Bank Risk-Taking, Securitization, Supervision, and Low Interest Rates: Evidence from Lending Standards potx

Hence, the softening of standards is over and above an improvement of the borrower’s collateral risk/ value and outlook, thus suggesting higher loan risk-taking by banks when short-term

Bank Risk-Taking, Securitization, Supervision, and Low Interest Rates:

Evidence from Lending Standards

Angela Maddaloni and José-Luis Peydró *

July 2009

Abstract

We analyze the root causes of the current crisis (Allen, 2009; Diamond and Rajan, 2009) by studying the determinants of bank lending standards in the Euro Area We use the answers from the confidential Bank Lending Survey where national central banks request banks quarterly information on their lending standards We find robust evidence that low short-term interest rates soften standards for both businesses and households and – by exploiting cross-country variation of Taylor-rule implied rates –

we find that rates too low for too long soften standards even further The softening is

over and above an improvement of the borrower’s collateral risk and outlook, thus suggesting higher loan risk-taking by banks In addition, we find that weaker banking supervision standards and higher securitization activity amplify the softening of lending standards due to low short-term rates, even when we instrument securitization Finally, low short-term rates have a stronger impact than long-term rates on the softening of standards These results help shed light on the origins of the current crisis and have important policy implications

*

The authors are at the European Central Bank, Kaiserstrasse 29, D 60311 Frankfurt am Main, Germany Contact information: angela.maddaloni@ecb.europa.eu, and jose.peydro@gmail.com / jose- luis.peydro-alcalde@ecb.europa.eu We thank Lieven Baert and Francesca Fabbri for excellent research assistance Any views expressed are only those of the authors and should not be attributed to the European Central Bank or the Eurosystem

“One (error) was that monetary policy around the world was too loose too long And that created this just huge boom in asset prices, money chasing risk People trying to get a higher return That was just overwhelmingly powerful We all bear a responsibility for that” … “The supervisory system was just way behind the curve You had huge pockets of risk built up outside the regulatory framework and not enough effort to try to contain that But even in the core of the system, banks got to be too big and overleveraged Now again, here’s an important contrast Banks in the United States, even with investment banks now banks, bank assets are about one times GDP of the United States In many other mature countries - in Europe, for example – they’re a multiple of that So again, around the world, banks got to just be too big, took on too much risk relative to the size of their economies.”

Timothy Geithner, United States Secretary of the Treasury, Charlie Rose’s PBS, May 2009

“I believe the causes cannot be found in any one market, such as the US Nor are they limited to a particular business, such as subprime mortgages These triggered the crisis, but they did not cause it The causes are the same as in any previous financial crisis: excesses and losing the plot in an extraordinarily favourable environment Indeed, some fundamental realities of banking were forgotten: cycles exist; lending cannot grow indefinitely; liquidity is not always abundant and cheap; financial innovation involves risk that cannot be ignored”

Emilio Botín, Chairman of Bank Santander, Financial Times, October 2008

I Introduction

The current financial crisis has had a dramatic impact on the banking sector of most developed countries, it has severely impaired the functioning of interbank markets, and it has triggered an economic crisis in these same countries

What are the root causes of this crisis? Several commentators and academics

have suggested that the global financial crisis was originated by an excessive softening of lending standards Three key elements were mentioned as drivers: too low levels of interest rates, high securitisation activity, and weak bank regulation supervision standards.2 Therefore, the crisis that started in the subprime mortgage market in the US may have been the manifestation of deep rooted problems, which

were not peculiar to one financial instrument and/or country but were present globally, albeit to different degrees (Allen, 2009, and Diamond and Rajan, 2009).3

Moreover, these root causes may have also been interrelated and mutually amplifying

in affecting the risk-taking of financial institutions (Rajan, 2005) In this paper, we empirically test these hypotheses

2

See for example Allen (2009), Brunnemeier (2009), Calomiris (2008), Taylor (2007 and 2008), Engel

(2009), and numerous articles in The Financial Times, The Wall Street Journal, and The Economist

Nominal rates were the lowest in almost four decades and below Taylor rates in many countries while real rates were negative (Taylor, 2008; and Ahrend, Cournède and Price, 2008)

3

Allen (2009), Rajan (2009) and Diamond and Rajan (2009) distinguish between proximate versus root causes of the current crisis

Low interest rates, weaker bank regulation supervision standards and high securitization activity may imply higher loan risk-taking by banks Moral hazard problems are severe in the banking industry due to e.g deposit insurance, potential bail-outs and very high levels of leverage; hence, high levels of liquidity increase incentives for bank risk-taking (Allen and Gale, 2007).4 Without bank agency problems, excess of liquidity would be given back to shareholders or central banks, but – due to bank moral hazard problems – banks may over-lend the extra-liquidity in bad projects Allen (2009) and Allen and Gale (2007 and 2004) connect too high levels of liquidity with too low levels of short-term interest rates.5 In fact, the level of overnight rates is a key driver of liquidity for banks since banks increase their balance sheets (leverage) when financing conditions through short-term debt are more favourable (Shin, 2009; Adrian and Shin, 2009; and Brunnermeier et al., 2009) Therefore, low short-term interest rates increase bank risk-taking through this channel and, hence, stronger banking supervision standards – via reducing bank agency problems – should reduce the higher risk-taking associated to low rates.6 Finally, low levels of both short and long-term rates may induce a search for yield from financial intermediaries due to their moral hazard problems Securitization of loans result in assets yielding attractive returns for investors, but the social cost may be lower screening and monitoring of securitized loans Hence, the impact of low rates on the softening on standards is stronger with higher securitization activity (Rajan, 2005)

