considerably” and “deteriorated somewhat” and the sum of 
the percentages for “eased somewhat” and “eased considerably”. The results shown are 
calculated as a percentage of the number of banks which did not reply “not applicable”. 
Bank bond yields refer to unsecured investment-grade euro area bank bond yields, 
based on the Merrill Lynch Global Index. 

Source: ECB.  
Notes: The net percentages are defined as the difference between the sum of the 
percentages for “deteriorated considerably” and “deteriorated somewhat” and the sum of 
the percentages for “eased somewhat” and “eased considerably”. The results shown are 
calculated as a percentage of the number of banks which did not reply “not applicable”. 

From a peak in the fourth quarter of 2011, bond yields of euro area banks have 
declined significantly (see Chart 62). Despite banks’ improved access to funding, 
banks’ issuance of bonds remained subdued (see Chart 63). This has been related 
to the provision of Eurosystem liquidity at attractive conditions, being – in particular 
in the vulnerable euro area countries – cheaper than wholesale funding via financial 
markets. 

In addition to banks’ access to wholesale funding, banks’ access to retail funding had 
also deteriorated substantially in the fourth quarter of 2011, owing to the steep fall of 
customer deposits, especially NFC deposits (see Chart 64). This aspect of the ad 
hoc question was introduced in the January 2012 BLS, i.e. reporting on the fourth 
quarter of 2011. The deterioration in banks’ access to retail funding reflected deposit 
withdrawals in some euro area countries related to the sovereign debt crisis. The 

Occasional Paper Series No 179 / September 2016 

51 

 
 
 
 
Chart 64 
Change in banks’ access to retail funding and MFI 
deposits from NFCs and households 

recovery in bank deposits since 2012 has been 
mirrored by banks’ assessment of a generally improved 
access to retail funding. 

Overall, the ad hoc question on euro area banks’ 
access to retail and wholesale funding complements 
the evidence on developments in bank deposits and 
bank bonds as well as banks’ cost of funding. It is also 
closely related to banks’ assessment of their market 
financing and liquidity position in relation to changes in 
credit standards (see Chapter 3). 

(net percentages of banks reporting deteriorated market access; annual percentage 
changes) 

banks' access to retail funding (lhs) 
NFC deposits with MFIs (rhs) 
household deposits with MFIs (rhs) 

30

20

10

0

-10

-20

9

6

3

0

-3

-6

Q2
2011

Q4
2011

Q2
2012

Q4
2012

Q2
2013

Q4
2013

Q2
2014

Q4
2014

Q2
2015

Q4
2015

Q2
2016

Source: ECB.  
Note: See the notes to Chart 63. 

4.2 

The impact of the sovereign debt tensions on bank 
funding and bank lending conditions 

In order to capture the impact of the sovereign debt tensions on banks’ cost of 
funding and on bank lending conditions, an ad hoc question on this topic was 
introduced in the January 2012 BLS, i.e. providing evidence from the fourth quarter 
of 2011 onwards. 

In the second half of 2011 tensions in euro area sovereign bond markets intensified. 
While such tensions had been confined broadly to Greece, Ireland and Portugal in 
the second half of 2010 and the first half of 2011, they spilled over in particular to 
Italy and Spain in the second half of 2011. Doubts regarding fiscal sustainability and 
uncertainty with respect to the health of bank balance sheets for the respective euro 
area countries contributed to stress in the affected sovereign bond markets and in 
the banking markets, given the close connection between bank balance sheets and 
governments. First, direct exposure to sovereign debt may affect banks’ balance 
sheets, change their riskiness as counterparties and, in turn, affect funding costs and 
funding conditions. Second, higher sovereign debt risk reduces the value of 
sovereign collateral that banks can use to raise Eurosystem funding. Moreover, the 
weaker financial positions of governments have lowered the funding benefits that 
domestic banks derived from implicit or explicit government guarantees. Beyond this, 
other effects may link sovereign market tensions to bank funding conditions, such as 
financial contagion from sovereign to sovereign or from a sovereign to banks. 

Banks’ replies to this question followed closely developments in euro area bank bond 
yields. The initial strong impact of the sovereign debt crisis on bank funding 

Occasional Paper Series No 179 / September 2016 

52 

 
 
 
 
 
 
conditions and banks’ credit standards in the fourth quarter of 2011 subsided 
subsequently following the three-year LTROs and the OMT announcement (see 
Chart 65) and turned into an easing impact in the second half of 2013 (see also 
Section 3.1). 

Chart 65 
Impact of the sovereign debt crisis on banks’ cost of 
funding and bank lending conditions for enterprises 

Chart 66 
The sovereign debt crisis and the deterioration in euro 
area banks’ access to wholesale funding markets 

(net percentages of banks reporting a tightening; percentages p.a.) 

(net percentages of banks) 

impact on banks' funding conditions (lhs)
impact on credit standards on loans to enterprises (lhs)
impact on margins for loans to enterprises (lhs)
unsecured bank bond yields (rhs)

impact of sovereign tensions on banks' funding
money markets
debt securities
securitisation

50

40

30

20

10

0

-10

-20

7.5

6.0

4.5

3.0

1.5

0.0

-1.5

-3.0

40

30

20

10

0

-10

-20

Q4
2011

Q1
2012

Q2
2012

Q3
2012

Q4
2012

Q1
2013

Q2
2013

Q3
2013

Q4
2013

Q1
2014

Q2
2014

Q3
2014

Q4
2011

Q1
2012

Q2
2012

Q3
2012

Q4
2012

Q1
2013

Q2
2013

Q3
2013

Q4
2013

Q1
2014

Q2
2014

Q3
2014

Sources: ECB, Bloomberg (Merrill Lynch Global Index) and ECB calculations. 
Notes: The net percentages are defined as the difference between the sum of the 
percentages for “contributed to a deterioration of funding conditions/tightening of credit 
standards/widening of credit margins considerably” and “somewhat” and the sum of the 
percentages for “contributed to an easing of funding conditions/easing of credit 
standards/narrowing of lending margins somewhat” and “considerably”. 
Bank bond yields refer to unsecured investment-grade euro area bank bond yields, 
based on the Merrill Lynch Global Index. 

Source: ECB.  
Notes: Aggregate net percentages reported for the impact of sovereign tensions on 
banks’ funding. Net percentage changes in access to wholesale funding markets based 
on those banks that indicated a positive or negative impact of sovereign debt tensions 
on their funding and reported as weighted net percentages of individual bank replies to 
the respective items of the ad hoc question on wholesale funding. 

The considerable impact of the sovereign debt crisis on banks’ wholesale funding via 
debt securities is also reflected when combining bank replies on the impact of the 
sovereign debt tensions on their funding with the individual bank replies to the ad 
hoc question on banks’ access to funding (see Chart 66). The banks that indicated 
an impact of the sovereign debt crisis on their funding were also particularly affected 
in their access to debt securities funding in the fourth quarter of 2011, i.e. in the most 
intensive period of the sovereign debt crisis. At the same time, the impact was not 
confined to this market, but spilled over also to banks’ access to money markets and 
to securitisation, owing to concerns of investors about banks’ resilience towards 
adverse developments in euro area sovereign bond markets. 

Occasional Paper Series No 179 / September 2016 

53 

 
 
 
4.3 

Impact of the ECB’s non-standard measures on banks 
and on bank lending conditions 

The announcement of the targeted longer-term refinancing operations (TLTROs) in 
June 2014 and of TLTRO-II in March 2016 24 as well as the announcement of the 
expanded asset purchase programme (APP) in January 2015 implied the need to be 
able to assess the impact of such measures on bank lending conditions (see also 
Section 3.1). Against this background, two sets of BLS ad hoc questions were 
designed, which have proven highly useful as an input to the monetary policy 
assessment of the ECB’s measures. 

With a view to the first series of TLTROs, these consisted firstly of two initial 
operations, which were conducted in September and December 2014. Secondly, 
additional TLTROs were conducted every quarter in 2015 and until June 2016. 
Thereafter, from June 2016 until March 2017, TLTRO-II is being conducted at a 
quarterly frequency. Via TLTRO-II, euro area banks are able to borrow up to a 
certain benchmark of their stock of eligible loans, less any amount still outstanding 
under the previous TLTROs. 25 Overall, the TLTROs aim primarily to enhance the 
functioning of the monetary policy transmission mechanism by supporting the 
liquidity provision to the banks in order to strengthen bank lending to the real 
economy. Against this background, the BLS ad hoc questions on the TLTROs ask 
about banks’ participation, why banks participated and for which purposes they have 
used the liquidity from the TLTROs. Moreover, the ad hoc questions ask about the 
impact on banks’ credit standards and terms and conditions. 

In addition, in order to provide a sufficient monetary stimulus and to address the risks 
of too prolonged a period of low inflation, the ECB introduced the APP. The 
expanded APP comprises the asset-backed securities purchase programme 
(ABSPP), the third covered bond purchase programme (CBPP3), which started in 
the fourth quarter of 2014, as well as the public sector purchase programme (PSPP) 
from March 2015 and the corporate sector purchase programme (CSPP) from June 
2016.26 These additional non-standard measures aim to achieve the price stability 
objective given that the key ECB interest rates were already very low. 

The APP increases banks’ excess reserves when the banks sell their holdings of 
public and private sector bonds and other securities to the ECB. In addition, banks 
may receive additional liquidity from an increase in customer deposits (when their 
customers sell public sector bonds). In order to reduce their excess liquidity, banks 
may decide to grant additional loans. This has been of special relevance given the 

24   See the information on the ECB’s website: 

http://www.ecb.europa.eu/mopo/decisions/html/index.en.html and 
http://www.ecb.europa.eu/mopo/implement/omt/html/index.en.html. 

25   See the ECB press release “ECB announces new series of targeted longer-term refinancing operations 

(TLTRO II)” on 10 March 2016. 

26   The APP ad hoc questions refer to the expanded asset purchase programme as announced by the 

ECB on 22 January 2015. This programme encompasses the purchase programmes for asset-backed 
securities (ABSPP) and covered bonds (CBPP3), as well as secondary market purchases of euro-
denominated bonds issued by euro area central governments, certain agencies established in the euro 
area and European institutions. The latest available data point for the APP ad hoc questions refers to 
the April 2016 BLS, i.e. the CSPP is not yet covered by the questions. 

Occasional Paper Series No 179 / September 2016 

54 

                                                                    
ECB’s negative deposit facility rate since June 2014 (see Section 4.4). Taking these 
issues into account, the BLS ad hoc questions on the APP ask first for the impact of 
the expanded APP on banks’ financial situation. Second, they request banks to 
indicate the use of the additional liquidity from the APP stemming from their sales of 
marketable assets and from an increase in customer deposits. Finally, the impact of 
the APP on bank lending conditions is investigated. 

According to evidence from other statistics, euro area banks have reduced their 
holdings of domestic government bonds since the announcement of additional non-
standard measures in the summer of 2014 and especially following the introduction 
of the PSPP in March 2015 (see Chart 67). In addition, since the announcement of 
additional non-standard measures, bank deposits have increased considerably (see 
Chart 68). In the initial period after the announcement of the expanded APP in 
January 2015, especially deposits from other financial intermediaries (OFIs) 
increased, pointing to public sector bond sales by OFIs. By contrast, in the fourth 
quarter of 2015 and the first half of 2016 in particular deposits from households and 
non-financial corporations increased. These developments have increased banks’ 
liquidity. 

Chart 67 
MFI purchases of euro area government bonds 

Chart 68 
Sectoral contributions to M3 deposit growth 

(12-month flows, not seasonally adjusted) 

(percentage points; annual percentage changes; monthly, seasonally adjusted) 

MFI purchases of government bonds
MFI purchases of domestic government bonds
MFI purchases of non-domestic government bonds

M3 deposits
non-financial corporations
households
general government
insurance corporations and pension funds
OFIs (other non-monetary financial intermediaries)

250

200

150

100

50

0

-50

-100

2013

Source: ECB. 

6

5

4

3

2

1

0

-1

-2

2014

2015

2016

2011

2012

2013

2014

2015

2016

Source: ECB. 

Against this background, the impact of the TLTROs and the expanded APP on 
banks’ financial situation and lending conditions is presented in this section, in 
particular with a view to comparing the impact of the two measures. 

