O C C A S I O N A L PA P E R
Financial Soundness Indicators:Analytical Aspects and Country Practices
V. Sundararajan, Charles Enoch, Armida San José,Paul Hilbers, Russell Krueger, Marina Moretti, and Graham Slack
212
INTERNATIONAL MONETARY FUND
Washington DC
2002
O C C A S I O N A L PA P E R 212
Financial Soundness Indicators:Analytical Aspects and Country Practices
V. Sundararajan, Charles Enoch, Armida San José,Paul Hilbers, Russell Krueger, Marina Moretti, and Graham Slack
INTERNATIONAL MONETARY FUND
Washington DC
2002
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Preface vii
List of Abbreviations viii
I Overview 1
Part I. Selected Analytical Aspects
II Indicators for Macroprudential Analysis 7
The Macroprudential Framework 7FSIs in the Context of the FSAP 8Qualitative Aspects 9
III Banking System 13
Bank Behavior and Vulnerabilities 13Banking Indicators 15
IV Other Sectors and Markets 23
Nonbank Financial Intermediaries 23Corporate Sector 24Household Sector 28Real Estate Markets 29
V Stress Testing of Financial Systems 35
Defining System-Wide Stress Tests 35Measurement Techniques 38
Part II. Country Practices
VI The IMF Survey on FSIs 45
Introduction 45Response to the Survey 46
VII Usefulness of FSIs 48
FSIs by Usefulness Group 48Additional FSIs Identified by Respondents 49
VIII Compilation and Dissemination Practices 52
Compilation and Dissemination of FSIs and Their Components 52Periodicity 56Accounting, Regulatory, and Statistical Issues 56
Contents
iii
CONTENTS
IX Analytical Frameworks and Research 61
Macroprudential Research 61Coverage of Financial Institutions 61Norms, Benchmarks, and Thresholds 63Presentation 64Composite Measures 64Business Surveys 65
X Concluding Remarks 66
Identification of Core and Encouraged Sets of FSIs 66Directions for Further Work 67
References 70
Appendices
I Explanation of FSI Terms 73II Aggregation Issues 76
III Additional FSIs Identified by Respondents 78IV Tables of Survey Results 79V Survey on the Use, Compilation, and Dissemination of
Macroprudential Indicators 92
Boxes
1.1. Definitions 23.1. Basel Capital Adequacy Ratio 163.2. Valuation of Capital 174.1. Sectoral Balance Sheet Analysis 316.1. Structure of the Survey on FSIs 458.1. Compilation and Dissemination Practices 558.2. Country Practices on Nonperforming Loans 57
Tables
1.1. Financial Soundness Indicators 32.1. FSIs Used in Financial System Stability Assessments 103.1. Income Summary 204.1. Determinants of Corporate Vulnerabilities 254.2. Indicators for the Corporate Sector 274.3. Cash Flow Summary 284.4. Household Indicators Used in Norway, Sweden, and the
United Kingdom 304.5. Real Estate Indicators 335.1. Data Requirements for an Integrated VaR Analysis 406.1. Summary of the Responses by Type of Economy 466.2. Summary of the Responses by Indicator 467.1. Group I FSIs by Type of Economy 497.2. Group II FSIs by Type of Economy 507.3. Groups III–IV FSIs by Type of Economy 518.1. FSIs: Compilation and Dissemination Practices 538.2. Periodicity of FSIs 568.3. Valuation Practices Affecting FSIs by Data Source 59
10.1. Core Set of FSIs 6710.2. Encouraged Set of FSIs 68
iv
Contents
Figures
2.1. Components of Macroprudential Analysis 85.1. Decision Sequence for Stress Testing 367.1. Summary of the Usefulness of FSIs 489.1. Institutional Coverage of Analysis 629.2. Factors Used to Identify Key Subsectors 629.3. Presentation of FSIs 64
Appendix Tables
A1.1. Explanation of FSI Terms 73A4.1. FSIs for Which Components Are Extensively Compiled 79A4.2. SDDS Subscribers: Compilation and Dissemination of FSIs
and Components 80A4.3. Usefulness of FSIs by Type of User and Type of Economy 82A4.4. Compilation and Dissemination of FSIs by Type of Economy 86A5.1. MPI Survey—Part I (a): User Questionnaire 96A5.2. MPI Survey—Part I (b): Supplementary Issues 98A5.3. MPI Survey—Part II (a): Compilation and Dissemination
Questionnaire 100A5.4. MPI Survey—Part II (b): Supplementary Issues 108A5.5. MPI Survey—Part II (c): Valuation Issues 109
v
The following symbols have been used throughout this paper:
. . . to indicate that data are not available;
— to indicate that the figure is zero or less than half the final digit shown, or that the itemdoes not exist;
– between years or months (e.g., 2000–01 or January–June) to indicate the years ormonths covered, including the beginning and ending years or months;
/ between years (e.g., 2000/01) to indicate a fiscal (financial) year.
“Billion” means a thousand million.
Minor discrepancies between constituent figures and totals are due to rounding.
The term “country,” as used in this paper, does not in all cases refer to a territorial entity thatis a state as understood by international law and practice; the term also covers some territorialentities that are not states, but for which statistical data are maintained and provided interna-tionally on a separate and independent basis.
The development of indicators of financial soundness responds to the need for bet-ter tools to assess financial systems’ strengths and vulnerabilities. A broad search fortools and techniques to detect and prevent financial crises was prompted by the inter-national financial turmoil of the late 1990s. More recent episodes of instability havefurther highlighted the importance of continuous monitoring of financial systems as acrisis prevention tool. The IMF has undertaken a number of initiatives in this area, no-tably in support of strengthened surveillance of member countries through the jointIMF-World Bank Financial Sector Assessment Program, launched in 1999. Initial ef-forts were aimed at identifying a broad set of prudential and macroeconomic vari-ables that are relevant for assessing financial soundness—referred to as macropruden-tial indicators. More recent work has focused on a subset of these indicators—bothaggregate bank balance sheet and income statement information, and aggregate indi-cators of financial fragility of nonfinancial firms and nonbank financial markets—re-ferred to as financial soundness indicators (FSIs).
This paper brings forward recent advances in our understanding of financial sound-ness indicators with a view to supporting ongoing efforts by national authorities andprivate institutions worldwide to monitor financial system soundness. The paper alsodiscusses the use of financial soundness indicators in the operational work of the IMF,and identifies significant gaps in knowledge and directions for further work. The mate-rial in this paper was originally prepared for discussions in the IMF Executive Board inJune 2001.
The insights contained in this paper are the result of the efforts of many. In particu-lar, we would like to express our appreciation for member countries’ participation inthe IMF Survey on the Use, Compilation, and Dissemination of Macroprudential In-dicators, which helped to provide comprehensive information on country practices. Anumber of background documents by IMF staff and others referred to in this paperwere also critical in distilling analytical lessons on the selection and use of the indica-tors. We would like to thank also Mahinder S. Gill, Alfredo M. Leone, PamelaMadrid, and Ewe-Ghee Lim for their inputs into this Occasional Paper; JacquelineIrving and Lucy Ulrich of the External Relations Department for editing and produc-tion coordination; and Raja Hettiarachchi and Kiran Sastry for valuable research as-sistance. The views expressed in this paper are those of IMF staff and do not neces-sarily reflect the views of national authorities or of IMF Executive Directors.
Carol S. Carson Stefan Ingves
Director Director
Statistics Department Monetary and Exchange Affairs Department
Preface
vii
BIS Bank for International SettlementsCAMELS Capital adequacy, asset quality, management soundness,
earnings, liquidity, sensitivity to market riskCGFS Committee on the Global Financial System, BISCPSS Committee on Payment and Settlement Systems, BISEBIT Earnings before interest and taxEBITDA Earnings before interest, tax, depreciation, and amortizationECB European Central BankFSAP Financial Sector Assessment ProgramFSI Financial soundness indicatorFSSA Financial System Stability AssessmentFX Foreign exchangeG-7 Group of SevenG-10 Group of TenGDP Gross domestic productIAIS International Association of Insurance SupervisorsIMF International Monetary FundIOSCO International Organization of Securities CommissionsMPI Macroprudential indicatorNBFI Nonbank financial intermediaryNPL Nonperforming loanOECD Organization for Economic Cooperation and DevelopmentOTC Over-the-counterRAROC Risk-adjusted return on capitalROA Return on assetsROE Return on equityROSC Report on Observance of Standards and CodesSDDS Special Data Dissemination StandardVaR Value at Risk
List of Abbreviations
viii
S tructural, institutional, and macroeconomic as-pects of financial system stability are receiving
growing attention both nationally and in interna-tional fora. The magnitude and mobility of interna-tional capital flows have made it increasingly impor-tant to strengthen the foundations of domesticfinancial systems as a way to build up resilience tocapital flow volatility. The soundness of financial in-stitutions is also a key part of the infrastructure forstrong macroeconomic performance and effectivemonetary policy at the national level. Hence, centralbanks and governments are paying increasing atten-tion to monitoring the health and efficiency of finan-cial institutions and markets, and to macroeconomicand institutional developments that pose potentialrisks to financial stability.
Such activities are typically embedded in centralbanks’ mandates to promote financial stability andsound payment systems. They differ from financialsupervisory activities insofar as they are primarily di-rected at a range of factors that may pose risks to thefinancial system as a whole—systemic risks—withsignificant macroeconomic repercussions. Financialsupervisory tasks, on the other hand, are often fo-cused more directly on the health of individual insti-tutions. Given the linkages between microeconomicconditions and macroeconomic and overall financialstability, the monitoring of developments and policyresponses to ensure financial stability poses specialchallenges, particularly when financial supervisionfunctions are separated from the central bank.
The development of measures of financial sectorsoundness, and of methods to analyze them, are thesubjects of this occasional paper. We refer to them asfinancial soundness indicators (FSIs) and macropru-dential analysis, respectively (see Box 1.1). The IMFhas been accumulating experience in these areas aspart of its surveillance, technical assistance, and pol-icy development work, and, more recently, in thecontext of the Financial Sector Assessment Program(FSAP).1 An initial, relatively broad set of indica-
tors—the so-called macroprudential indicators—wasidentified in this earlier work, comprising aggregatedprudential indicators, macroeconomic variables asso-ciated with financial system vulnerability, and mar-ket-based indicators. A consultative meeting onmacroprudential indicators was held at IMF head-quarters in September 1999. High-level experts fromcentral banks, supervisory agencies, international in-stitutions, academia, and the private sector discussedtheir experiences in using, measuring, and dissemi-nating indicators of financial system soundness. AnIMF Executive Board meeting in January 2000 dis-cussed the state of knowledge in these areas and pro-posals for further work.2 Recent Board papers on theSpecial Data Dissemination Standard (SDDS) and onthe FSAP also discussed related issues.3
Discussions at the January 2000 review high-lighted the need for more research and analysis to im-prove understanding of what determines financialsystem soundness and to deal with the considerableconceptual and statistical difficulties that arise indefining and compiling indicators of financial sound-ness. The Board recommended that the IMF conducta survey of member countries on their needs andpractices related to indicators of financial soundness.The Board also concurred on the need for better indi-cators on developments in specific sectors and mar-kets that have proven to be relevant in assessing fi-nancial sector vulnerabilities, but that have beendifficult to gauge in practice. These include nonbankfinancial institutions, the corporate sector, house-holds, and real estate markets. Moreover, the Boardpointed to the need to select a smaller and more oper-ationally useful “core set” of indicators, intended to
I Overview
1
1The FSAP was launched jointly by the IMF and the WorldBank in May 1999. The program is designed to identify financial
system strengths and vulnerabilities and to help to develop appro-priate policy responses. Financial System Stability Assessments(FSSAs) are prepared by IMF staff in the context of Article IVconsultations, by drawing on the FSAP findings, for discussion inthe IMF Executive Board. In the World Bank, the FSAP reportsprovide the basis for producing Financial Sector Assessments andformulating financial sector development strategies. See IMF(2001a, b) and Hilbers (2001).
2See Evans, Leone, Gill, and Hilbers (2000).3See IMF (2000c, 2001b).
I OVERVIEW
serve as a basis for structuring data work in supportof financial system monitoring, including through theFSAP, and as a focal point for efforts by the IMF toencourage compilation and dissemination of macro-prudential information by national authorities.
Since then, the IMF has substantially advancedthe work on the measurement and analysis of finan-cial soundness, including through activities in thecontext of the FSAP and the Survey on the Use,Compilation, and Dissemination of MacroprudentialIndicators, conducted in the summer of 2000.4 Ef-forts have been directed, in particular, to gauge theusefulness of specific indicators; identify analyti-cally relevant definitions of these indicators; ap-praise compilation and dissemination practicesamong member countries; explore methods ofmacroprudential analysis, notably stress testing; andexplore the role of nonbank financial intermediaries,the corporate sector, and real estate markets in as-sessing financial system vulnerabilities.
Other international organizations have also fo-cused on these issues. For instance, the topic of theOctober 2000 Bank for International Settlements(BIS) annual meeting of central bank economistswas Marrying the Macro- and Micro-Prudential Di-mensions of Financial Stability.5 At the European
Central Bank (ECB), the Working Group on Macro-prudential Analysis of the Banking SupervisionCommittee received a mandate in 2000 to preparesemi-annual reports on macroprudential develop-ments in Europe. These analyses, which are notmade public, serve as input to discussions on finan-cial stability issues in the ECB Governing Council.The Asian Development Bank has a program to col-lect and disseminate FSIs and related macroeco-nomic series for a group of Asian-Pacific countries.Similar efforts are ongoing at the national level in anincreasing number of countries.6
This paper proposes two sets of indicators that areconsidered useful for the purpose of periodic moni-toring, and for compilation and dissemination effortsby national authorities (Table 1.1). The core set in-cludes indicators for the banking sector that shouldhave priority in future compilation and monitoringof FSIs. The encouraged set includes additionalbanking indicators, as well as data on other institu-tions and markets that are relevant in assessing fi-nancial stability—the corporate sector, real estatemarkets, and nonbank financial institutions and mar-kets. In particular, indicators of corporate health andof developments in real estate markets are consid-ered a priority in light of their analytical significancefor assessing financial vulnerabilities in a wide vari-ety of circumstances. Their compilation, which is atpresent limited, should therefore be encouraged sothat they could be included in the core set, in duecourse.
Working with two sets of FSIs—a core set and anencouraged set—avoids a one-size-fits-all approach,and provides a degree of flexibility in the selection ofindicators that are most relevant to assessing vulnera-bilities in country-specific circumstances. Indicatorsof the core set can be combined with selected, addi-tional indicators of the encouraged set that might beof particular relevance in the country concerned, de-pending on its level of financial development, institu-tional structure, and regional circumstances.
Six criteria were applied in order to identify thecore set, and some of those were applied to suggestthe encouraged set: focus on core markets and insti-tutions; analytical significance; revealed usefulness;relevance in most circumstances (i.e., not country-specific); availability; and parsimony—that is,achieving the maximum information content with alimited number of FSIs. The revealed usefulness andavailability were judged based on the results of thesurvey noted earlier (see Part II), the analytical sig-nificance and parsimony were judged based on a sur-vey of the literature as well as new empirical analysis
2
Box 1.1. Definitions
Financial soundness indicators (FSIs) are indica-tors compiled to monitor the health and soundnessof financial institutions and markets, and of theircorporate and household counterparts. FSIs includeboth aggregated information on financial institu-tions and indicators that are representative of mar-kets in which financial institutions operate. Macro-prudential indicators include both FSIs and otherindicators that support the assessment and monitor-ing of the strengths and vulnerabilities of financialsystems, notably macroeconomic indicators.
Macroprudential analysis is the assessment andmonitoring of the strengths and vulnerabilities of fi-nancial systems. This encompasses quantitative in-formation from both FSIs and indicators that providea broader picture of economic and financial circum-stances, such as GDP growth and inflation, alongwith information on the structure of the financialsystem, qualitative information on the institutionaland regulatory framework—particularly through as-sessments of compliance with international financialsector standards and codes, and the outcome ofstress tests (see Figure 2.1 in Chapter II).
4The survey explicitly listed around 60 indicators, identified inearlier work.
5See www.bis.org/publ.
6In some countries—for instance, Finland, Hungary, Iceland,Norway, Sweden, and the United Kingdom—central banks pub-lish special reports dealing with financial stability issues.
Overview
undertaken in the IMF on the definition, interpreta-tion, and analysis of FSIs (see Part I). Both the surveyand the analytical aspects were brought to bear injudging focus and country relevance.
Ideally, indicators included in the core and encour-aged sets should also be comparable across coun-tries—which would be possible if there existed in allareas internationally agreed prudential, accounting,
3
Table 1.1. Financial Soundness Indicators
Core Set
Deposit-taking institutionsCapital adequacy Regulatory capital to risk-weighted assets
Regulatory tier I capital to risk-weighted assets
Asset quality Nonperforming loans to total gross loansNonperforming loans net of provisions to capitalSectoral distribution of loans to total loansLarge exposures to capital
Earnings and profitability Return on assetsReturn on equityInterest margin to gross incomeNoninterest expenses to gross income
Liquidity Liquid assets to total assets (liquid asset ratio)Liquid assets to short-term liabilities
Sensitivity to market risk Duration of assetsDuration of liabilitiesNet open position in foreign exchange to capital
Encouraged Set
Deposit-taking institutions Capital to assetsGeographical distribution of loans to total loansGross asset position in financial derivatives to capitalGross liability position in financial derivatives to capitalTrading income to total incomePersonnel expenses to noninterest expensesSpread between reference lending and deposit ratesSpread between highest and lowest interbank rateCustomer deposits to total (noninterbank) loansForeign currency-denominated loans to total loansForeign currency-denominated liabilities to total liabilitiesNet open position in equities to capital
Market liquidity Average bid-ask spread in the securities market1
Average daily turnover ratio in the securities market1
Nonbank financial institutions Assets to total financial system assetsAssets to GDP
Corporate sector Total debt to equityReturn on equityEarnings to interest and principal expensesCorporate net foreign exchange exposure to equityNumber of applications for protection from creditors
Households Household debt to GDPHousehold debt service and principal payments to income
Real estate markets Real estate pricesResidential real estate loans to total loansCommercial real estate loans to total loans
1Or in other markets that are most relevant to bank liquidity, such as foreign exchange markets.
I OVERVIEW
and statistical standards to which all countries ad-hered—to facilitate monitoring of the financial sys-tem, not only at the national but also at the globallevel. The latter is important in view of the magnitudeand mobility of international capital flows, and therisk of contagion of financial crises from one countryto another. Advancing international comparability ofFSIs and convergence toward best practice are impor-tant goals for further work in this area.
The review contained in this occasional paperhighlights that work on measuring and analyzingFSIs has advanced substantially in recent years, andproposes specific areas where more work is needed.
• National authorities should be encouraged tocompile and monitor FSIs systematically, basedon available data.
• At the same time, guidelines are necessary to ar-rive at clear definitions of the indicators. Look-ing ahead, the IMF is working to produce, inconsultation with national authorities and stan-dard setters, a Compilation Guide on FinancialSoundness Indicators.
• At the IMF, monitoring and analysis of FSIsshould continue to be strengthened through theFSAP process and, more broadly, in the contextof surveillance, technical assistance, and policydevelopment work.
• Better indicators of the health of nonbank finan-cial institutions and markets need to be devel-oped—reflecting the specificities of each marketsegment—and of financial institutions’ exposureto the household and real estate sectors.
• With regard to the corporate sector, data availabil-ity remains a key obstacle, particularly for non-listed companies, which represent a significantshare of the sector in many countries. Furtherwork to systematically compile FSIs of the nonfi-nancial corporate sector should be encouraged.
• Analytical tools that use FSIs need to be furtherdeveloped, including more refined methods ofaggregate stress testing of financial systems.
• Finally, the development of benchmarks for thelevel of FSIs would help monitor and interpretdevelopments in the financial system, keeping inmind that benchmarks are most often country-specific and can change over time.
Monitoring and analysis of FSIs are just one ele-ment in an overall assessment of financial stability.
Other elements include analyses of macroeconomicdevelopments, market-based data such as stock pricesand credit ratings, structural information on the finan-cial sector, and—last but not least—qualitative assess-ments, in particular assessments of observance of rel-evant international standards and codes. Theseelements, which feed into macroprudential analysis,will help to identify various dimensions of risks aswell as the capacity of the system to cope with andmanage these risks, thereby helping to form a judg-ment on overall financial stability. While these toolsstill remain imperfect and continue to evolve, overtime, macroprudential analysis can reduce the inci-dence of crises by providing national authorities witha set of tools to comprehensively assess their financialsectors and identify weaknesses at an early stage.
The paper is organized in two parts—Part I fo-cuses on selected analytical aspects of defining andanalyzing FSIs, and Part II discusses country prac-tices in the use, compilation, and dissemination ofFSIs.
Within Part I, Chapter II introduces the frameworkof macroprudential analysis, including its quantita-tive as well as qualitative aspects, and reviews theexperience with macroprudential analysis and indi-cators gained through the FSAP. Chapter III focuseson the definition and interpretation of indicators ofthe current health of the banking system, primarilyderived by aggregating indicators of the health of in-dividual banks. Indicators of specific sectors andmarkets that can have an impact on financial systemstability—specifically, nonbank financial intermedi-aries (NBFIs), the corporate sector, households, andreal estate markets—are discussed in Chapter IV.Chapter V looks at stress testing as a key componentof macroprudential analysis.
Within the second part of this paper, Chapter VIintroduces the Survey on the Use, Compilation, andDissemination of Macroprudential Indicators. Chap-ter VII discusses survey results in terms of perceivedusefulness of specific FSIs. Survey results on thecompilation and dissemination of FSIs or their com-ponents are reported in Chapter VIII, and responsesrelated to the analytical frameworks used by coun-tries to analyze these indicators are reported inChapter IX.
Chapter X concludes with proposals for a core setand an encouraged set of indicators to be used forthe purpose of periodic monitoring, and for compila-tion and dissemination by national authorities. Thechapter also discusses directions for further work onFSIs.
4
Part I
Selected Analytical Aspects
The Macroprudential Framework
Macroprudential analysis is a key building blockof any policy framework for vulnerability analysis. Itis a methodological tool that helps to quantify andqualify the soundness and vulnerabilities of financialsystems.7 It uses aggregated prudential data to obtaindirect information on the current health of financialinstitutions; macroeconomic data to help set theanalysis in the context of broader economic and fi-nancial trends; stress tests and scenario analysis todetermine the sensitivity of the financial system tomacroeconomic shocks; market-based informa-tion—such as prices and yields of financial instru-ments and credit ratings—as complementary vari-ables conveying market perceptions of the health offinancial institutions; and qualitative information oninstitutional and regulatory frameworks to help in-terpret developments in prudential variables. Struc-tural data—including on the size of the main seg-ments of the financial system, ownership structure,and concentration—typically supplement the analy-sis (Figure 2.1).
Of these broad categories of data—commonly re-ferred to as macroprudential indicators—the focusof this paper is on aggregated prudential data and, tosome extent, on selected market indicators. There isno universally accepted definition of macropruden-tial indicators. Broad definitions include all possibleindicators related to financial system soundness, in-cluding relevant macroeconomic indicators (such asexchange and interest rates, and balance of paymentsdata), and market-based indicators (such as stockprices of financial institutions, credit spreads, andcredit ratings). This paper adopts, under the term “fi-nancial soundness indicators” (FSIs), a somewhatnarrower definition, which includes mainly aggre-gated microprudential indicators of the health of fi-nancial institutions and indicators of the health ofthe major clients of financial institutions (the corpo-rate and household sectors). This definition also in-
cludes indicators of key developments in markets inwhich financial institutions operate—such as thebreadth and depth of the money and capital markets,and developments in, and bank exposure to, the realestate markets.8
Macroprudential analysis closely complementsand reinforces early warning systems and other ana-lytical tools—currently in use or under developmentat the IMF—to monitor vulnerabilities and preventcrises. Early warning systems generally focus onvulnerabilities in the external position, using macro-economic indicators as key explanatory variables.9Macroprudential analysis and the associated stresstesting focus on vulnerabilities in domestic financialsystems, using FSIs as the most significant statisti-cal building block, and relate countries’ financialsector soundness to macroeconomic, external, andcapital account developments. Although FSIs andthese analyses primarily aim to predict bankingcrises, they also provide an important input to moregeneral vulnerability analyses and early warningsystems. Their usefulness for these purposes willdepend on the resolution of measurement and/oravailability problems, which have so far made it dif-ficult to incorporate them in vulnerability analysissystematically.10
An in-depth understanding of national financialsystems requires intertemporal as well as cross-sectional analyses. Caution needs to be applied inboth, however. Shifts in regulations such as account-ing and provisioning norms can lead to breaks intime series and affect the robustness of intertemporalcomparisons. Differing accounting, prudential, and
II Indicators for Macroprudential Analysis
7
7Macroprudential analysis focuses on the health and stability offinancial systems, whereas microprudential analysis deals withthe condition of individual financial institutions.
8Macroeconomic indicators are not included in this definition,given their different source and character. They are, of course,part of the broader macroprudential analysis (see Figure 2.1),however, both as leading indicators of financial sector problemsin their own right and as inputs into stress testing. See also Evans,Leone, Gill, and Hilbers (2000).
9See, in particular, Berg, Borensztein, Milesi-Ferretti, andPatillo (1999), and IMF (2000d).
10For the purpose of estimation of a robust early warning sys-tem, a variable must be reasonably comparable over time andacross countries. See Berg, Borensztein, Milesi-Ferretti, andPatillo (1999).
II INDICATORS FOR MACROPRUDENTIAL ANALYSIS
statistical standards, as well as differences in thestructure of financial systems, typically make cross-country comparisons of FSIs difficult. Peer groupanalysis—the analysis of domestic intermediarieswithin a group (e.g., by size or market niche)—oftenprovides important insights and can supplementcross-country comparisons. The use of benchmarksand thresholds for the level of FSIs would also helpin analyzing FSIs. However, benchmarks are mostoften country-specific and shifts in their levels aredifficult to discern as they occur.
FSIs in the Context of the FSAP
Macroprudential analysis is the basis for assess-ments of the soundness of financial systems that arecarried out in the context of the FSAP and the re-lated Financial System Stability Assessments(FSSAs). Financial sector assessments typicallybegin with an analysis of the macroeconomic envi-ronment and a description of the structure of the fi-nancial system. Within the financial system, thehealth of the banking sector is analyzed by lookingat levels and trends in selected FSIs—typically ofcapital adequacy, asset quality, profitability, liquid-
ity, and exposure to market risks—and the linkagebetween these indicators and changes in the macro-economic environment. In this sense, FSIs play akey role in FSSAs, which focus on financial stabilityissues and macro-financial linkages. Banking sectordata, along with information on the rest of the finan-cial system, bank borrowers (most commonly thecorporate sector), and—when data availability al-lows—price trends in, and exposures to, real estatemarkets, typically serve as the basis for quantifyingthe vulnerability of the financial system. The combi-nation of data analysis and other qualitative informa-tion (see above) is used to produce an overall assess-ment of the stability of the financial system.
The range of FSIs used in FSSAs has variedsomewhat depending on the particular country case,but typically has followed some adaptation of theCAMELS framework.11 An analysis of the indica-tors used in the FSSAs issued as of end-April 2001(Table 2.1) shows that the most commonly used FSIsinclude, in order of frequency of use: (1) profitabil-ity indicators such as returns on assets and returns on
8
11Capital adequacy, asset quality, management soundness,earnings, liquidity, sensitivity to market risk.
Figure 2.1. Components of Macroprudential Analysis
MacroeconomicData
eg., inflation, interest and exchange rates
Market-Based Dataeg., stock prices,
credit ratings
QualitativeInformationeg., compliancewith standards
Structural Information
eg., relative size,ownership
STRESSTESTS
Macroprudential Analysis
FSIs
Qualitative Aspects
equity, interest margin ratios, and noninterest in-come and expenses ratios; (2) asset quality indica-tors, notably nonperforming loan (NPL) ratios andprovisions; (3) capital adequacy ratios, in particularthe ratio of regulatory (Basel) capital to risk-weighted assets; (4) sensitivity to market risk indica-tors, notably open foreign exchange exposures; and(5) liquidity ratios. A limited number of FSSAs alsolooked at indicators of vulnerability in the corporatesector and one of the FSSAs included a more de-tailed analysis of the financial position of house-holds (net worth, net financial assets, and stocks tototal assets). Two reports included data on real estate(nonperforming mortgage loans, real estate collat-eral values, and real estate prices).
The selection and use of FSIs reflect several limi-tations. First, data for compiling indicators appearedto be often unavailable or available with only shortconsistently collected histories. As a result, the timeseries used in most FSSAs were limited in length.Second, compilation practices for FSIs varied signif-icantly across countries, due to differing prudential,accounting, and statistical standards, thereby limit-ing the possibility of cross-country comparisons.Nonetheless, some reports present cross-countrycomparisons—with the usual caveat that not all indi-cators are strictly comparable—in an attempt tobenchmark FSIs to those in other countries at similarlevels of financial development. Despite the limita-tions, FSIs were generally considered useful as away of organizing the analysis and potentially fos-tering better data collection and quality in the fu-ture.12 With varying complexity, all FSSAs includedstress testing of financial institutions’ resilience tomacroeconomic shocks. Commonly used shocks in-cluded a slowdown in economic growth, balance ofpayments shocks, and changes in inflation, interest,and exchange rates. In some of the more sophisti-cated models, asset price developments and conta-gion effects were used as channels through whichshocks transmitted to financial institutions.
Qualitative Aspects
In carrying out financial sector assessments, it isimportant to evaluate how risk is managed by risk-taking units and how risk management is governedby regulatory authorities.13 Different financial insti-tutions have different risk appetites. Moreover, the
level of risk-taking is strongly influenced by the par-ticular institutional and regulatory framework of thefinancial system.
As absolute risk levels may not by themselvesfully indicate financial institutions’ or a system’svulnerabilities, an implicit concept of “net risk” isoften applied to the assessment of financial institu-tions’ or system vulnerabilities.14 This concept al-lows combining the quantitative and qualitative as-pects of financial vulnerability.15 The “net risk”approach involves quantitatively evaluating all risksfaced by financial institutions (including the direc-tion of the risk assumed) and qualitatively adjustingfor institutional characteristics to assess the extent towhich the risks are adequately managed throughmarket discipline and internal governance in an in-stitution, and through regulatory and supervisoryframeworks in the system as a whole. Such analysescan be synthesized into an overall risk assessmentfor individual institutions, and an overall stability as-sessment for the financial system, which evaluate thequantity of all risks against the quality of the institu-tions and institutional arrangements.16 By definition,however, combining qualitative and quantitative aspects of risk is not an exact method and requiresjudgment.