6

There are other channels by which low levels of interest rates affect bank (loan) risk-taking First, lower risk-less rates increase the attractiveness of risky assets in a mean-variance portfolio framework Second, in habit formation models agents become more risk-averse during economic slowdowns because their consumption decreases relative to their status-quo (Campbell and Cochrane, 1999), thus a tightening in monetary policy by depressing real activity may increase investors’ risk aversion Third, low rates may decrease banks’ intermediation margins (profits), thus reducing banks’ charter value, increasing in turn incentives for risk-taking (Keeley, 1990) Fourth, there could also be monetary illusion with low levels of short-term rates which would make banks to desire riskier products to increase returns (Shiller, 1997; and Akerlof and Shiller 2009) Fifth, an environment in which central banks focus only on consumer goods price stability may make monetary policy rates too low, fostering

in turn asset price and credit bubbles (Borio 2003; Borio and Lowe, 2002) For Acharya and

Richardson (2009) the fundamental cause of the crisis was the credit boom and the housing bubble

These were largely developed by too low levels of monetary policy rates (Taylor, 2007)

We empirically analyze the following questions: Do low levels of both short and long-term interest rates soften bank lending standards? Are the effects stronger with higher securitization activity or weaker banking supervision standards? And, do results differ across type of loans, i.e across business, house purchase, and households’ consumption loans?

There are four major challenges to identify the previous questions First, monetary policy rates are endogenous to the (local) economic conditions Second, banking supervision standards may be endogenous to monetary policy especially in cases when the central bank is responsible for both Third, securitization activity is endogenous to monetary (bank liquidity) conditions, since these affect the ability of banks to grant loans Fourth, it is very difficult to obtain data on the pool of potential borrowers approaching a bank, to know their quality, and then to know whether, why and how banks change their lending standards to customers

Our identification strategy relies upon the data we use, the Euro Area Bank Lending Survey, which allows us to tackle the four previous identification challenges.7 First, we use data from the Euro Area countries, where monetary policy rates are identical However, there are significant cross-country differences in terms of GDP growth and inflation, implying in turn significant exogenous cross-sectional variation of Taylor-rule implied rates (Taylor, 2008) Second, banking supervision standards in the Euro Area are responsibility of the national supervisory authorities (often national central banks), whereas monetary policy is decided by the Governing Council of the Eurosytem.8 Third, there is significant cross-sectional variation in securitization activity partly stemming from cross-country differences in the regulation of the market for securitization Fourth, we have access to the confidential Bank Lending Survey database of the Eurosystem National central banks request quarterly information on the lending standards they apply to customers and on the loan demand they receive The rich information allows us to analyze whether banks

7 Banks are not only the key financial intermediaries that reduce the information problems which are crucial for the real effects of monetary policy through credit markets (Bernanke and Gertler, 1995), but banks are also the main providers of credit in most economies and, in particular, in the Euro Area (see for example Hartmann, Maddaloni, Manganelli, 2003, and Allen, Chui and Maddaloni, 2004)

8 International guidelines like Basel are also very important for bank regulation, but there is rule for discretion in supervision standards, in particular for banking capital see Laeven and Levine (2009) and Barth, Caprio and Levine (2006)

change their lending standards, to whom (average or riskier borrowers), how (loan spreads, size, collateral, maturity or covenants), and why (due to changes in borrower risk, or in bank balance-sheet strength, or in bank competition)

The evidence we provide suggests that banks take on higher risk when overnight rates are lower This conclusion arises from the combination of the following robust results: First, a softening of lending standards is associated to low overnight rates The association is highest for business loans.9 Second, higher GDP growth also implies a softening of standards, i.e standards are pro-cyclical Our findings are economically relevant: taking into consideration the standard deviation of overnight rates and GDP growth, the impact of a change in the overnight rate doubles a change in GDP growth both for business and households’ consumption loans, but it is similar for loans for house purchase Third, by exploiting cross-country variation of Taylor-rule implied rates, we find – especially for loans for house purchase – that a softening of lending

standards due to short-term rates too low for too long (measured as the number of

periods when short-term rates are lower than Taylor-rule implied rates) Fourth, low overnight rates have a stronger impact than low long-term rates on the softening of standards.10 Fifth, all the lending standards are softened when short-term rates are low, both for average and for riskier borrowers The softening implies lower loan margins, lower collateral requirements, longer loan maturity, less covenants and larger loan size Finally, and more importantly, there is a softening of standards even when changes in standards are not associated to improvements in borrowers’ credit-

9

Jiménez, Ongena, Peydró and Saurina (2009) and Ioannidou, Ongena and Peydró (2009) are the first

to investigate the impact of short-term (monetary policy) rates on loan risk-taking by banks They use comprehensive credit registers for business loans from Spain and Bolivia respectively They find that low levels of overnight rates increase loan risk-taking by banks Our results complement these papers

by analyzing not only business loans but also loans for house purchase and consumption, and also by analyzing all Euro Area countries In addition, we do not have the comprehensive credit register but we have the potential pool of borrowers and we know whether, how and why banks change their lending standards For indirect evidence on short-term rates and risk-taking, see Bernanke and Kuttner (2005), Rigobon and Sack (2004), Manganelli and Wolswijk (2007), Axelson, Jenkinson, Strömberg and Weisbach (2007), Den Haan, Sumner, and Yamashiro (2007), and Calomiris and Pornrojnangkool (2006)