Euro area banks confirm in their replies to both the TLTRO and the expanded APP 
ad hoc questions a positive impact of these measures on their liquidity position (see 
Chart 69 and Chart 70). In particular for the TLTROs, this impact has been 
dominant. In the case of the APP, the positive impact on market financing conditions 
was the dominant effect on banks’ financial situation in the initial period after the 
expanded APP announcement. In particular in the first quarter of 2015, banks’ 

Occasional Paper Series No 179 / September 2016 

55 

 
 
financing via secured and unsecured bank bonds considerably improved in the 
context of the APP (see Chart 71), reflecting the substantial decline in banks’ cost of 
market-based funding. In the second and third quarters of 2015, however, the 
positive effect on banks’ market financing conditions was diminished by the repricing 
taking place in euro area financial markets and remained mainly for covered bonds 
in the first quarter of 2016. At the same time, the positive impact of the expanded 
APP on banks’ liquidity position increased up to the first quarter of 2016, mainly 
owing to an increase in customer deposits. 

Chart 69 
Impact of the expanded APP on banks’ financial 
situation 

Chart 70 
Impact of the TLTROs on banks’ financial situation 

(net percentages of banks reporting an improvement over the past six months) 

(percentages of banks reporting an improvement over the past six months) 

50

40

30

20

10

0

-10

-20

60

50

40

30

20

10

0

Apr-
15

Oct-
15

Apr-
16

Apr-
15

Oct-
15

Apr-
16

Apr-
15

Oct-
15

Apr-
16

Apr-
15

Oct-
15

Apr-
16

Apr-
15

Oct-
15

Apr-
16

Oct-Jan-Jul-Jan-Jul-Oct-Jan-Jul-Jan-Jul-Oct-Jan-Jul-Jan-Jul-Oct-Jan-Jul-Jan-Jul-

14 15 15 16 16 14 15 15 16 16 14 15 15 16 16 14 15 15 16 16

liquidity
position

market
financing

profitability

capital ratio

total assets

liquidity
position

market
financing

profitability

capital ratio

Source: ECB. 
Notes: The APP ad hoc questions are biannual questions from April 2015 onwards. 
Banks can indicate either a positive or a negative impact of the APP on their financial 
situation. 

Source: ECB. 
Notes: The TLTRO ad hoc questions were introduced in the October 2014 BLS and 
have been biannual questions from January 2015 onwards. They assume that there is 
only a positive impact from the TLTROs on banks’ financial situation. 

The impact of the additional non-standard measures on bank profitability has been 
mixed (see Chart 69 and Chart 71). For the TLTROs, banks assessed the impact on 
their profitability more positively than for the APP, related to the attractive TLTRO 
funding conditions and in particular the price attractiveness of TLTRO-II. In the July 
2016 BLS round, more than half of the respondent euro area banks indicated that 
past TLTROs, which included the first TLTRO-II operation, contributed to improving 
their profitability. The positive impact on banks’ profitability became the most 
important TLTRO contribution to banks’ financial situation in the July 2016 BLS 
round, whereas it had been the positive effect on banks’ liquidity position previously. 
By contrast, for the APP, banks reported a broadly neutral impact on their profitability 
up to the fourth quarter of 2015 at the euro area level, but a negative impact on 
profitability in the first quarter of 2016. While capital gains were achieved because of 
the rise in asset prices in particular in the initial period of the expanded APP, banks’ 
net interest margin declined in the environment of a flat yield curve and very low 
interest rates. The latter impact became dominant according to reporting banks in 
the first quarter of 2016, more than offsetting the positive impact stemming from 
capital gains (see Chart 72). At the same time, banks may not have taken into 
account in their replies the broader positive impact from the ECB’s monetary policy 

Occasional Paper Series No 179 / September 2016 

56 

 
 
 
measures that should lead to a lower provisioning cost of banks and larger 
intermediation volumes. 

Chart 71 
Impact of the expanded APP on banks’ liquidity position 
and market financing conditions 

Chart 72 
Impact of the expanded APP on banks’ profitability 

(net percentages of banks reporting an improvement over the past six months) 

(net percentages of banks reporting an improvement over the past six months) 

sales of marketable assets
deposit increase
total

financing via ABS
covered bonds
unsecured bank bonds
equity issued
total

net interest margin
capital gains/losses
capital ratio
total

140

120

100

80

60

40

20

0

140

120

100

80

60

40

20

0

Apr-15

Oct-15

Apr-16

Apr-15

Oct-15

Apr-16

liquidity position

market financing

50

40

30

20

10

0

-10

-20

-30

Apr-15

Oct-15

profitability

Apr-16

Source: ECB. 
Note: The APP ad hoc questions are biannual questions from April 2015 onwards. 

Source: ECB. 
Note: The APP ad hoc questions are biannual questions from April 2015 onwards. 

Euro area banks participating in the BLS indicated that they use the additional 
liquidity from both the TLTROs and the expanded APP primarily for granting loans, in 
particular to enterprises (see Chart 73 and Chart 74). This use of funds is 
particularly dominant for the TLTROs, given that the TLTROs were targeted at 
improving bank lending to the euro area non-financial private sector, excluding loans 
to households for house purchase. 

When comparing banks’ indications on the use of liquidity from the TLTROs and the 
expanded APP with actual loan developments, it can be seen that MFI lending to the 
non-financial private sector has recovered from its trough in February 2014 (see 
Chart 75). Following the announcement of additional non-standard measures in the 
summer of 2014, the recovery of loans, which had already started, strengthened. 
Nonetheless, the annual growth of loans to non-financial corporations remained 
modest until the second quarter of 2016. 

Occasional Paper Series No 179 / September 2016 

57 

 
 
 
Chart 73 
Use of liquidity from the ECB’s TLTROs and the 
expanded APP 

Chart 74 
Use of liquidity from the ECB’s TLTROs and the 
expanded APP for granting loans 

(average percentage of respondents per category; sum of contributed somewhat and 
considerably; over the past six months) 

(percentage of respondents; sum of contributed somewhat and considerably; over the 
past six months) 

refinancing
granting loans

purchasing assets

NFCs
house purchase
consumer credit

70

60

50

40

30

20

10

0

100

80

60

40

20

0

Jul-15 Jan-16 Jul-16 Apr-15 Oct-15 Apr-16 Apr-15 Oct-15 Apr-16

Jul-15 Jan-16 Jul-16 Apr-15 Oct-15 Apr-16 Apr-15 Oct-15 Apr-16

funds obtained from the
TLTROs

increased liquidity from
APP via sales
of marketable assets

increased liquidity from
APP via
increased customers'
deposits

funds obtained from the
TLTROs

increased liquidity from
APP via sales
of marketable assets

increased liquidity from
APP via
increased customers'
deposits

Source: ECB. 
Notes: The TLTRO ad hoc questions are biannual questions from January 2015 
onwards. The APP ad hoc questions are biannual questions from April 2015 onwards. 
For “refinancing”, the unweighted average of substituting for deposit shortfalls, 
substituting for maturing debt, substituting for interbank lending and substituting for 
(other) Eurosystem liquidity operations. For “granting loans”, the unweighted average of 
loans to NFCs, to households for house purchase and consumer credit and other 
lending to households. For “purchasing assets”, the unweighted average of domestic 
sovereign bonds and other financial assets for the TLTROs and the unweighted average 
of euro area marketable assets, excluding sovereign bonds, and non-euro area 
marketable assets for the APP.  

Source: ECB. 
Notes: The TLTRO ad hoc questions are biannual questions from January 2015 
onwards. The APP ad hoc questions are biannual questions from April 2015 onwards. 

Chart 75 
MFI loans to the non-financial private sector and 
announcement of additional non-standard measures 

Chart 76 
Impact of the TLTROs and the expanded APP on bank 
lending conditions 

(annual percentage changes) 

(percentages for TLTROs; net percentages for APP; over the past six months) 

annual growth of NFC loans
annual growth of HH loans
annual growth of loans to NFPS 

NFC
house purchase
consumer credit

4

2

0

-2

TLTROs 

expanded APP 

10

0

-10

-20

-30

-40

-50

-4

2011

2012

2013

2014

2015

2016

Source: ECB.  
Notes: Data are adjusted for sales and securitisation. “TLTROs” and “expanded APP” 
refer to the announcement dates of the respective measures, i.e. June 2014 and 
January 2015 respectively. “NFC” denotes non-financial corporations, “HH” denotes 
households and “NFPS” denotes non-financial private sector. 

Jul-
15

Jan-
16

Jul-
16

Jul-
15

Jan-
16

Jul-
16

Apr-
15

Oct-
15

Apr-
16

Apr-
15

Oct-
15

Apr-
16

TLTRO impact on
credit standards

TLTRO impact on
terms and
conditions

APP impact on
credit standards

APP impact on
terms and
conditions

Source: ECB. 
Notes: See the notes to Chart 69 and Chart 70. A (net) easing impact is displayed with 
a negative sign. 

The use of the additional liquidity for refinancing played a somewhat larger role for 
the TLTROs than for the APP (see Chart 73). This was in particular the case as 
banks replaced the funds obtained through the three-year LTROs in December 2011 

Occasional Paper Series No 179 / September 2016 

58 

 
 
 
 
 
 
 
 
and February 2012 with TLTRO liquidity. In addition, the percentage of banks which 
used the TLTRO funds for refinancing increased in the July 2016 BLS round, as 
banks used the funds obtained through the first TLTRO-II operation to replace funds 
borrowed under the first series of TLTROs. By contrast, the replacement of the funds 
from Eurosystem liquidity operations played a smaller role in the APP. 

Moreover, banks have partly used the liquidity obtained from the TLTROs and the 
APP for purchasing financial assets. This was the case for the APP in particular 
when the liquidity was stemming from the sales of marketable assets. 

Both non-standard measures have a stronger impact on banks’ terms and conditions 
than on banks’ credit standards, i.e. they have a stronger impact on banks’ price and 
non-price conditions when granting a new loan than on banks’ loan approval criteria 
(see Chart 76). This reflects that both the TLTROs and the APP have in particular an 
impact on banks’ liquidity and funding conditions, which allows them to pass through 
eased monetary policy conditions to their customers. In this sense, the TLTROs and 
the APP contribute to enhancing the monetary policy transmission and to repairing 
the bank lending channel. 

Chart 77 
Banks’ liquidity position, competitive pressures and 
lending margins for loans to enterprises by TLTRO 
participation 

Chart 78 
Banks’ liquidity position, competitive pressures and 
lending margins for loans to enterprises by APP-related 
liquidity inflows 

(unweighted net percentages) 

liquidity position 
competition
dummy

Factors contributing to
changes in credit standards

riskier loans
average loans
dummy

Changes in margins

(unweighted net percentages) 

liquidity position 
competition

Factors contributing to
changes in credit standards

riskier loans
average loans
dummy

Changes in margins

10

0

-10

-20

-30

-40

-50

10

0

-10

-20

-30

-40

-50

Q3
2014

Q2
2015

Q1
2016

Q4
2014

Q3
2015

Q2
2016

Q3
2014

Q2
2015

Q1
2016

Q4
2014

Q3
2015

Q2
2016

banks
participating in
TLTRO

other banks

banks
participating in
TLTRO

other banks

10

0

-10

-20

-30

-40

-50

10

0

-10

-20

-30

-40

-50

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2015

Q3
2015

Q4
2015

Q1
2016

Q2
2015

Q3
2015

Q4
2015

Q1
2016

APP-related liquidty
inflows

Other banks

APP-related liquidty
inflows

Other banks

Source: ECB.  
Notes: Based on unweighted individual data. Net percentages for banks indicating their 
participation in at least one of the TLTROs and other reporting banks. Evidence on 
TLTRO participation refers to the results of the September 2015, January 2015, July 
2015, January 2016 and July 2016 BLS. Selected factors contributing to changes in 
credit standards as well as changes in margins refer to loans to enterprises. 

Source: ECB. 
Notes: Based on unweighted individual data. Net percentages for banks indicating APP-
related liquidity inflows in the October 2015 and April 2016 BLS over the past six months 
and for other reporting banks. Selected factors contributing to changes in credit 
standards as well as changes in margins refer to loans to enterprises. 

Cross-checking these results with those for other parts of the BLS questionnaire and 
from a granular perspective, a more nuanced picture can be obtained.27 To this end, 

27   While the TLTRO and APP-related ad hoc questions address changes in access to funding and in loan 
margins exclusively related to the respective measures, the regular questionnaire provides a more 
encompassing summary of all coinciding idiosyncratic and macroeconomic effects not exclusively 
related to the effects of the TLTROs and the APP.  