Incentives
There are many institutional characteristics of a fi-nancial system that must be considered for qualita-tive adjustments to gross risk. The nature of govern-ment subsidies and taxes, payment culture andinsolvency regime, credit and deposit guarantees, thequality of supervision and regulation, moral hazard,corporate governance, and management quality allaffect the overall incentive structure of a financialsystem and must be taken into account in qualitativeadjustments.17
9
12See Carson (2001) for a discussion of the factors affectingdata quality.
13The linkages between the development of a sound bankingsystem and well-functioning banking regulation and supervisionare discussed in Sundararajan (1999). See also Sundararajan,Marston, and Basu (2001).
14For a description of a “net risk” approach to risk assessmentin the context of dynamic banking supervisory practices, see Of-fice of the Superintendent of Financial Institutions (1999).
15The importance of a healthy balance of quantitative and qual-itative information in order to provide a meaningful picture of theextent and nature of financial risks has been recently highlightedby the Multidisciplinary Working Group on Enhanced Disclosureof the Financial Stability Forum (2001).
16It should be noted, however, that regulatory factors could in-fluence the size and movement of FSIs, notably through the es-tablishment of minimum regulatory ratios.
17The incentive audit approach, outlined by Chai and Johnston(2000), looks at three factors that affect the risk-taking and moni-toring behavior of participants (investors, borrowers, and interme-diaries) at the core of the financial system: (1) market structureand the availability of financial instruments that affect market dis-cipline; (2) government safety nets, including implicit and explicitexchange rate and deposit/investor guarantees; and (3) the legaland regulatory framework, including high quality enforcement.
II INDICATORS FOR MACROPRUDENTIAL ANALYSIS
10
Tabl
e 2.
1.F
SIs
Use
d in
Fin
anci
al S
yste
m S
tabi
lity
Ass
essm
ents
ElSo
uth
Cam
eroo
nC
anad
aC
olom
bia
Salv
ador
Esto
nia
Hun
gary
Icel
and
Indi
aIr
anIr
elan
dK
azak
hsta
nLe
bano
nPe
ruPo
land
Afr
ica
Yem
en
Cap
ital a
dequ
acy
Reg
ulat
ory
capi
tal t
o ri
sk-
wei
ghte
d as
sets
1X
XX
XX
XX
XX
XX
XT
ier
1 ca
pita
l to
risk
-w
eigh
ted
asse
ts2
XX
XX
XX
XC
apita
l to
asse
tsX
XX
XX
XX
X
Ass
et q
ualit
y
(a) L
endi
ng in
stitu
tions
Loan
s (o
r cr
edit)
by
sect
orX
XX
XX
XX
Larg
e ex
posu
res
to a
sset
s
(or
capi
tal)
XX
XX
N
PLs
to g
ross
loan
s (o
r to
to
tal a
sset
s)3
XX
XX
XX
XX
XX
XX
XX
XFX
NPL
s to
gro
ss F
X lo
ans
XX
Prov
isio
ns (
plus
col
late
ral
valu
es)
to N
PLs
XX
XX
XX
XX
XX
XPr
ovis
ions
to
gros
s lo
ans
XX
XX
XX
NPL
s ne
t of
pro
visi
ons
ratio
s4X
XLo
ans
to c
olla
tera
l val
ues
X
(b) B
orro
win
g in
stitu
tions
Tota
l deb
t to
equ
ity
XX
XR
etur
n on
ave
rage
equ
ity (
ROE)
XX
Earn
ings
to
debt
ser
vice
XEx
tern
al d
ebt
to t
otal
deb
tX
X
Earn
ings
Ret
urn
on a
vera
ge a
sset
s (R
OA
)5X
XX
XX
XX
XX
XX
XX
XX
XR
etur
n on
ave
rage
equ
ity (
ROE)
X
XX
XX
XX
XX
XX
XX
XIn
tere
st m
argi
n ra
tios6
XX
XX
XX
XX
XX
Non
inte
rest
inco
me
ratio
s7X
XX
XX
XX
XX
Non
inte
rest
exp
ense
s ra
tios8
XX
XX
XX
XX
XPe
rson
nel c
ost
ratio
s9X
XX
X
Liqu
idity
Liqu
id a
sset
rat
ios1
0X
XX
XX
XX
XX
XLo
ans
(or
depo
sits
) to
tot
al
asse
tsX
XX
XX
XLo
ans
to d
epos
itsX
XX
XX
XX
XX
XLo
ans
and/
or d
epos
its b
y cu
rren
cyX
XX
XX
XX
XX
Cen
tral
ban
k cr
edit
to t
otal
ban
k
liabi
litie
sX
XX
X
Qualitative Aspects
11
Vola
tility
rat
io11
XX
Inte
rban
k tu
rnov
er r
atio
and
bi
d/as
k sp
read
XX
Sens
itivi
ty t
o m
arke
t ri
sks
Dur
atio
n of
ass
ets
and
liabi
litie
sX
XX
Net
ope
n FX
pos
ition
XX
XX
XX
XX
1 In
one
case
,cap
ital n
et o
f pro
visi
onin
g ga
p (N
PLs
min
us p
rovi
sion
s) w
as c
alcu
late
d as
a s
hare
of r
isk-
wei
ghte
d as
sets
.2 I
n on
e re
port
,tie
rs 1
and
2 w
ere
expr
esse
d in
dom
estic
cur
renc
y le
vels
rat
her
than
as
a ra
tio.
3 In
two
case
s,fo
recl
osed
ass
ets
or r
estr
uctu
red
loan
s w
ere
adde
d to
the
NPL
figu
re.
4 Rat
ios
to lo
ans,
or t
ier
1 ca
pita
l,or
gro
ss in
com
e.5 O
ne r
epor
t lo
oked
at
the
risk
-adj
uste
d re
turn
on
capi
tal (
RA
ROC
),de
fined
as
ratio
of i
nter
est
mar
gin
to a
sset
s m
ultip
lied
by t
he p
oten
tial l
oss.
6 Rat
ios
to t
otal
inte
rest
inco
me,
or t
otal
ave
rage
ass
ets,
or a
vera
ge n
et a
sset
s,or
inte
rest
ear
ning
ass
ets.
7 Rat
ios
to t
otal
inco
me,
or a
vera
ge n
et a
sset
s,or
inte
rest
inco
me.
8 Rat
ios
to t
otal
non
inte
rest
exp
ense
s,or
ave
rage
net
ass
ets.
9 Non
inte
rest
inco
me
per
empl
oyee
;pro
fits
per
empl
oyee
;loa
ns p
er e
mpl
oyee
;and
dep
osits
per
em
ploy
ee.O
ne r
epor
t lo
oked
at
prof
its p
er b
ranc
h.10
Rat
ios
of li
quid
ass
ets
to t
otal
ass
ets,
to d
epos
its,t
o sh
ort-
term
liab
ilitie
s,to
tot
al li
abili
ties.
11C
alcu
late
d as
tot
al v
olat
ile li
abili
ties
(tot
al b
orro
wed
fund
s) n
et o
f liq
uid
asse
ts t
o to
tal a
sset
s ne
t of
liqu
id a
sset
s.
II INDICATORS FOR MACROPRUDENTIAL ANALYSIS
An important aspect of the incentive structure isthe legal framework. As all financial instruments arelegal contracts, enforceability, recourse, and net ex-pected returns are highly dependent upon a financialsystem’s legal framework. If a country has a well-es-tablished commercial law with a court system wellversed in financial litigation, legal risk is minimal. Ifit is not, qualitative adjustments to gross risk forthese factors are essential.
Even well-functioning legal systems require quali-tative adjustments of risk. There are underlying dif-ferences of financial contract enforceability amongcommon and codified legal systems. Such differ-ences also affect the accounting systems used, andfrom which financial soundness indicators are de-rived. Differences in accounting information forcommon versus codified legal systems are derived inpart from differences in stakeholders in economieswith the two legal foundations. Under a commonlaw system, the principal stakeholder is the corpo-rate shareholder. Under a codified legal system,creditors, labor, government, and other interestedparties may be the relevant stakeholders. Differentstakeholders require different information, which af-fects construction of financial ratios.18
Assessing the incentive structure should also takeinto account the objectives of managers, owners, anddirectors of financial institutions. Such objectivesmay differ and profit maximization may not alwaysbe the main objective. An example of where differ-ences can affect financial institutions’ vulnerabilityis in the area of lending. Bank managers interested inexpanding business may reward employees by a per-centage of loan volume contracted. Since loan qual-ity is typically determined much later in the process,such behavior can lead to strong loan growth and in-come in the short run, with deterioration in loanquality and shareholder capital later on.
Observance of Standards and Codes
Assessments of observance and implementationof relevant financial sector codes, good practices,and standards help to capture key qualitative as-pects of financial system stability, and are neededto supplement quantitative assessments carried outin macroprudential analysis. Such assessments, inparticular, capture how financial system risk is
managed through regulatory and supervisoryframeworks by analyzing the extent to which ob-servance of existing standards helps to address theidentified vulnerabilities and risks. Such analysesare routinely carried out as part of the FSAP/FSSAprocess.19 In this context, they have helped coun-tries to focus on key operational and supervisoryrisks and to identify needed corrective actions andinstitutional strengthening plans. They can alsohelp to reveal the quality of FSIs—for instance, ofcapital adequacy ratios through the assessment ofcompliance with the Basel Core Principles for Ef-fective Banking Supervision.
The standards that have been assessed to date in thecontext of the FSAP/FSSA process—with country-specific prioritization of which standards were mostrelevant for assessment in each case—have been theCode of Good Practices on Transparency in Monetaryand Financial Policies, the Basel Core Principles forEffective Banking Supervision, the Core Principlesfor Systemically Important Payment Systems, the In-ternational Organization of Securities Commissions(IOSCO) Objectives and Principles of Securities Reg-ulation, and the International Association of Insur-ance Supervisors (IAIS) Insurance Core Principles. Inselected cases, the Organization for Economic Coop-eration and Development (OECD) Principles of Cor-porate Governance have also been assessed in thecontext of the FSAP.
Monitoring information on implementation ofstandards can be a useful component of financialsystem vulnerability analysis. A high degree of ob-servance of relevant standards contributes to the sta-bility of financial systems that are integrated intoglobal financial markets and face a variety of finan-cial innovations and shocks. Standards assessmentsare also helpful in identifying and implementing reg-ulatory and operational reforms needed for the de-velopment of countries’ financial systems over timeand their integration into global markets.
12
18See, for example, Ball (2001).
19While FSAP reports provide detailed assessments ofstrengths and vulnerabilities, observance of standards, institu-tional structures, and overall stability and developmental needs,the focus of FSSAs is on financial system stability issues of sig-nificance for macroeconomic performance and policies. For de-tails, see IMF (2001b). Summary assessments of financial sectorstandards and codes from the FSAP process are included in theFSSA and are also issued as Reports on Observance of Standardsand Codes (ROSCs). See IMF (2001c).
Bank Behavior and Vulnerabilities
Financial systems are exposed to a variety ofrisks, and the extent of exposure to these risks de-pends on the portfolio characteristics of individualbanks, their systemic importance, the linkages withother institutions and markets, as well as the size andnature of the risks. Typically, an individual portfoliowill be vulnerable to shocks to credit risk, liquidityrisk, and market risk (including interest rate, ex-change rate, equity price, and commodity pricerisks). Market risk and credit risk shocks can affectthe portfolios of financial institutions either directlythrough changes in the value of financial assets thatare marked-to-market, or indirectly through changesin the financial position of debtors that reduce creditquality. Shocks to depositor or investor confidencemay create liquidity problems that also affect thebalance sheets of financial institutions. These shocksare eventually reflected in the profitability and capi-tal adequacy of financial institutions. Financial sys-tem vulnerability increases when shocks hit portfo-lios that are not liquid, hedged, or sufficientlydiversified, and when there is insufficient capital toabsorb the shocks.20
Recent papers have attempted to deepen ourknowledge of financial institutions’ characteristicsand behavior that may increase the probability ofcrises. In their study based on work done for theSouth Africa FSAP mission, Barnhill, Papapana-giotou, and Schumacher (2000) conclude that whilemarket risk, credit risk, portfolio concentration, andasset/liability mismatches are all important risk fac-tors, in many countries credit quality is the most im-portant source of vulnerability during periods of fi-nancial stress. Hence, particularly in the lesssophisticated financial systems, the main channelthrough which shocks affect the risk profile of finan-cial institutions is a collapse in borrowers’ creditwor-thiness. These results point to the need to emphasize,
in the selection of a core set of FSIs, the quality of theloan portfolio of financial institutions, while at thesame time monitoring the importance of nonlendingactivities in the generation of bank income.
Cortavarría, Dziobek, Kanaya, and Song (2000)review evidence that bank behavior may actuallyamplify financial crises.21 Procyclical effects can betransmitted through three channels: capital, credit,and provisions. In times of recession, banks arelikely to incur higher levels of loan losses, and con-sequently lower capital, than when the economy isstrong. Moreover, retained earnings from bank prof-its, which add to Tier 1 capital, also tend to fall dur-ing a recession and rise in boom periods. Evidenceof procyclical behavior through shifts in credit sup-ply can be found in the credit crunch literature,which postulates that increased risk perceptions dur-ing a crisis and a shortage of bank capital lead todownward shifts in the supply of loans.22 On theother hand, loan standards typically become morerelaxed during economic expansions. A complicat-ing factor in almost all the empirical evidence on thisissue is the regulatory response during banking dis-tress (tightening regulations), which may itself pro-duce a procyclical effect during a downturn. From apolicy perspective, however, this regulatory responseis often intended to bring credit expansion to a moresustainable path.
Provisioning systems with a focus on ex post fac-tors (such as interest past due) may also amplify fi-nancial crises. During an expansion, default ratestypically fall, and banks relying mainly on ex postcriteria respond by reducing the level of provisions,showing higher profits, and distributing more divi-dends. During the contraction that follows, when de-fault rates rise, banks are suddenly faced with theneed for higher provisions, which reduce capital,financial strength, and the ability to lend, thus con-tributing to a protracted downturn. Although empiri-cal evidence of these effects is rather weak, provi-
III Banking System
13
20Systemic liquidity provision and the functioning of interbankmarkets can also affect the ability of the system to absorbshocks.
21For a recent discussion of procyclicality in the financial sys-tem, see also Borio, Furfine, and Lowe (2001).
22See for instance Agénor, Aizenman, and Hoffmaister (2000).
III BANKING SYSTEM
sioning may indeed provide incentives for banks toengage in procyclical behavior.
Delgado, Kanda, Mitchell Casselle, and Morales(2000) highlight that the availability of foreign cur-rency loans to domestic borrowers influences theassessment of risks. Banks generally transfer cur-rency risk to borrowers who commit to debt-servicepayments in foreign currency, regardless of the cur-rency denomination of their revenue. This exposurecompounds credit and currency risks, however: bynot refinancing or hedging the obligation, the bor-rower remains exposed to an exchange rate risk thattranslates into a credit risk to the lender. Counter-party exposure also results from the risk that the do-mestic currency market value of the collateral back-ing the obligation declines. In this case, theborrower does not face direct exchange rate risk;however, the bank is exposed to a potential creditrisk in the event of industry- or company-specificadversities, as the collateral no longer covers theobligation. Because the same demand factors oftensupport domestic activities and asset prices (seeChapter IV), it is not unusual that countries experi-ence both effects simultaneously.
Dziobek, Hobbs, and Marston (2000) analyze thedeterminants of bank liquidity—defined as the de-gree to which a financial institution is able to meetits obligations under normal business conditions.Volatility in the depositor (and creditor) base de-pends on the type of depositor, insurance coverage,and maturity. Banks that rely on a narrow or highlyvolatile funding base are more prone to liquiditysqueezes. Household deposits are typically more sta-ble than, for instance, the deposits of institutional in-vestors or corporate entities. Deposit concentration(i.e., fewer, larger-sized deposits) can also be indica-tive of volatility. Deposit insurance increases the sta-bility of the deposits it covers, with the importantcaveat that insurance schemes that are not crediblemay not have this effect. On the external front, for-eign financing (for instance, through commercialcredit lines), and deposits of nonresidents (either inforeign or domestic currency) can become highlyvolatile in situations of distress and make the finan-cial system vulnerable to external shocks or adversedevelopments in the domestic economy. As regardsinstrument maturity, the longer the time before theliability matures (in terms of remaining maturity),the more stable the funding is. However, in countrieswhere banks are required to meet early withdrawalrequests with only minor penalties, maturity may beless relevant in determining funding stability.
Ultimately, the liquidity properties of assets and li-abilities depend on a country’s liquidity infrastructureand the resulting systemic liquidity. Dziobek, Hobbs,and Marston (2000) develop a framework for assess-ing the adequacy of arrangements for market liquid-
ity. The components of a balanced liquidity infra-structure are largely institutional in nature—includingthe existence of legal contract rights and informationdisclosure. Prevailing monetary arrangements, designaspects of central bank instruments, and arrange-ments for payments and money market operationsalso bear directly on banks’ ability to manage short-term liquidity. For instance, high transaction costs re-sulting from rigid instrument design and trading rulescan discourage trades and contribute to price volatil-ity. Foreign exchange regulations—such as capitalcontrols and prudential controls on open foreign cur-rency positions—can affect access to foreign cur-rency liquidity. For example, overly tight limits on netpositions in foreign exchange can constrain banks’ability to manage liquidity through currency conver-sion. Restrictions on the use of currency derivativesmay limit the incentive for developing hedging mech-anisms that can improve management of liquidity andother types of risks.
Bank involvement in off-balance-sheet activitiesalso has implications for systemic financial risks.Schinasi, Craig, Drees, and Kramer (2000) reviewthe key features of modern banking and, in particu-lar, over-the-counter (OTC) derivatives markets thatare relevant for assessing their soundness.23 Interna-tionally active financial institutions have become ex-posed to additional sources of instability because oftheir large and dynamic exposures to credit risks em-bodied in their OTC derivatives activities. Althoughmodern financial institutions still derive most oftheir earnings from intermediating, pricing, andmanaging credit risk, they are doing increasinglymore of it off-balance-sheet. For example, a simpleswap transaction is a two-way credit instrument inwhich each counterparty is both a creditor and adebtor. But there are important differences comparedwith traditional banking. The credit exposures asso-ciated with derivatives are time varying and dependon the price of underlying assets. Hence, financialinstitutions need to assess the potential change in thevalue of the credit extended (by marking it to mar-ket), and form expectations about the future path ofthe underlying asset price. This, in turn, requires anunderstanding of the underlying asset markets.Moreover, Breuer (2000) notes that off-balance-sheet positions can build up financial institutions’
14
23Compared with exchange-traded derivatives markets, OTCderivatives markets—in which transactions are not clearedthrough a centralized clearinghouse—have the following fea-tures: management of credit risk is decentralized at the level ofindividual institutions; there are no formal centralized limits onindividual positions, leverage, or margining; there are no formalrules for risk and burden sharing; and there are no formal rules ormechanisms for ensuring market stability and integrity. On OTCderivatives markets, see also IMF (2000b), Chapter IV.
Banking Indicators
leverage that is not explicitly recorded on-balance-sheet. The creditor and debtor relationships implicitin OTC derivatives transactions between financialinstitutions can create situations in which the possi-bility of isolated defaults can threaten access to li-quidity of key market participants—similar to a tra-ditional bank run. The rapid unwinding of positions,as all counterparties run for liquidity, is character-ized by creditors demanding payment, selling collat-eral, and putting on hedges, while debtors drawdown capital and liquidate other assets. This can re-sult in extreme market volatility.
Banking Indicators
The variety of risks to which banks are exposedjustifies looking at aspects of bank operations thatcan be categorized under the CAMELS framework.This involves the analysis of six groups of indicatorsof bank soundness: capital adequacy, asset quality,management soundness, earnings, liquidity, and sen-sitivity to market risk. This section looks at specificindicators within these categories, with two caveats.First, management soundness is not dealt with ex-plicitly in the section. Although this aspect is key tobank performance and, to some extent, is reflected infinancial institutions’ accounts, its evaluation is pri-marily a qualitative exercise, and its analysis is anintegral part of banking supervision. Second, mea-surement of bank off-balance-sheet positions will bedealt with both under capital adequacy (as they af-fect leverage) and under asset quality (as they affectcredit risk).
Although implicitly the indicators reviewed in thissection refer to the consolidation of bank accounts atthe national level, it is important to note that, for in-ternationally active banks, the assessment of sound-ness should ideally include the consolidation of fi-nancial statements of foreign branches and affiliates.In this regard, as Baldwin and Kourelis (forthcom-ing) point out, analysts should be aware of potentialdifferences across national boundaries in the treat-ment of loan-loss provisioning, asset and liabilityvaluation, recognition of income and expenses, anddeferral of gains and losses. Due attention should bepaid to the accounting standards used in each coun-try, and consolidation should be performed follow-ing uniform accounting standards.
Capital Adequacy
Capital adequacy and availability ultimately deter-mine the robustness of financial institutions toshocks to their balance sheets. Aggregate risk-basedcapital ratios (the ratio of regulatory capital to risk-weighted assets) are the most common indicators of
capital adequacy, based on the methodology agreedto by the Basel Committee on Banking Supervisionin 1988.24 Simple ratios of capital to assets withoutdifferential risk weights often complement this mea-sure. An adverse trend in these ratios may signal in-creased risk exposure and possible capital adequacyproblems. In addition to the amount of capital, itmay also be useful to monitor indicators of capitalquality. In many countries, bank capital consists ofdifferent elements that have varying availability andcapability to absorb losses, even within the broadcategories of tier 1, tier 2, and tier 3 capital.25 Ifthese capital elements can be reported separately,they can serve as more reliable indicators of the abil-ity of banks to withstand losses, and help to putoverall capital ratios into context.
The Basel Committee’s minimum standards forrisk-weighted capital adequacy were originally in-tended to apply only to internationally active banks,but are now used in most countries—industrial,emerging, and developing—and for most banks(see Box 3.1). Recent proposals have been put for-ward by the Basel Committee to update this stan-dard, to account for the rapid development of newrisk-management techniques and financial innova-tion.26 These proposals introduce greater refine-ment into the existing system of risk weighting, torelate its categories more accurately to the eco-nomic risks faced by banks—including as measuredby banks’ own internal ratings systems, or, lesselaborately, based on ratings from external ratingagencies. However, improved risk measurementcomes at the expense of comparability. Under thenew proposal, each bank’s way of estimating creditrisk can differ, which, being reflected in differentrisk-weighted assets and capital ratios, would makeaggregation of individual bank ratios problematic.This issue has not so far been tackled explicitly inthe Basel proposal.
Well-designed loan classification and provision-ing rules are key to obtaining a meaningful capitalratio. Loan classification rules determine the levelof provisioning, which affects capital both indi-
15
24The Basel Committee’s 1988 risk measurement frameworkassigns all bank assets to one of four risk-weighting categories,ranging from zero to 100 percent, depending on the credit risk ofthe borrower. The Basel Capital Accord requires internationallyactive banks in Bank for International Settlements (BIS) membercountries to maintain a minimum ratio of capital to risk-adjustedassets of 8 percent.
25Tier 1 capital consists of permanent shareholders’ equity anddisclosed reserves; tier 2 capital consists of undisclosed reserves,revaluation reserves, general provisions and loan-loss reserves,hybrid debt-equity capital instruments, and subordinated long-term debt (over five years); tier 3 capital consists of subordinateddebt of shorter maturity (two to five years). See Basel Committee(1988, 1998).
26See Basel Committee (2001).
III BANKING SYSTEM
rectly (by reducing income) and directly (throughinclusion of general provisions, to some extent, inregulatory capital).27 Moreover, in most Group ofTen (G-10) countries, banks are required to deductspecific provisions (or loan-loss reserves) fromloans—that is, credit is calculated on a net basis—
which reduces the value of total assets and hence ofcapital (see Box 3.2).28
Simple gearing ratios—the ratio of capital to assets, without differential risk weights—arealso meaningful indicators and are often used, as
16
Box 3.1. Basel Capital Adequacy Ratio
The Basel capital adequacy ratio was adopted in1988 by the Basel Committee on Banking Supervisionas a benchmark to evaluate whether banks operating inthe G-10 countries have sufficient capital to survivelikely economic shocks. The ratio calls for minimumlevels of capital to (i) provide a cushion against lossesdue to default arising from both on- and off-balance-sheet exposures; (ii) demonstrate that bank owners arewilling to put their own funds at risk; (iii) providequickly available resources free of transactions and liq-uidation costs; (iv) provide for normal expansion andbusiness finance; (v) level the playing field by requiringuniversal application of the standard to internationallyactive banks; and (vi) encourage less risky lending.
The original Basel capital ratio, along with subse-quent amendments, requires international banks tohave a specific measure of capital greater than or equalto 8 percent of a specific measure of assets weighted bytheir estimated risk. The ratio is an analytical constructwith complex definitions of the numerator (capital) andthe denominator (risk-weighted assets) that cannot bederived directly from standard financial statements.The formula states that a banking enterprise must havecapital on a worldwide consolidated basis equal to 8percent or more of its risk-weighted assets, which in-cludes off-balance-sheet positions.
Risk-based Capital Capital x 100Adequacy Ratio = ————————— ≤ 8
Risk-Weighted Assets
where: Capital = (tier 1 Capital – Goodwill) + (tier 2Capital) + (tier 3 Capital) – Adjustments
Tier 1 capital, or “core capital,” consists of equitycapital and disclosed reserves that are consideredfreely available to meet claims against the bank.
Tier 2 capital consists of financial instruments andreserves that are available to absorb losses, but whichmight lack permanency, have uncertain values, mightentail costs if sold, or otherwise lack the full loss-absorption capacity of tier 1 capital items.
Tier 3 capital consists of subordinated debt with anoriginal maturity of at least two years for use, ifneeded, against market risk exposures associated withfluctuations in the market value of assets held.
Goodwill is subtracted because the value of goodwillmay fall during crises, and various adjustments are madeto capital to prevent possible double counting of value.
Risk-weighted assets, the denominator, are theweighted total of each class of assets and off-balance-sheet asset exposures, with weights related to the riskassociated with each type of asset. In the examplegiven in the table below, the book value of assets is940, but the value of risk-weighted assets is 615.
Capital adequacy ratios are often not directly compa-rable between countries because national supervisorshave some leeway in defining weights and adjustmentsand, even more importantly, national practice may varyin the valuation of assets, recognition of loan losses,and provisioning, which can significantly affect theratio. Moreover, an aggregate measure of capital ade-quacy potentially disguises information on individualinstitutions; thus, for macroprudential analysis, it isuseful to supplement the aggregate ratio with informa-tion on the dispersion of ratios for individual institu-tions or subsectors of the banking system.
Recent developments in the ratio include attempts torefine the weighting system. In particular, the BaselCommittee has a proposal to revamp the standard topermit greater differentiation between assets based ontheir risk, including the possibility of using (under lim-ited conditions) internal model-based measures of riskexposures.
Example of Estimation of Risk-Weighted Assets
Value of RiskType of Asset Holdings weight Result
U.S.Treasury bonds 200 0 % 0Mortgage loans 250 50 % 125Corporation bonds 120 100 % 120Consumer loans 370 100 % 370
Total 940 — 615
27The Basel Capital Accord allows banks to include generalprovisions in tier 2 capital, up to 1.25 percent of (risk) assets.
28Although accounting and prudential standards usually requirethe deduction of provisions from loans, international statisticalstandards recommend recording loans gross of provisions untilthe loan is written off.
Banking Indicators
Cortavarría, Dziobek, Kanaya, and Song (2000)point out.
The analysis in Breuer (2000) highlights that ex-plicitly including off-balance-sheet positions pro-duces a more accurate measure of bank leverage. Toassess leveraged positions in off-balance-sheet trans-actions resulting from a derivative contract, the basicderivative instruments—forwards and options—canbe replicated by holding (and in the case of options,constantly adjusting) positions in the spot market ofthe underlying security, and by borrowing or lendingin the money market. This replication of the contractmaps the individual components into own-fundsequivalents (equity) and borrowed-funds equivalents(debt), which can be used to measure the leveragecontained in long and short forward positions and op-tion contracts. This on-balance-sheet asset equivalentof the exposure is also called the current notionalamount. Overall leverage ratios, defined as on-balance-sheet assets plus off-balance-sheet exposures(gross or net), can be obtained following this method.
Summary Points
Indicators covered in this section suggest that twomain measures are important for tracking capital ad-equacy: the ratio of regulatory capital to risk-weighted assets (the Basel capital adequacy ratio),and the ratio of capital to assets (the gearing ratio).
In countries where bank derivatives trading is con-sidered of systemic importance, it is also advisable,when monitoring capital ratios, to adjust for off-bal-ance-sheet items.
Asset Quality
Risks to the solvency of financial institutions mostoften derive from impairment of assets. This sectionlooks at indicators that directly reflect the currentstate of bank credit portfolios,29 including informa-tion on loan diversification, repayment performanceand capacity to pay, and currency composition. Indi-cators of asset quality need to take into accountcredit risk assumed off-balance-sheet via guarantees,contingent lending arrangements, and derivatives—asubject covered at the end of the section. The qualityof financial institutions’ loan portfolios is also di-rectly dependent upon the financial health and prof-itability of the institutions’ borrowers, especially thenonfinancial enterprise sector. Indicators of the fi-nancial strength of corporate and household borrow-ers are discussed in detail in Chapter IV.