10

Due to the saving glut and the existence of current account “imbalances”, savers were looking for investment opportunities abroad However, they were seeking short-term assets (Gross, 2009) and, in fact, Brender and Pisani (2009) reports that about one third of all foreign exchange reserves are in the form of bank deposits Little is known about the maturity composition of the remainder, most of which

is invested in interest-bearing securities The scarce available data on the composition of USD foreign exchange reserves that can be gleaned from the US Treasury International Capital data suggests that over half of foreign official holdings of US securities had a maturity of less than three years (see Gross, 2009)

worthiness, but due to improvements in bank balance-sheet constraints (higher bank liquidity or capital, or better bank access to market finance) and also due to higher banking competition, especially from non-banks and market finance Hence, the softening of standards is over and above an improvement of the borrower’s collateral risk/ value and outlook, thus suggesting higher loan risk-taking by banks when short-term rates are low.11

Using time-varying measures of banking supervision standards for bank capital,

we find that the impact of low short-term rates on the softening of lending standards over and above improvements in borrower’s credit-worthiness is larger when supervision standards are weaker, both for loans for house purchase and for consumption However, the level effect of supervision standards is not as significant

as the direct effect of rates on lending standards The lack of strong significance of the direct effect of banking supervision on lending standards may be consistent with the

arguments made by Allen (2009) and Rajan (2009) concerning the need for “good”

supervision regulation, which does not necessarily mean more stringent supervision.12Finally, in contrast with short-term rates, we don’t find that the impact of low long-term rates on the softening of standards depends on banking supervision standards Finally, we analyze securitization activity.13 We find that the impact of low short-term rates on the softening of standards for all type of loans is larger when securitization activity is higher However, if we consider the tightening of standards only related to bank balance-sheet’s constraints, securitization activity in conjunction with overnight rates has a significant impact only for loans for house purchase and consumer credit Moreover, we find significant effects for short-term rates but not for long-term rates Finally, instrumenting securitization activity by the regulation of the market for securitization in each country does not significantly modify the results, where the instrument has a t-stat higher than 8 in the first-stage regression and, hence,

11

That is, the effect of low rates on the softening of standards is over and above the firm balance sheet channel of monetary policy (Bernanke and Gertler, 1995) Because of imperfect information, incomplete contracts and imperfect bank competition, expansive monetary policy increases banks’ loan supply (Bernanke, Gertler and Gilchrist, 1996; Bernanke, 2007; Kashyap and Stein, 2000; Diamond and Rajan, 2006; Stiglitz, 2001; and Stiglitz and Greenwald, 2003)

it does not suffer from weak instrument concerns (Staiger and Stock, 1997) In consequence, the previous set of results suggests higher loan risk-taking by banks when securitization activity is high and short-term rates are low

The analysis of conditions and terms of the loans suggest that when short-term

rates are low and securitization activity is high margins on loans to riskier firms are

not affected while margins on riskier households – either for house purchase or for consumption – are softened In addition, collateral requirements, covenants, maturity and loan-to-value ratio restrictions are softened

When analyzing at the factors by which banks change the standards, in a situation with low short-term rates and high securitization activity, the results we find highlight: (i) the importance of the “shadow banking system” in setting of the softening of bank lending standards (both stemming from higher competition from non-banks and from market finance, which both have a different level of regulation and supervision than banks), (ii) the importance of bank balance-sheet liquidity in the softening of standards, and (iii) the risk transfer effects linked to securitization in the sense that the collateral risk and value may matter less for banks when granting loans

if banks can transfer these risks off

All in all we find that low short-term rates soften lending standards The softening is over and above improvements in borrower’s collateral risk/ value and outlook, and all the relevant standards are softened Hence, our results suggest that banks take on higher loan risk when overnight rates are low In addition, the impact of low short-term rates on the softening of standards is stronger when securitization is high or banking supervision standards are weak, thus suggesting that low levels of short-term rates may create excessive bank risk-taking (Allen and Gale, 2007; Rajan, 2005).14 Finally, low short-term rates matter statistically and economically more than

14

From Allen and Gale (2007) for example, low short-term interest rates create high risk-taking by banks because of moral hazard problems in banks Hence, since we find that softer banking supervision standards make stronger the impact of low rates on higher risk-taking, the evidence suggests excessive risk-taking due to low short-term rates

In addition, since – as explained earlier – the higher impact of low rates on the softening of standards due to high securitization, that we find, may also be due to moral hazard problems (Rajan, 2005); our evidence, therefore, suggests excessive risk-taking when short-term rates are low as compared to a situation with low agency problems in the banking sector (i.e., banks grant more loans when short-term

low long-term rates on the softening of standards, both directly and indirectly via softer bank supervision standards and higher securitization levels These results help shed light on the root causes of the current global crisis (Allen, 2009; Rajan, 2009; and Diamond and Rajan, 2009) and have important policy implications for monetary policy, banking regulation and supervision, and for financial stability

The rest of the paper proceeds as follows Section II describes the data, introduces the variables employed in the empirical specifications, and reviews the empirical strategy Section III discusses the results and Section IV concludes

II Data and Empirical Strategy

A The Bank Lending Survey (BLS) dataset

The main dataset used in the paper are the answers from the Euro Area BLS The national central banks of the Eurosystem request information on bank lending standards since 2002 through the Euro Area BLS, a quarterly survey on banks' lending practices based on the answers of a representative sample of banks in each country The questions asked were chosen on the basis of theoretical considerations related to the monetary policy transmission channels and on the experiences of other central banks running similar surveys, in particular in the US and in Japan The main set of questions did not change since the start of the survey in 2002:Q4.15

The survey contains 18 specific questions on past and expected credit market developments Past developments refer to credit conditions over the past three months, while expected developments focus on the next three months There are two main borrower sectors that are the focus of the survey: enterprises and households Loans to households are further disentangled in loans for house purchase and for consumer credit, consistently with the classification of loans in the official statistics for the Euro Area