Occasional Paper Series No 179 / September 2016 

59 

 
                                                                    
 
individual replies to the ad hoc questions on the TLTROs and the APP as well as to 
the standard questions of the BLS are combined. 

Indeed, the fraction of BLS banks reporting an improvement in their liquidity position 
was – at least initially – higher among banks that indicated their participation in at 
least one of the TLTROs (see Chart 77, left-hand side) as well as, albeit to a lesser 
extent, among the banks that reported liquidity inflows related to the APP28 (see 
Chart 78, left-hand side). In parallel, both groups pointed to increased competitive 
pressures more often than their peers in the case of the TLTROs and initially also for 
the APP-related liquidity inflows. 

Likewise, these groups reported more frequently a decline in their margins for 
average loans to enterprises (see Chart 77 and Chart 78, right-hand side). For 
banks participating in the TLTROs this was true particularly during the initial 
quarters, i.e. between the third quarter of 2014 and the first quarter of 2015. 
Similarly, for the initial quarters this also applied to banks reporting liquidity inflows 
related to the expanded APP, i.e. between the second and fourth quarters of 2015. 
The decline in banks’ margins for average loans might partly indicate some 
competitive spillover effects to their peers in the following quarters. By contrast, for 
the decline in margins on riskier loans the development was less clear-cut. 

4.4 

The impact of the ECB’s negative deposit facility rate on 
banks’ net interest income and bank lending 

The ECB cut its deposit facility rate (DFR) into negative territory in June 2014, with 
further reductions in 2015 and 2016. The impact of this measure on customer 
lending and deposit rates is likely to increase the demand for loans and may provide 
an incentive for enterprises and households to invest and for the latter to also 
increase consumption expenditure. In addition, given that banks have to pay a price 
for holding excess liquidity at the central bank, banks may aim to expand their 
lending volume to the private sector to improve their overall net interest income. This 
impact should support the ECB’s monetary policy objective and contribute to a return 
of inflation rates to levels below, but close to, 2% in the medium term. At the same 
time, the negative DFR is likely to have a negative direct impact on banks’ net 
interest income as lending rates decline further, while customer deposit rates may 
decline less or have reached their lower bound. Mainly via the impact on banks’ net 
interest income, the DFR may also have a negative impact on bank profitability in the 
short term. However, the positive contribution of the low level of interest rates to 
economic growth should support bank profitability via higher good-quality loan 
demand and lower non-performing loans in the medium term. 

A BLS ad hoc question on the impact of the DFR was introduced in April 2016 as a 
semi-annual question. It aims at providing qualitative evidence on the DFR impact on 
banks’ net interest income, lending conditions and lending volume. Given that this 

28   APP-related liquidity inflows comprise increases in customer deposits and liquidity resulting from 

banks’ sales of securities. 

Occasional Paper Series No 179 / September 2016 

60 

                                                                    
question has only been included for a limited period, the available evidence on the 
DFR impact is so far limited and caution in the interpretation of results is warranted. 

Chart 79 
Impact of the negative DFR on banks’ net interest 
income and bank lending 

Chart 80 
Impact of the negative DFR: relationship with 
competition, the narrowing of margins and housing loan 
volumes 

(net percentage of respondents; over the past and next six months) 

(unweighted net percentage of respondents; over the past six months) 

April 2016 round
expectations

banking competition
margins on average loans

Banking competition
margins on average loans

25

0

-25

-50

-75

-100

e
m
o
c
n

i

.
t
n

i

t
e
n

’

s
k
n
a
b

s
e
t
a
r

i

g
n
d
n
e

l

i

n
g
r
a
m
n
a
o

l

s
e
t
a
r

i

g
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d
n
e

l

s
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m
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v

l

i

g
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d
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e

l

s
e
g
r
a
h
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e
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a
r

.
t
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i
-
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o
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i

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a
m
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a
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l

s
e
g
r
a
h
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e
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a
r

.
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i
-
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o
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s
e
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u
o
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l

i

g
n
d
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l

s
e
t
a
r

i

g
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d
n
e

l

i

n
g
r
a
m
n
a
o

l

s
e
g
r
a
h
c

e
t
a
r

.
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-
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l

i

g
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e

l

enterprises

households for house
purchase

consumer credit and
other lending

10

0

-10

-20

-30

-40

-50

-60

10

0

-10

-20

-30

-40

-50

-60

Q4
2015

Q1
2016

Q4
2015

Q1
2016

Q4
2015

Q1
2016

Q4
2015

Q1
2016

negative impact
on housing
margins

other banks

positive impact
on housing loan
volumes

other banks

Source: ECB.  
Notes: The net percentages are defined as the difference between the sum of the 
percentages for “increased considerably” and “increased somewhat” and the sum of the 
percentages for “decreased somewhat” and “decreased considerably”. The results 
shown are calculated as a percentage of the number of banks which did not reply “not 
applicable”. The timescale in the legend refers to the respective BLS survey round. 
“Expectations” stands for expectations that banks provided in the April 2016 round. 

Source: ECB. 
Notes: Unweighted net percentages of individual survey replies. Groupings based on the 
impact of the negative DFR according to the April 2016 BLS. The chart on the left 
groups banks into those indicating a negative impact on margins for housing loans and 
other reporting banks. The chart on the right groups banks into those indicating a 
positive impact on housing loan volumes and other reporting banks. “Banking 
competition” refers to the factor contributing to changes (here an easing) in credit 
standards; “margins on average loans” refer to changes for housing loans. 

The overall impact on banks’ net interest income has been negative according to a 
broad majority of participating banks in the first round with the new ad hoc question. 
A net percentage of more than 80% of euro area BLS banks reported a decline in 
their net interest income29 between the fourth quarter of 2015 and the first quarter of 
2016 and expected a further reduction in the second and third quarters of 2016 (see 
Chart 79). As regards the impact on lending conditions, in the April 2016 BLS, banks 
reported in particular a decrease in lending rates and loan margins for loans to both 
enterprises and households. At the same time, a smaller fraction, in net terms, 
indicated rising non-interest rate charges on loans across all categories. These 
effects were broadly foreseen to persist in the following six months. With regard to 
the impact of the negative DFR on loan volumes, while banks in this first round of the 
ad hoc question did not report any notable positive impact on volumes for loans to 
enterprises for the past six months, they did report some increase in net terms for 
loans to households, in particular for housing loans. For the following six months, 
they projected a further extension of their loan volume including also loans to 
enterprises. 

29   The net interest income is defined as the difference between the interest earned and interest paid on 

the outstanding amount of interest-bearing assets and liabilities by the bank. 

Occasional Paper Series No 179 / September 2016 

61 

 
                                                                    
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Taking into account the limited evidence available so far, a first cautious 
interpretation suggests that banks aim to compensate for the decline in their net 
interest income with an increase in loan volumes and to some extent with an 
increase in non-interest charges. 

Evidence from individual BLS bank replies on the impact of the negative DFR on 
lending also suggests that banks indicating a negative impact on their margins for 
housing loans face somewhat higher competitive pressures than their peers not 
stating such an impact (see Chart 80).30 At the same time, banks that stated a 
positive impact on the volume of housing loans reported somewhat higher 
competitive pressures and in particular a stronger easing of margins on average 
housing loans. Overall, this first microdata evidence provides some initial support for 
the notion that banks are trying to improve their net interest income via an increase 
in loan volumes. However, the extension of loan volumes largely hinges on demand 
for loans and, thereby, also on the interest rate elasticity of loan demand and on 
banks’ competitive environment (for survey evidence on this relationship, see also 
Chart 10 and Chart 53). Competitive pressures would induce banks to lower their 
loan margins in particular in the context of a targeted extension of their loan base. 

4.5 

The impact of supervisory and regulatory changes on 
bank funding and bank lending conditions 

Following the announcement of the Basel III rules in December 2010 by the Basel 
Committee on Banking Supervision (BCBS) containing the details of the global 
regulatory standards on bank capital adequacy and liquidity, two semi-annual BLS 
ad hoc questions were introduced to assess the impact of changes in the regulatory 
framework on banks’ balance sheets as well as on credit standards and loan 
margins. The ad hoc questions were introduced in July 2011, with bank replies on 
the first half of 2011. 

The Basel III rules, which were translated by the European Commission into the 
Capital Requirements Regulation/Capital Requirements Directive IV (CRR/CRD 
IV)31, aim at enhancing banks’ resilience towards shocks following the experience 
gained during the financial crisis. In particular, banks have to strengthen and to 
improve the quality of their capital, which in the medium term should have a positive 
impact on banks’ ability to provide credit to the economy. In addition, the gradual 
introduction of the liquidity coverage ratio (LCR) from 1 January 2015 onwards 
strives to ensure that banks have sufficient liquidity in terms of freely transferable 
assets that can be quickly converted into cash in private markets without a significant 
loss in value.32 This increases banks’ ability to withstand short-term unexpected 
liquidity shocks as experienced during the financial crisis when interbank lending 
was seriously hampered. To complement and act as a backstop to banks’ risk-based 

30   A similar relationship is also seen for the negative impact on margins for loans to enterprises. 
31   See the regulatory requirements set out in the CRR/CRD IV. 
32   See the European Commission Delegated Act of 10.10.2014 to supplement Regulation (EU) 575/2013 

with regard to liquidity coverage requirement for Credit Institutions (C(2014) 7232 final). 

Occasional Paper Series No 179 / September 2016 

62 

                                                                    
capital requirements, the CRR/CRD IV also aims to enable the monitoring of the risk 
of excessive bank leverage, which refers to banks’ Tier 1 capital relative to banks’ 
total assets.33 Since January 2015 banks need to disclose their leverage ratio and 
the minimum requirement of 3% is envisaged to become binding in 2018. Against 
this background, banks have frontloaded part of the necessary balance sheet 
adjustment. 

In order to assess the impact of the CRR/CRD IV and other regulatory or supervisory 
action, it is of interest to collect evidence on banks’ balance sheet adjustment with 
respect to their capital, liquidity and leverage. Such balance sheet adjustments may 
have an impact on banks’ lending behaviour and, hence, are of relevance when 
assessing the monetary policy transmission. 

Chart 81 
Euro area banks’ risk perceptions and the impact of 
supervisory or regulatory changes on banks’ assets 

Chart 82 
Banks’ cost of capital contributing to a tightening of 
credit standards for NFCs by reduction of risk-weighted 
assets 

(net percentages of banks reporting an increase; net percentages of factors contributing 
to a tightening of credit standards) 

(unweighted net percentages) 

total risk-weighted assets
risk-weighted average loans
risk-weighted riskier loans
total assets
NFC factors - risk perceptions
HH HP factors - risk perceptions
dummy

banks reducing RWAs
other banks
dummy

30

20

10

0

-10

-20

-30

-40

-50

25

20

15

10

5

0

-5

H1
2011

H2
2011

H1
2012

H2
2012

H1
2013

H2
2013

H1
2014

H2
2014

H1
2015

H2
2015

H1
2016

H1
2011

H2
2011

H1
2012

H2
2012

H1
2013

H2
2013

H1
2014

H2
2014

H1
2015

H2
2015

H1
2016

Source: ECB.   
Notes: “Total assets” are available from H2 2014. “NFC factors” and “HH HP factors” 
refer to factors having an impact on credit standards for loans to enterprises and for 
loans to households for house purchase. For enterprises, “risk perceptions” are an 
unweighted average of “general economic situation and outlook”, “industry or firm-
specific situation and outlook/borrower’s creditworthiness” and “risk on collateral 
demanded”. For households, “risk perceptions” are an unweighted average of “general 
economic situation and outlook”, “housing market prospects” and “borrower’s 
creditworthiness”. 

Source: ECB. 
Notes: Unweighted net percentages based on individual BLS replies for banks’ cost of 
capital contributing to a tightening of credit standards for NFCs. Banks are grouped into 
those indicating a reduction of their risk-weighted assets (RWAs) in response to 
regulatory and supervisory action and other reporting banks. Quarterly net percentages 
averaged by half-year.  

Banks have indicated that they reduced substantially their risk-weighted assets in the 
period from 2011 to 2013 in connection with these regulatory or supervisory actions 
(see Chart 81). When reducing their risk-weighted assets, banks have generally 
reduced to a larger extent riskier loans, i.e. loans with a higher risk weight, than 
average loans. This is in line with banks’ risk-averse behaviour in their loan approval 
decisions, as reflected in the important contribution of risk perceptions as a factor 

33   See “Basel III leverage ratio framework and disclosure requirements”, BCBS, Bank for International 

Settlements, January 2014. 