The ratio of nonperforming loans (NPLs) to totalloans is often used as a proxy for asset quality of aparticular bank or financial system. Cortavarría,Dziobek, Kanaya, and Song (2000) note that inmany countries, including most G-10 countries, as-sets are considered to be nonperforming when (1)principal or interest is due and unpaid for 90 days ormore; or (2) interest payments equal to 90 days ormore have been capitalized, refinanced, or rolledover. Some countries use forward-looking classifica-tion criteria, which focus on repayment capacity andcash flow of the borrower, and mirror more accu-rately the current economic value of a loan, thereforeproviding better quality indicators. For countries thatare using the usual classification system, which in-cludes five categories: standard, special mention,substandard, doubtful, and loss, NPLs are often de-fined as loans in the three lowest categories. Never-theless, the classification criteria vary across coun-tries; hence, available measures of NPLs are notalways comparable across countries and not evenover time. In addition, some countries count only theunpaid portion of the loan, rather than the entireloan, as nonperforming. Meaningful cross-countrycomparisons of national NPL figures would requirea common definition of NPLs.
A notion of asset quality geared toward the capac-ity of a bank to withstand stress should also considerthe level of provisions. Provisions can be general—
17
Box 3.2.Valuation of Capital
Bank capital (or equity) equals assets minus lia-bilities. Since capital is a residual, it cannot be mea-sured directly and its quantification requires thateach item affecting its level be evaluated—includ-ing assets, liabilities, off-balance-sheet commit-ments, and other items. The valuation of assets isthe most important component and different meth-ods are needed to evaluate the main categories ofassets (loan portfolio, securities, fixed assets, otherassets). Methodological issues include: (1) marketvalue versus book value, (2) replacement value ver-sus yield-based value, and (3) going concern valueversus liquidation value. Valuation of liabilities ismore straightforward, although the valuation ofsome elements of tier 2 regulatory capital (notablysubordinated debt and hybrid instruments) may becomplicated. The impact of off-balance-sheet itemson capital is particularly difficult to evaluate be-cause of the mostly contingent nature of theseitems. Finally, a wide range of other items must betaken into account, including hidden reserves andlosses in the form of unbooked transactions, good-will, franchise value, and financial damages andpenalties linked with pending legal cases.
29Credit (assets for which the counterparty incurs debt liabili-ties) is a more comprehensive concept than loans, and includesloans, securities other than shares (e.g., bonds), and miscella-neous receivables.
III BANKING SYSTEM
for possible losses not yet identified—or specific—for identified losses (loan-loss reserves). The defini-tion and rules concerning general and specific provi-sions vary across countries, although standardizedlevels seem to gravitate toward 20 percent, 50 per-cent, and 100 percent for substandard, doubtful, andloss categories.30 In some countries banks are alsorequired to hold a general provision, sometimes cal-culated as 1 percent of standard-quality loans. Thecoverage ratio—the ratio of provisions to NPLs—provides a measure of the share of bad loans forwhich funds have already been set aside. An impor-tant indicator of the capacity of bank capital to with-stand NPL-related losses is the ratio of NPLs net ofprovisions to capital.31
In situations of systemic banking distress, figureson restructured loans (and loan recoveries) are usedas indicators of progress with NPL management.Trends in NPLs should be looked at in conjunctionwith information on recovery rates—for example,using the ratio of cash recoveries to total NPLs.Such information points to the level of effort or theability of financial institutions to cope with highNPL portfolios.
Lack of diversification in the loan portfolio sig-nals an important vulnerability of the financial sys-tem. Loan concentration in a specific economic sec-tor or activity (measured as a share of total loans)makes banks vulnerable to adverse developments inthat sector or activity. This is particularly true for ex-posures to the real estate sector (see Chapter IV).Country- or region-specific circumstances often de-termine the particular sectors of the economy thatneed to be monitored for macroprudential purposes.
Exposure to country risk can also be important incountries that are actively participating in the interna-tional financial markets. Data on the geographical dis-tribution of loans and credit allow the monitoring ofcredit risk arising from exposures to particular(groups of) countries, and an assessment of the impactof adverse events in these countries on the domesticfinancial system through contagion.
Concentration of credit risk in a small number ofborrowers may also result from connected lendingand large exposures. Monitoring of connected lend-ing is particularly important in the presence ofmixed-activity conglomerates in which industrial
firms control financial institutions.32 Credit standardsmay be relaxed for loans to affiliates, even when loanterms are market-based. Connected lending can bemeasured against capital; the definition of what con-stitutes a connected party is usually set in considera-tion of the legal and ownership structures prevalent ina particular country. Consequently, this indicator isoften difficult to use in cross-country comparisons.
The assessment of large exposures, usually calcu-lated as a share of capital, aims at capturing the po-tential negative effect on a financial institution if asingle borrower experiences difficulties in servicingits obligations.33 Baldwin and Kourelis (forthcom-ing) note that it is important to monitor this indicatorat the level not only of individual banks and the ag-gregate financial sector, but also of financial groups.If a number of affiliates have dealings with the sameborrower, the group’s credit risk exposure could wellbe underestimated if taken on a solo basis. More-over, members of a group may sell loans to affiliatedentities in advance of a periodic reporting in order toobscure their true exposure.
In countries where domestic lending in foreign cur-rency is permitted, it is important to monitor the ratioof foreign currency-denominated loans to total loans.Delgado, Kanda, Mitchell Casselle, and Morales(2000) note that, ideally, a measure of risk from do-mestic lending in foreign currency should identifyloans to unhedged domestic borrowers. In thesecases, hedging would also include “natural hedges,”or borrowings for which the adverse exchange rateimpact on domestic currency obligations is compen-sated by a positive impact on revenue and profitabil-ity. The level of this ratio is related to that of foreigncurrency-denominated deposits to total deposits, al-though differences may be observed, notably whensources of foreign currency financing are availablefrom lines of credit and other capital inflows. Hence,foreign currency loans should also be monitored as ashare of foreign currency deposits and other foreigncurrency funding. Notably, however, because of thecompound nature of credit and currency risk in for-eign exchange-denominated lending, even institutionswith a balanced foreign exchange position face riskswhen engaging in this type of lending.
Impact of Off-Balance-Sheet Operations
Monitoring bank soundness requires tracking therisks involved in off-balance-sheet operations (viaguarantees, contingent lending arrangements, and de-
18
30Collateral could be taken into account in establishing provi-sions and a conservative value of the collateral could be deductedfrom the loan amount.
31The accounting treatment of provisions must be consideredwhen looking at NPL ratios. As indicated above, in most G-10countries, local accounting and prudential standards requirebanks to deduct specific provisions from loans, which adjusts thevalue of loans in response to changes in quality. In these cases,NPLs should be measured as a percentage of gross, rather thannet, loans.
32See Baldwin and Kourelis (forthcoming).33Exposure refers to one or more loans to the same individual
or economic group. There is no standard definition of “large.” Insome countries, it refers to exposures exceeding 10 percent ofregulatory capital.
Banking Indicators
rivative positions). As a general rule, FSIs should becalculated using “exposures”—that is, positions thatare both on- and off-balance-sheet—rather thanmerely positions on the balance sheets. However, fi-nancial derivatives and off-balance-sheet positionspresent special problems in evaluating the condition offinancial institutions because of the lack of reportingof positions in some countries, inadequate counter-party disclosure, high volatility, and the potential forspill-over effects. Such concerns have led the account-ing profession to move toward explicit recognition ofvirtually all derivatives on balance sheets using a mar-ket value or equivalent measure of value (e.g., usingdelta-based equivalents).34 International standardshave also been proposed for the recognition, valua-tion, and disclosure of information on derivatives.35
Derivatives and, in particular, OTC derivatives,can contribute to the buildup of vulnerabilities andshould be explicitly monitored. Although the institu-tions that intermediate the bulk of transactions inOTC derivatives markets are a limited number oflarge internationally active institutions (includingcommercial banks), smaller-scale interbank and in-terdealer activity account for a significant share ofdaily turnover.36 This is because of the low cost andflexibility of OTC derivatives, which makes them ef-ficient vehicles for position taking and hedging.Data on notional amounts of OTC derivatives trans-actions are common indicators in this area.
Summary Points
Indicators highlighted in this section as importantin assessing bank asset quality include NPLs to totalloans, NPLs net of provisions to capital, sectoral dis-tribution of loans to total loans, connected lending tocapital, large exposures to capital, and, where ap-plicable, foreign currency-denominated loans tototal loans. Ideally, indicators should be constructedusing figures for “exposures” (on- and off-balance-sheet) rather than just loans.
Earnings and Profitability
Accounting data on bank margins, income, andexpenses are widely used indicators of bank prof-itability. Common operating ratios are net income toaverage total assets—also known as return on assets
(ROA)—and net income to average equity—alsoknown as return on equity (ROE).37
Vittas (1991) notes that three types of operatingratios may be used in analyzing the performance ofbanks: operating asset ratios, operating income ra-tios, and operating equity ratios. The first relates allincomes and expenses to average total assets, thesecond to gross income, and the third to average equity. A summary of terms used in income state-ments can be found in Table 3.1.
Differences in capital structure, business mix, andaccounting practices across countries, among indi-vidual banks, and over time must be considered inanalyzing bank performance, and highlight the needto look at several operating ratios simultaneously.Differences in capital structure refer to differences inbank leverage. Banks with lower leverage (higherequity) will generally report higher operating assetratios (such as ROA), but lower operating equity ra-tios. Hence, an analysis of profitability based on op-erating equity ratios (such as ROE) disregards thegreater risks normally associated with high leverage.Operating income ratios may also be affected byleverage; notably, the interest margin and net incomeratios will be higher, while the noninterest incomeand noninterest expenses ratios will be lower forbanks with lower leverage (higher equity). The rea-son for this is that banks with higher equity need toborrow less to support a given level of assets andthus have lower interest expenses, which results inhigher net interest and net income.
Differences in business mix derive from differingcombinations of high- and low-margin business—for example, retail banking, which is associated withhigher lending rates, lower deposit rates, and higheroperating costs, and wholesale corporate banking. Inthis case, an analysis based on interest margins andgross income only may be misleading, since twobanks may show wide differences in these ratios andstill have equal ROA and ROE. Such an analysis dis-regards the fact that high margin business involveshigh operating costs. In the same vein, banks thatoffer a wider range of services, such as investmentbanks, will have much higher operating costs butalso higher noninterest income.
Accounting practices that distort operating ratioscover such issues as the valuation (and revaluation,in the presence of inflation) of assets, the treatmentof reserves for depreciation, employees’ pensions,loan-loss provisions, and the use of hidden reserves.The possible impact of these factors must be takeninto account in interpreting the ratios.
19
34The delta-normal method uses the linear derivative to approx-imate the change in portfolio value and the normal distribution asthe underlying statistical model of asset returns.
35See Basel Committee on Banking Supervision and Interna-tional Organization of Securities Commissions (1998).
36Schinasi, Craig, Drees, and Kramer (2000) report that in1998 contracts between the major players accounted for roughlyone-half of notional principal in interest rate derivatives and one-third in foreign exchange derivatives.
37The ratios can be calculated with various income measures—for example, before or after provisions and before or after taxcharges and (net) extraordinary items.
III BANKING SYSTEM
Returns can also be calculated on a risk-adjustedbasis. The risk-adjusted return discounts cash flowsaccording to their volatility: the more volatile thecash flow, the higher the discount rate and the lowerthe risk-adjusted return. Risk-adjusted return on cap-ital (RAROC) states the return on capital required tooffset losses on the underlying asset should volatilitycause its value to decline (by two or more standarddeviations). RAROC is particularly useful to banksin evaluating businesses and products according totheir place along a risk/return spectrum, so as to cor-rectly price a transaction and manage the risk-ad-justed return. At the individual transaction level,RAROC is calculated as the ratio of interest marginassociated with the operation (e.g., a loan) to loanvalue multiplied by the potential loss. At the aggre-gate level, it can be computed as interest margin toassets multiplied by the potential loss. Estimatingthe potential loss requires data on historical defaultand recovery rates and banks’ ability to liquidate theassets (liquidity risk).
Summary Points
Relying too heavily on just a few indicators ofbank profitability can be misleading. While ROA,ROE, and interest margin (and noninterest expenses)to gross income remain the key measures, theyshould ideally be supplemented by the analysis ofother operating ratios.
Liquidity
The level of liquidity influences the ability of abanking system to withstand shocks. Common mea-sures of liquidity include liquid assets to total assets(liquid asset ratio), liquid assets to short-term liabili-ties, or loans to assets as a crude measure.38 The defin-
ition of liquid assets differs across countries but, ingeneral terms, it refers to cash and its equivalents—any asset that is readily convertible to cash withoutsignificant loss. These indicators reflect the maturitystructure of the asset portfolio and can highlight exces-sive maturity mismatches and a need for more carefulliquidity management. Loan to deposit ratios (exclud-ing interbank deposits) are also sometimes used to de-tect problems—a high ratio indicating potential liquid-ity stress in the banking system. These ratios may alsoreflect loss of depositor and investor confidence in thelong-term viability of the institutions.
Information on the volatility of bank liabilities cansupplement the information provided by liquidity ra-tios. Dziobek, Hobbs, and Marston (2000) propose afunding volatility ratio calculated as volatile liabili-ties minus liquid assets to illiquid assets (total assetsminus liquid assets). A positive ratio indicates risk,since volatile liabilities are not fully covered by li-quid assets. In practice, however, there are problemsin applying this ratio, since it is difficult to knowwhich assets should be classified as liquid and whichliabilities should be classified as volatile.39 Moregenerally, bank liabilities that are subject to the riskof reversal of capital flows, such as external creditlines and deposits of nonresidents, should be moni-tored closely—for instance, through indicators of thesize of this type of funding in total bank liabilities.Such indicators of exposure to international capitalmovements reflect the relevance of macroprudentialanalysis for assessments of external vulnerability.
As bank liquidity depends on the level of liquidityof the overall system, it is important to monitor mea-sures of market liquidity. The focus may be on thetreasury bill or central bank bill market, or on othermarkets that are most relevant to the liquidity ofbank assets. Market liquidity can be captured by in-dicators of the tightness, depth, and resilience of amarket.40 Tightness indicates the general cost in-curred in a transaction irrespective of the level ofmarket prices and can be measured by the bid-askspread (the difference between prices at which amarket participant is willing to buy and sell a secu-rity). Depth denotes the volume of trades possiblewithout affecting prevailing market prices and isproxied by the turnover ratio.41 Resilience refers to
20
Table 3.1. Income Summary
+ Interest income
– Interest expenses
= Interest margin (net interest income)
+ Noninterest income
= Gross income
– Noninterest expenses
= Net income
38Indicators of the maturity structure should distinguish be-tween domestic and foreign liabilities and indicate the currencydenomination of the liabilities.
39The need to further develop broad principles for quantifyingfunding liquidity risk was recently highlighted by the Multidisci-plinary Working Group on Enhanced Disclosure of the FinancialStability Forum. See Financial Stability Forum (2001).
40See Committee on the Global Financial System (1999). No-tably, in times of particular financial distress, dealers may not bewilling to make a market at all in certain securities. Such in-stances can be captured through surveys of primary security deal-ers. See Nelson and Passmore (2001).
41The turnover ratio is the ratio of the average trading volumeover a given period of time to the outstanding volume of securities.
Banking Indicators
the speed at which price fluctuations resulting fromtrades are dissipated; while there is still no consen-sus on an appropriate measure, one approach is toexamine the speed of the restoration of normal mar-ket conditions after trades.
Where foreign currency transactions are relevant,liquidity management can be complicated if the avail-ability of foreign currency is limited and interbankforeign exchange lines are vulnerable to disruption. Inthese cases, it is also important to measure the liquid-ity of foreign exchange markets and monitor its deter-minants. Foreign exchange liquidity will also dependon developments in the external sector, which is sub-ject to the risk of reversal of capital flows (see above)or to the adequacy of foreign exchange reserves. Moregenerally, sectoral balance sheet developments—suchas in some indicator of reserve adequacy or corporateliquidity—could indicate buildup of liquidity stress inthe same or other sectors.42
Standing central bank facilities, which are ac-cessed at the initiative of banks, provide liquidity tobanks (usually against collateral) and are an essen-tial component of the liquidity infrastructure. On theother hand, a large increase in central bank credit tobanks and other financial institutions—as a propor-tion of their capital or their liabilities—often reflectssevere liquidity (and frequently also solvency) prob-lems in the financial system. Jácome and Madrid(forthcoming) point out that beyond the traditionallender-of-last-resort role of the central bank, whichis supposed to address limited liquidity problems,monetary authorities often get involved in bankingcrisis resolution because they are the most important(if not the only) source of large funds immediatelyavailable.43 This participation usually implies pro-viding liquidity support beyond best practices, in-jecting capital resources (in cash or bonds) to dis-tressed institutions, and financing debt reschedulingand relief to the corporate sector. Monitoring centralbank lending to financial institutions, therefore, canbe important. Notably, however, these types of sup-port are not always easily identifiable in centralbanks’ financial statements, limiting the potentialusefulness of this indicator to recognize banking li-quidity (and solvency) problems.44
The dispersion in interbank rates is a highly rele-vant indicator of liquidity problems and bank dis-tress. Very often, banks themselves first detect prob-lems as they are exposed, or potentially exposed, to
troubled institutions in the interbank market. Highdispersion in interbank rates—measured, for in-stance, by the spread between highest and lowestrates in the market—may signal that some institu-tions are perceived as risky by their peers. As sup-plying banks can control their interbank positionsthrough price and quantitative controls, high-risk in-stitutions may be forced to engage in aggressive bid-ding for deposits. Changes in interbank credit limitsor an unwillingness of some institutions to lend toothers may indicate serious concerns.
Summary Points
Although liquid assets to total assets (the liquidasset ratio) and liquid assets to liquid liabilities remainthe main indicators of bank liquidity, this sectionshows that “indirect” measures are also important andshould be regularly monitored. These include indica-tors of systemic liquidity, such as bid-ask spreads andturnover ratios, central bank lending to deposit-takinginstitutions, and the dispersion in interbank rates(measured by the highest-to-lowest rate spread).
Sensitivity to Market Risk45
Banks are increasingly involved in diversified op-erations, all of which involve one or more aspects ofmarket risk. In general, the most relevant compo-nents of market risk are interest rate and exchangerate risk. Moreover, in some countries, banks are al-lowed to engage in proprietary trading in stock mar-kets, which results in equity price risk. Bank expo-sure to commodity price risk derived from thevolatility of commodity prices varies significantlyamong countries, but is generally relatively small.Interest rate, exchange rate, equity price, and com-modity price risks can be assessed by calculating netopen positions according to the methodology pro-posed by the Basel Committee.46 Measures of sensi-tivity to market risk would include the following:
• The duration of assets and liabilities is gener-ally considered an accurate indicator of sensi-tivity to interest rate risk.47 The greater the du-
21
42See Box 4.1 for further discussion of sectoral balance sheetanalysis.
43Moreover, governments may feel tempted to shift to centralbanks the cost of bank resolution, at least partially, so as to hidethese costs within the central bank balance sheet.
44Such transactions may also have important implications forthe conduct of monetary policy and the financial position of thecentral bank, as described in Jácome and Madrid (forthcoming).
45See Chapter V for a discussion of the stress tests that are usedin measuring sensitivity to market risk.
46See Basel Committee (1997, 1998).47Duration is the weighted average life of an asset or liability
(the weights being the present value of each cash flow as a per-centage of the price of the asset or liability). Duration adjusts ma-turity to account for the size and timing of payments between nowand maturity (e.g., the duration of a zero-coupon bond is equal toits maturity). In general, duration rises with maturity, falls with thefrequency of coupon payments, and falls as the yield rises. Thegreater the duration of a bond, the greater is its volatility. Forworking purposes, duration can be defined as the approximate per-centage change in price for a 1 percent change in yield. A discus-sion of the duration model can be found in Chapter V.
III BANKING SYSTEM
ration or “average” life mismatch between as-sets and liabilities, the greater is the risk. Alter-natively, the average repricing period can beused to assess interest rate risk. The averagerepricing period refers to the average time torepricing for floating rate instruments and the remaining time to maturity for fixed rate instruments.
• The most common measure of foreign exchangeexposure is the net open position. According tothe Basel Committee on Banking Supervision, abank’s net open position in each currency shouldbe calculated as the sum of the net spot position,the net forward position, guarantees, net futureincome and expenses not yet accrued but alreadyfully hedged, the net delta-based equivalent ofthe total book of foreign currency options, andany other item representing a profit or loss inforeign currencies, depending on accountingconventions.
• The starting point for measuring a bank’s equityrisk exposure is its net open position in each eq-uity. Equity derivative positions must be con-verted into notional equity positions (e.g., usingdelta-based equivalents).48
• Indicators of commodity price risk can be con-structed that are similar to those for equity riskby looking at the absolute size of the investmentin each commodity.
Summary Points
This section highlights some of the indicators andanalytical methods used to measure sensitivity tomarket risk. Important indicators include the dura-tion of assets and liabilities, and net open positionsin foreign currencies and equities.
22
48For details on the methodology, see Basel Committee (1998).
Indicators of the health of financial systems shouldnot simply look at the banking sector. Experience
shows that risks to financial system stability can de-rive from developments in nonbank financial inter-mediaries (NBFIs), the corporate sector, households,and real estate markets.
Nonbank Financial Intermediaries
The presence and growth of NBFIs has raisedmacroeconomic and prudential issues, most recentlyduring the Asian crisis. NBFIs—finance companies,collective investment schemes, insurance companies,and others—can build up substantial vulnerabilitiesand risks that often go undetected, partly owing tonontransparent disclosure practices and inadequateoversight. The collapse of NBFIs during the Asianturmoil (e.g., in Korea and Thailand) contributed di-rectly or indirectly to a systemic crisis in the financialsystem. Accordingly, there is a need for a betterawareness of the role of NBFIs in financial systemstability and better monitoring of their condition.49
NBFIs’ Behavior and Vulnerabilities
In many advanced countries, NBFIs already play alarge enough role in the financial system to be con-sidered systemically important, while elsewhere theirrapid growth implies that they may be systemicallyimportant in the near future. NBFIs and banks oftenhave ownership and investment linkages that makeeach subsector vulnerable to adverse developments inthe other. Loss of consumer and investor confidencein NBFIs, even when their size remains relativelyunimportant, can potentially undermine confidencein the entire system. Moreover, the systemic risksarising from a particular class of NBFIs—the highlyleveraged financial institutions—were highlighted by
market turmoil following the near-failure of a largehedge fund in 1998. The size and growth in the oper-ations of NBFIs raises a number of issues relating tothe overall structure and functioning of financial sys-tems, and thus have implications for financial systemstability as well as for monetary and exchange ratepolicy.
NBFIs are typically not subject to the same pruden-tial requirements as banks. Lower (or no) capital ade-quacy requirements increase NBFIs’ vulnerability inthe event of a shock. In addition, differential treatmentmay produce regulatory arbitrage and cause NBFIs togrow at the expense of banks, thus potentially increas-ing the vulnerability of the system (since NBFIs maypotentially invest in riskier projects without the com-mensurate increase in necessary provisions and re-serves). Preferential prudential treatment also de-creases NBFIs’ cost of funds and potentially allowsthem to offer higher funding rates than banks, henceattracting funds away from banks.
Competition between banks and nonbanks on theliability side is of particular concern when NBFIscan issue short-term financial instruments that canrapidly convert liabilities into means of payment.The existence of such quasi-deposits affects mone-tary operations since it may lead to an underestima-tion of money demand and a change in the moneymultiplier, thus reducing the effectiveness of reserverequirements as a monetary policy instrument andcomplicating monetary programming.50
The lending and funding operations of NBFIs canhave an impact on a country’s external debt, re-serves, and exchange rate if they are carried out inforeign currency on a significant scale. Similarly, infinancial systems with relatively thin foreign ex-
IV Other Sectors and Markets
23
49A related issue, which is not explicitly covered in this paper,is that of offshore financial centers and the risks involved in theoperations of these centers through links to domestic financialsystems. See, for instance, IMF (2000e).
50In many countries, due to the nature of the instruments issuedby NBFIs, their liabilities are not included in the narrow mone-tary aggregates (M1 and M2), which typically include the trans-ferable deposit liabilities of the banking sector (mostly commer-cial banks). The liabilities of NBFIs are often included in widermonetary aggregates (M3 and M4), or are not included in mone-tary aggregates at all. In countries with substantial nonbankquasi-deposits, the wider monetary aggregates (M3 and M4) needto be monitored for monetary policy purposes. See IMF (2000f).
IV OTHER SECTORS AND MARKETS
change and securities markets, the transactions ofcollective investment schemes, hedge funds, or secu-rities firms can have a significant impact on the re-serves, exchange rate, and securities prices. Thebuildup or liquidation of large positions can lead tohigh volatility in financial markets. Thus, indicatorsof gross and net positions of NBFIs in foreign ex-change and securities may be important dependingon the size of the positions relative to the overallmarket.
Indicators for Nonbank FinancialIntermediaries
The development of specific FSIs for the NBFIsector would help to monitor, and raise awareness of,potential risks emanating from this sector. Such indi-cators should include the size of the NBFI sector—NBFI assets to total financial assets—to determine itssystemic importance. The size threshold in terms ofsystemic importance would vary from country tocountry depending on the institutional setting, suchas the manner in which NBFIs raise funds from thepublic (and from which segments of the public—small savers or wholesale investors). One way tomeasure relative importance would be to look at theliability side, and especially quasi-deposit liabilities,which are arguably more “systemically sensitive.”The use of indicators such as NBFI assets to GDP isalso revealing. Rapid expansion of credit and accu-mulation of assets in general, and in the NBFI sectorin particular, may indicate the potential for problemsin this sector. Accordingly, indicators of the growth incredit would be important. Another indicator of pos-sible problems relates to overexpansion (and there-fore unhealthy competition), which could be signaledby the growth in the number of NBFIs as well as bydeclining profit margins and/or capital.
Specific FSIs for the NBFI sector—resulting fromthe aggregation of balance sheet and income state-ment data by type of institution—would be useful inhelping to gauge the health of NBFIs and detect theexistence of potential risks. However, work onNBFIs is at an earlier stage than that on banks andmore needs to be done to identify FSIs for the sec-tor.51 These indicators could include capital to assetratios (to measure gearing and capital cushion) or
risk-weighted equivalents if available. Balance sheetor intermediation risk ratios could include liquidasset ratios and sector concentration ratios (to detectexposure to real estate or industrial sectors). NBFIscan be active in international markets or engage inforeign currency lending, making net foreign ex-change exposure to capital another important indica-tor. Finally, the sustainability of the sector might begauged by returns on equity and assets, and other op-erating ratios. Although to some extent similar tothose used for banks, such indicators would need topay due attention to the balance sheet and incomecharacteristics of each subcomponent of the sector—such as finance (and leasing) companies, securitiesfirms, collective investment schemes, and insurancecompanies. In the case of finance companies, for in-stance, indicators need to be adjusted to the basiccharacteristics of receivables (including off-balance-sheet risks) and the mix of funding sources. In thecase of insurance, the indicators need to capture thespecificity of each insurance market (i.e., health,life, property/casualty, and reinsurance).
Summary Points
Recent experience confirms the NBFIs’ potentialsystemic role and the need to monitor their health andvulnerabilities. Data availability remains a key con-straint in this area. Information about the NBFI sec-tor—notably the unregulated entities—is generallydifficult to obtain, assemble, and aggregate in a waythat is consistent and comparable across countries. Al-though indicators exist that can capture the size andimportance of NBFIs in the economy, more researchand analysis is needed to develop a set of FSIs thatcaptures the specificities of these intermediaries.
Corporate Sector
The quality of financial institutions’ loan portfo-lios is directly dependent upon the financial healthand profitability of the institutions’ borrowers, espe-cially the nonfinancial enterprise sector. The key roleplayed by the corporate sector in recent episodes offinancial sector distress is a reminder of the impor-tance of monitoring developments in this sector. Thissection reviews recent literature on firms’ character-istics and behavior that may increase the probabilityof crises. It also reviews evidence in support of theselection of specific FSIs for the corporate sector.
Corporate Behavior and Vulnerability
Recent theoretical and empirical work on the cor-porate sector and financial distress has looked athow firms respond to macroeconomic shocks, and
24
51The Financial Stability Forum recently recommended disclo-sure of a series of indicators for securities firms, insurance com-panies, and leveraged investment funds, in addition to banks.These included indicators of market risk, funding liquidity risk,and credit risk, as well as information of the nonlife insurancesector. These indicators are aimed at disclosure at the individualinstitution level. The Forum recognizes the need for further devel-opment of risk assessment concepts and methods in this area. SeeFinancial Stability Forum (2001).
Corporate Sector
how this response in turn affects financing and in-vestment decisions of the corporate sector and,through those decisions, the macroeconomy. Thevariables identified in some of this work are listed inTable 4.1. Much of this literature has focused on twoaspects that are key to ensuring the repayment ofcorporate obligations: corporate net worth and cashflow, and marketable collateral. The “financial accel-erator” approach stresses the role of microeconomicrigidities that occur due to informational asymme-tries, where corporate net worth plays the role of col-lateral and helps to overcome incentive problems inlending. In these studies, macroeconomic shocks af-fect the real sector through corporate balance sheeteffects.52 The “collateral” approach stresses macro-economic rigidities in the form of underdeveloped
domestic financial markets and lack of internation-ally acceptable collateral. In these studies, crisis sus-ceptibility is due to a shortfall in collateral needed toget domestic and foreign financing.53
Through the two channels of corporate balancesheets and collateral, the corporate sector is exposedto shocks such as a fall in asset prices, an increase ininterest rates, or a slowdown in growth. Levels ofcorporate leverage influence the ability of firms towithstand these shocks, as empirically documentedin a recent study by Kim and Stone (1999). Themore leveraged and the less liquid the corporate sec-tor, the more vulnerable it is to shocks. Large corpo-rate debts denominated in foreign currency alsomake firms vulnerable to real devaluations, whichaffect their net worth and can render the economy fi-nancially fragile.54
25
52See for instance Bernanke and Gertler (1995), Krugman(1999), Kim and Stone (1999), and Gertler, Gilchrist, and Na-talucci (2000). For a review of this literature, see Stone andWeeks (2001).
53See for instance Kiyotaki and Moore (1997), and Caballeroand Krishnamurthy (2000).
54Céspedes, Chang, and Velasco (2000).