The backward-looking questions cover the period from the last quarter of 2002 to the first quarter of 2009 In order to use a balanced panel, the analysis is restricted to the 12 countries which comprised the Euro Area in 2002:Q4 Over this period we consistently have data for 12 Euro Area countries (Austria, Belgium, France, Finland, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, and Spain) The sample of banks is representative of the banking sector in each country Therefore it comprises banks of different size, although national guidelines on the formation of the sample expressed a preference to include the largest banks in each country

The questions imply only qualitative answers and no figures are required The survey is carried out by the national central banks of the Euro Area countries Typically the questionnaire is sent to senior loan officers, like for example the chairperson of the bank’s credit committee The response rate has been virtually 100% all the time

The questionnaire covers both supply and demand factors Concerning the supply factors, which are addressed in ten different questions, attention is given to changes in lending standards, to the factors responsible for these changes and to the credit conditions and terms applied to customers

Lending standards are defined as the internal guidelines or criteria that guide a bank's loan policy and are addressed in two questions, each referring to a different borrower (enterprises and households, further disentangled in loans for house purchase and consumer loans).16 The question asked is: “Over the past three months, how have your bank’s lending standards as applied to the approval of loans (to enterprises or to households) changed?” Banks can chose their answers among five

choices, ranging from “eased considerably” to “tightened considerably.” (See Appendix for a detailed description of the questions used in the paper).17

The successive set of questions gives respondents the opportunity to assess how specific factors affected lending standards as applied to the approval of loans to both

enterprises and households In particular whether the changes in standards were due to changes in bank balance-sheet strength (either bank liquidity, capital, or access to market finance), to changes in competitive pressures (either from other banks or from non-banks), to changes in expected general economic conditions or changes in borrower risk (borrower’s collateral risk/ value or borrower’s outlook) We will use this information to assess whether the changes of standards are just due to changes in borrower credit-worthiness to assess bank risk-taking and also to understand the channels by which low rates, high securitization and weak supervision affect loan risk-taking by banks

Finally, we have information on the changes in the terms and conditions of a loan These are the contractual obligations agreed upon by the lender and the borrower, such as the interest rate (both for average and for riskier borrowers), the loan collateral, size, maturity and covenants We use this information to assess whether the different standards are adjusted for the risk taken

Concerning demand factors, which are the topic of seven questions, various factors related to financing needs and the use of alternative finance are mentioned Three questions look at borrowing demand from enterprises and four at demand from households Finally, the survey also allows participating banks to give free-formatted comments in response to an open-ended question.18

The Euro Area results of the survey (which are a weighted average of the results obtained for each Euro Area country) are published every quarter on the website of the ECB In few countries, the answers from the Survey at the national level are published by the respective national central banks However, the overall sample including all the answers at the country and bank level is confidential

For the purpose of this paper we concentrate only on few questions from the BLS that we describe in detail in Appendix I The questions are related either to the previous three months or to the expected change in lending standards for the next three months We find very similar results using either of the two set of questions and

18

For the purpose of this paper we do not use the answers to questions related to the demand; however,

in non-reported regressions we control for demand answers The results are qualitatively similar

opt to report only the results related to actual changes since these ones are based on actual standards applied to and actual loan demand received

B Macroeconomic and financial variables

We use several macroeconomic and financial variables in our analysis We lag by one quarter the macro and financial variables, hence we use information from 2002:Q3 to 2008:Q4.19 All the series have quarterly frequency to be consistent with the answers from the BLS The main proxy for the monetary policy rate is the quarterly average of the EONIA overnight interest rate, as published by the ECB The main macroeconomic controls we use are: the annual real GDP growth rate and the inflation rate.20 The inflation rate is defined as the quarterly average of monthly inflation rate expressed in annual terms

To exploit the cross-sectional differences in the stance of monetary policy at each moment in time and to get exogenous variation of monetary policy, we calculate for each country a Taylor-rule implied rate over the sample period and then use the difference between this rate and the actual EURIBOR 3 months rate as explanatory variable (we follow Taylor, 2008, and Ahrend, Cournède and Price, 2008) These rule-implied rates are calculated following simple country Taylor rules with coefficients 0.5 for inflation and output gap (see Taylor, 1993) Output gap and inflation are country specific, while the natural rate has been set at 2.1 and the inflation target at 1.9.21 We also define the periods of “expansive” monetary policy as the number of consecutive quarters in which the nominal short-term rate, measured by

21

The output gap for each Euro Area country is the average of the output gap estimates from the European Commission, the OECD and the IMF As a robustness check we have also used the Taylor rule specification in Gerdesmeier, Mongelli and Roffia (2007) with interest-rate smoothing In particular, we use the estimated coefficients for the Euro Area and we plug them in a different Taylor- rule equation for each country The results are qualitatively similar to the ones obtained with simple Taylor rules from Taylor (1993 and 2008) and Ahrend, Cournède and Price (2008)

the EURIBOR 3 months, was below the Taylor-rule implied rate starting in 1999:Q1, i.e when the euro was implemented

To assess the impact of long-term rates, we also use 10 year Treasury bond yield different for each country We also control in some robustness regressions for the term spread, which is calculated as the difference between the 10 year rate and the 3-month rate, house prices growth and credit growth (the source is ECB, see Appendix for details)

One of the most notable innovations in financial markets over the last few years has been the use of securitization Thus, we also construct a variable which measures securitization activity This is the ratio between the volume of all the deals involving asset-backed securities and mortgage-backed securities in each quarter, as reported by Dealogic, normalized by the outstanding volume of loans.22 The securitization variable is country-specific since we have information about the nationality of the collateral.23 The volume of loans is available from the official ECB statistics