Occasional Paper Series No 179 / September 2016 

63 

 
 
 
 
                                                                    
 
 
having a net tightening impact on credit standards for loans to enterprises and loans 
to households for house purchase (see Chapter 3). 

Likewise, evidence from individual BLS bank replies suggests that for banks that 
reduced their risk-weighted assets in response to regulatory and supervisory action, 
the cost of capital weighed more heavily on their loan supply. More specifically, for 
most of the period until the end of 2014, the net percentage of banks whose cost of 
capital contributed to a tightening of their credit standards for loans to NFCs was 
higher for banks that had indicated a reduction of their risk-weighted assets than for 
the other banks (see Chart 82). Only in 2015 did the difference dissipate, as banks’ 
need to reduce their risk-weighted assets became somewhat less relevant. 

Since 2014 banks’ total assets and risk-weighted average loans have broadly 
stabilised, while banks continued to reduce their riskier loans. In line with this 
development, risk perceptions as a factor contributing to tightening credit standards 
became overall more muted. 

Chart 83 
Impact of supervisory or regulatory changes on euro 
area banks’ capital 

Chart 84 
Increase in retained earnings from TLTRO profits by 
general recapitalisation via retained earnings 

(net percentages of banks reporting an increase; net percentages of factors contributing 
to a tightening of credit standards) 

(unweighted net percentages) 

total capital
retained earnings
capital issuance

NFC factors - capital position
NFC factors - liquidity position
dummy

dummy

50

40

30

20

10

0

-10

30

25

20

15

10

5

0

H1
2011

H2
2011

H1
2012

H2
2012

H1
2013

H2
2013

H1
2014

H2
2014

H1
2015

H2
2015

H1
2016

banks that recapitalise via
retained earnings

other banks

Q3
2014

Q4
2014

H1
2015

H2
2015

H1
2016

Q3
2014

Q4
2014

H1
2015

H2
2015

H1
2016

Source: ECB. 
Note: “NFC factors” refer to factors having an impact on credit standards for loans to 
enterprises. 

Source: ECB. 
Notes: Unweighted net percentages based on individual BLS replies. Banks are grouped 
into those indicating recapitalisation via retained earnings in response to regulatory and 
supervisory action and other banks not indicating this type of recapitalisation. 

The broad stabilisation in euro area banks’ assets is also in line with banks’ 
improved capital and liquidity position (see Chart 83), which provides scope for 
banks to increase their loans. Banks have built up their capital since the first half of 
2011, when the ad hoc question was introduced, in response to increased regulatory 
requirements and market participants’ greater attention to the soundness of banks’ 
balance sheets during the financial crisis. Both retained earnings and capital 
issuance played a role in banks’ capital increase. While weak bank profitability 
limited banks’ ability to accumulate retained earnings in particular in 2011 and 2012, 
banks’ retained earnings overall increasingly contributed to their capital increase 
from the second half of 2013 onwards. This reflects a tentative improvement in bank 

Occasional Paper Series No 179 / September 2016 

64 

 
 
 
profitability, while the considerable volume of impaired loans continued to dampen 
bank profits. 

Evidence from individual bank replies suggests in addition that in particular 
profitability gains from the initial TLTROs also contributed to banks’ retained 
earnings. Indeed, banks that indicated an increase in their capital via retained 
earnings reported substantially more often to have bolstered their capital positions 
via retained earnings from profits accrued in the context of the initial TLTROs in 
September and December 2014 (see Chart 84). 

Chart 85 
Impact of supervisory or regulatory changes on credit 
standards and margins of euro area banks 

(net percentages of tightening) 

loans to SMEs
loans to large firms
loans to households for house purchase
consumer credit and other lending to households

40

30

20

10

0

-10

-20

H1
2011

H1
2012

H1
2013

H1
2014

H1
2015

H1
2016

H1
2013

H1
2014

H1
2015

H1
2016

credit standards

credit margins

Source: ECB. 

As concerns the impact on bank lending conditions, the 
regulatory or supervisory action had a net tightening 
impact on banks’ credit standards and credit margins, in 
particular in 2011 and 2012 when banks’ need to adjust 
their balance sheets was high. The net tightening 
affected mainly loans to enterprises, in particular to 
large firms, whereas loans to households were less 
affected (see Chart 85). The short-term impact of the 
CRR/CRD IV and other regulatory or supervisory action 
on euro area bank lending conditions diminished over 
time as banks had built up their capital buffers in 
response to the financial crisis.   

Overall, the ad hoc questions on the impact of the 
CRR/CRD IV and other regulatory or supervisory action 
are an important complementary element in the 
analysis of the need for banks to adjust their balance 
sheets and its impact on bank lending conditions. 

4.6 

Evidence on the level of credit standards 

The analysis of the BLS results focuses on net percentage changes in credit 
standards. This allows a statement on whether credit standards have tightened or 
eased in net terms over the past three months or whether the degree of net 
tightening/net easing has increased or decreased. 

At the same time, information on the level of credit standards is useful to put into 
perspective banks’ replies to the standard questions on the changes in credit 
standards. 

Compared with the option to cumulate changes in credit standards in order to derive 
the current level, it seems preferable to collect direct evidence on the level of credit 

Occasional Paper Series No 179 / September 2016 

65 

 
 
standards from the banks.34 A simple cumulation of net percentages does not seem 
appropriate for a number of reasons. First, the initial level of credit standards when 
the BLS was launched is unknown and any point in time at which credit standards 
may have been at a neutral level is difficult to determine. Defining a starting point for 
a cumulation is therefore subject to uncertainty. Second, the qualitative nature of the 
survey makes it difficult to derive the current level of credit standards as the precise 
amount of tightening or loosening is unknown. Finally, a simple cumulation of 
changes in credit standards to derive their level would be misleading owing to the 
fact that reported changes tend to exhibit a bias towards “tightening”35, implying that 
cumulated changes have an upward trend (see Chart 86).36 

Chart 86 
Changes and cumulated changes in credit standards 
applied to the approval of loans or credit lines to 
enterprises 

Chart 87 
Level of credit standards and reporting bias adjustment 

(net percentages) 

(cumulated net percentages) 

cumulated net percentages
net percentages

cumulated net percentages
small bias
large bias

line
Series6
dummy

700

600

500

400

300

200

100

0

-100

600

400

200

0

-200

Q1
2003

Q1
2004

Q1
2005

Q1
2006

Q1
2007

Q1
2008

Q1
2009

Q1
2010

Q1
2011

Q1
2012

Q1
2013

Q1
2014

Q1
2015

Q1
2016

Q1
2003

Q1
2004

Q1
2005

Q1
2006

Q1
2007

Q1
2008

Q1
2009

Q1
2010

Q1
2011

Q1
2012

Q1
2013

Q1
2014

Q1
2015

Q1
2016

Source: ECB.  

Source: ECB. 
Notes: “Large bias” is the difference between the cumulated credit standards and the 
linear trend since the first quarter of 2003. “Small bias” is the difference between the 
cumulated credit standards and the linear trend (based on the period from the first 
quarter of 2003 until the fourth quarter of 2008). 

Detrending the cumulated net percentages may be one option to take out the 
tightening bias from the series, assuming that the level of banks’ credit standards 

34   A comparable approach has been applied in the US for the Senior Loan Officer Opinion Survey which 
since 2011 likewise includes an annual special question on the level of lending standards relative to a 
longer-run benchmark (see Bassett and Rezende, 2015, for further details). 

35   For the Senior Loan Officer Opinion Survey in the US, Schreft and Owens (1991) first identified such 
bias for the early years of the survey. Bassett and Rezende (2015) report on such negative bias in the 
replies on quarterly changes of lending standards also for very recent periods. 

36   Based on an analysis of individual BLS replies for the Dutch sample matched with respective 

quantitative bank balance sheet data, van der Veer and Hoeberichts (2013) find that changes in both 
credit standards and cumulated changes in credit standards have information content for business 
lending. By contrast, Del Giovane et al. (2011) do not find clear-cut evidence for such information 
content of cumulated changes in credit standards for the individual replies of the Italian BLS sample. 
Likewise, in a more recent paper Nobili and Orame (2015) do not find any explanatory power of the 
cumulated variables when included as additional variables to explain loan growth; this finding holds 
both for Italian BLS banks and Italian non-BLS banks participating in the Italian regional bank lending 
survey (RBLS). For France, Labonne and Lamé (2014) provide some descriptive evidence and 
discussion using French individual BLS replies. 

Occasional Paper Series No 179 / September 2016 

66 

 
 
 
                                                                    
 
would fluctuate around a mean over time and have a tendency to revert to that 
mean. In this sense, a tightening going beyond the trend (i.e. a positive deviation 
from the trend) is counted as a tight level of credit standards. Along the same lines, a 
downside deviation from the trend is counted as a loose level of credit standards. 
Differences in the steepness of the trend would imply a change in what banks 
perceive as a neutral level of credit standards. 

However, the detrending requires making assumptions about the size and nature 
(linear or non-linear) of the bias, which has a strong impact on the information 
content of the absolute level (see circles in Chart 87) and the relative level of credit 
standards (see arrows in Chart 87).37  

For illustrative purposes, two detrended cumulated net percentages of credit 
standards for loans to enterprises, based on a simple linear trend, are presented 
here in order to demonstrate the implications of assuming a larger or smaller bias in 
the banks’ replies. 

The first linear trend assumes a relatively strong bias and is therefore relatively steep 
(see Chart 88). It is based on the longest-available historical period of BLS data, 
from the first quarter of 2003 until the first quarter of 2016, i.e. the last available data 
point. 

Chart 88 
Cumulated net tightening of credit standards on loans 
to euro area enterprises assuming a large bias 

Chart 89 
Cumulated net tightening of credit standards on loans 
to euro area enterprises assuming a moderate bias 

(cumulated net percentages) 

(cumulated net percentages) 

cumulated credit standards, NFC loans
linear trend (since Q1 2003)
detrended credit standards (based on trend since Q1 2003)

cumulated credit standards, NFC loans
linear trend (Q1 2003 - Q4 2008)
detrended credit standards (based on trend Q1 2003 - Q4 2008)

700

600

500

400

300

200

100

0

-100

-200

700

600

500

400

300

200

100

0

-100

-200

Q1
2003

Q1
2004

Q1
2005

Q1
2006

Q1
2007

Q1
2008

Q1
2009

Q1
2010

Q1
2011

Q1
2012

Q1
2013

Q1
2014

Q1
2015

Q1
2016

Q1
2003

Q1
2004

Q1
2005

Q1
2006

Q1
2007

Q1
2008

Q1
2009

Q1
2010

Q1
2011

Q1
2012

Q1
2013

Q1
2014

Q1
2015

Q1
2016

Sources: ECB and ECB calculations. 
Note: Detrended credit standards are defined as the difference between the cumulated 
credit standards and the linear trend since the first quarter of 2003. 

Sources: ECB and ECB calculations. 
Note: Detrended credit standards are defined as the difference between the cumulated 
credit standards and the linear trend (based on the period from the first quarter of 2003 
until the fourth quarter of 2008). 

Detrending the cumulated credit standards with the first trend implies that a 
considerable amount of the sharp tightening in the course of the financial crisis, in 

37   Apart from an aggregate bias in the time series, see also Nobili and Orame (2015) for an analysis of 

the Italian banking sector regarding an upward bias in the BLS regarding credit constraints reflecting a 
potential sample-driven bias. Their analysis suggests a higher sensitivity of lending dynamics to the 
supply conditions for Italian BLS banks than for Italian non-BLS banks participating in the Italian RBLS. 

Occasional Paper Series No 179 / September 2016 

67 

 
                                                                    
 
particular in 2007-08, would be covered by the trend. Consequently, a higher level of 
cumulated credit standards would be perceived as neutral than when assuming a 
lower trend. The second linear trend assumes a more moderate bias and, hence, a 
lower level of credit standards as being neutral. It is based on the shorter period from 
the first quarter of 2003 until the fourth quarter of 2008, i.e. shortly after the collapse 
of Lehman Brothers when credit standards had been tightened severely (see 
Chart 89). 