Table 4.1. Determinants of Corporate Vulnerabilities
Financial Accelerator Models1 Collateral Models1_________________________________________________________ ___________________________
BG(95) K(99) KS(99) GGN(00) KM(97) CK(00)
Structural vulnerabilitiesAccess to nonbank financing XCorporate governance XLegal infrastructure X
Macroeconomic shocksInterest rate changes X X XExchange rates changes XCapital flows/liquidity X X XDomestic demand X XTerms of trade X XDeflation X XProductivity X
Corporate sector indicatorsLeverage X X X X X XForeign debt X X XShort-term or floating-rate debt X XLiquid assets XMarketable collateral X X X XAsset prices X X X X XCurrent cash flow X XDividends X
Banking indicators2
Availability of credit X XCost of credit X
1BG: Bernanke and Gertler; K: Krugman; KS: Kim and Stone; KM: Kiyotaki and Moore; CK: Caballero and Krishnamurthy; GGN: Gertler, Gilchrist andNatalucci.
2Some studies look specifically at bank vulnerabilities (capital adequacy and liquidity), which would feed into corporate vulnerability through the chan-nels of availability (rationing) and cost of bank credit.
IV OTHER SECTORS AND MARKETS
Prolonged distress in the corporate sector nega-tively affects firms’ repayment capacity and credit-worthiness, and results in a worsening of bank assetquality and ultimately higher NPLs. Gray (1999) ex-amines how NPLs directly link corporate sector vul-nerability to financial sector vulnerability. In hismodel, reduced corporate equity as a result of macro-economic shocks results in an increase in NPLs, withthe size of the increase depending on the compositionof corporate debt (i.e., the importance of nonbank-financed debt). Nonpayments may be triggered byilliquidity, insolvency, or a collapse in credit culturein situations of systemic distress—a behavior knownas “strategic defaulting.” Since banks often bookNPLs after a period (often three months) of nonpay-ment, direct indicators of corporate health such ascash flow adequacy can be more timely indicators ofbanking problems than NPL figures.
More recent IMF efforts in this area point to astrong link between macroeconomic developmentsand corporate leverage, and between corporate lever-age and the probability and intensity of financialcrises.55 Stone and Weeks (2001) analyze the finan-cial crises of the 1990s by dividing them into twostages: pre- and post-crisis equilibria. The first stageis a long buildup of balance sheet stress rooted inpoor corporate governance, financial deepening, ac-celerated capital inflows, and, in many cases, over-heating of the economy. These tensions leave theeconomy susceptible to financial shocks. A shock—usually external—triggers a sudden crisis, or a shiftfrom a stable equilibrium into a new contractionaryequilibrium. Empirical results show that both corpo-rate leverage and aggressive bank lending can be sig-nificant indicators of the probability of a crisis. Cor-porate leverage, the availability of nonbankfinancing, and the legal environment are key ele-ments in determining the intensity of crises. This hasclear policy implications—the need to pay attentionto corporate sector balances as well as to the breadthand quality of the domestic financial system.
Corporate Indicators
The literature reviewed above points to the impor-tance of specific balance sheet and cash flow informa-tion—notably, data on leverage, interest cover, liquid-ity, and profitability—as indicators of corporate sectorsoundness. Recent studies have examined specificmeasures of corporate vulnerability, as summarized inTable 4.2. The table also includes indicators from a re-view of corporate rating methodologies.56
Excessive corporate leverage increases the vulner-ability of corporate entities in the event of a shockand may impair their repayment capacity. A knownindicator is total debt to equity, also called the gear-ing (or leverage) ratio. In general, indicators of cor-porate leverage can have total debt, total liabilities,or total long-term debt as the numerator; and equity,capital (defined as debt plus equity), or assets as thedenominator.
Standard and Poor’s (2000) discusses the limita-tions of some of these indicators. First, traditionalmeasures focusing on long-term debt have lost muchof their significance since companies rely increas-ingly on short-term borrowing. Second, the ratiossuffer from difficulties in estimating the true eco-nomic value of assets.57 Third, off-balance-sheetitems should be factored into the analysis of lever-age, such as operating leases, guarantees, contingentliabilities, and securitization (e.g., of accounts re-ceivables). Fourth, the type of equity matters. For in-stance, many preferred stock issues have characteris-tics that make them quasi-debt in nature—such asfixed redemption dates, fixed dividend requirements,and (on occasion) higher redemption values. Fifth,broad indicators such as the ratio of total liabilitiesto total assets do not provide a good measure of riskof default, but are rather a proxy of what is left forthe shareholders in case of liquidation. Sixth, corpo-rate debt-equity ratios depend on countries’ legal andaccounting definitions of debt and equity, and arenot easily comparable across countries.
Profitability is a critical determinant of corporatestrength, affecting capital growth, attraction of equity, operating capacity, ability to withstand ad-verse events, and, ultimately, repayment capacityand survival. Sharp declines in corporate sector prof-itability—for example, as a result of economic de-celeration—may serve as a leading indicator of fi-nancial system distress. Care should be taken toidentify cyclical movements in corporate sectorprofitability, however. The most significant measuresof profitability include (1) return on equity (earningsbefore interest and tax (EBIT) to average equity); (2)return on assets (EBIT to average assets); and (3) op-erating income to sales (EBIT to sales). Although theabsolute levels of these ratios are important, it isequally important to focus on trends. Moreover,profitability information is particularly affected bymarket structure—that is, industry characteristics,
26
55There is a vast literature on the determinants of corporateleverage and its relevance to probability of financial distress andcorporate credit ratings. See Rajan and Zingales (1995).
56See Fitch IBCA (1998), and Standard and Poor’s (2000).
57Methods to mark asset values to market can be used, althoughthey have shortcomings even at the individual firm level, and arehardly feasible at the aggregate level. Similarly, market values ofequity are sometimes used, but these also have shortcomings asstock prices have a short-term bias, are correlated to alternativeinvestment opportunities and are highly volatile, and may ulti-mately not reflect a company’s ability to service its debt.
Corporate Sector
competitive environment, and pricing flexibility—implying that the analysis of these indicators wouldbe best performed at the subsectoral level.
Earnings are also viewed in relation to a com-pany’s burden of fixed charges. Cash flow adequacyis often measured by the coverage ratio—earnings tointerest expenses (interest payable less interest capi-talized).58 Earnings can be measured before interestand taxes (EBIT); or before interest, taxes, deprecia-tion, and amortization (EBITDA).59 This ratio mea-sures the risk that a firm may not be able to make thepromised fixed payments on its debts, and can re-flect the closeness to corporate financial distress bet-
ter than corporate leverage. In addition to the interestcoverage, other measures are often considered im-portant, such as the debt payback period (total debtto discretionary cash flow). All these ratios are par-ticularly critical in the analysis of corporate financialstrength in distress situations.60 A description of themain cash flow items is contained in Table 4.3.
Corporate liquidity determines the sector’s abilityto carry out business without endangering creditquality. Liquidity ratios include: (1) the currentratio—current assets (cash and accounts receivables)to current liabilities (debt and other liabilities com-ing due within a year); and (2) the quick ratio or acidtest—current assets minus inventories to current lia-bilities. Notably, the current ratio is influenced byinventory valuation methods, which make interna-tional comparison particularly problematic.
Assessments of corporate sector vulnerabilityshould also measure the ratio of corporate foreigncurrency debt to total debt, since significant currencydepreciation could put severe pressure on those
27
Table 4.2. Indicators for the Corporate Sector1
BPS (00) SW (01) Fitch S&P
LeverageTotal liabilities to equity XTotal debt to total assets XTotal debt to equity XTotal debt to capital XLong-term debt to equityTotal debt to market value of
equity X XTotal debt plus off-balance-sheet
liabilities to capital plus off-balance-sheet liabilities X
ProfitabilityReturn on equity XReturn on assets XOperating income to sales X X
Cash flow adequacyEBIT to interest expenses X XEBITDA to interest expenses XDebt payback period X
LiquidityCurrent ratio XQuick ratio
1BPS: Barnhill, Papapanagiotou and Schumacher; SW: Stone and Weeks; Fitch: Fitch IBCA; S&P: Standard andPoor’s.
58Interest expenses should be calculated to include leasingcosts. Ideally, earnings should be adjusted to arrive at cash flowavailable for operations (e.g., by amending for noncash provi-sions and contingency reserves, asset write-downs that do not af-fect cash, and blocked funds overseas). See Moody’s (1998).
59A recent study by Moody’s (2000) concludes that the use ofEBITDA interest coverage ratios can be misleading, notably asthey (1) overstate cash flow in periods of working capital growth;(2) can be manipulated through aggressive accounting policies; (3)do not consider the amount of required reinvestment; and (4) saynothing about the quality of earnings. EBITDA, however, remainsa legitimate tool for analyzing poorly performing corporations.
60Ratios such as funds flow from operations to total debt (andother off-balance-sheet liabilities) are more meaningful in assess-ing long-term profitability trends of corporate entities and sectors.
IV OTHER SECTORS AND MARKETS
banks whose clients have large foreign exchangedebt-servicing burdens. This applies to both firmsborrowing domestically in foreign currency andfirms turning to foreign forms of financing.61 Simi-larly, the ratio of foreign liabilities to foreign assetsof the corporate sector may also be useful as foreigncurrency debt that is not matched with foreign cur-rency earnings also increases the vulnerability of thecorporate sector.62
Despite the growing theoretical and empirical liter-ature on the subject, aggregate corporate sector bal-ance sheet and income data remain limited at best, inquantity and timeliness—a fact that in itself limits thescope of research. As regards quantity, the data areusually available—at the disaggregated level—forlisted companies only. This may bias the sample sig-nificantly, although the direction of this bias is theo-retically ambiguous, and empirically it is likely to dif-fer from market to market. As regards data quality,accounting quality determines the extent to which thepicture determined by corporations’ accounts, individ-ually or at the aggregate level, can be relied upon as anaccurate and comparable indicator of corporatestrengths and weaknesses. Accounting quality can beassessed by looking at a country’s accounting policies,including consolidation principles, income recogni-tion rules, valuation (including inventory pricing) anddepreciation methods, and goodwill treatment.
Summary Points
A number of key indicators of corporate soundnessemerge from this section. They include total debt toequity as a measure of leverage; EBIT to average equity as a measure of return on equity; EBIT to inter-est and principal payments as a measure of debt-service coverage; and corporate foreign currency debtto foreign current assets as a measure of vulnerabilityto foreign exchange risk. Measures of liquidity, suchas the current and quick ratios, can also be useful inassessing corporate vulnerabilities.
Household Sector
Although banks are often more exposed to compa-nies than to households, the size of the exposure tothe latter can be substantial, particularly in the mostadvanced economies. Furthermore, household con-sumption behavior has a strong effect on banks’main credit customers—the corporate sector—andhousehold asset allocation decisions can impactbank liabilities and asset prices. This section reviewsthe literature on linkages between the household sec-tor and financial intermediaries and markets, anddiscusses recent approaches to monitoring house-hold developments that are relevant for the assess-ment of financial system soundness.
Household Behavior and Vulnerability
Two types of models are most relevant for ex-plaining the linkages between households and the fi-nancial system—those that analyze household sav-ing and borrowing decisions and those that explaintheir asset allocation.63
Household consumption and saving decisions areinfluenced by the availability of bank credit. There isan extensive empirical literature on the importance ofcurrent disposable income and household debt to fu-ture consumption. A recent study by Murphy (1998)finds that in the United States the ratio of debt serviceto income is a statistically significant predictor of fu-ture consumer spending and income growth: a highdebt-service ratio sustained over several quarters pre-cedes reductions in the rate of growth of consumptionand income (although with an elasticity of signifi-cantly less than one). He argues that this can be ex-plained by a reduction in bank lending in response to
28
Table 4.3. Cash Flow Summary
Funds flow from operations
+ (–) Decrease (increase) in noncash current assets
– (+) Decrease (increase) in nondebt current liabilities
= Operating cash flow
– Capital expenditure
= Free operating cash flow
– Cash dividends
= Discretionary cash flow
– Acquisitions
+ Asset disposals
+ (–) Other sources (uses) of cash
= Prefinancing cash flow
Source: Standard and Poor’s (2000).
61In some cases, strengthened financial sector supervision maycreate relative incentives for firms to borrow abroad, therebyshifting foreign exchange exposure-related vulnerabilities to thecorporate sector.
62In the case of foreign exchange (as well as interest rate) expo-sures, swaps, caps, and hedges are tools that can significantly af-fect corporate financial positions.
63Household consumption patterns can also be a leading indi-cator of corporate and financial sector distress. For example, thereis some evidence that consumers react at an early stage to macro-economic shocks such as higher interest rates, notably in their de-mand for housing and consumer durables. See Bernanke andGertler (1995).
Real Estate Markets
a rise in household debt burden that directly affectsconsumption (especially of durable goods) and indi-rectly affects income growth. Empirical evidence onthis point, however, is not conclusive.64
Financial institutions typically react to changes inmacro and household financial variables (such asearnings, collateral, and debt levels) by restrictingaccess to credit if these variables signal changes inthe borrowers’ capacity to repay their obligations.Liquidity constraints may affect the composition ofhousehold balance sheets, especially the leveragedpurchases of consumer durables and residentialhousing, and the preference for liquid assets. This, inturn, may affect the corporate sector—as householdconsumption has a large impact on domestic output,and household participation in the equity marketmay affect the ability of firms to raise funds for in-vestment. Thus, banks are exposed to households di-rectly, through their repayment capacity on con-sumer and mortgage loans, as well as indirectly,through the effect that household consumption deci-sions have on corporate sector financial strength.
Banks are also exposed to households through theliabilities side of their portfolios. The decision to de-posit savings in financial institutions is part of theportfolio allocation behavior of households, which isa function of the supply and demand of assets basedon current wealth, and of households’ risk propen-sity.65 Household deposits typically provide bankswith the most stable and low-cost source of funding.Since, in principle, these funds may be withdrawnrapidly, the stability of household deposits is veryimportant given the often substantial maturity gapthat arises from banks’ intermediation function (i.e.,channeling short-term savings into longer-term in-vestment). Stability is a function of the confidencethat households have in the individual institutionsand the financial system as a whole. Although directmeasures of consumer confidence in the financialsector are difficult to identify, indirect measures thatfocus on bank liquidity are available, such aschanges in the level or volatility of savings depositsor changes in the interest rates paid.66
Household Indicators
The vulnerability of households may be assessedthrough the use of sectoral balance sheets, flow of
funds, and other macro and microeconomic data.Table 4.4 presents indicators used and approachestaken by three central banks in monitoring develop-ments in the household sector. These indicators tendto follow from the variables highlighted by the liter-ature as important: wealth, current income, debt, andasset prices. Indicators include debt to GDP or to as-sets, and debt burden (principal and interest pay-ments) to disposable income. Some of the other indi-cators used follow from credit risk analysis (seeChapter V), such as the ratio of debt to collateralvalue (or loan-to-value ratio), which is important formortgage loans.
Most of the analysis of the vulnerability of thehousehold sector is primarily focused on direct bankexposure and thus relies heavily on debt-servicingcapacity. However, the other indicators on assetcomposition highlight the concern that householdsmay be significantly exposed to equity and real es-tate price movements.
One potentially useful approach in looking at thelinkages between households, firms, financial insti-tutions, and the macroeconomy at the empirical levelis that of using national sectoral balance sheets (seeBox 4.1). Sectoral balance sheets permit the exami-nation of a comprehensive set of linkages betweenhouseholds, firms, financial institutions, the publicsector, and the rest of the world, and can potentiallyhelp to better understand the complex interactionsamong these sectors. This approach, however, is lim-ited by data availability.
Summary Points
Due to the direct and indirect exposure of finan-cial institutions to the household sector, indicatorsof household financial strengths and vulnerabilitiesare important in assessing financial institutions’soundness and resilience to shocks. Key indicatorsof financial strength of the household sector in-clude household indebtedness to GDP and house-hold debt burden to income. These indicatorsshould be complemented with detailed data on fi-nancial institutions’ credit outstanding to thehousehold sector.
Real Estate Markets
In many countries, unbalanced real estate develop-ments have contributed to financial sector distress.Notwithstanding their importance from a macropru-dential standpoint, analyses of developments in thereal estate markets are rarely undertaken on a sys-tematic basis. This section presents some evidenceon the link between macroeconomic developments
29
64For instance, a recent paper by De Ruiter and Smant (1999)finds that in the Netherlands high debt ratios do not slow durablesconsumption.
65In particular, portfolio diversification reduces risks to house-hold income. This underscores the need to monitor the composi-tion of household balance sheets, not just net wealth, to bettergauge vulnerabilities.
66For a discussion of bank liquidity indicators, see Chapter III.
IV OTHER SECTORS AND MARKETS
and real estate prices and between the real estate sec-tors and financial sector soundness.
Macro-Financial Linkages
Rapid increases in real estate prices—often fueledby expansionary monetary policies or by large capitalinflows—followed by a sharp economic downturncan have a detrimental impact on financial sectorprofitability and health, by affecting credit qualityand the value of collateral. The literature on real es-tate market developments can be categorized intothree groups: papers that explain how real estate mar-
kets function in normal circumstances, those thatfocus on the emergence of price bubbles, and thosethat study the (over)exposure of the financial systemto risky real estate loans.
In well-functioning markets, the price formationprocess should equilibrate supply and demand, andthe fundamental equilibrium price would be theprice at which the existing stock of real estate equalsreplacement costs.67 If the price of real estate isabove (below) the replacement cost, construction
30
Table 4.4. Household Indicators Used in Norway, Sweden, and the United Kingdom
Norway
National accounts and financial market dataWage income and disposable income trendsSavings trends Interest expenses to cash incomeInterest expenses to interest income excluding interest on insurance claimsGross loan debt to disposable incomeGross loan debt to gross claims excluding insurance claimsGross loan debt to value of housing wealthComposition of financial assets (deposits, securities, and equities)Composition of interest-bearing debtNet investment in financial assets to disposable income trends
Micro data Interest and debt burdens classified by age, socioeconomic conditions (e.g., employment status), and income categories
Sweden
Risk buildup indicatorsLending to households by category of financial institutionLending by type of creditLending by income decileHousing pricesEmployment and incomeStock prices
Repayment ability indicatorsWages, real disposable income, and wealthInterest cost after tax to disposable incomeHousehold debt to disposable income
United Kingdom
Leverage indicatorsTotal and mortgage interest payments to personal disposable incomeTotal lending (debt stock) to the household sector to residential and financial wealthSecured and unsecured debt to residential and financial wealthNet financial wealthReal household income
Financial distress indicatorsPersonal bankruptciesMortgages in arrears to total mortgages
Potential threat indicatorsHousing prices, including asset bubbles as measured by the ratio of housing prices to earnings Interest rate changesUnemployment
Source: Begum, Khamis, and Wajid (forthcoming).
67Di Pasquale and Wheaton (1996).
Real Estate Markets
will increase (decrease) until the market regainsequilibrium—that is, the adjustment of stock of realestate takes place in the construction sector. An in-crease in the number of investors, the existence ofoptimistic investors, an increase in the number of of-fice workers, or other similar events can trigger anoutward shift of the demand curve, and the newequilibrium will move to a higher level. In well-functioning markets, real estate cycles will be drivenby normal economic cycles, due to the changes inexpected growth in income, real interest rates, taxes,future demographic profile, etc.68
Growth in construction in excess of income growthand other fundamentals may be related to price bub-bles that develop from credit booms. A number ofmechanisms can trigger or amplify the appearance ofcycles and bubbles in real estate markets, some dueto nonfinancial characteristics of real estate markets,
others due to the lending behavior of banks.69 Theseinclude (1) fixed supply and the behavior of investorswilling to purchase property in periods of risingprices; (2) construction time lags in the adjustment ofproperty supply to increasing demand; (3) the impactof rising real estate prices on loan collateral values;(4) moral hazard in the form of over-guaranteed andunder-regulated financial institutions, leading to riskybehavior and high investment and asset prices; (5) in-creased competition for financing risky real estateprojects subsequent to financial liberalization; (6) ris-ing real estate prices resulting in greater lending to
31
Box 4.1. Sectoral Balance Sheet Analysis1
Sectoral balance sheet analysis is potentially usefulin assessing vulnerabilities in the financial system fromstresses elsewhere in the economy. Balance sheetanalysis uses sectoral breakdowns in the national ac-counts for the following sectors: households, nonfinan-cial corporations, nonbank financial institutions, bank-ing institutions, the government, and the rest of theworld. In addition to identifying the specific asset/lia-bility components that may be particularly vulnerableto fluctuations in asset prices, interest rates, and in-come flows, the balance sheets of all sectors taken to-gether can help to clarify the linkages among sectorsthat could transmit financial disturbances. A useful, al-beit partial, framework for such analysis is provided bythe flow of funds accounts.2
A number of countries have started to utilize sectoralbalance sheet data in their assessments of financial sta-bility. The approach used combines macro, micro, andsometimes a market view of the sectors, focusing onthe risk posed to the banking sector by the enterpriseand household sectors. The macro approach uses sec-toral balance sheet and flow of funds data includingloan growth to enterprises, enterprise debt and interestrate burdens, sectoral trends in enterprise profits, profit
margins and dividend payments, debt and interest bur-dens of households, financial wealth of households,and real income of households.
Although there is some merit in using sectoral bal-ance sheets to form judgments about buildup of finan-cial stress in some sectors and their implications forother sectors, there are also important limitations.Specifically, transactions based on balance sheet dataare unlikely to provide an accurate picture of assetprice movements and would not capture off-balance-sheet items. A more robust analysis should begrounded in a comprehensive macro model specifyingthe behavioral features of assets markets and derivingsectoral balance sheets consistent with the flows andprices determined by the model.
More generally, the usefulness of this approach isconstrained by the very limited availability of data. Inthe UN system of national accounts, sectoral balancesheet data are available only for two industrializedcountries. Flow data on capital finance accounts bysector exist for only 15 countries (of which 12 are in-dustrialized), either from UN or OECD sources. Infor-mation on sectoral balance sheets from nationalsources is limited, and generally focused on banks andother financial institutions.3
1This box is based on Begum, Khamis, and Wajid (forth-coming).
2Flow of funds accounts link savings and investment in thenational accounts with their associated lending and borrowingactivities. Because they provide information on changes in as-sets and liabilities, these accounts are an important comple-ment to balance sheet data.
3As part of the IMF’s ongoing work to facilitate the imple-mentation of internationally agreed statistical standards, theQuarterly National Accounts Manual provides guidance tocountries in the compilation of national accounts. See Bloem(2001).
68IMF (2000a), in particular Chapter III on “Asset Prices andthe Business Cycle.”
69Real estate markets are characterized by heterogeneity, con-sisting of a series of geographical and sectoral submarkets thatlack a central trading market. No two properties are identicaland information on market transactions is often limited and notgenerally available. Also, real estate markets are typically char-acterized by infrequent trades, a negotiated pricing process,large transaction costs, and very rigid supply. In contrast tostock markets and other financial markets there is, therefore, noclear market price.
IV OTHER SECTORS AND MARKETS
the real estate sector, as a bank’s own holdings of realestate—hence its capital—increase in value.
The arguments above suggest that the higher theexposure of banks to real estate, the more amplifiedthe cycles in real estate markets. Still, banks seem tounderestimate the risks associated with high expo-sure to this sector due to the following factors:
• Disaster myopia or low frequency of shocks:Real estate cycles are often long and a wholegeneration may have passed since the last severedownturn in prices. During a boom period, prof-itability in terms of (expected) returns is highand the risks are underestimated.
• Inadequate data and weak analysis: Even underthe best circumstances, it may be difficult to esti-mate the present value of a real estate project. Itwill depend, among other things, on projectedrents, discount rates, anticipated inflation, loss invalue due to depreciation, and vacancies due tothe development of competing projects. In manycountries, data on building permits, new con-struction contracts, rents, market prices, and va-cancy rates are not readily available or are diffi-cult to obtain and verify.
• Perverse incentives or moral hazard resultingfrom a combination of highly leveraged real es-tate developers and asymmetric information maylead to bank financing of real estate projects thatare riskier than if they were financed largelythrough equity—as developers will initiateriskier projects when they can shift most of thedownside risk to banks. This is more likely tooccur in economies with highly leveraged banks,poorly designed financial safety nets and weaksupervision, and/or weak corporate governance.
Empirical analysis so far on the link between realestate market developments and banking distress hasbeen limited. A recent IMF study reviews the experi-ence of 13 cases of extreme price swings in the realestate market associated with increased banking sec-tor vulnerability.70 The authors find a strong correla-tion between real estate price developments andcredit growth: real estate booms are generally pre-ceded or accompanied by a boom in banking creditto the private sector, and busts by a strong contrac-tion of credit growth. This supports the notion thatthe availability of financial resources is one of thedriving forces of prices in this market.
The empirical results also show that in most of thecases studied, real estate prices surged sharply andbegan falling prior to the beginning of financial dis-
tress.71 On average, residential real estate prices cor-rected for inflation rose by more than 20 percent fromseven to two years before the beginning of financialdistress; then fell by more than 15 percent two yearsprior to the beginning of financial distress; and thencontinued to fall at least until the peak of the crisis. Asimilar pattern can be observed for commercial prop-erty prices in most countries for which there are data.For the few cases where data on stock prices of realestate companies are available, there is a tendency forthese prices to fall drastically before a banking crisisand to bottom out or stabilize by the onset of crisis. Alogit-probit analysis of episodes of banking distressand real estate price developments confirms that adownturn in residential real estate prices increases theprobability of banking distress.72
Case studies highlight the role that shocks to out-put and monetary conditions, combined with weakcapital positions of banks, can play in increasing thevulnerability of the financial system to real estatemarket price swings. However, the lack of high fre-quency data on real estate markets and poor data oncredit exposure (and NPLs) to the real estate sectorfor most of the countries has so far prevented morethorough analyses.
Real Estate Indicators
Ideally, a range of indicators should be analyzedto get a sense of real estate market developments(demand, supply, prices, and links to the businesscycle) and to assess financial sector exposure to thereal estate sector (Table 4.5).
To determine bank exposure to the real estate sec-tor, it is important to have information on the size ofthe credit exposure and its riskiness. To accomplishthe latter, it may be necessary to distinguish betweendifferent types of real estate-related loans, whichmay have very different risk characteristics. For ex-ample, it would be useful to distinguish betweenlending: (1) for the purpose of investment in (pur-chase of) commercial real estate; (2) for the purposeof investment in residential real estate, includingmortgages; (3) for the purpose of real estate con-struction or, more generally, lending to constructioncompanies; and (4) collateralized by real estate. Thedegree of risk involved could be estimated by the av-erage probability of default as well as the default re-covery rate for the different types of debt, as in Barn-hill, Papapanagiotou, and Schumacher (2000).73 A
32
70Hilbers, Lei, and Zacho (2001).
71Cross-country comparisons of real estate developments, how-ever, are complicated by differences among countries in financingstructure, tax structure, and the use of real estate as collateral.
72Commercial real estate prices were not analyzed due to thescarcity of data.
73See Chapter V for details.
Real Estate Markets
critical aspect of this analysis is the ratio of loan tovalue (where value is equal to market value of equityfor firms, and to housing value for mortgages andcollateralized loans). Default is likely to occur whenthe loan to value ratio exceeds a threshold that canbe estimated from historical series. An alternativewould be to use the NPL ratio as the expected de-fault rate for the different types of loans.
A major obstacle to in-depth analyses of real es-tate markets is the availability of data, in particularfor emerging markets. No major international data-base provides data on real estate prices or other in-dicators of developments in real estate markets. TheBank for International Settlements (BIS) maintainsa small database with annual residential and com-mercial property prices for 17 industrialized coun-tries, but only part of the data is publicly available.In some advanced and emerging markets, real estate
indicators are available from commercial sources,generally focusing on the largest cities and coveringprices (sales and rentals) as well as current and fore-cast supply, demand, and vacancy rates. Sectoralbreakdowns cover industrial, commercial, retail,and residential space. These data are heterogeneous:differences exist with respect to timeliness, assetsconsidered, quality, and coverage.74 Finally, finan-cial sector data on the exposure of the financial sys-tem to real estate markets are also difficult to obtain,
33
74In particular, some commercial property indices cover onlyoffices, while others include retail property as well as propertyused for production and storage. There are also technical differ-ences, such as the weights used to combine different localitiesand qualities of property, as well as whether the mean or the me-dian price in the sample is chosen.
Table 4.5. Real Estate Indicators
Indicator Definition and measurement issues
PricesReal estate price index In equilibrium, price would equal cost; thus, this price index can be compared to
the construction cost index to assess the incentive to build. Subindices that reflect developments in subsectors (commercial, industrial, and residential) orgeographical areas are also useful in assessing exposure to real estate.
Construction cost index This index could proxy for fundamental prices under certain conditions;however, market imperfections and inclusion of other nonconstruction costs in the index often drive replacement costs away from fundamental prices.
Rents In principle, the present discounted value of future rents should equal the price of the property. However, the path of rents may be difficult to predict and rentsmay include other services, such as utilities, which drive the discounted value oftoday’s rents away from fundamental prices.
Land prices Since land is in fixed supply, speculation will be reflected in rapidly rising land prices at rates higher than construction costs.Thus, land prices could be indicators of the development of bubbles.
Supply and demandProperty stock available Current supply of property.
Vacancy or occupancy rates Gap between demand and supply.
Number/value of new buildings Additions to current supply.
Number/value of sales Indication of current demand. In particular, the number and value of sales in a given period divided by the stock of supply at the beginning of the period provides an indicator of the tightness of the market.
Stock price indices The stock price of real estate firms should equal the present discounted valueof profits; changes in the index could signal changing perceptions on sectorprofitability.
Exposure to the real estate sectorLoans outstanding While this may give a broad indicator of exposure, different types of real estate
loans (e.g., residential mortgages, commercial mortgages, loans to constructioncompanies, other loans collateralized by real estate) may have differentcharacteristics.
Loan-to-value ratio This ratio is an important indicator of the probability of default.
NPLs This indicator could act as a proxy for the expected default rate.
IV OTHER SECTORS AND MARKETS
and the quality and definition of such indicatorsvary significantly.
Summary Points
A number of key indicators of financial institu-tions’ exposure to real estate markets emerge fromthis section. They include the loans outstanding tothe real estate sector to total loans, possibly supple-
mented by data on nonperforming loans to the sector (as a share of total real estate loans). Theusefulness of these data, however, is often limitedby the fact that different types of real estate-relatedloans have very different risk characteristics. In addition, it is important to monitor developments in real estate markets, particularly with regard to prices, for both residential and commercial realestate.