In addition, since securitization is endogenous to the financial system regulation and to the business cycle, in particular to the level of short-term interest rates, we instrument the level of securitization activity with a time invariant indicator based on the legal environment for securitization in each country We construct this indicator

from country information contained in the report Legal Obstacles to Cross-Border Securitization in the EU, European Financial Markets Lawyers Group, 2007 This

measure assesses the legal environment for securitization The view taken is that a more regulated environment can be conducive to a framework of “legal certainty” which may be attractive for investors The indicator results in ample cross-country variation in the Euro Area.24

22

As a robustness check we use also gross volumes of new loans issued In addition, since it can be presumed that loans are securitized by the banks with a quarter lag after they have been granted, we lag the numerator of the ratio by one quarter In both cases results do not change

23

We are taking into account only deals for which the underlying collateral resides in one of the Euro Area countries Thus, we do not include securitization from Euro Area banks of loans granted outside the Euro Area

24

See Appendix II for details

We also use a capital stringency index which assesses the capital supervision

standards for bank capital (see Laeven and Levine, 2009) Capital stringency is an

index of regulatory oversight of bank capital This index is based on the following questions: Is the minimum capital asset ratio requirement risk weighted in line with the Basel guidelines? Does the minimum ratio vary as a function of market risk? Are market values of loan losses not realized in accounting books deducted from capital? Are unrealized losses in securities portfolios deducted? Are unrealized foreign exchange losses deducted? What fraction of revaluation gains is allowed as part of capital? Are the sources of funds to be used as capital verified by the regulatory or supervisory authorities? Can the initial disbursement or subsequent injections of capital be done with assets other than cash or government securities? Can initial

disbursement of capital be done with borrowed funds? Thus, capital stringency does

not measure statutory capital requirements Instead, it measures the regulatory approach to assessing and verifying the degree of capital at risk in a bank (Laeven and Levine, 2009).25

Table 1 shows the summary statistics of the main variables used, including the correlations across variables and across countries.26 Table 1, Panel A, shows that the average overnight rate (common across countries) was 2.87 with a standard deviation

of 0.81, whereas long-term rates had an average of 4.05 and 0.45 as standard deviation Average GDP growth was 2.44% while its standard deviation was 2.09, ranging from a minimum of -7.39 to a maximum of 8.46 Inflation average was 2.51 with 0.99 as standard deviation Average Taylor rate differences were -1.37, which indicates that on average monetary policy was expansive, with a standard deviation of 2.59, a minimum value of -9.58 and a maximum of 3.47, i.e there is ample variation

of Taylor-rule implied rates over the sample Securitization has an average of 1.76 with a maximum value of 1.62, ranging from 0 to 10.33 Capital index that measures regulation supervision standards for bank capital ranges from 3 to 7 and the securitization instrument based on regulation of the securitization at the country level varies from 1.5 to 14 In Table 1, Panel B, C and D, we can see that there is ample variation of lending standards applied to non-financial firms and to households with

maximum variation for loans for house purchase It is also interesting to note that the average lending standards were positive, which implies tightening

The correlations among the variables are not very strong As we can see in Table

1 there is significant cross-country variation between Taylor-rule implied rates (GDP growth and inflation were high in some countries whereas in others were low) In addition, there is also ample cross-sectional variation of securitization in the Euro Area, and also in banking supervision standards All in all, the dynamics of the lending standards, of the securitization activity, supervision and of the business cycles show significant heterogeneity across Euro Area countries from 2002 to 2009

C Empirical strategy

We want to empirically address the impact on the softening of lending standards

of both short and long-term rates, of securitization and of banking supervision regulation Moreover, we want to analyze whether the softening of standards implies higher loan risk-taking by banks

There are four major challenges to identify the previous questions First, monetary policy rates are endogenous to the (local) economic conditions Second, banking supervision regulation may be endogenous to monetary policy especially in cases when the central bank is responsible for both Third, securitization activity is endogenous to monetary (bank liquidity) conditions, since these affects the ability of banks to grant loans Fourth, it is very difficult to obtain data on the pool of potential borrowers approaching a bank, to know their quality, and then to know whether, how and why banks change their lending standards

Our identification strategy to tackle the four previous identification challenges relies upon the data we use, the Euro Area Bank Lending Survey dataset

First, with regard to the monetary policy measure, there is an identical monetary policy (overnight) rate for all the countries, which show some significant time variation between 2002 and 2009.27 At the same time, in our sample the Euro Area comprises 12 countries with imperfect business cycle synchronization and thus with

27

In Bernanke and Blinder (1992), and in Christiano, Eichenbaum, and Evans (1996), among others, the overnight interest rate is the indicator of the stance of monetary policy The ECB targets the overnight rate as a measure of the stance of its monetary policy

different levels of GDP growth and inflation.28 Therefore, we can exploit exogenous cross-sectional variation of the stance of monetary policy For example, Spain and Ireland have grown at a much higher rate and with a higher inflation rate than Germany and France, the two largest Euro Area countries during the 2002-06 period Hence, the monetary policy rates may have been too low for Ireland and Spain and maybe high for Germany and France (Taylor, 2008)

Second, banking supervision regulation in the Euro Area is decided by the national supervisory authorities and/or national central banks, whereas monetary policy is decided by the European Central Bank and Eurosystem as a whole Therefore, banking supervision and regulation standards are exogenous to monetary policy rates in the Euro Area

Third, there is significant cross-sectional variation in securitization activity partly arising from cross-country differences in the regulation of the market for securitization

Fourth, we have access to the confidential Bank Lending Survey dataset of the Eurosystem As explained earlier, national central banks request from banks quarterly information on the lending standards they apply to customers and on the loan demand they receive The survey started in 2002:Q4 and it collects the answers from a representative sample of around 90 banks This rich information allow us to analyze not only whether banks change the lending standards for the pool of borrowers they receive, but also to whom they change the standards (average or riskier borrowers), why (due to changes in borrower risk, or in bank balance-sheet strength, or in competition) and how (loan spreads, size, collateral, maturity or covenants)