When comparing both detrended cumulated credit standards for loans to enterprises 
(i.e. assuming a large or a small bias), it can be seen that following tight credit 
standards at the start of the BLS, both estimated detrended credit standards 
declined from mid-2004 and reached a loose level of credit standards before the 
outbreak of the financial crisis, in a more or less pronounced manner. From the third 
quarter of 2007 both detrended credit standards increased and turned into a tight 
level of credit standards, i.e. being above the neutral zero line. However, while the 
detrended credit standards based on the assumption of a steep bias would have 
turned into a loose level of credit standards from the third quarter of 2014, the level 
of credit standards based on the assumption of a moderate bias would still be 
assessed as tight until the first quarter of 2016, although to a diminishing degree. 

The developments in these two detrended credit standards illustrate the difficulty 
when using (detrended) cumulated net percentages of credit standards for an 
assessment of whether the current level of credit standards would need to be 
qualified as rather tight or loose. 

Against this background, since 2014, the April BLS questionnaire has included an 
annual ad hoc question on the current level of credit standards as compared with the 
midpoint of a historical range of levels that have prevailed between the first quarter 
of 2003 and the current quarter, as well as between the second quarter of 2010 (i.e. 
when the sovereign debt crisis started to intensify) and the current quarter. When 
asking banks for the current level of credit standards, it is useful to ask for the level 
relative to a benchmark. This allows a historical comparison even if only a few data 
points are available. 

The following part presents the main results for the ad hoc question, bearing in mind 
that an assessment of the current level, in particular compared with a long-term 
historical range, may be difficult for banks and needs therefore to be treated with 
some caution. 

Reflecting the net easing of credit standards since the second quarter of 2014 for 
loans to enterprises and since one to two quarters earlier for loans to households, 
the percentage of euro area banks assessing the current level of their credit 
standards as tighter compared with the midpoint of the range of credit standards 
since 2003 became overall smaller between the first quarter of 2014 and the first 
quarter of 2016 (see Chart 90). 

Occasional Paper Series No 179 / September 2016 

68 

Chart 90 
Level of credit standards relative to the level of credit 
standards since 2003 

Chart 91 
Level of credit standards relative to the level of credit 
standards since Q2 2010 

(percentages of banks and net percentages) 

(percentages of banks and net percentages) 

looser
basically unchanged

tighter 
net percentage

looser
basically unchanged

tighter 
net percentage

100

90

80

70

60

50

40

30

20

10

0

100

90

80

70

60

50

40

30

20

10

0

Q1
2014

Q1
2015

Q1
2016

Q1
2014

Q1
2015

Q1
2016

Q1
2014

Q1
2015

Q1
2016

Q1
2014

Q1
2015

Q1
2016

Q1
2014

Q1
2015

Q1
2016

Q1
2014

Q1
2015

Q1
2016

all NFCs

-

HP

-

CC

all NFCs

-

HP

-

CC

Source: ECB.  
Notes: “All NFCs” indicates loans to all non-financial corporations, “HP” indicates loans 
to households for house purchase, and “CC” indicates consumer credit and other 
lending to households. “Tighter” is defined in this chart as the sum of the percentages of 
banks reporting “moderately tighter than the midpoint of the range”, “considerably tighter 
than the midpoint of the range” and “at the tightest level during this period”; “broadly 
identical” is defined as the sum of the percentages of banks reporting “basically identical 
to the midpoint of the range” and “levels have remained constant during this period”; 
“looser” is defined in this chart as the sum of the percentages of banks reporting 
“moderately looser than the midpoint of the range”, “considerably looser than the 
midpoint of the range” and “at the loosest level during this period”. 

Source: ECB. 
Note: See the notes to Chart 90. 

At the same time, in net terms around 40% of the participating euro area BLS banks 
continued to assess the level of their credit standards on loans to enterprises in the 
first quarter of 2016 as being tighter compared with the historical range since 2003. 
This implies that banks would need to ease on average further before they would 
reach a level of credit standards that would correspond to the historical range since 
2003. When assuming that a long-term average of credit standards corresponds 
broadly to a neutral level of credit standards, banks would currently still be in a 
period of tight credit standards, despite the considerable net easing of credit 
standards in the recent past. 

For loans to households, banks’ assessment was overall more moderate in the first 
quarter of 2016. In particular for housing loans, the net percentage of euro area 
banks which assessed the level of their credit standards as tighter compared with the 
historical benchmark has fallen considerably since the first quarter of 2014, when 
this ad hoc question was asked for the first time. 

Over a shorter historical range since the second quarter of 2010 (i.e. when the 
sovereign debt crisis started to intensify), an overall smaller percentage of euro area 
banks’ assessed their current level of credit standards as tighter compared with the 
midpoint of the historical range (see Chart 91). In particular, for loans to enterprises, 
euro area banks assessed their level of credit standards in the first quarter of 2016 in 
net terms as broadly similar to the benchmark. While 33% of the euro area BLS 
banks indicated their level of credit standards on loans to enterprises in the first 
quarter of 2015 as tighter compared with the relevant range, 30% of the banks 

Occasional Paper Series No 179 / September 2016 

69 

 
 
 
 
 
 
 
 
 
 
assessed it as looser. Hence, the net tightening of credit standards on loans to 
enterprises between the third quarter of 2010 and the end of 2013, as reported in the 
standard BLS questions (see Section 3) was broadly offset by the net easing since 
2014. 

Given that a considerable tightening of credit standards took place in the first period 
of the financial crisis, the evidence for the period since the second quarter of 2010 
appears broadly consistent with euro area BLS banks’ indications of tighter credit 
standards compared with the historical range since 2003. 

Occasional Paper Series No 179 / September 2016 

70 

5 

The bank lending survey in empirical 
analysis 

The BLS generally serves as a tool for analysing bank lending conditions in the 
context of monetary policy transmission. It provides otherwise unobservable 
qualitative information on loan supply and demand and their driving factors which 
helps to improve the analytical assessment of credit supply and demand conditions 
and their impact on loan growth, including the forecast of loan growth. Especially 
since the financial crisis, the analysis of credit supply constraints has become an 
important element in the analysis and forecasting of loan developments. 

This section provides an overview of models using the euro area BLS in the analysis 
of loan developments. The growing literature using BLS data covers a suite of 
models and analytical frameworks ranging from the assessment of the impact of 
credit supply on loan growth, through the specific impact of the financial and the 
sovereign debt crises on loan supply, to the transmission of the ECB’s non-standard 
monetary policy measures to loan developments across euro area countries. In 
addition, the BLS data are partially employed in models assessing the relationship 
between monetary policy, financial stability and macro- or microprudential policies. In 
their application most analyses use aggregate country data, while a smaller fraction 
employs individual bank replies to the BLS in combination with the respective banks’ 
balance sheet data or lending rate data. 

Section 5.1 below addresses the more general distinction between credit supply and 
demand effects. The subsequent sections cover studies using BLS information with 
a focus on identifying the specific impact of the financial and sovereign debt crises 
(Section 5.2), on the transmission of the ECB’s non-standard monetary policy 
measures (Section 5.3) and on the relationship between monetary policy, financial 
stability and macro- or microprudential policies (Section 5.4). 

5.1 

Model-based analysis of loan supply and its impact on 
loan growth in the euro area 

The general key area and starting point of analyses using BLS data is the 
assessment of loan supply conditions or credit constraints, and their impact on loan 
developments and ultimately on real economic activity in the euro area. These 
assessments take advantage of the additional qualitative information the BLS 
provides on banks’ lending behaviour, which is unobservable from other quantitative 
data such as bank balance sheet data, loan volumes, bank lending rates or financial 
market data. These types of studies mostly take the form of cross-country panel 
analyses using aggregate BLS data in combination with country-specific macro and 
financial variables. An early example is De Bondt et al. (2010), who provide evidence 

Occasional Paper Series No 179 / September 2016 

71 

in particular for the leading indicator properties of credit standards in explaining loan 
growth and real GDP growth. 38 They show that the BLS has predictive power for 
euro area real GDP growth one year ahead. In addition, changes in credit standards 
contribute significantly to explaining bank loan growth three to four quarters ahead 
(see also the evidence provided in Section 3.1). Moreover, Hempell and Kok 
Sørensen (2010) rely on the BLS for disentangling loan supply and demand effects 
in static and dynamic cross-country panel models. Cappiello et al. (2010) use 
instrumental variable panel regressions to explain GDP growth with loan growth and 
changes in credit standards. The latter studies provide empirical evidence on the 
existence of loan supply effects and, more specifically, on the bank lending channel 
of monetary policy transmission in the euro area. 

Chart 92 
Actual and adjusted credit standards for loans to 
enterprises 

(net percentages) 

BLS change credit standards
loan supply indicator
Series1

Lehman

Sov.debt  VLTROs OMT FG

CE APP

100

75

50

25

0

-25

2005

2007

2009

2011

2013

2015

Sources: ECB and Altavilla et al. (2015). 
Notes: The lending supply indicator is based on individual BLS responses and adjusts 
the change in credit standards (net tightening (+) / net easing (-)) by taking into account 
bank-specific loan demand (BLS), macroeconomic conditions (actual and expected) at 
country level, the riskiness conditions of NFCs in the euro area and monetary policy 
conditions (Eonia and forward rates). Correction is obtained using an Inverse Propensity 
Score Method; probit model estimated on pooled BLS data. - "FG" and "CE" indicate 
"forward guidance" and "credit easing", respectively. Latest observation: July 2016 BLS. 

More recent studies using aggregate country BLS data 
typically apply different versions of a Bayesian panel 
vector autoregressive (panel BVAR) framework to 
capture endogeneities and interlinkages between the 
different macroeconomic variables. In a parallel 
analysis of the euro area and the US, Ciccarelli et al. 
(2015)39 test the credit channel of monetary policy 
transmission in a panel BVAR framework, using data on 
credit standards from the BLS and the Senior Loan 
Officer Opinion Survey (SLOOS)40 for the euro area 
and the US, respectively, for the identification of the 
credit channel. Their findings suggest that in the euro 
area all sub-channels of the credit channel are at work 
and amplify a monetary policy shock on GDP and 
inflation, while in the US the bank lending channel was 
insignificant and monetary shocks were mainly 
transmitted via the firm balance sheet channel. 

Inspired by Bassett et al. (2014) for the US,41 Altavilla et 
al. (2015) apply an alternative approach to using survey 
information in a panel BVAR. They construct an 
indicator for the tightening of loan supply based on 
individual BLS replies (see Chart 92) by adjusting 

individual banks’ answers on the net tightening of credit standards on loans to euro 

38   See also Lacroix and Montornès (2010) for an analysis of the leading indicator properties of the French 
BLS results. In addition, Guichard et al. (2009) provide evidence on the leading indicator properties of 
aggregate euro area credit standards for changes in business investment. Their aggregate time series 
was, however, back-cast to Q4 1999 drawing on US credit standards, the slope of the yield curve and 
responses to a French business survey. 

In an earlier version of this paper, they were the first to apply such a framework to aggregate BLS data. 

39  
40   For earlier VAR analysis using the SLOOS, see Lown and Morgan (2006). 
41   Bassett et al. (2014) used individual survey information from the SLOOS matched with further bank-
specific information to develop their indicator, which renders a loan supply variable “purged” of 
demand-related components as reflected in replies to questions on loan demand in the SLOOS as well 
as other bank-specific and macroeconomic information. Owing to the anonymity of the individual BLS 
replies, Altavilla et al. (2015) were restrained to using within-survey information at the bank level 
complemented with aggregate information at the country level to purge demand-related effects from 
their indicator. 

Occasional Paper Series No 179 / September 2016 

72 

                                                                    
 
area enterprises resulting from factors which are not directly related to loan supply, 
like macroeconomic, firm-specific and monetary conditions. The adjusted loan supply 
indicator provides in part somewhat different signals regarding the gravity of the 
tightening as compared with aggregate BLS results on the net tightening of credit 
standards. This relates to the fact that factors not directly related to “pure” supply-
side determinants of changes in credit standards are largely filtered out. The authors 
embed this indicator as an external instrument into their panel BVAR to identify loan 
supply shocks. Their results indicate that loan supply shocks resulted in higher 
lending rates, a protracted contraction of loan volumes and GDP growth as well as 
incentives for firms to tap debt securities markets for their funding. 

Studies focusing on individual euro area countries only to a limited extent use 
aggregate national BLS data for disentangling loan demand and loan supply to 
explain aggregate credit growth. In this context, Lacroix and Montornès (2010) 
identify leading indicator properties of aggregate French BLS results. Burdeau 
(2015) assesses in the framework of a dynamic disequilibrium model the credit 
supply and demand dynamics for loans to French SMEs. For Italy, Panetta and 
Signoretti (2010) show the high correlation between residuals of estimated credit 
demand equations and changes in Italian credit standards reported by banks in the 
Italian BLS sample, indicating the relevant role of credit supply factors for loan 
growth. In general, these studies face the problem of a rather limited number of 
observations from the respective national time series on changes in credit standards 
which renders econometric inference a challenging endeavour. 