34
H aving discussed specific FSIs, it is important tolook at methods to analyze them. A variety of
methods are available to analysts to derive from FSIsconclusions about the stability of financial sys-tems—from simple ratio analyses to more complexmacro and microeconomic modeling. The focus ofthis chapter is on one particular method—stress test-ing—originally developed as a bank risk manage-ment tool, but the object of growing interest for itspotential application to analyses of strengths andvulnerabilities at the level of the system as an aggre-gate, as opposed to the individual institutions.
Defining System-Wide Stress Tests
Stress testing is a key element of macroprudentialanalysis that helps to monitor and anticipate poten-tial vulnerabilities in the financial system. It adds adynamic element to the analysis of FSIs—that is, thesensitivity, or probability distribution, of FSI out-comes in response to a variety of (macroeconomic)shocks and scenarios.75 By anticipating the potentialimpact of specified events on selected FSIs, stresstests also help to focus on financial system vulnera-bilities arising from particular banking system,macroeconomic, and sectoral shocks.
Stress testing, as used in the context of assess-ments of financial system stability, is a generic termthat refers to a range of statistical techniques. Stresstesting measures are used to help to identify (1) riskexposures in individual financial institutions; and (2)system-wide risk exposures that potentially havesystemic consequences for the financial system.
Stress testing is a process encompassing a varietyof techniques that include:
• Sensitivity analysis, which seeks to identify theexposures and likely elasticity of responses of financial institutions to relevant economic vari-ables, such as interest rates, exchange rates,equity prices, etc.
• Scenario analysis, which seeks to assess the re-silience of financial institutions and the financialsystem to an exceptional but plausible economicscenario.
• Contagion analysis, which seeks to take accountin a stressful situation of the implications oftransmission of shocks from individual financialexposures to potential vulnerabilities in the fi-nancial system as a whole.
System-wide stress testing methodologies derivefrom stress tests conducted at the individual institu-tion level. As a result, there are similarities, but alsoimportant differences, between the two techniques.Individual portfolio stress tests aim at assisting inmanaging risks within a financial institution and en-suring the optimal allocation of capital across risk-taking activities.76 A good stress test needs to be rel-evant to the current portfolio, include all relevantmarket rates, encompass potential regime shifts andmarket illiquidity, and consider the interaction ofdifferent risks. Specification issues include (1) thetype of risk or risks to be considered and appropriatemodels to be used; (2) the range of factors to be con-sidered—a single factor sensitivity test or the simul-taneous movement in a group of risk factors as inscenario analysis; (3) the specification of the type ofshock (i.e., whether the shock affects the level,volatilities, and/or correlation of prices), the size ofthe shock, and the time horizon; (4) the assets to beincluded; (5) whether to use historical prices, hypo-thetical prices, or Monte Carlo-simulated prices;77
V Stress Testing of Financial Systems
35
75Commonly tested shocks include a slowdown in economicgrowth, balance of payments shocks, and changes in inflation, in-terest rates, and exchange rates. Equity and security price shocksmay also be important, particularly in the most advanced coun-tries where banks and bank borrowers have significant capitalmarket exposures. It is important to identify shocks that are repre-sentative of past country experiences, or that are justified by ob-served volatilities and correlations in the data.
76The Committee on the Global Financial System (CGFS) hasrecently undertaken a global census of stress tests in use at majorfinancial institutions. See CGFS (2000 and 2001).
77The Monte Carlo method is a stochastic technique that gener-ates prices by performing repeated statistical sampling experi-ments from random numbers. It approximates the market’s price-generating process.
V STRESS TESTING OF FINANCIAL SYSTEMS
36
Figure 5.1. Decision Sequence for Stress Testing
Source: Blaschke, Jones, Majnoni, and Martinez Peria (2001).
Type of risk model
Type of stress test
Market risk(Interest rate risk, exchange
rate risk)Credit risk Other risks
(Liquidity, operational)
Type of shock
Sensitivity(Single factor)
Scenario(Multiple factors simultaneously)
Other(Extreme value, maximum loss)
Type of scenario
Individual market variables (E.g., prices or interest rates) Underlying volatilities Underlying correlations
Core assets to be shocked, peripheral assets to be shocked,size of shocks, and time horizon
Aggregation (across business units, product lines) and repricing of portfolio (marked to market), comparison with present portfolio, adjustment to
present portfolio, and risk management techniques
Historical Hypothetical Monte Carlo simulation
Defining System-Wide Stress Tests
and (6) the aggregation (across business units and/orproduct lines) of the portfolio. Figure 5.1 provides asummary of these specification issues.
Aggregate stress tests are measures of the risk ex-posure of a group of institutions to a specified stressscenario. Their aim is to help to identify structuralvulnerabilities and overall risk exposures in a finan-cial system that could lead to the disruption of finan-cial markets. The emphasis is on potential externali-ties and market failures. Aggregation of stresstesting scenarios has the potential to expose the vul-nerability of a system to simultaneous attempts byfirms to reduce exposures—a cumulative effect onmarket liquidity usually not captured by individualportfolio stress tests. An FSAP stress test is not asimple extension of firm-specific stress test method-ology: (1) there are direct links to macro imbalances,(2) the test looks at system-wide exposures, and (3)the measures must aggregate across product groupsand financial intermediaries.
The type and range of FSIs used in stress tests de-pend on model specification. In simple models, theimpact of changes in a macroeconomic variable(such as a slowdown in GDP, which increases creditrisk) is measured in terms of resulting changes inthe FSI capturing banks’ exposure to that risk (suchas nonperforming loan ratios). In more sophisti-cated models, the impact of shocks is measured interms of changes in capital adequacy ratios. Thechannels through which shocks ultimately affectcapital adequacy would usually involve indicatorsof bank sensitivity to market risks, asset quality andprovisioning, liquidity, and profitability. The resultsof stress tests provide information on the elasticityof a given FSI to macroeconomic shocks, and suchelasticity itself can be used as an indicator of bankvulnerability to individual risks or a combination ofrisk factors.
Stress testing of financial systems presents variousmethodological challenges. It is difficult to decidethe scope of the test and to clearly delineate aggre-gate portfolios that are systemically important. Inpractice, (1) complex interlocking claims among fi-nancial institutions make it difficult to take aggre-gate net positions at face value (i.e., interbank claimsmay represent a small net aggregate position, but thegross positions may be systemically significant); (2)a narrow focus on “systemically important” institu-tions (e.g., banks, if nonbanks do not present a sys-temic threat) may be more manageable, but mayoverlook potential vulnerabilities; and (3) inclusionof foreign-owned banks requires information on thestability of the parent group.
Other challenges include aggregation issues andthe choice of models. Aggregation of stress testsmay be accomplished either by compiling the resultsof stress tests of individual portfolios—which may
not be comparable if the tests were conducted usingdifferent methodologies—or by applying a commonstress test to an aggregated portfolio—which maysuffer from less detailed knowledge of the individualinstitutions. Finally, while the aim of an aggregatestress test is to identify structural vulnerabilities (i.e.,externalities and market failures), the tools for quan-tifying these effects in a simple measure are not yetwell developed.78 Bearing in mind these limitations,approaches do exist that can be used in conductingassessments of financial system soundness.79 Dataavailability and the sophistication of the financialsystem largely determine the approach to be used ineach country with respect to each relevant risk.
The Macro-Stress Test Linkage
The value added of a system-wide stress testcomes from the coordination between an informedforward-looking macroeconomic perspective, ascope that covers all systemically important finan-cial groups, and the ability to detect system-wide ex-posures. Hence, it is important to properly identifymacroeconomic shocks and scenarios. Macro-finan-cial linkages go two ways—shocks can have a nega-tive impact on the health of debtors and creditors,which in turn can have an adverse impact on macro-economic performance. Stress tests, however, focuson the former linkage: the impact of macroeconomicshocks on the health and stability of the financialsystem, and of the banking sector in particular.80
Several studies have analyzed the types of shocksor changes to the macroeconomic environment thatmay be important in increasing the vulnerability offinancial systems. In the aftermath of the Asian cri-sis, a wave of financial sector studies confirmed thatmacroeconomic shocks to output, exports, pricesand the terms of trade, asset price booms, and inap-propriate monetary and exchange rate policies, allresulted in financial pressures and contributed tocrises in financial systems that are inherently frag-ile.81 More recently, Johnston, Chai, and Schu-macher (2000) and Blaschke, Jones, Majnoni, andMartinez Peria (2001) identify a number of shocksthat are typically considered when assessing finan-cial systems’ resilience using stress tests. These in-
37
78For instance, results from the most complex simulation tech-niques may be strongly model-dependent and sensitive to the pa-rameter used.
79For a detailed discussion of these approaches, see Blaschke,Jones, Majnoni, and Martinez Peria (2001).
80In the presence of large, complex financial institutions withinsurance activities, however, attention should also be paid to vul-nerabilities arising from the nonbanking activities of the group.
81For a complete review of this literature, see Evans, Leone,Gill, and Hilbers (2000).
V STRESS TESTING OF FINANCIAL SYSTEMS
clude higher interest rates, foreign exchange devalu-ation, higher inflation, lower growth rates, and unfa-vorable changes in the terms of trade. Blaschke,Jones, Majnoni, and Martinez Peria (2001) reviewthe experience of conducting stress tests in the con-text of the FSAP, and conclude that the impact ofthese types of macroeconomic shocks on the bank-ing system can be significant.
• Credit shocks. Macroeconomic factors that helpto explain the behavior of the NPL ratio includethe real interest rate, the terms of trade, the ex-change rate, GDP growth, and real estate prices.This evidence is based on a limited number ofcountries, however, and should be considered asa starting point in the analysis, rather than a de-finitive relationship.
• Liquidity shocks. Withdrawal of deposits orcredit lines may cause a liquidity shock to finan-cial institutions. Liquidity shocks may also becorrelated to other shocks and indirectly affectbank liquidity. For example, during currency at-tacks, banks may face a liquidity crisis as depos-itors withdraw their funds from the banking sys-tem to purchase foreign currency. Hence,financial institutions may lose access to both do-mestic and foreign exchange funding during acurrency crisis.
• Interest rate shocks. For interest rate risk, shocksmay take the form of a parallel shift in the yieldcurve, a change in the slope of the yield curve,and a change in the spread between different in-terest rates with the same time horizon. Theseshocks typically affect the level of interest rates,but may also increase their volatility and correla-tion. Larger shocks may take place particularlyin countries with illiquid money and capital mar-kets as well as countries that are vulnerable tocurrency crises.
• Exchange rate shocks. Shocks to one or more ex-change rates can affect financial institutions’soundness, depending on their type of exposure.Switches in currency regimes, capital account lib-eralization, increasing use of derivatives, changesin regulation and supervision, and the entry of for-eign banks are all factors that can make a differ-ence in how a financial system reacts to foreignexchange shocks. In countries where domesticlending in foreign currency is allowed, exchangerate fluctuations can have direct as well as indirectimpacts, as some borrowers may be exposed tocurrency risk that translates into credit risk for thelender (see Chapter II).
• Equity price shocks. Particularly in the more ad-vanced countries, banks have significant direct
and indirect exposures to capital markets as a re-sult of their own investment and trading portfo-lios and those of their borrowers. In addition, ad-verse developments in these markets can resultin a marked general economic slowdown and,consequently, lead to deterioration in the creditquality of the loan book. Shocks related to ad-verse capital market developments can be mea-sured by market-based indicators such as stockmarket prices and credit spreads.82
Measurement Techniques
Individual Risk Factor Assessments
Financial institutions face a number of risks—re-lated to changes in credit quality, liquidity, interestrates, exchange rates, and equity and commodityprices. Stress tests typically consider these risks sep-arately. The basic method in assessing the impact ofeach risk factor is to determine the exposure of theportfolio to each risk and then to estimate the changein the market value of the portfolio that may resultfrom a change in the risk factor (i.e., the risk sensi-tivity of the net exposure). This may be relativelystraightforward in the case of spot foreign exchangeholdings, but more complex for holdings that are ex-pected to deliver cash flows over time (e.g., bondsand loans). The following sections briefly describethe different techniques that can be useful in assess-ing individual risk factors.
Credit Risk
Credit risk is the risk of default of a counterpartyor obligor on its contractual obligations (i.e., the riskthat principal or interest on an asset may not be paidin full according to contractual agreements). Mea-suring the credit risk of a portfolio of instruments in-volves estimating the likelihood of default on eachinstrument,83 the extent of losses in the event of de-fault, and the likelihood that other obligors will de-fault at the same time (i.e., the joint distribution orcorrelation of defaults).
Several estimation methods are available, includ-ing from commercial sources.84 Most of these ap-proaches, however, are microeconomic and havelimitations in estimating the impact on the financialsystem of a common external shock and in detecting
38
82For examples of market-based indicators for the UnitedStates, see Nelson and Passmore (2001).
83For instance, the default mode approach uses an average de-fault probability and the mark-to-market approach uses a defaulttransition matrix based on the borrower’s credit rating.
84Theses include J.P. Morgan’s Creditmetrics, Credit Suisse’sCreditRisk+, and KMV’s Credit Monitor Model.
Measurement Techniques
elements of systemic risk. A proper specification ofthe impact of macroeconomic factors on financial in-stitutions would enable an analysis of differentsources of credit risk in countries at different levelsof economic development, of different sizes, andwith different financial structures.
One approach that helps to assess the systemic im-pact of macroeconomic shocks is the nonperformingloan (NPL) approach.85 It uses time series of NPLsfor homogenous groups of banks or borrowers as thedependent variable in a regression using macroeco-nomic factors as independent variables—such asnominal interest rates, inflation, GDP growth, andterms of trade. The coefficients of the regressionprovide an estimate of the sensitivity of bank bor-rowers to the relevant macroeconomic and financialrisk factors. This approach also permits dynamicanalyses of short-run and long-run (equilibrium) ef-fects—for instance, by using an error correctionmodel. Assuming a linear risk exposure to themacroeconomic variable, an expression of thevolatility of NPLs can be derived as a function of thevolatilities of the macroeconomic variables and theunexplained volatility. A major shortcoming of thisapproach is the lack of long and reliable time seriesfor NPLs, particularly for transition and developingcountries that are experiencing structural changes.
Liquidity Risk
There are two types of liquidity risk: asset liquid-ity risk and funding liquidity risk. The former refersto the inability to sell assets at current market pricesbecause of the size of the assets and the shortamount of time available for liquidation (a situationcommonly referred to as “fire sales”). The latterrefers to the inability to access sufficient funds tomeet payment obligations in a timely manner. Twomain methods are available to assess liquidity risk:the sources and uses of funds approach and thestructure of funds approach.
• The sources and uses of funds approach definesas liquidity gap the difference between thesources and uses of funds: a deficit occurs whenuses of funds exceed sources. This method re-quires forecasting of uses and sources of fundsin any given liquidity planning period.
• The structure of funds approach looks at thestructure of the sources and uses of funds. Futureliquidity requirements are forecast by dividingbank deposits and other sources of funds intocategories based on their probability of being
withdrawn, and identifying the sources of fundsthat can become illiquid in certain situations.
Interest Rate and Other Market Risks
Interest rate risk is the risk of loss by a financialinstitution when the interest rate sensitivity of its as-sets and liabilities are mismatched. Simple methodssuch as gap analysis—including the repricingmodel, the maturity-gap model, and the durationmodel—can be used to assess this risk (see alsoChapter III). Gap analysis requires the compilationof a maturity (or repricing) schedule for all assetsand liabilities.86 The “gap” is the difference in inter-est flows on the holdings of assets and liabilities ineach time bucket, measured in terms of net assets forthe repricing model. In the maturity gap and durationmodels, the “gap” is the difference in the maturity ofassets and liabilities, measured in terms of weightedmaturity for the maturity-gap model and average lifefor the duration model. In the simple repricingmodel, the value of assets and liabilities does notchange with a change in interest rates, while in themore complex duration model the value of assetsand liabilities changes according to the interest elas-ticity of each asset or liability. The duration modelprovides more accurate estimates of the change inthe market value of a portfolio due to changes in in-terest rates.87 However, its additional data require-ments (i.e., the cash flow profile and expectedchange in the interest rate term structure) make itdifficult to use in countries with less sophisticatedstatistical systems.
Exchange rate and equity price risks can be as-sessed by calculating net open positions (see Chap-ter III). Exchange rate risk is the risk that exchangerate changes will affect the value of an institution’sassets and liabilities (both on- and off-balance-sheet), capital position, and income. Equity pricerisk is the risk that stock price changes will affectthe value of an institution’s portfolio. It has a spe-cific and a general component. A risk is specificwhen it is associated with movements in the price ofan individual stock. A risk is general when it is re-lated to movements of the stock market as a whole.Commodity price risk refers to the potential lossesthat may result directly from changes in the marketprice of bank assets, liabilities, and off-balance-
39
85For details see Blaschke, Jones, Majnoni, and Martinez Peria(2001).
86For the simple repricing model, this requires the sorting of as-sets and liabilities according to their time to repricing for floatingrate instruments, and remaining time to maturity for fixed rate in-struments; net assets are then classified in a limited number oftime categories or “buckets.” For the duration model, it is neces-sary to know the timing of future cash flows, which may also begrouped into different buckets.
87See, for instance, Saunders (2000).
V STRESS TESTING OF FINANCIAL SYSTEMS
sheet instruments, as well as indirectly through theloan portfolio, due to commodity price changes.Even if financial institutions do not take positions incommodities or commodity-linked instruments di-rectly, they may be subject to commodity price riskindirectly via the impact on their loan portfolios.This occurs if the borrowers’ ability to repay theirdebt is affected by shocks to commodity prices.This indirect source of commodity risk can be par-ticularly important for many banks in developingcountries that lend to exporters and/or importers ofcommodities.
Value at Risk
The Value at Risk (VaR) framework is a multivari-ate approach to risk assessment that is used to cap-ture multiple risks arising under normal market cir-
cumstances. The VaR is an estimate of the maximumloss on a portfolio with a given probability over apreset horizon. It is used in financial institutions as arisk management tool to set limits to the amount ofrisk that is undertaken, typically, in the trading book.VaR techniques can complement stress tests in thatthe latter are used to measure risks arising at the tail-end of the distribution of market circumstancesunder which financial systems operate.
There are two broad approaches to estimating aVaR. The local valuation method uses an estimate ofthe sensitivity of the portfolio multiplied by the esti-mated price change to arrive at the estimated changein value of the portfolio. The full valuation approachrecalculates the value of the portfolio using histori-cal or Monte Carlo simulations of prices. The corre-lations and volatilities used for a VaR calculation canbe based on historical or on implied observations.
40
Table 5.1. Data Requirements for an Integrated VaR Analysis
Financial Environment
• Time series of short-term interest rates or credit spreads on loans of different quality, to undertake volatility and correlationanalyses
• Specific estimates of the term structure of interest rates for each currency, and credit risk level at the date of the risk assessment
• Prices for a set of interest rate options for each currency
Portfolio Structure
• Asset/liability maturity mismatches that create interest rate risk
• Asset/liability currency mismatches that create foreign exchange risk
• Credit quality of governments, companies, and individuals to which the institution has loaned money and that affect the risk ofadverse rating changes and default
• The level of geographic and economic sector concentration (diversification) in the asset portfolio that affects portfolio credit risk
• The level of seniority and security for the loans in the portfolio that substantially affects the recovery rates on loans that maydefault
• Off-balance-sheet transactions that either reduce (i.e., hedge) or increase the institution’s risk level
Business Loans
• Each bank’s business loan broken down, for each currency, by sector, credit quality, maturity, and yield
• Estimates of typical debt to value ratios for loans of various credit qualities broken down by sector
• Balance sheets, income statements, and credit classification for all large exposures
• Time series of default rates on business loans by credit quality one year (or up to five years) prior to default
• Estimates of loan default recovery rates by sector and seniority of loan
Mortgage Loans
• Number and amounts of real estate loans broken down by loan-to-value ratios
• Typical loan-to-value ratio at which mortgage loans default
Other Securities and Money Market Deposits
• Amounts of government securities, equity securities, etc., broken down for each currency by type, credit quality, maturity, and yield
Source: Barnhill, Papapanagiotou, and Schumacher (2000).
Measurement Techniques
VaR techniques are usually applied to the mea-surement of market risk, but they have also beenused to assess credit risk. Barnhill, Papapanagiotou,and Schumacher (2000) attempt to measure banks’integrated market and credit risks using a full-valua-tion VaR in which the two types of risks are corre-lated. In their model, corporate credit risk is a func-tion of leverage and the volatility of the firm’s equityvalue. The paper simulates the financial environmentas a probability distribution of 8,000 scenarios,where under each scenario, each bank client has adifferent debt to equity ratio. These simulated debtto equity ratios are then mapped into credit risk cate-gories and the value of each client loan is discountedby the (simulated) interest rate that corresponds tothe credit risk category under each scenario (Table5.1). Their methodology provides a base for evaluat-ing potential changes in a bank’s asset/liability port-folio composition (e.g., credit quality, sectoral andgeographic concentration, maturity structure, andcurrency composition) as well as its capital ratio.
VaR techniques have several limitations, how-ever.88 The VaR measure is not the maximum
amount that a portfolio could lose; rather, it is aloss threshold that will be exceeded with only asmall probability. VaR techniques can provide use-ful information to decision makers about the likelypattern of events that will influence the value of aportfolio, but they are less useful in providing in-formation about unlikely events. In addition, theanalysis is sensitive to the assumed distribution andunderlying estimation techniques.89 Data require-ments for conducting VaR analyses are substantial,and the degree of detail required on individual po-sitions makes it practical to apply this method to in-dividual institutions only. In view of the variety ofVaR techniques used in financial institutions, ag-gregating individual VaR results in a meaningfulmanner can be very difficult. For these reasons, theVaR framework is rarely used in conducting aggre-gate stability assessments.
41
88Blaschke, Jones, Majnoni, and Martinez Peria (2001).
89For example, the normal distribution is typically used, but ifthe true distribution has fatter tails, the VaR may underestimatepossible losses. Moreover, linear approximations are commonlyused to estimate changes in the value of the portfolio, but thismay underestimate the VaR if movements in asset prices arelarge and the portfolio includes many assets with nonlinear pay-offs (e.g., options).
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Part II
Country Practices
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Introduction
The Survey on the Use, Compilation, and Dissem-ination of Macroprudential Indicators, conductedjointly in mid–2000 by the IMF’s Monetary and Ex-change Affairs Department and Statistics Depart-ment, has been an important step in the IMF’s pro-gram to develop a common set of FSIs. Theobjective of the survey was to obtain information onnational needs and practices related to FSIs in order
to (1) gauge the usefulness of specific indicators; (2)assess compilation and dissemination practices inorder to help identify international best practiceswhere possible; (3) evaluate whether the SpecialData Dissemination Standard (SDDS) or other vehi-cles could have a role in encouraging the public dis-semination of FSIs; and (4) explore the analyticalframeworks used by member countries in macropru-dential analysis. The structure of the survey is de-scribed in Box 6.1.
VI The IMF Survey on FSIs
45
Box 6.1. Structure of the Survey on FSIs
The survey had two parts (see Appendix V). The firstpart, the User Questionnaire, gathered informationfrom financial supervisors, financial policy officials,and the private sector on the usefulness of the FSIs andmethods of macroprudential analysis. The second part,the Compilation and Dissemination Questionnaire, in-quired about national practices in compiling and dis-seminating FSIs.
The structure of the survey benefited from consulta-tions with national authorities, international organiza-tions, and the private sector.1 These consultations alsocontributed importantly to improving the list of FSIs tobe surveyed and to assessing their uses and potentialreliability. The survey covered a total of 56 FSIs se-lected as representative of the work and focus of abroad range of users.The FSIs and their componentswere grouped into six major categories derived fromthe CAMELS framework used by bank supervisors toevaluate individual financial institutions. The six cate-gories of FSIs included in the survey were:2
• Capital adequacy;• Asset quality (lending institutions);• Asset quality (borrowing institutions);• Profitability and competitiveness;• Liquidity; and• Sensitivity to market risks.
The FSIs included in the survey largely focused oninformation about depository corporations (banks), butincluded some key information on their corporate andhousehold counterparties (see Table 6.2). This focuswas determined in light of the importance of bankinginstitutions and the generally greater amount of infor-mation available for banks compared to other types ofinstitutions. However, further research is needed on an-alyzing and quantifying the influence of the conditionof nonbank financial institutions and financial marketson financial sector soundness.
Central banks in each economy received the survey,with a request that they coordinate its distribution,completion, and return to the IMF. They were asked todistribute the survey within their economies towhichever parties they judged could best provide rep-resentative information on needs and practices relatingto FSIs. These parties included central government pol-icy or analysis offices, supervisory agencies, and pri-vate sector participants.
The survey was made available in English, French,and Spanish, and was dispatched in early June 2000 tothe IMF membership and several offshore financialcenter nonmembers. Copies were also sent to relevantinternational organizations. Responses were requestedby the end of July 2000. Most responses were receivedduring July and August 2000.
1Consultations on the design of the survey were held withthe Asian Development Bank, the Bank for International Set-tlements, the Basel Committee on Banking Supervision, theCommittee on the Global Financial System, the EuropeanCentral Bank, the Financial Stability Forum, the InternationalAssociation of Insurance Supervisors, the Organization ofEconomic Cooperation and Development, and the WorldBank. Consultations were also held with central banks and su-pervisory offices in nine countries and with representativesfrom the private sector—commercial and investment banks,rating agencies, investment research firms, and real estatemarket research firms.
2The quality of management of financial institutions wasnot included in the survey because of concerns that quantita-tive measures of management would not be reliable.
VI THE IMF SURVEY ON FSIS
Response to the Survey
The IMF received a total of 122 responses to thesurvey (74 percent of those receiving it), covering142 countries and other jurisdictions. All of the 122respondents completed the first part of the survey—the User Questionnaire, while 93 respondents com-pleted the second part—the Compilation and Dis-semination Questionnaire. The high response rate isan indication of the importance attached worldwideto issues relating to macroprudential analysis and thepossible role of FSIs in such analysis. This view isbolstered by the effort made by respondents to an-swer the survey thoroughly and provide detailedcomments. Table 6.1 shows a summary of the re-sponses by type of economy.
Table 6.1 shows that the response was broadlybased—all industrial economies responded to thesurvey, the response rate from emerging economies
was very high, and over half of all developingeconomies responded. The response rate of emerg-ing and developing economies was lower for theCompilation and Dissemination Questionnaire thanfor the User Questionnaire, perhaps reflecting morelimited programs than those in industrial countries tocompile and disseminate FSIs.
Table 6.2 provides a summary of the responses byindicator. It shows the number of respondents com-piling and disseminating each of the FSIs includedin the survey, and users’ evaluation of the usefulnessof FSIs. The next two chapters will discuss these re-sults in greater depth. Chapter VII will discuss users’evaluation and the usefulness ratings, while ChapterVIII will discuss country compilation and dissemi-nation practices. The qualitative results of the surveywill be discussed in Chapter IX. In addition to the ta-bles and figures included in the text, Appendix IVprovides detailed survey results.
46
Table 6.1. Summary of the Responses by Type of Economy1
Worldwide Industrial Economies Emerging Economies2 Developing Economies____________________ ____________________ ____________________ ____________________Percent Percent Percent Percent
Number of of total Number of of total Number of of total Number of of totalresponses sent survey responses sent survey responses sent survey responses sent survey
Total responses 122 74 24 100 53 88 45 56
Africa 24 60 — — 4 100 20 56Asia-Pacific 26 76 3 100 14 82 9 64Europe 40 87 19 100 15 94 6 55Middle East 6 43 — — 5 71 1 14Western Hemisphere 26 83 2 100 15 94 9 69
1Responses from regional central banks that covered their respective memberships are counted as a single response.2There is no standard list of emerging economies. For the purposes of this paper, the group of emerging economies was based on the tables used in
the May 2000 issue of the IMF’s World Economic Outlook.
Table 6.2. Summary of the Responses by Indicator
Number Number AverageFSI Compiling FSIs Disseminating FSIs Usefulness Score
1. Capital adequacy1.1 Basel capital adequacy ratio 85 53 3.81.1a Ratio of Basel tier I capital to risk-weighted assets 81 44 3.61.1b Ratio of Basel tier I + tier II capital to risk-weighted assets 79 43 3.41.1c Ratio of Basel tier I + II + III capital to risk-weighted assets 36 21 3.01.2 Distribution of capital adequacy ratios (number of institutions
within specified capital adequacy ratio ranges) 21 11 3.31.3 Ratio of total on-balance-sheet assets to own funds 34 17 3.2
2. Asset quality
(a) Lending institutions2.1 Distribution of on-balance-sheet assets, by Basel risk-weight category 77 33 3.42.2 Ratio of total gross asset position in financial derivatives to own funds 15 5 2.8
Response to the Survey
47
Table 6.2 (concluded)
Number Number AverageFSI Compiling FSIs Disseminating FSIs Usefulness Score
2.3 Ratio of total gross liability position in financial derivatives to own funds 13 5 2.82.4 Distribution of loans, by sector 76 60 3.62.4a of which: loans for investment in commercial real estate 41 30 3.22.4b of which: loans for investment in residential real estate 51 40 3.22.5 Distribution of credit extended, by sector 46 35 3.52.6 Distribution of credit extended, by country or region 42 28 3.12.7 Ratio of credit to related entities to total credit 26 7 3.42.8 Ratio of total large loans to own funds 29 8 3.52.9 Ratio of gross nonperforming loans to total assets 42 28 3.92.10 Ratio of nonperforming loans net of provisions to total assets 39 22 3.8(b) Borrowing institutions2.11 Ratio of corporate debt to own funds (“debt-equity ratio”) 17 9 3.42.12 Ratio of corporate profits to equity 15 9 3.32.13 Ratio of corporate debt-service costs to total corporate income 13 9 3.22.14 Corporate net foreign currency exposure 6 2 3.22.15 Ratio of household total debt to GDP 13 7 3.02.15a of which: ratio of mortgage debt to GDP 25 16 2.82.15b of which: ratio of household debt owed to depository corporations
to GDP 29 23 2.92.16 Number of applications for protection from creditors 13 10 2.7
3. Profitability and competitiveness3.1 Rate of change in number of depository corporations 35 28 2.73.2 Ratio of profits to period-average assets (ROA) 42 29 3.63.3 Ratio of profits to period-average equity (ROE) 44 31 3.63.4 Ratio of net interest income to total income 39 23 3.53.5 Ratio of trading and foreign exchange gains/losses to total income 30 16 3.33.6 Ratio of operating costs to net interest income 38 21 3.43.7 Ratio of staff costs to operating costs 37 21 3.23.8 Spread between reference lending and deposit rates 25 16 3.53.9 Share of assets of the three largest depository corporations in
total assets of depository corporations 35 16 2.9
4. Liquidity 4.1 Distribution of three-month local currency interbank rates for
different depository corporations 23 12 2.94.2 Average interbank bid-ask spread for three-month local currency
deposits 18 11 2.94.3 Ratio of liquid assets to total assets 37 20 3.54.4 Ratio of liquid assets to liquid liabilities 37 22 3.64.5 Average maturity of assets 18 5 3.44.6 Average maturity of liabilities 18 5 3.44.7 Average daily turnover in the Treasury bill (or central bank bill) market 33 24 2.84.8 Average bid-ask spread in the Treasury bill (or central bank bill) market 25 14 2.84.9 Ratio of central bank credit to depository corporations to
depository corporations’ total liabilities 20 11 2.9 4.10 Ratio of customer deposits to total (noninterbank) loans 33 14 3.24.11 Ratio of customer foreign currency deposits to total (noninterbank)
foreign currency loans 24 11 2.9
5. Sensitivity to market risk indicators
5.1 Ratio of gross foreign currency assets to own funds 24 9 3.15.2 Ratio of net foreign currency position to own funds 25 11 3.45.3 Average interest rate repricing period for assets 17 4 3.05.4 Average interest rate repricing period for liabilities 16 3 3.05.5 Duration of assets 22 9 3.25.6 Duration of liabilities 21 7 3.25.7 Ratio of gross equity position to own funds 21 8 2.95.8 Ratio of net equity position to own funds 15 8 3.05.9 Ratio of gross position in commodities to own funds 7 2 2.45.10 Ratio of net position in commodities to own funds 8 3 2.4
The first part of the survey, the User Question-naire, gathered information from three types of
users of macroprudential information—financial su-pervisors, policy analysts within the central bank orgovernment, and the private sector (mainly financialmarket participants, financial rating agencies, andacademics)—regarding their needs for data. Userswere asked to rate the usefulness of each FSI and thepreferred periodicity and timeliness. The quantita-tive information on the usefulness of FSIs was sup-plemented by a series of open-ended questions aboutthe analytic framework applied in each country, na-tional research programs on FSIs, and special issuesaffecting macroprudential analysis.