These data overcome some of the problems inherent to data on actual credit granted, which do not allow to infer conditions offered to the pool of potential borrowers, i.e those that were either rejected by the banks or that found the terms of the loans too expensive and decided not to take the loans In addition, the BLS data contain information for all type of loans (loans for business, for house purchase and for consumption) and on all type of standards (loan spreads for average or riskier borrowers, loan size, maturity, covenants, etc) Finally, the survey data also contain information on why banks changed their standards: is it because of an improvement in

28

See for example Camacho, Pérez-Quiros and Saiz (2006)

the borrower credit-worthiness, or because the bank has more liquidity to lend, or because there is higher competition for banks (both stemming from the banking sector

or from the non-banking sector, e.g the shadow banking system)? All this information helps us to disentangle loan demand and supply (i.e the sample selection issue) and to analyze bank loan risk-taking

We run a series of GLS panel regressions where the left-hand side variable is the net percentage of banks that have tightened their lending standards over the previous quarter – i.e., the difference between the percentage of banks in each country reporting an increase in the tightening of standards minus the percentage of banks reporting a softening of lending standards.29 Therefore, a positive figure indicates a net tightening, and a negative figure a net easing of lending standards.30 On the right hand side we have measures of monetary policy rates, long-term rates, securitization activity and banking regulation, all lagged by one quarter The monetary policy is measured either by the quarterly average of overnight rates (EONIA) or by the differences between the rates implied by a Taylor rule and the 3-month Euribor.31 The normal panel we use is (country, quarter) with country fixed-effects that capture time-invariant differences in the banking, economical and legal structure of each country

We also control for GDP growth and inflation and, in some specifications, we control for time (quarter) fixed effects, country risk, credit growth, term spread, house prices and bank size and fixed-effects

III Results

We start analyzing in Table 2 the impact of overnight rates (EONIA) on lending standards for loans to non-financial firms, for house purchase and for consumption

In particular, a weight of 0.5 is given to the percentage of banks answering that they have tightened somewhat and a weight of 1 to the percentage of banks that have tightened considerably We do not report results relative to the use of diffusion indexes, but they do not differ qualitatively from the results obtained with net percentages

31

Taylor-rule implied rates for Euro Area are normally calculated with 3 months rates (See Taylor, 2008; and Ahrend, Cournède and Price, 2008)

(Question 1 and 8 of BLS, see Appendix) The dependent variable “Changes in lending standards” is the net percentage of banks which have reported to have tightened their lending standards for the approval of loans.32 In column 1, we see that the coefficient on overnight rates is equal to 24.889*** Therefore, a higher level of overnight rates implies higher lending standards for non-financial firms, i.e a tightening of lending standards.33 Once we control in column 2 with real GDP growth and inflation rate (i.e the main determinants of overnight rates), results are still highly statistically significant: the coefficient on overnight rates is 22.152*** The coefficient on GDP growth is negative and equal to -3.287*** Higher GDP growth softens lending standards to non-financial firms; hence, lending standards are pro-cyclical On the other hand, the coefficient on inflation is 5.283***, which indicates that a higher inflation rate tightens lending standards to non-financial firms

From column 3 to 6 we report the results of the same regressions for lending standards to households for house purchase and for consumption Results are very similar to column 1 and 2 both for overnight rates, GDP growth and inflation However, the effect of overnight rates on standards is stronger for loans to non-financial corporations than for loans to households (22.152***, 11.544*** and 8.249*** respectively)

Results are also highly economically significant: a one sigma decrease of overnight rates softens standards to enterprises almost three times more than a one sigma increase of real GDP growth (17.89 and 6.87 respectively) In addition, since the standard deviation of lending standards for firms is 33.73, 1 sigma EONIA moves more than half sigma of standards for firms (17.89/33.73) Concerning loans to households, both overnight rates and GDP growth have similar economic significance (9.32 and 9.56 respectively) for loans for house purchase, while for loans for consumption overnight rates have almost double economic importance than GDP growth (6.66 and 3.95 respectively)

*** means significant at 1% level, ** significant at 5%, and * significant at 10% For convenience

we also indicate the significance levels of the coefficients in the text

Banks may soften their lending standards when overnight rates are lower because

of improvements in borrowers’ net worth and quality of collateral as shown by Matsuyama (2007), Bernanke and Gertler (1995), or Bernanke, Gertler, and Gilchrist (1996 and 1999) At first instance we have used GDP growth to control for the improvement of borrowers’ net worth From column 7 to 12 we make a further identification step The left hand side variable is now defined as the change in lending standards due to changes in banks’ balance sheet constraints, i.e changes in standards not associated to borrowers’ quality (it corresponds to Question 2 and 9 of BLS, see Appendix) From column 7 to 12 we see that low overnight rates softens lending standards because of improvements in banks’ balance sheet position In this case lending standards are softened because of “pure” bank-supply factors and thus they reflect an increase in loan risk-taking by banks Results are both statistically and economically highly significant Moreover, now EONIA is economically more important than GDP growth for all type of loans including loans for house purchase

In Table 2 we have used the level of overnight rates as an indicator of monetary policy This measure of monetary policy is time-varying However, to get cross-sectional variation in the monetary policy stance and to assess the level of short term rates against a benchmark, we calculate the difference between the rate implied by a country-specific Taylor-rule and a nominal short-term rate.34 Note also that this measure provides exogenous cross-sectional variation of monetary policy stance (due

to different levels of inflation and/or GDP growth) as the deviation of the stance in a country at a given point in time with respect to the Euro area average is due to common monetary policy rates decided for the whole Euro Area