However, an increasing number of studies for individual countries take advantage of 
the heterogeneity and the larger number of observations at the granular level by 
combining individual BLS replies with quantitative data at the individual bank level, 
such as bank balance sheet data, bank lending rates and financial market data. 
Such granular data allow for a deeper identification of structural relationships, 
making it possible to trace the different channels of monetary policy transmission 
and particularly the credit channel. Such studies have been conducted on the Italian, 
German, French and Dutch BLS banks. Overall, they confirm the findings at the euro 
area level regarding the explanatory power of loan supply effects and the existence 
of a bank lending channel of monetary policy transmission in the respective 
countries. 

The first seminal work in this context was provided by Del Giovane et al. (2011) for 
Italy.42 For the banks in the Italian BLS sample, they combine individual BLS bank 
replies and bank balance sheet data to disentangle demand and supply effects in 
Italian loan developments, estimating a reduced-form lending equation for Italian 
BLS banks. Del Giovane et al. (2013) build upon the latter work and assess the loan 
dynamics of individual Italian BLS banks within a structural econometric model to 
identify the impact of loan supply and demand factors on developments in lending 
spreads and loan growth. For Germany, Blaes (2011) broadly follows the initial 

42   The first empirical analyses combining individual BLS data with quantitative bank-level data were 

conducted in Hempell (2005), but were limited by a rather short sample period of eight quarters at the 
time of the study. 

Occasional Paper Series No 179 / September 2016 

73 

                                                                    
reduced-form approach applied by Del Giovane et al. (2011). In an extension, the 
reduced-form equation is augmented by latent determining factors of changes in 
credit standards derived via dynamic factor analysis. These latent factors summarise 
the effects of bank-related and risk-related effects covered by the broader set of 
determining factors included in the survey. 43 Also, Labonne and Lamé (2014) apply a 
reduced-form approach using French individual BLS bank replies; their analysis 
focuses on the impact of regulatory capital requirements on bank lending (see also 
Section 5.4). Finally, van der Veer and Hoeberichts (2013) likewise apply a similar 
reduced-form approach when analysing Dutch individual BLS replies and relevant 
quantitative microdata on lending volumes and rates. The focus in their assessment 
is the additional inclusion of cumulated values both for credit standards and loan 
demand as additional explanatory variables to cover the actual degree of tightness in 
credit supply or the level of loan demand. In contrast to their results, Del Giovane et 
al. (2011) and Nobili and Orame (2015) do not find evidence supporting the view that 
these constructed level variables have additional explanatory power for loan 
dynamics, on top of the changes in credit standards (a more detailed discussion on 
the level of credit standards is provided in Section 4.6).44 

5.2 

Analysis of the specific impact of the financial and the 
sovereign debt crises on euro area loan supply 

An increasing range of studies have taken advantage of the qualitative information 
contained in the BLS to identify loan supply effects and the changes in the monetary 
transmission channels during the recent financial and sovereign debt crises. Overall, 
they find more pronounced credit constraints during the crises, coupled with stronger 
effects of the bank lending channel in the transmission of monetary policy. The 
empirical approaches range from (dynamic) cross-country panel models, through 
Bayesian cross-country panel VARs, to dynamic panel models at the individual bank 
level for individual countries. 

Turning first to early work using cross-country panel models, Hempell and Kok 
Sørensen (2010) provide evidence that the impact of supply-side constraints related 
to banks’ access to wholesale funding and their liquidity position was reinforced 
during the early financial crisis. According to their results, corresponding adjustments 
in banks’ loan portfolios occurred primarily via prices rather than outright quantity 
restrictions during this period.45 

43   A first assessment on the latent driving factors of credit standards and credit demand based on 

individual BLS replies for the euro area and for Germany was provided in Hempell (2007) within a static 
principal component model. 

44   For an encompassing discussion in this respect covering the Dutch and Italian cases, see van der Veer 

and Hoeberichts (2013) and Nobili and Orame (2015), respectively. 

45  

In an assessment of banks’ deposit margins applying a cross-country panel estimation approach, 
Hempell and Kok Sørensen (2011) find indications of cross-subsidisations from the higher pricing of 
loans to the higher remuneration of deposits using information on banks’ loan terms and conditions 
extracted from the BLS. At the same time, using country-level information from a BLS ad hoc question 
on banks’ access to wholesale funding markets, their results indicate that the disruptions to market-
based funding observed during the financial and sovereign debt crises had adversely affected euro 
area banks’ deposit margins. 

Occasional Paper Series No 179 / September 2016 

74 

                                                                    
In order to better cover the interlinkages between different macroeconomic 
parameters, more recent studies using aggregate country BLS data typically apply 
panel BVARs. Within such a framework, Ciccarelli et al. (2013) employ cross-country 
aggregate BLS information for the identification of loan supply shocks. In line with 
the above-mentioned paper from Hempell and Kok Sørensen, their results also 
indicate an amplified propagation channel during the financial crisis, particularly for 
countries facing sovereign debt distress. According to their results, this amplification 
operates via the credit channel comprising both the bank lending channel and the 
borrower balance sheet channel. In this context, they highlight the time-varying 
character of the monetary transmission mechanism and the influence of the financial 
fragility of sovereigns, banks, firms and households. In the same vein, Hristov et al. 
(2012), in relation to an earlier version of Ciccarelli et al. (2013), find a significant 
contribution of loan supply shocks to the decline in loan volumes and real GDP 
during the financial crisis. They likewise stress the heterogeneity of these effects 
regarding timing and magnitude across euro area countries. Bijsterbosch and 
Falagiarda (2015) address this observed time-varying character and heterogeneity 
across countries by estimating the panel BVARs as a time-varying parameter VAR 
(TVP-VAR). For robustness, they compare their identification of loan supply shocks 
based on sign restrictions with information from the BLS on changes in credit 
standards. They find a similar evolution of the BLS information and their model-
driven structural credit supply shocks, with a high positive correlation between the 
two measures. In line with the cited previous results, their findings suggest that the 
effects of credit supply shocks on loan growth and GDP growth have increased since 
the start of the financial crisis, displaying a high degree of cross-country 
heterogeneity between countries more affected by the sovereign debt crisis and 
other countries. While according to their results the importance of loan supply as a 
constraining factor for GDP growth declined in most of the countries more affected 
by the sovereign stress, particularly after mid-2012, tight loan supply conditions 
remained a restraining factor for loan growth in most euro area countries until the 
end of their sample period in mid-2013. 

As described in the previous section, Altavilla et al. (2015) use anonymous individual 
BLS bank replies instead of aggregate BLS results to construct an indicator for the 
tightening of loan supply as an external instrument for their panel BVAR to identify 
loan supply shocks. For the recent crises, they show that tightening shocks to the 
supply of loans to enterprises explain a sizeable share of the decline in loan volumes 
and real activity observed following the euro area sovereign debt crisis. In addition, 
in their model tightening shocks explain the widening of credit spreads and the 
substitution between bank loans and bonds issued by firms observed during this 
period. For illustration, Chart 93 includes their results in a summary of two different 
model estimates using BLS information and assessing the different supply factors 
contributing to loan growth during the crises. 

Occasional Paper Series No 179 / September 2016 

75 

Chart 93 
Estimates of the impact of supply shocks to the annual 
growth of loans to enterprises 

(percentage points) 

range of estimated contributions of credit supply factors
range of estimated contributions of credit supply factors
NFC loan growth

3

2

1

0

-1

-2

-3

-4

-5

2011

2012

2013

2014

2015

2016

Source: ECB. 
Notes: Ranges of estimated contributions of loan supply factors (light blue bars) to the 
annual growth rate of loans to enterprises based on two different models using BLS 
information (panel VAR model: Darracq Paríes and de Santis, 2015; Bayesian VAR: 
Altavilla et al. 2015). Latest observation: Q2 2016. 

At the national level, individual BLS bank replies 
matched with additional quantitative bank-specific data 
allow for a closer structural identification of the 
propagation channels. For Germany, Blaes (2011)46 
finds that the relative explanatory power of BLS 
indicators varies substantially over time. While the 
explanatory power remained very limited until mid-
2009, it increased markedly afterwards. According to 
these results, pure bank-side determinants of changes 
in credit standards, i.e. banks’ capital position, access 
to market financing and banks’ liquidity position, 
contributed to more than one-third of the explained 
negative loan development during this period in 
Germany. For Italy, results by Del Giovane et al. 
(2013)47 suggest that loan supply restrictions were 
stronger during the sovereign debt crisis than the global 
financial crisis, mainly related to stronger bank funding 
constraints (see also the evidence provided in Chapter 
3 for Italy and in Chapter 4 for the euro area). 
According to their findings, the tightening during the 
sovereign debt crisis was largely driven by the widening 

of the sovereign spread and less so by idiosyncratic bank funding problems. Via a 
counterfactual exercise they estimate such supply effects to have levelled up interest 
rates by more than 2 percentage points and reduced loan volumes by more than 8% 
in the second quarter of 2012 relative to the scenario of no tightening of credit 
standards in the course of the crisis. 

5.3 

Assessment of the transmission of the ECB’s non-
standard measures to euro area loan developments 

Against the background of the series of non-standard measures applied by the ECB 
in response to the global financial crisis and the sovereign debt crisis, first studies 
also use BLS information to assess the transmission of these measures to loan 
developments and economic activity. These studies include qualitative BLS results in 
their panel BVAR frameworks to take account of otherwise unobservable information 
on the determinants of the bank lending process. The latter is of particular relevance 
in the context of the transmission of the ECB’s non-standard measures as they were 
largely targeted at directly improving banks’ funding and liquidity environment in 
order to address related impairments in the monetary transmission channels. 

In this context, Ciccarelli et al. (2013) provide some preliminary evidence for the euro 
area for their sample period up to the third quarter of 2011. According to their 
assessment, via its liquidity-providing measures, such as the full allotment policy and 

46 See Section 5.1 for some further details on this study. 
47 See Section 5.1 for some further details. 

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76 

                                                                    
 
the LTROs, the Eurosystem deactivated the bank lending channel with regard to 
monetary policy shocks defined as changes in the monetary policy rate. By contrast, 
they find the non-financial borrower channel of monetary policy to be quantitatively 
significant over the whole period 2008-11 for countries particularly exposed to the 
sovereign debt crisis with respective credit frictions persisting. By contrast, Boeckx et 
al. (2014) model in their BVAR a monetary policy shock as an ECB balance sheet 
extension rather than a change in the monetary policy rate. They find that supply 
conditions are significantly loosened after an expansionary shock to the ECB 
balance sheet, while loan demand is not significantly affected. Following their 
interpretation, these results corroborate the view of an operational bank lending 
channel of monetary policy transmission during this sample period.48 

Darracq-Paries and De Santis (2015), in turn, focus their assessment on the specific 
effects of the three-year LTROs introduced by the ECB in December 2011 via credit 
supply channels. They interpret this measure as a credit supply shock and identify 
this shock drawing on BLS information. The size of the shock is computed by using 
BLS replies to the regular April 2012 BLS round as well as to confidential ad hoc 
questions dedicated to this measure in February 2012 (see Section 2.3). Their 
results suggest an expansionary impact of the three-year LTROs over the short to 
medium term, with a more immediate impact on output and only a gradual effect on 
loan dynamics. In addition, they find a limited effect on bank lending spreads as 
compared with loan volumes which they interpret as an indication that the LTROs 
have acted more via quantitative credit easing than a lower cost of financing. 

5.4 

Relationship between monetary policy, financial stability 
and macro- or microprudential policies  

Several studies also use the unique qualitative information contained in the BLS 
results to assess more closely the relationship between monetary policy, financial 
stability and macro- or microprudential policies. Again the approaches vary 
depending on the national or euro area-wide focus of the study and on data 
availability. 