Figure 7.1 presents respondents’ average usefulnessscores for the six major categories of FSIs, disaggre-gated by type of economy—industrial economies,emerging economies, and developing economies. Thescale for scores is: 1—not useful, 2—sometimes use-ful, 3—useful, and 4—very useful.
Respondents judged all major categories of FSIs tobe broadly useful, with slightly more users in emerg-ing countries deeming them useful than did otherusers.90 Indicators of capital adequacy, asset quality(lending institutions), and profitability were mostwidely deemed to be useful, followed by indicators ofliquidity and sensitivity to market risk. Fewer users inindustrial economies, in particular, deemed the liquid-ity and sensitivity to market risk indicators useful.Several industrial economy respondents commentedthat the liquidity and sensitivity to market risk indica-tors were sophisticated and possibly difficult to con-struct to achieve precise results.
FSIs by Usefulness Group
The FSIs are divided into four groups in Tables7.1–7.3 based on their average usefulness scores forall respondents. Group I comprises the FSIs deemedvery useful, as reflected in average usefulness scores
of 3.5 and above. Group II comprises FSIs deemeduseful, with average scores of 3.0–3.4; Group IIIcomprises moderately useful FSIs, with scores of2.5–2.9; and Group IV comprises less useful FSIs,with scores of 2.4 and lower.
Very Useful FSIs
Table 7.1 presents the 13 FSIs with an averageusefulness score of 3.5 or over. These FSIs includecentral elements of bank soundness: two of them—the Basel capital adequacy ratio and one of its com-ponents—relate to the capital base, which serves as abuffer to withstand shocks; while four of them mea-sure profitability, which serves to sustain the capital
VII Usefulness of FSIs
48
90Appendix IV, Table A4.3 provides a detailed matrix with use-fulness scores for FSIs by type of user and type of economy.
Figure 7.1. Summary of the Usefulness of FSIs(Average usefulness scores by type of economy)
2
0
1
4
3
Sens
itivit
y to
mar
ket r
isk
Liquid
ity
Prof
itabil
ity an
d
compe
titive
ness
Asset q
uality
:
borro
wing in
stitu
tions
Asset q
uality
:
lendin
g ins
titut
ions
Capita
l ade
quac
y
Industrial countriesEmerging countriesDeveloping countries
Source: IMF Survey on the Use, Compilation, and Disseminationof Macroprudential Indicators.
Additional FSIs Identified by Respondents
base. The quality of banks’ assets—as covered bydata on nonperforming loans, the distribution of as-sets, and asset liquidity—comprise the remainder ofthe FSIs in Group I.
Useful FSIs
Table 7.2 presents the Group II FSIs, with averageusefulness scores of 3.0 to 3.4. These FSIs coversome of the elements of capital adequacy, the distri-bution of bank credit by risk-weight category and bycountry, the financial conditions of the corporate andhousehold sectors, some of the elements of operatingincome and expenses of banks, the maturity and du-ration of assets and liabilities, and other marketrisks. This is the largest group, comprising 27 FSIsor 48 percent of all FSIs surveyed.
The 40 indicators in Groups I and II represent asizeable group of FSIs that have been judged usefulfor analyzing financial soundness, among which 13were on average judged very useful. These FSIscover all six categories of FSIs and comprise 71 per-cent of the indicators surveyed. Notably, users inemerging and developing countries generallymarked the usefulness of these 40 indicators equal toor higher than those in industrial countries.91
In assessing FSIs in Groups I and II, the responsesfrom supervisors, policy officials, and private sector
respondents were broadly similar, although supervi-sors tended to rate the FSIs more useful than theother users did, and policy officials tended to assigngreater usefulness to FSIs on the financial conditionof the household sector (Appendix IV, Table A4.3).
Moderately Useful FSIs and Less Useful FSIs
Table 7.3 presents those FSIs with usefulnessscores of 2.5–2.9 (Group III) and under 2.5 (GroupIV). The Group III FSIs include several indicatorsrelated to asset quality and many of the liquidity in-dicators. In general, there is no clear break betweenthe Group II and Group III FSIs—7 of the 14 GroupIII FSIs have borderline average scores of 2.9 andmost have average scores of 3 or higher within atleast one of the types of economy groupings.
Only two FSIs (the ratio of gross positions in com-modities to own funds and the ratio of net position incommodities to own funds) are classified in Group IV.Many respondents indicated that banks in their coun-tries are forbidden to hold commodity positions.
Additional FSIs Identified by Respondents
The User Questionnaire also asked respondents toidentify FSIs they considered useful but were notcovered in the survey. A relatively small number ofadditional FSIs were suggested. Appendix III pro-vides a summary of respondents’ suggestions.
49
Table 7.1. Group I FSIs by Type of Economy(Very useful FSIs, with average usefulness ratings of 3.5 and higher)
Industrial Emerging DevelopingFSI All Countries Countries Countries Countries
1.1 Basel capital adequacy ratio 3.8 3.7 3.9 3.61.1a Ratio of Basel tier I capital to risk-weighted assets 3.6 3.6 3.6 3.5
2.4 Distribution of loans, by sector 3.6 3.5 3.6 3.52.5 Distribution of credit extended, by sector 3.5 3.3 3.6 3.62.8 Ratio of total large loans to own funds 3.5 3.2 3.6 3.62.9 Ratio of gross nonperforming loans to total assets 3.9 3.9 3.9 3.82.10 Ratio of gross nonperforming loans net of provisions to
total assets 3.8 3.8 3.8 3.8
3.2 Ratio of profits to period-average assets (ROA) 3.6 3.5 3.8 3.63.3 Ratio of profits to period-average equity (ROE) 3.6 3.5 3.8 3.63.4 Ratio of net interest income to total income 3.5 3.3 3.6 3.63.8 Spread between reference lending and deposit rates 3.5 3.4 3.6 3.5
4.3 Ratio of liquid assets to total assets 3.5 3.2 3.6 3.54.4 Ratio of liquid assets to liquid liabilities 3.6 3.2 3.7 3.7
91For example, among the Group II FSIs, six have average use-fulness scores in emerging and developing countries that aremarkedly higher than those in industrial countries.
VII USEFULNESS OF FSIS
The most frequently identified useful additionalFSIs were asset prices. Among the asset prices sug-gested were the prices of real estate, both commer-cial and residential, and equity prices, including the
stock prices of the depository corporations’ subsec-tor relative to the overall stock price index, andstock prices disaggregated by industry sectors. Toprevent the masking of relevant information through
50
Table 7.2. Group II FSIs by Type of Economy(Useful FSIs, with average usefulness ratings of 3.0 to 3.4)
Industrial Emerging DevelopingFSI All Countries Countries Countries Countries
1.1b Ratio of Basel tier I + II capital to risk-weighted assets 3.4 3.2 3.6 3.41.1c Ratio of Basel tier I + II + III capital to risk-weighted assets 3.0 2.9 3.1 3.11.2 Distribution of capital adequacy ratios (number of institutions
within specified capital adequacy ratio ranges) 3.3 3.3 3.4 3.11.3 Ratio of total on-balance-sheet assets to own funds 3.2 2.9 3.3 3.3
2.1 Distribution of on-balance-sheet assets, by Basel risk-weight category 3.4 3.2 3.5 3.4
2.4a Loans for investment in commercial real estate 3.2 3.3 3.3 3.12.4b Loans for investment in residential real estate 3.2 3.3 3.2 3.22.6 Distribution of credit extended, by country or region 3.1 3.2 3.2 2.82.7 Ratio of credit to related entities to total credit 3.4 3.0 3.6 3.52.11 Ratio of corporate debt to own funds (“debt-equity ratio”) 3.4 3.4 3.5 3.32.12 Ratio of corporate profits to equity 3.3 3.1 3.4 3.22.13 Ratio of corporate debt service costs to total corporate income 3.2 3.2 3.4 3.02.14 Corporate net foreign currency exposure 3.2 3.2 3.4 2.92.15 Ratio of household total debt to GDP 3.0 3.2 3.0 2.8
3.5 Ratio of trading and foreign exchange gains/losses to total income 3.3 3.2 3.4 3.3
3.6 Ratio of operating costs to net interest income 3.4 3.0 3.6 3.63.7 Ratio of staff costs to operating costs 3.2 2.8 3.4 3.4
4.5 Average maturity of assets 3.4 3.0 3.4 3.64.6 Average maturity of liabilities 3.4 3.0 3.4 3.64.10 Ratio of customer deposits to total (noninterbank) loans 3.2 2.9 3.3 3.3
5.1 Ratio of gross foreign currency assets to own funds 3.1 2.7 3.2 3.25.2 Ratio of net foreign currency position to own funds 3.4 3.1 3.6 3.55.3 Average interest rate repricing period for assets 3.0 2.8 3.3 3.05.4 Average interest rate repricing period for liabilities 3.0 2.8 3.2 3.05.5 Duration of assets 3.2 3.0 3.4 3.05.6 Duration of liabilities 3.2 3.0 3.3 3.05.8 Ratio of net equity position to own funds 3.0 2.8 3.0 3.1
Additional FSIs Identified by Respondents
the aggregation process and to help in the identifica-tion of outliers, clustering of problems, or tiering inmarkets, there also were calls for more informationon the distribution or dispersion of observations.
Several respondents identified the ratio of grossnonperforming loans to total loans as useful, in lieuof the FSI in the survey that used total assets as thedenominator.
51
Table 7.3. Groups III–IV FSIs by Type of Economy(Modestly useful and less useful FSIs, with average usefulness ratings of 2.5 to 2.9, and under 2.5, respectively)
Industrial Emerging DevelopingFSI All Countries Countries Countries Countries
Group III FSIs (average usefulness ratings of 2.5 to 2.9)
2.2 Ratio of total gross asset position in financial derivatives to own funds 2.8 2.7 3.0 2.6
2.3 Ratio of total gross liability position in financial derivatives to own funds 2.8 2.7 2.9 2.6
2.15a Ratio of household mortgage debt to GDP 2.8 3.1 2.8 2.72.15b Ratio of household debt owed to depository corporations
to GDP 2.9 3.0 2.8 2.82.16 Number of applications for protection from creditors 2.7 2.8 2.7 2.5
3.1 Rate of change in number of depository corporations 2.7 2.4 2.7 2.93.9 Share of assets of the three largest depository corporations
in total assets of depository corporations 2.9 2.7 3.1 2.9
4.1 Distribution of three-month local-currency interbank rates for different depository corporations 2.9 2.7 3.1 2.8
4.2 Average interbank bid-ask spread for three-month local-currency deposits 2.9 2.9 3.0 2.7
4.7 Average daily turnover in the treasury bill (or central bank bill) market 2.8 2.3 3.0 3.1
4.8 Average bid-ask spread in the treasury bill (or central bank bill) market 2.8 2.3 3.0 3.0
4.9 Ratio of central bank credit to depository corporations to depository corporations’ total liabilities 2.9 2.6 3.1 2.8
4.11 Ratio of customer foreign currency deposits to total (noninterbank) foreign currency loans 2.9 2.6 3.1 2.9
5.7 Ratio of gross equity position to own funds 2.9 2.8 3.0 3.0
Group IV FSIs (average usefulness ratings of 2.4 and lower)
5.9 Ratio of gross position in commodities to own funds 2.4 2.3 2.5 2.45.10 Ratio of net position in commodities to own funds 2.4 2.3 2.5 2.5
The second part of the survey, the Compilationand Dissemination Questionnaire, requested in-
formation on the types of FSIs compiled, the avail-ability of components that could be used to compileFSIs, and national practices in disseminating FSIs;the periodicity of compilation and dissemination;and various accounting, regulatory, and statisticalpractices related to FSIs.
Compilation and Dissemination of FSIs and Their Components
Country practices on the compilation and dissemi-nation of FSIs and their components are mixed.92
With only a few exceptions, compilation of FSIsthemselves is quite limited, and dissemination ofFSIs—especially outside the industrial countries—isscanty. However, compilation and dissemination ofcomponents of FSIs are more extensive.93
Table 8.1 provides information (by usefulnessgroup) on the extent to which each FSI is compiledand disseminated. On compilation, the table showsthat:
• Only 6 FSIs—all related to capital adequacy orthe distribution of loans—are compiled by halfor more of the respondents, with three FSIs eachfrom Groups I and II indicators, respectively.
• Twenty-nine FSIs are compiled by one-quarterto one-half of the respondents.
• Twenty-one FSIs are compiled by less than one-quarter of all respondents.
On dissemination, the table shows that:
• Only two FSIs (Basel capital adequacy ratio anddistribution of loans by sector) are disseminated
by half or more of the respondents; both of theseFSIs are Group I indicators.
• Fourteen FSIs are disseminated by one-quarterto one-half of all respondents.
• Forty FSIs (75 percent of the total) are dissemi-nated by less than one-quarter of all respondents.
In contrast, the compilation and dissemination ofthe components used to construct FSIs are muchmore extensive. For example, 81 percent of all re-spondents compile the components of the ratio ofliquid assets to liquid liabilities, but only 40 percentof them compile the ratio itself. Table 8.1 also showsthe extent to which the components of FSIs are com-piled and disseminated.94
On compilation, Table 8.1 shows that while only 6FSIs are compiled by half or more of the respon-dents (as noted above), the components of 30 FSIsare compiled by half or more of the respondents. Im-portantly, these 30 FSIs95 for which components areextensively compiled comprise:
• All 13 of the Group I FSIs identified by users asmost useful;
• Twelve or 44 percent of the Group II FSIs identi-fied by users as useful; and
• Five or 36 percent of the Group III FSIs identi-fied by users as moderately useful.
In addition, while the 6 FSIs noted above coveronly 50 percent and 25 percent of the indicators inthe capital adequacy and asset quality (lending) cate-gories, respectively, the 30 FSIs span a much widerrange of categories with sizeably higher shares, asfollows: capital adequacy (67 percent of the indica-tors); asset quality (lending) (75 percent); profitabil-ity and competitiveness (100 percent); liquidity (45percent); and sensitivity to market risk (30 percent).
VIII Compilation and DisseminationPractices
52
92Appendix IV, Table A4.4 provides detailed information onthe compilation and dissemination of FSIs.
93Components refer to the numerators or denominators thatallow an indicator to be compiled or elements of the numerator ordenominator that allow each, and hence the indicator itself, to becompiled.
94Table 4.3 reports figures for the least available component ofeach FSI because all components must be available in order tocompile the FSI.
95A summary presentation of the 30 FSIs is shown in AppendixIV, Table A4.1.
Compilation and Dissemination of FSIs and Their Components
53
Table 8.1. FSIs: Compilation and Dissemination Practices
Percent Percent Percent Percent Usefulness Compiling Disseminating Compiling Disseminating
FSI Score FSIs FSIs Components Components
Group I FSIs (average usefulness ratings of 3.5 to 4.0)
1.1 Basel Capital Adequacy Ratio 3.8 91 57 91 571.1a Ratio of Basel tier I capital to risk-weighted assets 3.6 87 47 87 65
2.4 Distribution of loans, by sector 3.6 82 65 82 432.5 Distribution of credit extended, by sector 3.5 49 38 57 442.8 Ratio of total large loans to own funds 3.5 31 9 56 222.9 Ratio of gross nonperforming loans to total assets 3.9 45 30 86 552.10 Ratio of nonperforming loans net of provisions to total
assets 3.8 42 24 75 45
3.2 Ratios of profits to period-average assets (ROA) 3.6 45 31 81 483.3 Ratios of profits to period-average equity (ROE) 3.6 47 33 80 493.4 Ratio of net interest income to total income 3.5 42 25 88 583.8 Spread between reference lending and deposit rates 3.5 27 17 57 49
4.3 Ratio of liquid assets to total assets 3.5 40 22 81 444.4 Ratio of liquid assets to liquid liabilities 3.6 40 24 77 42
Group II FSIs (average usefulness ratings of 3.0 to 3.4)
1.1b Ratio of Basel tier I + tier II capital to risk-weighted assets 3.4 85 46 85 46
1.1c Ratio of Basel tier I + II + III capital to risk-weighted assets 3.0 39 23 39 23
1.2 Distribution of capital adequacy ratios (number of institutions within specified capital adequacy ratio ranges) 3.3 23 12 23 12
1.3 Ratio of total on-balance-sheet assets to own funds 3.2 37 18 83 58
2.1 Distribution of on-balance-sheet assets, by Basel risk-weight category 3.4 83 35 83 35
2.4a Loans for investment in commercial real estate 3.2 44 32 44 322.4b Loans for investment in residential real estate 3.2 55 43 55 432.6 Distribution of credit extended, by country or region 3.1 45 30 52 352.7 Ratio of credit to related entities to total credit 3.4 28 8 68 232.11 Ratio of corporate debt to own funds (“debt-equity
ratio”) 3.4 18 10 37 272.12 Ratio of corporate profits to equity 3.3 16 10 42 272.13 Ratio of corporate debt-service costs to total
corporate income 3.2 14 10 33 202.14 Corporate net foreign currency exposure 3.2 6 2 19 102.15 Ratio of household total debt to GDP 3.0 14 8 27 17
3.5 Ratio of trading and foreign exchange gains/losses to total income 3.3 32 17 69 44
3.6 Ratio of operating costs to net interest income 3.4 41 23 87 573.7 Ratio of staff costs to operating costs 3.2 40 23 84 54
4.5 Average maturity of assets 3.4 19 5 34 184.6 Average maturity of liabilities 3.4 19 5 37 184.10 Ratio of customer deposits to total
(noninterbank) loans 3.2 35 15 85 65
5.1 Ratio of gross foreign currency assets to own funds 3.1 26 10 54 445.2 Ratio of net foreign currency position to own funds 3.4 27 12 76 245.3 Average interest rate repricing period for assets 3.0 18 4 18 45.4 Average interest rate repricing period for liabilities 3.0 17 3 17 35.5 Duration of assets 3.2 24 10 24 105.6 Duration of liabilities 3.2 23 8 23 85.8 Ratio of net equity position to own funds 3.0 16 9 27 14
Group III FSIs (average usefulness ratings of 2.5 to 2.9)
2.2 Ratio of total gross asset position in financial derivatives to own funds 2.8 16 5 33 12
VIII COMPILATION AND DISSEMINATION PRACTICES
On dissemination, the result is the same as forcompilation, albeit to a lesser degree. Table 8.1shows that while only two FSIs (as noted above) aredisseminated by half or more of the respondents, thecomponents of 8 FSIs are disseminated by half ormore of the respondents.96
The results on component compilation in particu-lar suggest that many countries may be in a positionto compile a good number of FSIs (especially theGroup I FSIs), although significant gaps remain.97
Box 8.1 discusses how compilation and dissemina-tion practices differ by type of economy.
In general, the broad availability of many compo-nents of FSIs derives from the accounting, statistical,tax, and registration systems that can be tapped forgenerating data on the components of FSIs, amongwhich monetary statistics98 and supervisory reportson banks’ balance sheets and income are among themost important.
Finally, since one of the objectives of the surveywas to evaluate whether the Special Data Dissemina-tion Standard (SDDS) or other vehicles would be ap-propriate to encourage dissemination of FSIs, it wasencouraging that the response rate of SDDS sub-
54
Table 8.1 (concluded)
Percent Percent Percent Percent Usefulness Compiling Disseminating Compiling Disseminating
FSI Score FSIs FSIs Components Components
2.3 Ratio of total gross liability position in financial derivatives to own funds 2.8 14 5 31 12
2.15a Ratio of household mortgage debt to GDP 2.8 27 17 27 172.15b Ratio of household debt owed to depository
corporations to GDP 2.9 31 25 31 252.16 Number of applications for protection from creditors 2.7 14 11 14 11
3.1 Rate of change in number of depository corporations 2.7 38 30 62 463.9 Share of assets of the three largest depository
corporations in total assets of depository corporations 2.9 38 17 72 32
4.1 Distribution of three-month local currency interbank rates for different depository corporations 2.9 25 13 25 13
4.2 Average interbank bid-ask spread for three-month local currency deposits 2.9 19 12 19 12
4.7 Average daily turnover in the treasury bill (or central bank bill) market 2.8 35 26 35 26
4.8 Average bid-ask spread in the treasury bill (or central bank bill) market 2.8 27 15 27 15
4.9 Ratio of central bank credit to depository corporations to depository corporations’ total liabilities 2.9 22 12 72 53
4.11 Ratio of customer foreign currency deposits to total (noninterbank) foreign currency loans 2.9 26 12 74 47
5.7 Ratio of gross equity position to own funds 2.9 23 9 59 34
Group IV FSIs (average usefulness ratings of 2.4 and under)
5.9 Ratio of gross position in commodities to own funds 2.4 8 2 16 65.10 Ratio of net position in commodities to own funds 2.4 9 3 15 5
96Several countries indicate that some FSIs are disseminatedwhile their components are not. If these FSIs are included withthe pool of FSIs whose components are disseminated, therewould be 13 FSIs altogether (instead of the 8 indicated above)that are potentially available for dissemination.
97For example, the results suggest that systems to compile sta-tistics on financial derivatives and the financial condition of non-financial sectors are not widely available, as indicated by the lim-ited degree to which components are compiled for FSIs number2.2—Ratio of total asset position in derivatives to total ownfunds, 2.3—Ratio of total liability position in derivatives to totalown funds, 2.13—Ratio of corporate debt service to income,2.14—Corporate net foreign currency exposure, and 2.15—Ratioof household debt to GDP.
98Monetary statistics published in the IMF’s International Fi-nancial Statistics are the most comprehensive source for interna-tionally comparable aggregate data on countries’ financial sys-tems. Monetary statistics are compiled on a high-frequencymonthly basis within an existing institutional framework, and in-ternationally agreed compilation standards exist, as embodied inthe IMF’s Monetary and Financial Statistics Manual. Similarly,euro area monetary statistics are used as a key element of the Eu-ropean Central Bank’s program on macroprudential indicators.
Compilation and Dissemination of FSIs and Their Components
scribers was very high—all but two of the 50 SDDSsubscribers (as of December 2001) had completedthe questionnaire.
For almost all FSIs, users in countries subscribingto the SDDS rated the usefulness of FSIs nearlyidentically with users in industrial and emerging
countries, which indicated that their priorities aresimilar to those already discussed in the paper. Al-though subscribers’ performance in the dissemina-tion of components of FSIs is somewhat better, theoverall results are broadly similar to those for thetotal population of respondents—that is, compilation
55
Box 8.1. Compilation and Dissemination Practices by Type of Economy
The average number of FSIs compiled and dissemi-nated by industrial, emerging, and developing coun-tries are shown in the first figure.1 Industrial countriescompile and disseminate the largest number of FSIsand emerging countries compile and disseminate thesecond largest number of FSIs. Industrial and emergingcountries compile on average more than half of the in-dicators specified in the survey.
A comparison of the number of FSIs compiled anddisseminated indicates that around 60 percent of com-piled FSIs are disseminated; this percentage is broadlythe same for each type of economy. Divergence be-
tween the number of FSIs compiled and disseminatedindicates that the private sector has access to a nar-rower range of financial soundness indicators than isavailable to national authorities. It also indicates thatthere is scope for increasing the number of publiclyavailable indicators of financial sector soundness in alltypes of economies.
The second figure reports on the percentage of indi-cators compiled in each FSI category disaggregated bytype of economy. It shows that industrial countries ingeneral compile the highest percentage of indicators ineach category of FSI, followed by emerging and devel-oping countries. The one exception is in the category ofliquidity, where emerging countries compile the high-est percentage of indicators. Notably, industrial coun-tries compile a significantly larger percentage of indi-cators on asset quality (borrowing institution) thanemerging and developing countries, probably reflect-ing the greater amount of statistical resources neededto compile indicators in that category.
1An FSI is counted as compiled and disseminated if the FSIitself, or all the components of the FSI, are compiled and dis-seminated.
Average Number of FSIs Compiled andDesseminated by Type of Economy1
30
40
10
05
15
25
35
20
Compilation
Indus
trial
Emer
ging
Develo
ping
Indus
trial
Emer
ging
Develo
ping
20
25
5
0
10
15
Dissemination
Source: IMF Survey on the Use, Compilation, and Dissemina-tion of Macroprudential Indicators.
1Figures in parentheses indicate the number of indicatorscompiled as a percentage of the total number of indicators in-cluded in the survey.
Percentage of Indicators Compiled ineach Category by Type of Economy
80
100
40
0
20
60Liq
uidity
Mar
ket r
isk
Prof
itabil
ity an
d
com
petit
ivene
ss
Asset
qua
lity:
borro
wing in
stitu
tions
Asset
qua
lity:
lendin
g ins
titut
ions
Capita
l
adeq
uacy
Industrial countriesEmerging countries
Developing countries
Source: IMF Survey on the Use, Compilation, and Dissemi-nation of Macroprudential Indicators.
VIII COMPILATION AND DISSEMINATION PRACTICES
and dissemination of FSIs by subscribers is limitedbut compilation and dissemination of components ismore extensive. Appendix IV, Table A4.2 providesinformation on the compilation and dissemination ofFSIs and their components by SDDS subscribers.
Periodicity
The survey also inquired about country practicesregarding the periodicity of compilation and dissem-ination, as well as users’ needs in those areas. On thelatter, users were asked to indicate whether the peri-odicity for FSIs should be monthly, quarterly, semi-annually, annually, or other specified periodicity(such as daily or weekly).
Table 8.2 lists, for each category of FSI, the exist-ing compilation and dissemination practices and themost common periodicity sought by users. Each celllists the most common periodicity (compiled orsought) and any other periodicity compiled or soughtat least 80 percent as often as the most common.
As shown in the first column of Table 8.2, usersclearly seek quarterly or monthly data for all themajor categories of FSIs. Although quarterly dataare sought most often in five of the six categories,monthly data are sought almost as often. For liquid-ity FSIs, a number of respondents sought higher fre-quency data, such as daily or weekly.
In terms of compilation, FSIs are compiled monthlyin about 42 percent of all cases,99 and quarterly inabout 34 percent of all cases. The FSIs compiled on amonthly basis are mainly capital adequacy indicatorsfrom banking supervision data, asset quality (lendinginstitution) indicators derived from monthly monetary
statistics or monetary statistics’ source data, and someliquidity and sensitivity to market risks indicators de-rived from high-frequency source data. Quarterly se-ries predominate in the profitability category and arenearly as common as monthly series in the categoriesfor capital adequacy and asset quality (lending institu-tions). Data are compiled annually most often withinthe category of asset quality (borrowing institutions).“Other” periodicities most often refer to daily orweekly compilations of FSIs related to interest ratesor securities market turnover.
The periodicity of dissemination of FSIs vary con-siderably between the different categories of FSIs.No general pattern could be ascertained and thenumber of responses was too low for valid conclu-sions to be made.
Accounting, Regulatory, and Statistical Issues
Information relating to accounting and regulatoryissues and statistical standards was sought in orderto gain insights into whether international best prac-tices exist and into the international comparability ofFSIs. The information was drawn from Part IIb ofthe Compilation and Dissemination Questionnaire.
International Comparability of FSIs
The Compilation and Dissemination Question-naire asked a series of quantitative and open-endedquestions about accounting and statistical issues inorder to assess the state of existing practices; possi-bly identify best practices that might be used as abasis for development of international standards; andhelp identify strategies for improving the compara-bility of FSIs.
56
Table 8.2. Periodicity of FSIs
Users’ Preference Compilation Practice DisseminationPractice
Capital adequacy Quarterly/monthly Quarterly/monthly Quarterly/monthly
Asset quality (lending institution) Quarterly/monthly Monthly/quarterly Monthly/quarterly
Asset quality (borrowing institution) Quarterly/other/annual Annual/quarterly Annual
Profitability and competitiveness Quarterly Quarterly Annual/quarterly
Liquidity Monthly Monthly Monthly
Sensitivity to market risks Quarterly/monthly/other Monthly N/A*
*Too few responses were received to produce valid results.
99A case refers to a single observation of an FSI by a respondent.