In Table 3, column 1 to 3, we see that lower values between Taylor-rate differences (i.e more expansive monetary policy or low levels of monetary policy rates) imply a softening of standards for loans to non-financial firms, for house purchase and for consumption Moreover, in column 4, 6 and 8 we see that the softening is over and above an improvement of borrowers’ collateral risk/ value and outlook – i.e., the softening also stems from pure bank-supply factors Next, we introduce an additional variable measuring for how long the stance of monetary policy

34

Another way to do it is through real short-term interest rates In this case, negative rates are low In non-reported regressions, we find virtually the same results if we use real rates

has been expansive in each country by counting the number of consecutive quarters in which nominal short-term rates have been lower than Taylor-rule implied rates As we

can see in column 5, 7 and 9, rates too low for too long imply an even further

softening of standards Results are significant for all type of loans but are stronger for loans for house purchase (-0.336*** for loans for house purchase as compared to -0.174 for business loans)

Short-term rates versus long-term rates

In Table 4 we include long-term rates in the analysis In column 1, 2 and 3, we find that short-term rates continue to be highly significant both economically and statistically as determinants of total lending standards for all type of loans Long-term rates are only significant determinants of lending standards to households for house purchase, which are generally long-term loans However short-term rates have a larger impact than long-term rates in explaining standards, even for loans for house purchase – note that the standard deviation of overnight rates is 0.81 whereas for long-term interest rates is 0.46

In column 4, 5 and 6 we see that low short-term rates are more important than low long-term rates in the softening of standards due to improvements in bank’s balance-sheet conditions (better bank liquidity, capital and access to market finance) and, thus unrelated to improvements in borrower’s risk In addition, in Table 5 Panel

A and B, we can see in detail the impact of both short-term and long-term rates on the specific factors affecting lending standards: better expected economic conditions, better borrower collateral risk/value and outlook, better bank capital or liquidity position or market access to finance and, finally, competitive pressures stemming either from the banking system itself or from non-banks We find that the softening is due to all factors It is interesting to note that for business loans the softening is due more to higher bank competition or to improvements in bank balance-sheets position than to improvements of the borrower’s risk of collateral

In Table 6 (Panel A to C) we look at the impact of low interest rates on credit conditions and terms of loans Low short-term rates soften all type of standards for all type of loans (price and non-price terms) It is interesting to note that the softening of standards to average and riskier borrowers is similar for loans for house purchase,

whereas low short-term rates imply softer standards for average borrowers than for riskier borrowers for business loans and consumer loans Instead, low long-term rates soften more standards for riskier rather than average businesses

All in all, our results suggest that low short-term rates imply higher loan taking by banks Banks soften the standards not only because of borrowers’ better conditions but also because banks’ balance-sheet constraints are relaxed Moreover, banks relax all standards including margins on both average and riskier loans, collateral, covenants, size, and maturity In addition, our results suggest that low short-term rates have a stronger impact on the softening of standards than long-term rates

risk-Banking regulation and supervision standards

Now we analyze whether the impact of low rates on the softening of standards is lower with stronger regulation supervision standards for bank capital In Table 7 we

introduce capital stringency which is an index of regulatory oversight of bank capital

(Laeven and Levine, 2009) This measure has cross-sectional variation and also some time variation (see Appendix and Section II) Hence, we use Taylor-rate differences

as the monetary policy measure to fully exploit the cross-sectional variation of both monetary policy rates and banking regulation supervision standards

We find that the impact of low short-term rates on the softening of lending standards (over and above improvements in borrower’s collateral risk and outlook) is larger with weaker supervision standards, both for loans for house purchase and for consumption (Table 7, Panel B) At the same time, the direct effect of short-term rates

on lending standards is more significant than the level effect of supervision standards Finally, in contrast with short-term rates, the softening impact of low long-term rates

on lending standards does not depend on banking regulation supervision standards The results we find are not very strong though, maybe because there is not enough variation of banking regulation supervision across Euro Area countries or maybe because it is difficult to capture how good regulation or supervision is with measures based on stringency of requirements This is consistent with the arguments

made by Allen (2009) and Rajan (2009) concerning the need for “good” supervision

regulation, which does not necessarily mean more stringent

Securitization

In Table 8 we introduce the securitization activity at the country level First, we note that higher securitization activity tends to softer lending standards, a result similar to the ones obtained by Mian and Sufi (2009) and Keys et al (2008) for the

US mortgage market More importantly, when we add an interaction term of securitization and overnight rates, we find that higher securitization activity amplifies the impact of low short-term rates on the softening of standards The results are similar for all type of loans We do not find, however, similar results when we interact

long-term rates with securitization

In Table 9 we consider changes in lending standards due to bank balance-sheet constraints We find that higher securitization activity makes stronger the impact of low short-term rates on the softening of lending standards both for loans for house purchase and for consumption This implies that there is softening of standards over and above improvements of borrower risk due low short-term rates and high securitization activity, thus suggesting higher loan risk-taking by banks when both

securitization activity is high and short-term rates are low, as suggested by Rajan

(2005)

In Table 10 we analyze the impact of securitization activity on all the factors that affect lending standards In Panel A we see that for loans to non-financial firms, the interaction between overnight rates and securitization activity has a significant coefficient when the softening of lending standards is due to more non-bank or market finance competition and also due to risk of collateral In Panel B we see that for loans

to households for house purchase, higher securitization makes stronger the impact of low short-term rates on the softening of lending standards due to more non-bank competition, better bank balance-sheet constraints, and also from better risk of collateral In Panel C, we find similar results for consumer credit except for change in standards due to competition