First studies in this regard are Maddaloni and Peydro (2011, 2013) using cross-
country panel regressions to assess the functioning of the risk-taking channel and, in 
this regard, the interaction of monetary and microprudential policies and their 
repercussions on financial stability. Their results suggest that low monetary policy 
rates tended to soften credit standards for household and corporate loans in the pre-
crisis period. This effect is found to be amplified by securitisation activity, by weak 
prudential policy on either bank capital or loan-to-value ratios and by low monetary 
policy rates for an extended period of time.49 In a complementary analysis, Ciccarelli 

48   Evidence from cross-country regressions in Maddaloni and Peydro (2013) likewise suggests that the 
provision of central bank liquidity was conducive to the transmission of lower monetary policy rates in 
the post-2008 period.  

49   Maddaloni and Peydro (2011) find similar evidence for a risk-taking channel also for the US using 

aggregate data from the SLOOS. Paligorova and Santos (2015) broadly confirm these findings in an 
encompassing panel estimation framework based on individual bank replies to the SLOOS. 

Occasional Paper Series No 179 / September 2016 

77 

                                                                    
et al. (2013)50 assess the impact of financial stability on monetary policy 
transmission. Within a panel BVAR framework, they find that monetary policy 
transmission is not only time-varying but also influenced by the financial fragility of 
sovereigns, banks, firms and households acting as amplification mechanisms. 

In direct relation to macroprudential policies, Tressel and Zhang (2016) use cross-
country data from the BLS in cross-country panel regressions to assess the 
effectiveness of these policies with regard to the macroprudential objective of 
containing the growth of housing loans as well as the appreciation of house prices. 
From the impact of the determinants of credit standards and lending conditions, such 
as banks’ capital positions and loan-to-value ratios, on loans and house prices, they 
draw inferences on the potential of these measures to attain such a macroprudential 
objective. They interpret their results as indicating that instruments targeting the cost 
of bank capital are most effective in slowing down credit growth, mainly via an 
increase in lending margins. They infer that limits on loan-to-value ratios are 
particularly effective in an environment of excessively loose monetary policy. 

Regarding the specific impact of banks’ capital ratios and related supervisory 
requirements on bank lending to enterprises, Labonne and Lamé (2014) match 
individual BLS replies of French banks with bank balance sheet data from banks’ 
quarterly reports to the supervisory authority for the period from 2003 to 2011; these 
data include discretionary capital requirements as set by the French supervisory 
authority. Analysing these data within a panel estimation framework, the authors find 
for French BLS banks a positive relationship between banks’ capital position and 
growth of lending to enterprises which, however, declines with the intensity of 
supervisory capital constraints. 

50   See also Sections 5.1-5.3 for some further details on this study. 

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78 

                                                                    
6 

Conclusions 

This paper has presented the development of the euro area BLS since its 
introduction in 2003 and its growing use in particular during the financial crisis. First, 
the BLS standard questions on bank lending conditions have proven to be an 
important tool for analysing bank loan supply and demand and for forecasting bank 
loan growth. Bank lending conditions and their contributing factors, like risk 
perceptions, banks’ cost of funds and balance sheet constraints and competition, as 
well as bank loan demand and its contributing factors, display a close relationship 
with quantitative macroeconomic and financial data and other survey data. The BLS 
thus complements the assessment of euro area economic developments with an 
insight into the specific impact of loan supply and demand on bank loan growth and 
ultimately real economic growth.  

Second, in particular the ad hoc questions on banks’ access to funding and on the 
impact of the ECB’s standard and non-standard measures during the financial crisis 
have served as an important input into the monetary policy assessment. Results for 
these ad hoc questions have provided evidence on the impact of the ECB’s 
measures like the TLTROs and the APP on banks’ financial situation (e.g. on bank 
profitability) and on the purposes for which banks use the additional funds (e.g. for 
granting loans). In addition, BLS bank replies have shown the impact of the ECB’s 
monetary policy measures on bank lending conditions. The literature review confirms 
the use of the BLS as an important tool for assessing the impact of the financial and 
sovereign debt crises on euro area loan supply and for assessing the transmission of 
the ECB’s non-standard measures to euro area loan developments. 

Moreover, the analysis of bank lending conditions across euro area countries 
attracted increasing attention during the financial crisis given the heterogeneity of 
bank funding conditions and differences in the pass-through of the ECB’s key rate 
cuts to bank lending conditions for borrowers. In particular, as presented in this 
paper for the four largest euro area countries, bank lending conditions in the 
vulnerable euro area countries deviated considerably from bank lending conditions in 
the less vulnerable countries during the financial crisis. Specifically, related to the 
housing market boom in some euro area countries ahead of the crisis, banks in 
Spain in particular tightened their credit standards at the beginning of the financial 
crisis considerably more than for instance banks in Germany. In addition, during the 
sovereign debt crisis, the tightening response of banks in the vulnerable countries, 
especially in Italy, was considerably more pronounced than that of banks in the less 
vulnerable countries. Overall, the dispersion of financing conditions increased across 
all euro area countries during the financial crisis. 

Going forward, the BLS – as a regular tool for reporting on bank lending conditions 
and for analysing loan demand and supply – will continue to play an important role in 
the assessment of bank lending conditions in the euro area. Given the importance of 
the monetary policy transmission channel in a bank-dominated financial system such 
as the one in the euro area, it will continue to provide a valuable input to the 

Occasional Paper Series No 179 / September 2016 

79 

Eurosystem’s monetary policy preparation. Specifically, the analysis based on the 
individual BLS bank replies is likely to play an increasing role, as it allows a more 
granular assessment of bank lending conditions and of the impact of the ECB’s 
monetary policy measures. 

Occasional Paper Series No 179 / September 2016 

80 

Annex 
Overview of changes in the bank 
lending survey questionnaire51 

New BLS questionnaire (from Q1 2015) 

Previous BLS questionnaire (until Q4 2014) 

Question  New item or definition 

Question  Previous item or definition 

1  Revised definition of credit standards (see Glossary) 

2  Revised factors affecting credit standards on loans or credit lines to 

enterprises: 

1 

2 

I. Loans or credit lines to enterprises 

* General economic situation and outlook 

* Expectations regarding general economic activity 

* Industry or firm-specific situation and outlook/borrower’s creditworthiness 

* Industry or firm-specific outlook 

* Your bank’s risk tolerance 

3  Revised definition of credit terms and conditions for new loans (see 

Glossary) 

* Overall terms and conditions 

* Your bank’s loan margin (i.e. the spread over a relevant market reference 
rate) 

4  NEW question: Factors affecting banks’ credit terms and conditions for new 

loans or credit lines to enterprises 

5  NEW question: Share of rejected enterprise loan applications 

6  Revised definition of loan demand (see Glossary) 

7  Revised factors affecting the demand for loans or credit lines to 

enterprises: 

* General level of interest rates 

* Debt refinancing/restructuring and renegotiation (when leading to an 
increase or prolongation of the amount borrowed) 

* Issuance/redemption of debt securities 

* Issuance/redemption of equity 

8  Revised definition of credit standards (see Glossary) 

9  Revised definition of loan demand (see Glossary) 

-- 

-- 

* Your bank’s margin on loans 

-- 

* Debt restructuring 

* Issuance of debt securities 

* Issuance of equity 

3 

-- 

-- 

4 

5 

6 

7 

10  Revised definition of credit standards (see Glossary) 

11  Revised factors affecting credit standards on loans to households for 

house purchase: 

8 

9 

II. Loans to households 

* General economic situation and outlook 

* Expectations regarding general economic activity 

* Housing market prospects, including expected house price developments 

* Housing market prospects 

* Borrower’s creditworthiness 

* Your bank’s risk tolerance 

12  Revised definition of credit terms and conditions for new loans (see 

10 

Glossary) 

* Overall terms and conditions 

-- 

-- 

-- 

* Your bank’s loan margin (i.e. the spread over a relevant market reference 
rate) 

* Your bank’s margin on loans 

* Other loan size limits 

-- 

51 See the ECB’s website for the current BLS questionnaire. For previous versions of the questionnaire, see 

the annex of the respective BLS website report. 

Occasional Paper Series No 179 / September 2016 

81 

 
 
 
 
 
 
 
 
 
 
 
 
                                                                    
13  NEW question: Factors affecting banks’ credit terms and conditions for new 

loans to households for house purchase 

14  Revised factors affecting credit standards on consumer credit and other 

lending to households: 

-- 

11 

* General economic situation and outlook 

* Expectations regarding general economic activity 

* Your bank’s risk tolerance 

15  Revised definition of credit terms and conditions for new loans (see 

12 

Glossary) 

* Overall terms and conditions 

-- 

-- 

* Your bank’s loan margin (i.e. the spread over a relevant market reference 
rate) 

* Your bank’s margin on loans 

* Size of the loan 

16  NEW question: Factors affecting banks’ credit terms and conditions for new 

consumer credit and other lending to households 

17  NEW question: Share of rejected applications for loans to households for 
house purchase and consumer credit and other lending to households 

18  Revised definition of loan demand (see Glossary) 

19  Revised factors affecting the demand for loans to households for house 

purchase: 

-- 

-- 

-- 

13 

14 

* Housing market prospects, including expected house price developments 

* Housing market prospects 

-- 

* General level of interest rates 

* Debt refinancing/restructuring and renegotiation (when leading to an 
increase or prolongation of the amount borrowed) 

* Regulatory and fiscal regime of housing markets 

* Internal finance of house purchase out of savings/down payment (i.e. 
share financed via the household’s own funds) 

-- 

* Other sources of external finance 

20  Revised factors affecting the demand for consumer credit and other 

15 

lending to households: 

* General level of interest rates 

* Consumption expenditure financed through real-estate guaranteed loans 
(“mortgage equity withdrawal”) 

-- 

* Internal finance out of savings 

-- 

* Other sources of external finance 

21  Revised definition of credit standards (see Glossary) 

22  Revised definition of loan demand (see Glossary) 

16 

17 

* Non-housing related consumption expenditure 

-- 

-- 

-- 

-- 

* Household savings 

* Other sources of finance 

-- 

-- 

* Securities purchases 

-- 

* Household savings 

* Other sources of finance 

Occasional Paper Series No 179 / September 2016 

82 

 
 
 
 
 
 
 
 
 
 
Glossary 

To assist respondent banks in filling out the questionnaire, this glossary defines the 
most important terminology used in the bank lending survey. This glossary has been 
revised together with the introduction of the enhanced bank lending survey 
questionnaire in April 2015. 

Capital 
Defined in accordance with the regulatory requirements set out in the CRR/CRD IV, 
which transposes the global standards on bank capital (i.e. the Basel III agreement) 
into the EU legal framework and entered into force on 1 January 2014. It includes 
both Tier 1 capital and Tier 2 capital (supplementary capital). 

Collateral 
The security given by a borrower to a lender as a pledge for the repayment of a loan. 
This could include certain financial securities, such as equity or debt securities, real 
estate or compensating balances. A compensating balance is the minimum amount 
of a loan that the borrower is required to keep in an account at the bank. 

Consumer confidence  
Consumers’ assessments of economic and financial trends in a particular country 
and/or in the euro area. They include assessments of the past and current financial 
situation of households and resulting (income) prospects for the future, assessments 
of the past and current general political and economic situation and resulting 
prospects for the future and assessments of the advisability of making residential 
investments (question 19), particularly in terms of affordability, and/or major 
purchases of durable consumer goods (question 20). In this sense, an increase in 
consumer confidence would tend to lead to an increase in the demand for loans. 

Consumer credit and other lending 
Consumer credit is defined as loans granted for mainly personal consumption of 
goods and services. Typical examples of loans in this category are loans granted for 
the financing of motor vehicles, furniture, domestic appliances and other consumer 
durables, holiday travel, etc. Overdrafts and credit card loans also typically belong in 
this category. “Consumer credit and other lending” to households also includes loans 
to sole proprietors and partnerships (see Households). Loans included in this 
category may or may not be collateralised by various forms of security or guarantee. 

Consumption expenditure financed through real estate-guaranteed loans 
“Consumption expenditure financed through real estate-guaranteed loans” should be 
treated as consumer credit, even though such loans are guaranteed by real estate 
assets, as the purpose of these loans is consumption. Consumption expenditure 
financed through real estate-guaranteed loans represents mortgage equity 
withdrawal, leading to higher non-housing-related consumption. 

Cost of funds and balance sheet constraints  
The bank’s capital and the cost related to the bank’s capital position can become a 

Occasional Paper Series No 179 / September 2016 

83 

balance sheet constraint that may inhibit the expansion of its lending. For a given 
level of capital, the bank’s loan supply could be affected by its liquidity position and 
its access to money and debt markets. Similarly, a bank could abstain from granting 
a loan, or be less willing to lend, if it knows that it will not be able to subsequently 
transfer the risk (synthetic securitisation) or the entire asset (true-sale securitisation) 
off its balance sheet. Moreover, risks related to non-performing loans may be 
reflected not only in the bank’s risk perceptions, but also in its cost of funds and 
balance sheet constraints. 