Accounting, Regulatory, and Statistical Issues
The responses highlighted a diversity of nationalpractices and revealed many reasons why FSIs mightnot be comparable across economies:
• Different, and often complex, standards exist forrecognizing substandard claims and provisioning(see Box 8.2);
• National definitions of regulatory capital dif-fer—for instance, as regards deductions andcomponents of each tier of capital. Moreover,numerous countries indicated that they have not approved the use of tier III capital within the base;
57
Box 8.2. Country Practices on Nonperforming Loans
Nonperforming loans (NPLs) carried by banks ontheir balance sheets and the provisions held by banksfor loan losses are components of two of the most im-portant FSIs identified in the survey: the ratios of grossNPLs to total assets and of NPLs net of provisions tocapital. Both FSIs had high average usefulness scoresand are compiled by more than 40 percent of the 93 respondents. The reason for their importance is thathigh levels of NPLs and inadequate provisioning canseverely affect the profitability and eventually the sol-vency of the banking system. However, the survey re-sults also suggest that there is as yet no internationalconsensus on sound practices for recognizing NPLsand on appropriate levels of loan loss provisioning.This lack of consensus severely limits the internationalcomparability of FSIs and impairs the ability of marketanalysts and regulators to monitor the financial system,particularly at the regional and global level.
The survey posed three supplementary open-endedquestions on NPLs—regarding the respondent’s sys-tem for recognizing NPLs; the rules governing the val-uation of provisions; and the rules on accrual of inter-est on NPLs. The results suggest that practices differconsiderably on the first two issues, although there isgreater convergence on the third one.
Of the 28 respondents that provided a sufficientamount of information, there are generally three differ-ent methods by which substandard loans are recog-nized. Four respondents leave the matter of recogni-tion to the discretion of banks—there is no specificsystem and banks have the responsibility to exercisetheir best judgment, which will then be assessed by ex-ternal auditors and supervisors on a periodic basis.Eight respondents employ qualitative criteria, basedupon well-defined weaknesses related to deteriorationin the borrower’s financial condition, inability of theborrower to generate cash flow to service debt in an or-derly manner, and deterioration in secondary sourcesof repayment such as guarantor support and loss in thevalue of collateral. Sixteen respondents employ quan-titative criteria, reflecting mainly the minimum periodof delinquency in payments before recognition. How-ever, this minimum period varies among the 16 re-spondents. Eleven respondents adopt a minimumdelinquency period of 90 days, the most prevalent cri-terion. Three respondents adopt a tighter standard of30 days; one respondent adopts a looser standard of180 days; and one does not specify a minimum periodbut adopts the criterion of a “past due” exceeding 20
percent of exposure to the borrower as constituting anonperforming loan.
On loan provisioning, 5 of the 24 respondents re-porting a sufficient amount of information leave the ex-tent of provisioning to the institution’s discretion orbest judgment. Four impose a qualitative criterion re-lated to the estimated realizable value of the loan, suchas the face value of the loan less the market value ofcollateral or the potential amount that can reasonablybe deemed collectible. Fifteen respondents impose spe-cific minimum standards, with an increasing level ofprovision depending on the degree of impairment ofthe loan. However, these minimum standards again dif-fer across respondents. For the three respondents using30 days of payment delinquency to recognize impair-ment, one specifies 20 percent, another 25 percent, andthe third 30 percent as minimum required provisions.For the five respondents using 90 days as the criterionfor impairment, one imposes 15 percent, two 20 per-cent, and two 25 percent as minimum required provi-sions. The respondent using 180 days as the impair-ment criterion specifies a 20 percent minimumprovision. For the six respondents using qualitative criteria, three impose 20 percent, two impose 25 per-cent, and one imposes 30 percent as minimum requiredprovisions.
There is greater convergence on the recognition ofaccrued interest for impaired loans. Of the 20 respon-dents providing a sufficient amount of information, 15require the cessation of interest accrual on NPLs. Twoallow recognition of accrued interest for substandardloans but require provisions for the amount accrued.Two allow accrued interest to be recorded in suspenseaccounts. One allows interest to be accrued and re-flected in the profit and loss account until it becomesvery probable that the interest will not be paid.
The Basel Committee on Banking Supervision hastaken up the task of setting standards for recognition ofsubstandard loans and for determining loan loss provi-sioning. The Committee has called for the timelyrecognition and measurement of impaired loans to bemade in accordance with documented policies and onthe basis of fundamental accounting concepts, and foradequacy of provisions to absorb the estimated lossesassociated with the loan portfolio. The Committee hasalso recommended that interest accrual should ceasewhen a loan becomes impaired or, if the accrual is con-tinued, that a provision for the full amount of the ac-crual be made.
VIII COMPILATION AND DISSEMINATION PRACTICES
• Consolidation practices for foreign branches andsubsidiaries differ (see section below). Withineach country, some FSIs use global consolidationsdrawn from supervisory data, while other FSIsuse national consolidations drawn from statisticalsources. Overall, however, some internationalconformity in consolidation exists because of therather widespread use of national consolidations;
• Valuation practices for financial instruments dif-fer (see section below). Key issues include thelimited use of market valuations for debt securi-ties and shares, and diverse practices for on-bal-ance-sheet recognition of derivatives, repurchaseagreements, and securities lending;
• Different rules exist for revaluing foreign cur-rency positions. Although there appears to beconvergence in industrial countries toward use ofmarket exchange rates in revaluing foreign currency-denominated positions, continued useof official rates in a number of emerging and de-veloping countries might hinder the comparabil-ity of FSIs.
The list of issues above indicates that practices arediverse and that cross-country comparison of FSIs ischallenging. International harmonization of FSIswould be a significant undertaking.
In January 2000, the Executive Board of the IMFdecided that a two-pronged strategy for promotingthe international comparability of FSIs would bepursued, in which initial work would use existing,unharmonized data, but over time efforts would bemade to foster greater harmonization of FSIs. Toallow users to evaluate data, descriptions (meta-data) of the accounting and statistical standards andpractices used should accompany dissemination ofFSIs.
Consolidation
The survey sought information on country prac-tices for consolidating information on foreignbranches and subsidiaries of financial institutionsinto single accounting statements or statistical re-ports. A key issue is whether data are compiled usinga national or global consolidation. A national consol-idation focuses on bank operations within the na-tional boundaries, which is the main policy focus ofnational authorities, whereas a global consolidationcaptures information on the global risks and finan-cial strengths and exposures of the worldwide enter-prise. Different areas of analysis might require dif-ferent types of consolidation.
The survey found strong differences in practicesby type of economy. Respondents in developingcountries adhered overwhelmingly to a national resi-
dency consolidation basis for most FSIs. This possi-bly reflects that banks headquartered in many devel-oping countries have few or no nonresident branchesor subsidiaries. It might also reflect limited supervi-sory infrastructures that could not effectively moni-tor and supervise nonresident operations. To someextent, respondents in emerging countries also re-ported this adherence to the use of national consoli-dations. In industrial countries, supervisors usedglobal consolidations most often, but also reportedthat both global and national consolidation data wereavailable for numerous FSIs.100
The survey also found differences in practices bycategory of FSI. These differences often reflectwhether the primary source data are supervisory orstatistical in nature. A summary of the practices bycategory of FSI is shown below.
• Capital adequacy. In industrial and emergingcountries, data are primarily from supervisorysources and are generally on a global consolida-tion basis, although both global and nationalconsolidations are often available. A number ofemerging economies and many developingeconomies only use national consolidations. Interms of worldwide totals, both consolidationsare available about equally, and for some FSIs upto one-quarter of respondents use both consoli-dations. A small number of countries report non-standard consolidations in their data, such as in-cluding nonresident branches but excludingnonresident subsidiaries.
• Asset quality (lending institutions). FSIs derivedfrom monetary statistics are overwhelmingly ona national consolidation basis; FSIs derived fromsupervisory sources are most often on a globalconsolidation basis, but in many cases are on anational basis or are available on both bases.
• Asset quality (borrowing institutions). FSIs arealmost exclusively on a national consolidationbasis because the underlying data are drawnfrom national macroeconomic statistical series.
• Profitability and competitiveness. Data are mostoften on a national consolidation basis or areavailable on both bases. However, a number ofcountries have data only on a global basis. Withinthe profitability category, nonstandard consolida-tions are used by a number of countries.
58
100The availability of FSI data on both consolidation basescould have some important advantages. For example, one respon-dent noted, “The survey does not address the main statistical as-pect, which is reconciliation between the home and host countryapproach, which will be viable if both supervisory and macroeco-nomic statistical data sources are used.”
Accounting, Regulatory, and Statistical Issues
• Liquidity. National consolidations are most com-mon, but the FSIs on liquid assets and averagematurities of assets and liabilities are often on aglobal basis. Global consolidation is not relevantfor some of the liquidity FSIs that refer solely tonational conditions.
• Sensitivity to market risks. National consolida-tions are most common. Global consolidationsare used to some extent in supervisory data in in-dustrial and emerging countries.
Valuation
The survey requested information on nationalpractices in valuing financial instruments, with sepa-rate information requested for foreign currency de-nominated-instruments. Respondents indicated, for
each major type of instrument, the type of valuationmethod used—historical cost, market value, thelower of cost or market, or other. The survey re-quested separate information for each major sourceof data—supervisory, statistical, and other. Table 8.3summarizes the results.
Broadly similar patterns exist for all three types ofsource data. For deposits and loans, respondentsmost commonly use historical valuations—in at leastthree-quarters of all responses in supervisory dataand in about nine out of ten cases in statisticaldata.101 In contrast, for securities (other than shares)and shares and other equity, no valuation methodclearly predominates, although respondents use mar-
59
Table 8.3.Valuation Practices Affecting FSIs by Data Source(All countries; number of responses)
Valuation Method for Foreign General Valuation Method Used Currency Denominated Instruments_________________________________ __________________________________
Frequency Conversion FrequencyMethod1 of revaluations2 exchange rate3 of revaluations4
H M L O B O E A G O B O1. Supervisory data sources
a. Deposits 62 6 1 5 47 9 39 5 24 2 61 5b. Loans 56 5 4 8 45 9 40 5 22 2 59 6c. Securities (other than shares) 20 23 11 17 51 14 39 5 20 3 50 12d. Shares and other equity 19 24 12 15 54 12 37 4 22 4 51 12e. Financial derivatives 9 30 1 13 37 14 33 4 14 3 36 13f. Miscellaneous receivables/payables 52 7 4 6 43 11 37 5 21 3 56 7g. Nonfinancial assets 41 9 8 13 42 15 32 4 21 6 49 8
2. Statistical data sourcesa. Deposits 42 4 0 1 29 6 27 2 17 2 36 9b. Loans 40 3 0 4 27 7 27 2 15 2 33 10c. Securities (other than shares) 14 19 7 7 31 10 29 2 13 2 34 10d. Shares and other equity 14 20 6 5 30 9 27 2 13 2 32 10e. Financial derivatives 8 18 2 5 20 11 22 2 9 3 23 11f. Miscellaneous receivables/payables 35 3 3 1 24 7 25 2 13 2 32 8g. Nonfinancial assets 22 8 3 10 28 8 24 2 12 2 32 7
3. Other data sourcesa. Deposits 9 2 0 1 8 0 7 0 4 1 10 1b. Loans 10 1 0 2 8 1 7 0 3 1 9 1c. Securities (other than shares) 3 6 1 1 8 2 7 0 4 1 9 2d. Shares and other equity 4 6 0 1 8 2 7 0 4 1 9 2e. Financial derivatives 1 5 0 1 5 2 6 0 2 1 6 2f. Miscellaneous receivables/payables 9 1 0 1 8 0 6 0 3 1 8 1g. Nonfinancial assets 5 3 1 2 7 1 6 0 3 0 7 1
1H = Historic cost; M = Market price/fair value; L = Lower of cost or market; O = Other.2B = On-balance-sheet date; O = Other.3E = Market rate (end period);A = Market rate (period average); G = Official rate; O = Other.4B = On-balance-sheet date; O = Other.
101Use of historical valuations is in accordance with interna-tional statistical standards.
VIII COMPILATION AND DISSEMINATION PRACTICES
ket values more often than the other valuation ap-proaches. For example, market values for shares andother equity are used in 40 percent of all cases, his-torical valuations in 29 percent of cases, and thelower of cost or market and other valuations in 14and 17 percent of cases, respectively. For financialderivatives, respondents use market valuations mostoften, with supervisors also reporting fairly commonuse of “other” valuations, which they sometimes in-dicated were hedge valuations. Historical valuationspredominate in miscellaneous receivables andpayables and in nonfinancial assets, but use of theother three types of valuations is not uncommon.
On the translation of the value of foreign cur-rency-denominated instruments into domestic cur-rency equivalents, respondents use end-of-periodexchange rates most often for all types of financialinstruments. A large minority of emerging and de-veloping countries reported that they used officialexchange rates. Foreign currency positions wererevalued most often at the rate applying on the balance sheet closing date. However, revaluationsof foreign currency positions at other frequencieswere not uncommon for securities (other thanshares), shares and other equities, and financial derivatives.
60
This chapter discusses the responses to the sup-plementary questions included in the User
Questionnaire to gather information on methods ofmacroprudential analysis, the institutional coverageof such analyses, preferences on the statistical pre-sentation of FSIs, and the use of business surveys tocomplement macroprudential analysis.
Macroprudential Research
The majority of the survey respondents (76 per-cent) reported doing macroprudential research oranalysis.102 Most respondents said they analyzedconditions in the banking sector, both at the aggre-gate level and at the level of the individual bank—al-though some analysts (mostly supervisors) also ana-lyzed conditions in subsets of banks, classified bydifferent categories and peer groups. Although theanalysis typically focused on the private banking sec-tor, several countries also reported separately moni-toring and analyzing developments in specific depos-itory institutions’ subsectors (e.g., state-owned banksand cooperatives), in the nondepository institutions’sector and subsectors, and in financial markets.
Most of the analysis was based on individual bankprudential data (consistent with the higher responserate among supervisors) derived from both on-siteand off-site inspections. However, the prudentialdata were often supplemented with macroeconomicand market information (especially the evolution ofasset prices) and, in a few cases, with data on thecondition of debtors.
Most respondents mentioned using CAMELS-type frameworks to analyze institutions but manyalso used statistical models, particularly early warn-ing models and models based on descriptive statis-tics such as correlations and trends in key indicators(e.g., credit growth and asset quality). In addition,
some respondents used time series models whileseveral others used qualitative analysis and stresstests, and a few used analytical frameworks such asthe financial accelerator model.103 The primary ob-jective of the analysis was the assessment of risks,covering equally credit, interest rate, foreign ex-change, liquidity, and macroeconomic risks.
The analysis was sometimes published as part ofan agency’s annual report or as a stand-alone docu-ment—particularly when it was performed on the fi-nancial system as a whole or on a particular sectorwithin the system. However, the information wasusually used solely for internal evaluations.
Coverage of Financial Institutions
Importance of Nondepository Financial Institutions
About 80 percent of the respondents reported thatinformation on nondepository financial institutions,markets, and activities was important to the overallanalysis of financial sector soundness. On nondepos-itory financial institutions,104 the majority of the re-spondents were most interested in information on in-surance corporations and pension funds, followed byother financial intermediaries (Figure 9.1). Respon-dents viewed many of these institutions as playingan important role in financial intermediation andpossibly in contagion. Several respondents men-tioned the importance of specialized financial inter-mediaries such as venture capital funds for advancedeconomies; and microcredit institutions and devel-opment banks or funds for developing countries.
IX Analytical Frameworks and Research
61
102Of those who reported doing some sort of research, 61 per-cent were supervisors, 25 percent were policy or research ana-lysts, and 14 percent were market or other participants. Thesepercentages are similar to the relative weight of each group in theresponse sample.
103Financial accelerator models are based on informationasymmetries between borrowers and lenders. They postulate thatwhen economic conditions are depressed and corporate net worthis low, access to credit is reduced even for worthwhile borrowers.When conditions improve and corporate net worth increases, re-newed access to credit by borrowers adds to the economic stimu-lus. In both cases, the effects are procyclical. See also Chapter IV.
104Defined as insurance corporations and pension funds, otherfinancial intermediaries, and financial auxiliaries in line with theIMF’s Monetary and Financial Statistics Manual.
IX ANALYTICAL FRAMEWORKS AND RESEARCH
Some respondents noted the importance of informa-tion on financial conglomerates, especially thosethat included insurance companies.
On financial markets, about 90 percent of those re-sponding on the issue indicated that data on the secu-rities markets (public and private debt and equitymarkets) were important.105 A few thought that infor-mation on foreign exchange markets (16 percent) andderivatives markets (6 percent) was also important.
Several respondents noted that borrower informa-tion (indebtedness and asset-liability mismatches)was useful as it provided some indication on emerg-ing credit quality trends and risks in the corporate,household, or foreign sectors. Some respondentssaid that they paid particular attention to large corpo-
rations while a few others mentioned the importanceof monitoring other financial activity, such as thefunctioning of payment, settlement, and clearingsystems. In addition, some respondents emphasizedthat qualitative information—such as the thorough-ness of supervision and the transparency of financialpolicies—was important to the overall assessment offinancial sector stability.
Disaggregation of “Depository Corporations” into Subsectors
Almost 60 percent of the respondents thought thatmore disaggregated information on depository cor-porations was needed, particularly breakdowns byownership, function, exposure to risk (e.g., geo-graphical, asset type, borrower type, etc.) and size(Figure 9.2). A few respondents felt that disaggre-gated data that highlighted distributions among
62
105The types of data mentioned included trading volumes, bid-ask spreads, and credit spreads.
60
80
20
0
40
All Responses
Insur
ance
and p
ensio
ns
Oth
er fin
ancia
l
inter
mediar
ies
Finan
cial a
uxilia
ries
Marke
ts
Oth
er fin
ancia
l
activ
ities
Insur
ance
and p
ensio
ns
Oth
er fin
ancia
l
inter
mediar
ies
Finan
cial a
uxilia
ries
Marke
ts
Oth
er fin
ancia
l
activ
ities
Insur
ance
and p
ensio
ns
Oth
er fin
ancia
l
inter
mediar
ies
Finan
cial a
uxilia
ries
Marke
ts
Oth
er fin
ancia
l
activ
ities
Insur
ance
and p
ensio
ns
Oth
er fin
ancia
l
inter
mediar
ies
Finan
cial a
uxilia
ries
Marke
ts
Oth
er fin
ancia
l
activ
ities
60
80
100 100
20
0
40
Supervisor
60
80
100
20
0
40
60
80
100
20
0
40
Policy/Research Market Participant/Other
Source: IMF Survey on the Use, Compilation, and Disseminationof Macroprudential Indicators.
Figure 9.1. Institutional Coverage of Analysis(As a percentage of total responses per category)
Figure 9.2. Factors Used to Identify KeySubsectors(As a percentage of total responses per category)
60
80
100
20
0
40
All Responses
Func
tion
Size
Owne
rship
Expo
sure
Func
tion
Size
Owne
rship
Expo
sure
Func
tion
Size
Owne
rship
Expo
sure
Func
tion
Size
Owne
rship
Expo
sure
60
80
100
20
0
40
Supervisor
60
80
100
20
0
40
Policy/Research
60
80
100
20
0
40
Market Participant/Other
Source: IMF Survey on the Use, Compilation, and Disseminationof Macroprudential Indicators.
Norms, Benchmarks, and Thresholds
banks or allowed for peer group analysis was alsouseful; one respondent felt that the breakdown ofbanks should be as fine as possible to enable isola-tion of distinctive activity patterns. Several stressedthat the type of disaggregation would depend on theissue being analyzed, however.
Almost 30 percent of all respondents (about halfof those who felt that more disaggregation was use-ful) mentioned that they analyzed or would like toanalyze institutions by ownership characteristics(e.g., domestic versus foreign, private versus state-owned, and publicly held stock versus privately heldequity). Of these respondents, almost all stated that abreakdown between domestic and foreign institu-tions was useful, with some saying that the domes-tic/foreign distinction was important because foreigninstitutions might operate under different regulatoryand supervisory regimes. At the same time, a quarterof the respondents stated that a breakdown betweenprivate and state-owned institutions was important.
About 20 percent of the respondents said that dis-aggregation by function or exposure was useful. Thefunctions most often mentioned were commercialbanking, universal banking, and specialized banking(especially mortgage lending and, to a lesser extent,development lending). About 80 percent of the re-spondents interested in disaggregation by exposureindicated that they would like information on inter-nationally active banks. Sixteen percent wanted dis-aggregated information on offshore banks, while an-other 16 percent wanted information on banksdisaggregated by their geographical market.
Only about 7 percent of respondents mentioned thatdisaggregating the sector by size or separating outsystemically important institutions was useful. How-ever, respondents may have underemphasized thisfactor since it was the subject of a separate question.
Systemically Important Institutions
Almost 60 percent of the respondents reporteddoing some evaluation of systemically important in-stitutions. Supervisors tended to be more concernedabout such institutions—two-thirds of them reportedthat they evaluated the condition of these institu-tions, as opposed to less than half of market partici-pants and about half of the government policy or re-search analysts.
Most respondents reported using a measure of size(of assets and/or deposits) to ascertain the impor-tance of an institution. Sometimes size was coupledwith other criteria—for instance, exposure to certainrisks (such as foreign exchange risk), complexity oftransactions, or complexity of ownership structure.However, some respondents only mentioned risk ex-posure, or used legal or prudential definitions, whileothers evaluated all institutions by sector or a partic-
ular category—which indicated that all institutionswithin a particular classification (e.g., problembanks, deposit-taking institutions, institutions withinsured deposits, commercial banks, and interna-tional banks) were sometimes considered systemi-cally important. This was often the case in countrieswith small, developing, or concentrated markets.
Many respondents said that the techniques used toevaluate the condition of systemically important insti-tutions were similar to those used to evaluate other in-stitutions. Most mentioned using the CAMELSframework or ratio analysis, while some used earlywarning models, other statistical models (e.g., Valueat Risk), and market assessments (e.g., ratings) to in-form their evaluations. Many respondents also usedtechniques such as increased supervision, includingincreased on-site examinations, reports from manage-ment, meetings with management, and external au-dits. Among the variables stressed by the respondentsas important in their evaluations were interbank activ-ity, liquidity, large exposures, foreign exchange expo-sure, consolidated positions for institutions that arepart of a financial group, and risk management prac-tices (including assessing internal models).
Of the respondents that evaluated systemically im-portant institutions, a slight majority said that the in-stitutions were not subject to enhanced statistical ordisclosure requirements, although some stressed thatthey were nonetheless subject to more intense super-vision. Of the respondents that mentioned enhancedstatistical or disclosure requirements, most requiredmore frequent, extensive, or detailed reporting, aswell as more frequent on-site examinations. Manyrespondents did not address this part of the question,however, making the results difficult to interpret.
Norms, Benchmarks, and Thresholds
Many respondents reported that specific norms,benchmarks, or thresholds were not used in macro-prudential analysis. While some of them were con-sidering using norms and benchmarks in the future,others preferred using comparisons with peer groupcountries to establish relative rankings.
Among those who reported using norms andbenchmarks for FSIs, some highlighted their criticalrole in guiding interpretation of the indicators. Forthis purpose, benchmarks were constructed in anumber of ways, including (1) historical averages,(2) bank supervisors’ prudential thresholds appliedat the aggregate level, (3) trigger points, (4) cross-country comparisons, and (5) criteria constructedfrom econometric studies.
Many respondents mentioned that benchmarkswere widely used in the implementation of pruden-tial standards, however. Since the majority of re-
63
IX ANALYTICAL FRAMEWORKS AND RESEARCH
spondents had implemented the recommendationsfrom the Basel Committee on Banking Supervision,the Basel recommendations in an aggregate formwere commonly used as benchmarks. Some respon-dents also mentioned international best practice asthe basis for forming their benchmarks. Overall,many respondents had adopted benchmarks orthresholds for capital adequacy ratios, liquidity, for-eign exchange exposures, and reserve requirements.However, warning level thresholds were applied pri-marily to individual banking institutions rather thanto the system as a whole.
Presentation
Generally, the majority of respondents preferredthe use of ratios and growth rates in presenting theirFSIs. However, many respondents also felt that thepreferred mode of presentation depended on the par-ticular FSI in question and the type of analysis beingconducted. For example, for sectoral aggregates, itwas useful to have weighted averages as well as sim-ple averages, accompanied by the frequency distrib-ution of institutions according to range of values ofthe indicators.
In this connection, some respondents noted thatmeasures of dispersion (standard deviations, his-tograms, Gini indices, etc.) could be particularlyuseful in presenting FSIs because they allowed theanalyst to identify outliers, trends in concentration,or tiering in markets, etc., which could be relevantfor the analysis of financial stability.
Figure 9.3 contains a breakdown of responses bymode of presentation and by type of user. The cate-gory “depends on FSI” is not exclusive—that is,some respondents identified several preferred modesof presentation but nonetheless indicated that it de-pended on the FSI or the type of analysis. The N/Acolumn presents the percentage of responses thatwere either not applicable or not completed.
Composite Measures106
Overall, the proportion of respondents that re-ported using composite measures (36 percent) wasonly slightly less than the proportion that did not use
them (38 percent). However, this result obscures thefact that there was substantial variation across usertypes. For example, while 41 percent of supervisorsreported using composite measures, only 29 percentof respondents engaged in policy/research and 23percent of market participants/others said that theyused such measures. Furthermore, 25 percent of allrespondents either said that they were not familiarwith the concept or the question was not applicable,or simply did not respond. A few mentioned thatthey were considering the use of such measures inthe future, however. One respondent, for instance,replied that there were plans to establish compositemeasures of the condition of the financial system, al-though none of the prototypes had yet been adopteddue to their instability.
64
106The possibility of developing a composite indicator of finan-cial system soundness was discussed at the 1999 ConsultativeMeeting on macroprudential indicators. There was a general sensethat the complex reality of financial markets may not lend itself tobeing captured in such indicators. In particular, composite indica-tors could prove simplistic and potentially misleading, as they mayconceal or misrepresent problems by offsetting positive and nega-tive signals from different individual components.
Figure 9.3. Presentation of FSIs(As a percentage of total responses per category)
60
80
20
0
40
All Responses
Single
point
estim
ates
Ratios
Growth
rate
Measu
res o
f disp
ersio
n
Stand
ard de
viatio
ns
Depen
ds o
n MPI N/A
Single
point
estim
ates
Ratios
Growth
rate
Measu
res o
f disp
ersio
n
Stand
ard de
viatio
ns
Depen
ds o
n MPI N/A
Single
point
estim
ates
Ratios
Growth
rate
Measu
res o
f disp
ersio
n
Stand
ard de
viatio
ns
Depen
ds o
n MPI N/A
Single
point
estim
ates
Ratios
Growth
rate
Measu
res o
f disp
ersio
n
Stand
ard de
viatio
ns
Depen
ds o
n MPI N/A
60
80
20
0
40
Supervisors
60
80
20
0
40
Policy/ResearchOfficials
60
80
20
0
40
Market Participants/Others
Source: IMF Survey on the Use, Compilation, and Disseminationof Macroprudential Indicators.
Business Surveys
Among the respondents using composite mea-sures, most used single point estimates, ratios, andgrowth rates to construct them. Many stated thatcomposite measures were based on the compileddata from balance sheets, income statements, andother statistical reports. Some countries also re-ported using early warning system-type models—which mostly used macroeconomic variables and notFSIs—to produce a composite measure. These mod-els would make these measures leading indicators ofa potential financial crisis, instead of concurrent in-dicators of the condition of the financial system.
Business Surveys
Overall, about half of all respondents reported thatthey made use of business survey results—qualita-tive or quantitative measures of business expecta-tions and potential leading indicators of instability—to supplement macroprudential analysis. The groupmaking the most use of business surveys (with 56percent) was policy/research officials involved in theanalysis of financial system soundness. About halfof all supervisors and market participants/othersmentioned that they used business surveys.
65
Identification of Core and Encouraged Sets of FSIs
Empirical and analytical evidence on the useful-ness of specific FSIs as well as the results of the sur-vey on macroprudential indicators were used toidentify core and encouraged sets of FSIs. The IMFExecutive Board discussed these FSI sets at a meet-ing in June 2001.107
To identify these sets, six criteria were applied:
• focus on core markets and institutions;
• analytical significance;
• revealed usefulness;
• relevance in most circumstances (i.e., not coun-try-specific);
• availability; and
• parsimony (achieving the maximum informa-tion content with a limited number of FSIs).
Ideally, indicators included in the core set shouldalso be comparable across countries—which wouldbe possible if countries adhere to internationallyagreed prudential, accounting, and statistical stan-dards—to facilitate monitoring of the financial sys-tem, not only at the national but also at the globallevel. The latter is important in view of the magni-tude and mobility of international capital, and therisk of contagion of financial crises from one coun-try to another. Advancing international comparabil-ity of FSIs and convergence toward best practiceare important goals for further work in this area. Inthe near term, most of these FSIs can be compiledfrom unharmonized national data that reflect differ-ent supervisory and accounting practices. Over thelonger term, if FSIs are to be comparable acrosscountries, it will be important to address harmo-nization of underlying accounting standards, aggre-gation and consolidation issues, and asset valua-
tion, classification, and provisioning rules. Theusefulness of the core set of FSIs can be enhancedif national authorities provide, along with the FSIs,descriptions of the concepts and compilation prac-tices used in their construction (i.e., the metadata).Metadata are particularly important in the absenceof harmonization and resolution of the issues men-tioned above.
Based on the criteria listed above, two key sets ofFSIs were identified:108
• The core set of 15 indicators, listed in Table 10.1,is focused on the banking sector, and is consid-ered to fulfill the six selection criteria mentionedabove. (1) All indicators included in the core setfocus on core institutions—the banking sector.(2) The analytical relevance of the five aspects ofbank vulnerability covered by the core set, aswell as of individual FSIs, is well documented inChapter III of this paper.109 (3) All indicatorswith usefulness ratings above 3.5—as identifiedin the survey—are included in this set.110 (4) TheFSIs in the core set are meaningful in most coun-try circumstances—a conclusion that is sup-ported by both analytical evidence and the resultsof the survey. (5) Compilation appears broadlyfeasible, given the relatively large number ofcountries that now compile these indicators ortheir components.111 (6) It provides data coveringall main categories of bank risk, within a limitedset of indicators. The core set should have prior-ity in future work on FSIs.