In Table 11, we analyze terms and conditions of loans and we find that the softening of higher securitization in conjunction with low short-term rates is for the following standards: (i) for firm loans: margins on average loans, collateral requirements, covenants, and maturity; (ii) house purchase loans: margins on both

average and riskier loans, collateral requirements, and loan-to-value ratio restrictions; and (iii) consumer credit: margins on both average and riskier loans, collateral

requirements, maturity, and non-interest rate changes

In a situation with low short-term rates and high securitization activity, the previous results suggest higher loan risk-taking by banks Moreover, when analyzing

at the factors by which banks change the standards, the previous results highlight: (i) the importance of the “shadow banking system” in setting of the softening of bank lending standards (both stemming from higher competition from non-banks and from market finance, which both have a different level of regulation and supervision than banks), (ii) the importance of bank balance-sheet liquidity in the softening of standards, and (iii) the risk transfer effects linked to securitization in the sense that the collateral risk and value may matter less for banks when granting loans if banks can transfer these risks off

Given that presumably the securitization activity in each country not only depends on the regulation and development of the financial system of that country, but also on short-term rates and the business cycle, securitization activity is endogenous to monetary policy Therefore, we instrument securitization by using an indicator of the regulatory environment for securitization in each country (see Section

2 and the Appendix for the explanation of the instrument) As shown in Table 12 Panel A, we find that the securitization activity is highly correlated with securitization regulation (t-statistic in the first stage regression is 8.10), thus the instrument does not suffer from weak instrument concerns (Staiger and Stock, 1997) Moreover, from the second-stage regression (Panel B), the estimates suggest that the impact of low short-term rates on the softening of standards is larger when the component of actual securitization predicted by the securitization regulation is higher We do not find,

however, similar results when we interact long-term rates with securitization

Our results suggests not only that low levels of short-term rates increase loan risk-taking but they may create excessive risk-taking since we find that the impact of low short-term rates on the softening of standards is stronger when securitization is high or banking supervision standards are weak It suggests excessive risk-taking as compared to a situation with zero or low bank agency problems: From Allen and Gale (2007) for example, low short-term interest rates create high risk-taking by banks

because of moral hazard problems in banks Hence, since we find that softer banking supervision standards make stronger the impact of low rates on higher risk-taking, our evidence suggests excessive risk-taking In addition, since as explained earlier, we find higher impact of low rates on the softening of standards due to high securitization, and there is theory that suggests that this is due to moral hazard problems in banks (Rajan, 2005), our evidence suggests excessive risk-taking when short-term rates are low, as compared to a situation with low agency problems in the banking sector.35

All in all, we find that low short-term interest rates, high securitization, and weaker banking regulation directly and in conjunction soften the lending standards This softening is over and above improvements in the borrowers’ credit-worthiness, thus indicating higher loan risk-taking by banks Moreover, the impact of short-term interest rates on the softening of lending standards is stronger with higher securitization and weaker banking supervision standards, thus suggesting excessive loan risk-taking by banks Finally, low short-term rates are more important than long-term rates for the softening of standards All these results, therefore, have implications for the origins of the current global financial crisis (see Rajan, 2005 and 2009; Allen 2009; Calomiris, 2008; Diamond and Rajan, 2009; Brunnemeier, 2008; Taylor, 2007 and 2008; and others).36

IV Conclusions

We analyze the root – and not the proximate – causes of the current crisis (Allen, 2009; Diamond and Rajan, 2009) by studying the determinants of bank lending standards in the Euro Area, where there are identical monetary policy rates but there is ample cross-sectional variation in GDP growth, inflation, securitization and bank regulation We use the answers from the confidential Bank Lending Survey where

to happen (see Jiménez, Ongena, Peydró and Saurina, 2009b) in turn affecting the real economy (see Ciccarelli, Maddaloni and Peydró, 2009)

national central banks request from banks quarterly information on the lending standards they apply to customers and on the loan demand they observe

We find robust evidence that low short-term interest rates soften standards for loans to both business and households, and the softening is over and above an improvement of the borrower’s collateral risk/ value and outlook, thus suggesting higher loan risk-taking by banks when overnight rates are low Moreover, lending standards are pro-cyclical and – by exploiting cross-country variation of Taylor-rule

implied rates – we find that short-term rates too low for too long soften standards even

further, especially for loans for house purchase

In addition, using a time-varying measure of supervision standards for bank capital, we find that weaker supervision standards increase the impact of low short-term rates on the softening of standards Moreover, we find that higher securitization activity increases the impact of low short-term rates on the softening of standards, even when we instrument securitization by the level of regulation in the market for securitization of each country Moreover, the impact of higher securitization and weaker supervision standards in conjunction with low short-term interest rates softens the lending standards over and above an improvement of the borrower’s collateral risk/ value and outlook, thus suggesting higher (and even excessive) loan risk-taking

by banks In particular, the results suggest that the softening is due to higher competition from non-banks and market finance (the shadow banking system), from credit risk-transfer (collateral risk is less important when the risk can be transferred off easily), and from better bank balance-sheets (more bank liquidity and better bank access to market finance)

Finally, low short-term rates are more important than long-term rates on the softening of standards directly and indirectly via softer bank supervision standards or higher securitization

All in all, the results suggest that all these root causes of the current crisis have a direct effect and also reinforce each other in the softening of lending standards set by banks (see Rajan, 2005 and 2009; Allen 2009; Calomiris, 2008; Diamond and Rajan, 2009; Brunnemeier, 2008; Taylor, 2007 and 2008; and others) These results help shed

light on the origins of the current crisis and have important policy implications for monetary policy, banking regulation and supervision, and for financial stability

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