Covenant 
A covenant is an agreement or stipulation expressed in loan contracts, particularly 
contracts with enterprises, by which the borrower pledges to take certain action (an 
affirmative covenant) or refrain from taking certain action (a negative covenant), and 
is consequently part of the terms and conditions of a loan. 

Credit line 
A credit line is a facility with a stated maximum amount which an enterprise is 
entitled to borrow from a bank at any given time. In the survey, a broad definition of 
credit lines should be applied, in which the information on the demand for new credit 
lines, and also on the use of credit lines previously granted, but not yet used, would 
be taken into account in assessing developments in loan demand. 

Credit standards 
Credit standards are the internal guidelines or loan approval criteria of a bank. They 
are established prior to the actual loan negotiation on the terms and conditions and 
the actual loan approval/rejection decision. They define the types of loan a bank 
considers desirable and undesirable, the designated sectoral or geographical 
priorities, the collateral deemed acceptable and unacceptable, etc. Credit standards 
specify the required borrower characteristics (e.g. balance sheet conditions, income 
situation, age, employment status) under which a loan can be obtained. In the 
survey, both changes in written loan policies and their application should be 
considered. Credit standards may change owing to changes in the bank’s cost of 
funds and balance sheet situation, changes in competition, changes in the bank’s 
risk perception, changes in the bank’s risk tolerance or regulatory changes, for 
instance. 

Credit terms and conditions 
Credit terms and conditions refer to the conditions of a loan that a bank is willing to 
grant, i.e. to the terms and conditions of the loan actually approved as laid down in 
the loan contract which was agreed between the bank (the lender) and the borrower. 
They generally consist of the agreed spread over the relevant reference rate, the 
size of the loan, the access conditions and other terms and conditions in the form of 
non-interest rate charges (i.e. fees), collateral or guarantees which the respective 
borrower needs to provide (including compensating balances), loan covenants and 
the agreed loan maturity. Credit terms and conditions are conditional on the 
borrower’s characteristics and may change in parallel with credit standards or 
independently of them. For instance, an increase in the bank’s funding cost or a 
deterioration in the general economic outlook can lead to both a tightening in the 
approval criteria (credit standards) and a tightening of the terms and conditions on 

Occasional Paper Series No 179 / September 2016 

84 

those loans that the bank is willing to approve and its customers are willing to 
accept. Alternatively, the bank may only change its credit terms and conditions (e.g. 
increasing the required spread to compensate for the additional cost/risk) and leave 
credit standards unchanged. 

Debt refinancing/restructuring and renegotiation 
“Debt refinancing/restructuring and renegotiation” as a factor for loan demand refers 
to loan refinancing, loan restructuring and/or loan renegotiations that lead to an 
increase or prolongation of the amount borrowed. This includes the use of debt 
restructuring to avoid defaulting on existing debt (the avoidance of default being 
interpreted as an increase in demand), for instance via extending the maturity of the 
loan to avoid possible payment difficulties at maturity. At the same time, for 
assessing changes in loan demand, it should not include loan refinancing, 
restructuring and/or loan renegotiations which lead only to a change in the terms and 
conditions of the loan other than the loan size or the maturity of the loan. 

Debt restructuring should not be interpreted as the switching between different types 
of debt (such as loans from monetary financial institutions (MFIs) and debt securities; 
this is already captured under the factor “Issuance/redemption of debt securities”), 
capital restructuring (substitution between debt and equity) or share buybacks 
(already captured under the factor “Issuance/redemption of equity”). Meanwhile, debt 
restructuring in the form of inter-company loans is already covered by the factor 
“Loans from non-banks”. 

Demand for loans 
Loan demand refers to gross demand for loans from enterprises or households 
(including loan rollovers), but apart from normal seasonal fluctuations. It refers to the 
bank loan financing need of enterprises and households, independent of whether 
this need will result in a loan or not. Banks should assess the evolution of the bank 
loan financing need of enterprises and households in nominal terms (i.e. 
independent of price-level developments) and with reference to the financing need 
prevailing in the previous quarter (i.e. banks should not assess the evolution of 
financing needs relative to historical averages or other reference values such as 
sales targets). Demand for loans can change owing to either a shift of the demand 
curve (while the price remains constant) or a movement along the demand curve (i.e. 
because of a change in the price). 

Down payment 
The down payment captures the share of internal finance in a household’s real 
estate investment, i.e. the share financed via the household’s own funds, and is thus 
one factor determining the demand for loans to households for house purchase. The 
higher the household’s internal financing out of its wealth, the higher the down 
payment and the smaller the household’s demand for loans for house purchase. 

Diffusion index 
The diffusion index is defined as the difference between the weighted sum of the 
percentages of banks responding “tightened considerably” and “tightened 
somewhat”, and the weighted sum of the percentages of banks responding “eased 
considerably” and “eased somewhat”. Regarding demand for loans, the diffusion 

Occasional Paper Series No 179 / September 2016 

85 

index is defined as the difference between the weighted sum of the percentages of 
banks responding “increased considerably” and “increased somewhat”, and the 
weighted sum of the percentages of banks responding “decreased considerably” and 
“decreased somewhat”. The diffusion index is weighted according to the intensity of 
the response, giving lenders who have answered “considerably” a weight twice as 
high (score of 1) as lenders having answered “somewhat” (score of 0.5). 

Enterprises 
In this context, enterprises are non-financial corporations, i.e. in line with the 
Eurostat definition, institutional units whose distributive and financial transactions are 
distinct from those of their owners and which are market producers, whose principal 
activity is the production of goods and non-financial services. These can be public 
and private corporations, as well as quasi-corporations. Quasi-corporations have no 
independent legal status, but keep a complete set of accounts and have an 
economic and financial behaviour that is different from that of their owners and 
similar to that of corporations. Sole proprietorships and partnerships are included in 
the household sector (see Households). 

Enterprise size 
The distinction between large and small and medium-sized enterprises is based on 
annual net turnover. A firm is considered large if its annual net turnover is more than 
€50 million. 

Households 
In line with the Eurostat definition, households are individuals or groups of individuals 
acting as consumers and possibly also as entrepreneurs producing market goods 
and non-financial and financial services (market producers) provided that, in the 
latter case, the corresponding activities are not those of separate entities treated as 
quasi-corporations (i.e. sole proprietorships and partnerships). Non-profit institutions 
serving households are included in the household sector. 

Housing market prospects, including expected house price developments 
In question 11, “housing market prospects, including expected house price 
developments” refers to the risk related to the collateral demanded. In question 19, it 
refers to expected developments in the housing market, including an increase 
(decrease) in demand for housing loans owing to an expected increase (decrease) in 
the cost of buying a house and/or in the perceived returns from investing in property.  

Loans 
The loans covered by the bank lending survey are those granted to euro area 
residents by domestic branches, including loans or credit lines to enterprises, loans 
to households for house purchase, and consumer credit and other lending to 
households. 

The definition of loans is that given in Regulation (EU) No 1071/2013 of the ECB of 
24 September 2013 concerning the balance sheet of the monetary financial 
institutions sector (recast) (ECB/2013/33). However, interbank loans should be 
excluded. Following this definition, financial (but not operating) leases granted by an 
MFI are to be recorded as loans. For the purposes of the survey, factoring, if 

Occasional Paper Series No 179 / September 2016 

86 

provided by an MFI, should also be treated as a loan. Financial leasing and factoring 
offered by institutions other than MFIs should not be included. 

Loan application 
Ideally, loan applications should cover formal loan applications as well as any 
informal loan requests which have not yet reached the stage of a formal loan 
application. If information on informal loan requests cannot be obtained, the bank’s 
response should at least refer to all formal loan applications. It should be referred to 
the volume of loan applications. Loan applications can be from both new and existing 
bank clients. However, applications from existing clients should be included only if 
the volume of an ongoing loan increases or a new loan is granted.   

Loan rejection 
“Loan rejection” refers to the rejection (as opposed to the approval) of the volume of 
formal loan applications or of loan requests. If information on the latter is unavailable, 
the bank’s response should at least refer to all formal loan applications which have 
been rejected. It should be referred to the volume of loan rejections relative to the 
volume of loan applications/requests. Loan rejections do not include cases in which 
the borrower withdraws a loan application/request because the bank’s conditions are 
considered unfavourable.  

Loan margin/spread over a relevant market reference rate 
The loan margin of a bank should be understood as the spread over a relevant 
market reference rate (e.g. EURIBOR, LIBOR or the interest rate swap of a 
corresponding maturity for fixed rate loans), depending on the characteristics of the 
loan. Such a spread would capture changes in the bank’s lending rates related to 
changes in the bank’s funding cost as well as in borrower risk, i.e. changes in the 
bank’s lending rates which are not related to variations of market rates (like 
EURIBOR or LIBOR). In detail, the spread would capture changes in the bank’s risk 
premium in its own market-based funding cost (e.g. in bank bond yields), changes in 
the bank’s deposit funding cost, changes in the bank’s risk assessment of borrowers, 
as well as changes in any other add-on factor not related to variations of market 
rates. 

Loan-to-value ratio 
The ratio of the amount borrowed to the appraisal or market value of the underlying 
collateral, usually taken into consideration in relation to loans used for real estate 
financing. 

Marketing campaigns 
Marketing campaigns should be interpreted as a factor affecting loan supply only 
when credit standards or credit conditions change. If this is not the case, marketing 
campaigns may be understood as a factor with a possible impact on loan demand. In 
this instance, respondents should indicate the role of marketing campaigns under 
“Other factors” in questions 7, 19 and 20 on the factors affecting loan demand. 

Maturity 
The concept of maturity used in questions 1, 6, 8 and 9 of the bank lending survey is 
original maturity, and only two different types are used, i.e. short-term and long-term. 

Occasional Paper Series No 179 / September 2016 

87 

Short-term loans are loans with an original maturity of one year or less and, 
consequently, long-term loans are loans that have an original maturity of more than 
one year. 

Net percentage (or balance) 
In the context of credit standards, the net percentage is defined as the difference 
between the sum of the percentages of banks responding “tightened considerably” 
and “tightened somewhat”, and the sum of the percentages of banks responding 
“eased considerably” and “eased somewhat”. Regarding demand for loans, the net 
percentage is defined as the difference between the sum of the percentages of 
banks responding “increased considerably” and “increased somewhat”, and the sum 
of the percentages of banks responding “decreased considerably” and “decreased 
somewhat”. 

Non-banks 
In general, these are non-monetary financial corporations. More specifically, they 
include insurance corporations and pension funds, financial auxiliaries and other 
financial intermediaries. 

Non-interest rate charges 
These are various kinds of fees which can be part of the pricing of a loan, such as 
commitment fees on revolving loans, administration fees (e.g. document preparation 
costs) and charges for enquiries, guarantees and credit insurance. 

Perception of risk and risk tolerance 
Perception of risk refers to the bank’s perception of actual risk and its reaction to 
developments related to the general economic situation and outlook, the industry or 
firm-specific situation and outlook, the borrower’s creditworthiness, as well as the 
collateral demanded (demand-side factors). By contrast, risk tolerance refers to the 
risk tolerance of the bank in its lending policy, which may alter owing to changes in 
the bank’s underlying business strategy (supply-side factors). Banks’ perception of 
actual risk and their risk tolerance may either change in line with each other or move 
in different directions. 

Occasional Paper Series No 179 / September 2016 

88 

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Acknowledgements 
We would like to thank Ad van Riet, Joao Sousa and Björn Fischer for their useful comments and suggestions on this paper. The views 
expressed in this paper are those of the authors and do not necessarily reflect those of the European Central Bank. 

Petra Köhler-Ulbrich 
European Central Bank, Frankfurt am Main, Germany; email: petra.koehler-ulbrich@ecb.int 

Hannah S. Hempell 
European Central Bank, Frankfurt am Main, Germany; email: hannah.hempell@ecb.int 

Silvia Scopel 
European Central Bank, Frankfurt am Main, Germany; email: silvia.scopel@ecb.int 

© European Central Bank, 2016 

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ISSN 
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DOI 
EU catalogue No 

1725-6534 (pdf) 
978-92-899-2342-2 (pdf) 
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