X Concluding Remarks
66
107A summary of the Board discussion can be found athttp://www.imf.org/external/np/mae/fsi/2001/eng/062501.htm.
108An explanation of terms used to define the indicators can befound in Appendix I.
109Durations of assets and liabilities are examples of indicatorsthat are highly relevant analytically—which is why they are in-cluded in the core set—although their compilation is not wide-spread. Appendix I offers alternative indicators in cases wheredurations are not easily available, at least in the short term.
110Two FSIs with usefulness ratings above 3.5 were not includedon parsimony grounds as they capture aspects of bank vulnerabilityalready covered by other FSIs. Some FSI definitions vary slightlyfrom the ones used in the FSI Survey and they should be consid-ered preliminary pending further work on the definition of FSIs.
111However, many countries would have to adjust existing datacompilation programs to compile the core FSIs.
Directions for Further Work
• The encouraged set of 26 indicators, listed inTable 10.2, includes additional indicators fordeposit-taking institutions as well as data onother institutions and markets that are relevantin assessing financial stability. FSIs in this setare considered to fulfill some, but not all, ofthe selection criteria. FSIs on deposit-takinginstitutions included in the encouraged set maybe particularly important in certain countries,but less so in others. In the case of nonbank fi-nancial intermediaries, further work is neededto obtain meaningful indicators of their healthand soundness; the FSIs included in the setsimply aim at capturing the importance of thissector in the financial system. Although FSIs for the corporate sector and real estatemarkets emerge from both analytical studiesand the survey as critical to assessments of fi-nancial vulnerabilities, their compilation—in terms of number of countries and cover-age—remains very limited. As a result of theselimitations, the encouraged set is somewhatmore tentative.
Working with two sets of FSIs—a core set and anencouraged set—avoids a one-size-fits-all ap-proach, and provides a degree of flexibility in theselection of indicators that are most relevant to as-sessing vulnerabilities in country-specific circum-stances. Indicators of the core set can be combinedwith selected, additional indicators of the encour-aged set that might be of particular relevance in thecountry concerned, depending on its level of finan-cial development, institutional structure, and re-gional circumstances.
Notably, within the encouraged set, indicators ofthe corporate sector and real estate markets may beconsidered as a priority in light of their analyticalsignificance for assessing financial vulnerabilitiesin a wide variety of circumstances, and their com-pilation should be encouraged. The exact method-ology of compilation, and the number and coverageof corporate indicators, will need to take into ac-count the specific circumstances of countries. Assoon as sufficient progress has been made in theseareas, some of these indicators should be includedin the core set.
Directions for Further Work
This paper has discussed the quantitative and, tosome extent, qualitative elements of the macropru-dential analysis of financial systems. This is ongoingwork—at the IMF and elsewhere—and it is encour-aging to see the growing interest in this subjectamong central banks and other national and interna-tional official institutions around the world.
The review highlights that work on measuring andanalyzing FSIs has advanced substantially in recentyears. At the same time, it points to specific areaswhere more work is needed.
• Definitional guidelines are necessary to arrive atclear definitions of the indicators, thereby ad-vancing international comparability and conver-gence toward best practice. Looking ahead, theIMF is working to produce a Compilation Guideon Financial Soundness Indicators in order tofacilitate, and encourage, national compilation of
67
Table 10.1. Core Set of FSIs
Capital adequacy Regulatory capital to risk-weighted assetsRegulatory tier I capital to risk-weighted assets
Asset quality Nonperforming loans to total gross loansNonperforming loans net of provisions to capitalSectoral distribution of loans to total loansLarge exposures to capital
Earnings and profitability Return on assets (net income to average total assets)Return on equity (net income to average equity)Interest margin to gross incomeNoninterest expenses to gross income
Liquidity Liquid assets to total assets (liquid asset ratio)Liquid assets to short-term liabilities
Sensitivity to market risk Duration of assetsDuration of liabilitiesNet open position in foreign exchange to capital
X CONCLUDING REMARKS
the indicators identified above. The Guidewill provide both definitions of, and compilationguidance for, FSIs, particularly the core set.
• Indicators of nonbank financial institutions andmarkets need to be developed that reflect thespecificities of each market segment—financecompanies, securities firms, collective invest-ment schemes, insurance companies, and oth-ers. Market liquidity indicators are also impor-tant and need to be uniformly defined andregularly collected.
• With regard to the corporate sector, while it ispossible to identify a set of useful indicators,data availability remains a key obstacle, bothat the aggregated and disaggregated level, andparticularly for nonlisted companies, which are a significant share of the sector in manycountries.
• Efforts to develop better indicators of financialinstitutions’ exposure to the household and real
estate sectors should be stepped up, notably inthe direction of more transparent information oncredit outstanding to these sectors.
• Analytical tools that use FSIs need to be furtherdeveloped, including more refined methods ofaggregate stress testing of financial systems.
• The development of benchmarks for the levelof FSIs would help to monitor and interpret de-velopments in the financial system. In particu-lar, guidance would be useful to help to deter-mine the relevant threshold that makes thelevel of, or change in, an indicator a source for concern. A high degree of flexibility is re-quired in the use of benchmarks, as they aremost often country-specific and can changeover time.
Monitoring and analysis of FSIs are just one ele-ment in an overall assessment of financial stability.Other elements include analyses of macroeconomicdevelopments, market-based data such as stock prices
68
Table 10.2. Encouraged Set of FSIs
Deposit-taking institutions Capital to assetsGeographical distribution of loans to total loansGross asset position in financial derivatives to capitalGross liability position in financial derivatives to capitalTrading income to total incomePersonnel expenses to noninterest expensesSpread between reference lending and deposit ratesSpread between highest and lowest interbank rateCustomer deposits to total (noninterbank) loansForeign currency-denominated loans to total loansForeign currency-denominated liabilities to total liabilitiesNet open position in equities to capital
Market liquidity Average bid-ask spread in the securities market1
Average daily turnover ratio in the securities market1
Nonbank financial institutions Assets to total financial system assetsAssets to GDP
Corporate sector Total debt to equityReturn on equity (earnings before interest and taxes toaverage equity)Earnings before interest and taxes to interest andprincipal expensesCorporate net foreign exchange exposure to equityNumber of applications for protection from creditors
Households Household debt to GDPHousehold debt service and principal payments to income
Real estate markets Real estate pricesResidential real estate loans to total loansCommercial real estate loans to total loans
1Or, in other markets that are most relevant to bank liquidity, such as foreign exchange markets.
Directions for Further Work
and credit ratings, structural information on the finan-cial sector, and—last, but not least—qualitative assessments, in particular assessments of observanceof relevant international standards and codes. Theseelements, which feed into macroprudential analysis,will help to identify various dimensions of risks aswell as the capacity of the system to cope with and
manage these risks, thereby helping to form a judg-ment on overall financial stability. Although thesetools still remain imperfect and continue to evolve,macroprudential analysis can reduce the incidence ofcrises by providing national authorities with a set oftools to comprehensively assess their financial sectorsand identify weaknesses at an early stage.
69
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This explanation of indicators included in thecore set and the encouraged set of FSIs is
provided to clarify this paper’s discussion. The terms may not correspond precisely to official defin-
itions or standards. The Compilation Guide on Fi-nancial Soundness Indicators will clarify the defi-nitions of the indicators included in Table A1.1below.
Appendix I Explanation of FSI Terms
73
Table A1.1. Explanation of FSI Terms
Depository Corporations (Core Set)
Regulatory capital to risk-weighted assets Capital as defined in the 1988 Capital Accord of the Basel Committee onBanking Supervision (and revisions) divided by risk-weighted assets. Capital isdefined using regulatory standards and does not correspond directly to capitalas shown in financial balance sheets. Risk-weighted assets equal the sum of eachcategory of asset (and on-balance-sheet equivalents of off-balance-sheetpositions) multiplied by a weight representing the credit risk associated witheach category.
Regulatory tier 1 capital to risk-weighted assets The Capital Accord (and revisions) defines three capital elements: tier 1—permanent shareholders’ equity and disclosed reserves; tier 2—undisclosedreserves, revaluation reserves, general provisions and loan-loss reserves, hybriddebt-equity capital instruments, and subordinated long-term debt (over fiveyears); and tier 3—subordinated debt (over two years original maturity).
Nonperforming loans to total gross loans Designed to capture the share of “problem” loans in the total loan portfolio.There is no standard definition of NPLs. In some countries, a loan is consideredto be nonperforming when the principal and/or interest payments on itaccording to the original terms of the loan agreement are past due (e.g., by 90days or more). Gross loans are used as the denominator as opposed to netloans, which deduct specific provisions (loan-loss reserves) from loans.
Nonperforming loans net of provisions to capital Compares NPLs and capital. NPLs are net of specific provisions (loan-lossreserves).
Sectoral distribution of loans to total loans1 Key sectors may include a dominant commodity export, or other sectors.Classification according to national accounts classifications is encouraged.
Large exposures to capital Exposure refers to one or more credits to the same individual/economic group.There is no standard definition of “large.” In some countries, it refers toexposures exceeding 10 percent of regulatory capital.
Return on assets Measures banks’ efficiency in using their assets. Can be calculated as net income(gross income less noninterest expenses) to average total assets.
Return on equity Measures banks’ efficiency in using their capital. Can be calculated as net incometo period average capital.
Interest margin to gross income Looks at profitability resulting from banks’ interest earning assets minus interestexpenses—that is, interest margin (or net interest income).
Noninterest expenses to gross income Compares administrative expenses and gross income (interest margin plusnoninterest income).
APPENDIX I
74
Table A1.1 (continued)
Depository Corporations (Encouraged Set)
Liquid assets to total assets (liquid asset ratio) Liquid assets, in general, refer to cash and assets that are readily convertible tocash without significant loss, often including government and central banksecurities.
Liquid assets to short-term liabilities Designed to capture the liquidity mismatch of assets and liabilities. A variety ofdefinitions are used at present.
Duration of assets Weighted average term-to-maturity of an asset’s (liability’s) cash flow, the Duration of liabilities weights being the present value of each future cash flow as a percent of the
asset’s full price.Alternative measures of interest rate sensitivity include: (1)average interest rate repricing period for assets and liabilities (period untilfinancial instruments are redeemed or the interest rates on them are reset orreindexed); and (2) average maturity of assets and liabilities.A currencybreakdown of duration helps to identify maturity mismatches in foreigncurrency.
Net open position in foreign exchange to capital Net on-balance-sheet and off-balance-sheet asset and liability positions in foreign currencies.According to the Basel Committee, net open positions ineach currency should be calculated as the sum of net spot position, net forwardposition, guarantees, net future income and expenses not yet accrued butalready fully hedged, net notional value of foreign currency options, and anyother item representing a profit/loss in foreign currencies.
Capital to assets Simple ratio of capital to total assets, without risk weighting.This is the inverseof the leverage ratio.
Geographical distribution of loans to total loans1 Loan exposure by foreign country or region.
Gross asset position in derivatives to capital The on-balance-sheet value of derivatives in an asset (or liability) position, plusGross liability position in derivatives to capital the fair value of off-balance-sheet derivatives in an asset (or liability) position.
Trading income to total income Designed to capture the share of banks’ income from trading activities, includingcurrency trading.
Personnel expenses to noninterest expenses Measures the incidence of personnel costs in total administrative costs.
Spread between reference lending and A simple measure of bank profitability as well as of efficiency and competition in deposit rates financial markets, it measures the difference (usually in basis points) between
representative rates.There is no standard definition of reference rates.
Spread between highest and lowest interbank rate Designed to capture banks’ own perception of problems facing banks withaccess to the interbank market.
Customer deposits to total (noninterbank) loans A simple measure of liquidity, it compares deposits to loans (excluding interbankactivity).
FX-denominated loans to total loans1 These indicators measure the relative size of these exposures.FX-denominated liabilities to total liabilities
Net open position in equities to capital Positions in each equity should be calculated as the sum of on-balance-sheetholdings of equities and notional positions in equity derivatives.
Market Liquidity
Average bid-ask spread in the securities market A measure of market tightness (the difference between prices at which amarket participant is willing to buy and sell a security).The specific market canbe that for Treasury bills and bonds, central bank bills, or other securities,depending on the particular conditions in the country.
Average daily turnover ratio in the securities As a measure of market depth, it is the volume of securities traded daily as a market percentage of total securities listed on an exchange.The indicator could be
calculated for a variety of markets.
Appendix I
75
Table A1.1 (concluded)
Nonbank Financial Intermediaries
NBFI assets to total financial system assets Captures the relative importance of NBFIs in a country’s total financial assets. Itcan be broken down by NBFI subsector.
NBFI assets to GDP Indicates the relative size of NBFIs in the economy. It can be broken down byNBFI subsector.
Nonbank Nonfinancial Corporations
Total debt to equity A measure of corporate leverage, it can be calculated as total debt to bookvalue of equity.
Return on equity Captures firms’ efficiency in using their equity. Can be calculated as EBIT(earnings before interest and taxes) to average equity.
Debt service coverage Measures firms’ capacity to cover their debt service payments. Can becalculated as EBIT to interest and principal expenses.
Corporate net FX exposure to equity Looks at firms’ exposure to foreign exchange risk. It can be calculated as thesum of net positions in each foreign currency.
Number of applications for protection from A measure of bankruptcy trends; it is influenced by the quality and nature of creditors bankruptcy and related legislation.
Households
Household debt to GDP Captures the overall level of household indebtedness (commonly related toconsumer loans and mortgages) as a share of GDP.
Household debt burden to income Measures households’ capacity to cover their debt payments (principal andinterest). Can be calculated as a share of total disposable income.
Real Estate Markets
Real estate prices Designed to capture price trends in the real estate market.There is no standarddefinition and various intracountry and subsectoral breakdowns are possible(e.g., industrial, commercial, retail, and residential).
Residential real estate loans to total loans Measures banks’ exposure to the real estate sector, with a focus on householdborrowers.There is no standard definition. May include mortgage lending and/orother loans collateralized by residential real estate.
Commercial real estate loans to total loans Measures banks’ exposure to the real estate sector, with a focus on corporateborrowers.There is no standard definition. May include loans for the purchaseof commercial real estate, loans to construction companies, and/or other loanscollateralized by commercial real estate.
1Data on credit, which is a more comprehensive concept than loans, can be used as an alternative to loans. Credit (assets for which the counterpartyincurs debt liabilities) includes loans, securities other than shares, and miscellaneous receivables.
S imple aggregation of balance sheets and in-come statements of individual institutions can
disguise important structural information, and it isoften necessary to supplement the aggregate datawith information on dispersion. For example, thecapital to asset ratio of a system is calculated by di-viding the total capital by total assets, which is es-sentially the average (or mean) capital to asset ratioof the system. If capital asset ratios were symmetri-cally distributed, this statistic would also conveyinformation about the middle capital asset ratio (themedian) as well as the most frequently observedcapital asset ratio (the mode). However, typicallythe distribution is not symmetric; hence, focusingon the mean values only may be misleading as themean can be affected by value of outliers—for ex-ample, one very strongly capitalized bank could bemore than offsetting many other undercapitalizedbanks.
Descriptive statistics on data dispersion provideways to supplement mean values with additional in-formation. Data skewness can be particularly useful,as it provides a measure of the size and direction ofasymmetry in the distribution of the observations.Positive skewness indicates that aggregation biasesthe results upwards (a substantial number of institu-tions are actually below the average), and the oppo-site is true for negative skewness. Skewness is zerowhen the distribution is symmetrical—that is, mean,median, and mode are equal. To get a sense of theproportional effect of the outliers, or the thickness ofthe tails, the kurtosis can also be calculated. Ways tocalculate the direction and degree of skewness andthe degree of kurtosis are discussed below.
Descriptive Statistics and Data Dispersion
Summary measures for a data set are often re-ferred to as descriptive statistics. Descriptive statis-tics fall into four main categories: (1) measures ofposition, (2) measures of variability, (3) measures ofskewness, and (4) measures of kurtosis. They can beuseful for beginning data analysis, for comparingmultiple data sets, and for reporting final results of asurvey.
Measures of position (or central tendency) de-scribe where the data are concentrated:
• Mean (first moment of the distribution, or x–) isthe mathematical average of the data and is acommon measure of central tendency.
• Median (Med) is the middle observation in adata set. The median is often used when a dataset is not symmetrical, or when there are outly-ing observations.
• Mode is the value around which the greatestnumber of observations are concentrated, or themost common observation.
Measures of variability describe the dispersion (orspread) of the data set:
• Range is the difference between the largest andthe smallest observations in the data set. Therange has limitations because it depends on onlytwo numbers in the data set.
• Variance (second moment of the distribution, orσ2) measures the dispersion of the distributionaround the mean, taking into account all datapoints.
• Standard Deviation (or σ) is the positive squareroot of the variance, and is the most commonmeasure of variability. Standard deviation indi-cates how close to the mean the observations are.
Measures of skewness indicate whether the dataare symmetrically distributed:
• Skewness (third moment of the distribution, orµ3) measures the degree of asymmetry of the dataset. Positive skewness indicates a longer right-hand side (tail) of the distribution; negative skew-ness a longer tail on the left. Distributions that aresymmetric have identical tails and thus no skew-ness. One easy way of determining skewness is tocompare the values of mean and the median rela-tive to the standard deviation:
x– – Medγ = _________σx
Appendix II Aggregation Issues
76
Appendix II
77
A more precise method to calculate skewness isthe Pearson coefficient:
n (xi – x–)3 . ni
µ3Σ __________
i=1 N— = _______________σ3 σ3
x
Measures of kurtosis indicate whether the data aremore or less concentrated toward the center:
• Kurtosis (fourth moment of the distribution, orµ4) measures the degree of flatness of the distri-
bution near its center, or equivalently the de-gree of thickness of the tails. It is large if thedistribution has sizeable tails that extend muchfurther from the mean than ± σ; kurtosis is zeroif the distribution is normal. A normalized mea-sure is:
n (xi – x–)4 . ni
µ4Σ __________
i=1 NK = — = _______________ – 3
σ4 σ4x
Appendix III Additional FSIs Identified byRespondents
78
The User Questionnaire asked respondents toindicate FSIs not covered in the survey that
they consider useful, or FSIs they use that differfrom those in the survey. Respondents identified arelatively small number of additional FSIs. Con-versely, few commented that the list of FSIs wastoo long.
As already noted in the body of the paper, addi-tional asset price information (real estate, equities,and bank equities) was requested most often, and anumber of respondents identified information on thedistribution of observations as being useful.
Some of the other additional FSIs identified arelisted below.
• Aggregate growth indicators for various types oflending;
• Distribution of loans by size of borrower;
• Indicators of the composition of liabilities (subor-dinated debt, guarantees, government credits,etc.);
• Turnover and spreads in securities repo andswaps markets;
• Number of banks and total assets by CAMELSranking;
• Ratings of banks and their distribution;
• More quickly available “flash indicators,” suchas bank and bond yields, that provide current as-sessments of markets;
• Developments in payments systems, includingcollateral held and liquidity.
Other observations by respondents
Respondents made a number of other observa-tions regarding FSIs and their compilation and dissemination.
• One concern expressed was that aggregation ofinformation on individual financial institutionscould result in the offsetting of positions of indi-
vidual units that could obscure the meaning ofsome FSIs.
• Several respondents said that regular compila-tion of a large range of FSIs might not justify theresource costs. One respondent said that finan-cial institutions were already subject to substan-tial data reporting requirements and would notwelcome new statistical demands. It was sug-gested that ad hoc compilation of FSIs could becarried out when needed.
• Several respondents said that many organiza-tions were working on financial stability issuesor closely related initiatives. Close cooperationamong parties working in the field was consid-ered desirable.
• One respondent suggested that the selection ofFSIs might wait until the completion of theBasel Committee’s work on the new capital ade-quacy framework.
• Several comments were made regarding theproper treatment of money market mutual fundsand whether they should be included within thedepository corporations sector, as done in thesurvey. It was noted that the risks faced bymoney market mutual funds could significantlydiffer from those faced by banking institutionsand therefore mutual funds might be excludedfrom the analysis or might be separately ana-lyzed. Alternatively, it was suggested that allmutual funds should have been covered in thesurvey because the greatest risks are likely to befaced by non-money market funds that tended toescape supervision by bank supervisors.
• Several countries commented that flexibilityshould be sought in presentation of macropru-dential information. One G-7 country com-mented that, “It is not possible to have uniformrules on the presentation of macroprudential in-dicators. At any rate, caution is advised in viewof the heterogeneity that may exist in terms ofnational concepts and calculation methods.”
Appendix IV Tables of Survey Results
79
Table A4.1. FSIs for which Components Are Extensively Compiled(Very useful FSIs—Group I—are in italics)
1.1 Basel capital adequacy ratio1.1a Ratio of Basel tier I capital to risk-weighted assets1.1b Ratio of Basel tier I + tier II capital to risk-weighted assets1.3 Ratio of total on-balance-sheet assets to own funds
2.1 Distribution of on-balance-sheet assets by Basel risk category2.4 Distribution of loans by sector2.4b Loans for investment in residential real estate2.5 Distribution of credit extended by sector2.6 Distribution of credit, by country or region2.7 Ratio of credit to related entities to total credit2.8 Ratio of total large loans to own funds2.9 Ratio of gross nonperforming assets to total assets2.10 Ratio of nonperforming loans net of provisions to total assets
3.1 Change in the number of depository corporations3.2 Ratio of profits to period-average assets (ROA)3.3 Ratio of profits to period-average equity (ROE)3.4 Ratio of net interest income to profits3.5 Ratio of trading and foreign currency gains/losses to profits3.6 Ratio of operating costs to net interest income3.7 Ratio of staff costs to operating costs3.8 Spread between reference lending and deposit rates3.9 Share of assets of the three largest depository corporations in total assets of depository
corporations
4.3 Ratio of liquid assets to total assets4.4 Ratio of liquid assets to liquid liabilities4.9 Ratio of central bank credit to depository corporations to their total liabilities4.10 Ratio of total customer deposits to total (noninterbank) loans4.11 Ratio of foreign currency customer deposits to total (noninterbank) foreign currency loans
5.1 Ratio of gross foreign currency assets to own funds5.2 Ratio of net foreign currency positions to own funds5.7 Ratio of gross positions in equities to own funds
APPENDIX IV
80
Table A4.2. SDDS Subscribers: Compilation and Dissemination of FSIs and Components1
Percent Percent Percent Percent Usefulness Compiling Disseminating Compiling Disseminating
FSI Score FSIs FSIs Components Components
1. Capital adequacy
1.1 Basel capital adequacy ratio 3.8 78 62 78 621.1a Ratio of Basel tier I capital to risk-weighted assets 3.6 74 48 74 481.1b Ratio of Basel tier I + tier II capital to risk-weighted
assets 3.4 76 48 76 481.1c Ratio of Basel tier I + II + III capital to risk-weighted
assets 3.0 46 28 46 28
1.2 Distribution of capital adequacy ratios (number of institutions within specified capital adequacy ratio ranges) 3.4 22 8 22 8
1.3 Ratio of total on-balance-sheet assets to own funds 3.1 40 18 80 60
2. Asset quality
(a) Lending institutions
2.1 Distribution of on-balance-sheet assets, by Basel risk-weight category 3.4 76 32 76 32
2.2 Ratio of total gross asset position in financial derivatives to own funds 2.9 28 10 50 16
2.3 Ratio of total gross liability position in financial derivatives to own funds 2.9 24 10 46 16
2.4 Distribution of loans, by sector 3.6 76 64 72 642.4a of which: for investment in commercial real estate 3.3 40 32 40 322.4b of which: for investment in residential real estate 3.3 56 48 56 482.5 Distribution of credit extended, by sector 3.5 48 36 54 422.6 Distribution of credit extended, by country or region 3.3 60 44 68 502.7 Ratio of credit to related entities to total credit 3.3 24 6 62 162.8 Ratio of total large loans to own funds 3.4 28 8 54 16
2.9 Ratio of gross nonperforming loans to total assets 3.9 46 32 80 582.10 Ratio of nonperforming loans net of provisions to
total assets 3.8 42 24 68 44
(b) Borrowing institutions
2.11 Ratio of corporate debt to own funds (“debt-equity ratio”) 3.5 24 16 48 36
2.12 Ratio of corporate profits to equity 3.3 22 14 48 362.13 Ratio of corporate debt service costs to total
corporate income 3.3 22 14 44 282.14 Corporate net foreign currency exposure 3.3 4 0 14 6
2.15 Ratio of household total debt to GDP 3.1 22 12 48 342.15a of which: mortgage debt to GDP 2.9 38 28 38 282.15b of which: debt owed to depository corporations to GDP 2.9 44 36 44 36
2.16 Number of applications for protection from creditors 2.7 22 18 22 18
3. Profitability and competitiveness indicators
3.1 Rate of change in number of depository corporations 2.6 40 30 60 503.3 Ratios of profits to period-average equity (ROE) 3.6 48 42 74 503.4 Ratio of net interest income to total income 3.5 44 30 82 643.5 Ratio of trading and foreign exchange gains/losses to
total income 3.3 36 24 74 543.6 Ratio of operating costs to net interest income 3.3 42 26 84 583.7 Ratio of staff costs to operating costs 3.1 42 28 82 563.8 Spread between reference lending and deposit rates 3.5 22 18 52 483.9 Share of assets of the three largest depository
corporations in total assets of depository corporations 2.8 38 18 72 32
4. Liquidity
4.1 Distribution of three-month local currency interbank rates for different depository corporations 2.9 18 8 18 8
Appendix IV
81
Table A4.2 (concluded)
Percent Percent Percent Percent Usefulness Compiling Disseminating Compiling Disseminating
FSI Score FSIs FSIs Components Components
4.2 Average interbank bid-ask spread for three-month local currency deposits 3.0 22 12 22 12
4.3 Ratio of liquid assets to total assets 3.4 40 20 70 344.4 Ratio of liquid assets to liquid liabilities 3.4 40 20 68 344.5 Average maturity of assets 3.3 16 6 30 144.6 Average maturity of liabilities 3.2 16 6 34 14
4.7 Average daily turnover in the treasury bill (or central bank bill) market 2.6 30 20 30 20
4.8 Average bid-ask spread in the treasury bill (or central bank bill) market 2.7 16 6 16 6
4.9 Ratio of central bank credit to depository corporations to depository corporations’ total liabilities 2.8 20 14 70 58
4.10 Ratio of customer deposits to total (noninterbank) loans 3.0 36 14 80 664.11 Ratio of customer foreign currency deposits to total
(noninterbank) foreign currency loans 2.8 26 14 68 48
5. Sensitivity to market risk indicators
5.1 Ratio of gross foreign currency assets to own funds 3.0 28 10 72 445.2 Ratio of net foreign currency position to own funds 3.3 28 10 50 18
5.3 Average interest rate repricing period for assets 3.0 26 2 26 25.4 Average interest rate repricing period for liabilities 3.0 26 2 26 2
5.5 Duration of assets 3.2 18 2 18 25.6 Duration of liabilities 3.2 18 2 18 2
5.7 Ratio of gross equity position to own funds 2.9 22 10 62 425.8 Ratio of net equity position to own funds 2.9 18 10 30 165.9 Ratio of gross position in commodities to own funds 2.3 10 4 26 125.10 Ratio of net position in commodities to own funds 2.4 14 6 24 10
1The denominator used in columns three and five is 50, the total number of SDDS countries as of December 2001.
APPENDIX IV
82
Table A4.3. Usefulness of FSIs by Type of User and Type of Economy
______________________________________________________________Supervisors________________________________________
Industrial Emerging Developing Average
1. Capital adequacy
1.1 Basel capital adequacy ratio 3.9 3.9 3.8 3.91.1a Ratio of Basel tier I capital to risk-weighted assets 3.8 3.6 3.7 3.71.1b Ratio of Basel tier I + tier II capital to risk-weighted assets 3.4 3.7 3.6 3.61.1c Ratio of Basel tier I + II + III capital to risk-weighted assets 3.1 3.3 3.2 3.2
1.2 Distribution of capital adequacy ratios (number of institutions within specified capital adequacy ratio ranges) 3.3 3.4 3.2 3.3
1.3 Ratio of total on-balance-sheet assets to own funds 2.8 3.3 3.1 3.1
2. Asset quality
(a) Lending institutions
2.1 Distribution of on-balance-sheet assets, by Basel risk-weight category 3.2 3.6 3.5 3.52.2 Ratio of total gross asset position in financial derivatives to own funds 2.5 3.0 2.4 2.72.3 Ratio of total gross liability position in financial derivatives to own funds 2.5 2.9 2.4 2.7
2.4 Distribution of loans by sector 3.6 3.6 3.5 3.62.4a of which: for investment in commercial real estate 3.3 3.3 3.2 3.32.4b of which: for investment in residential real estate 3.3 3.3 3.2 3.3
2.5 Distribution of credit extended by sector 3.4 3.6 3.7 3.62.6 Distribution of credit extended by country or region 3.3 3.1 2.8 3.12.7 Ratio of credit to related entities to total credit 3.1 3.6 3.6 3.5 2.8 Ratio of total large loans to own funds 3.4 3.7 3.7 3.6
2.9 Ratio of gross nonperforming loans to total assets 3.9 3.8 3.9 3.9 2.10 Ratio of nonperforming loans net of provisions to total assets 3.9 3.7 3.8 3.8
(b) Borrowing institutions
2.1I Ratio of corporate debt to own funds (“debt-equity ratio”) 3.4 3.5 3.3 3.4 2.12 Ratio of corporate profits to equity 3.2 3.4 3.3 3.3 2.13 Ratio of corporate debt service costs to total corporate income 3.3 3.3 3.0 3.2 2.14 Corporate net foreign currency exposure 3.2 3.3 3.1 3.2
2.15 Ratio of household total debt to GDP 3.1 2.8 2.8 2.9 2.15a of which: mortgage debt to GDP 3.0 2.7 2.8 2.8 2.15b of which: debt owed to depository corporations to GDP 3.0 2.7 3.0 2.9
2.16 Number of applications for protection from creditors 2.6 2.8 2.6 2.7
3. Profitability and competitiveness
3.1 Rate of change in number of depository corporations 2.6 2.7 3.0 2.8
3.2 Ratio of profits to period-average assets (ROA) 3.6 3.8 3.6 3.73.3 Ratio of profits to period-average equity (ROE) 3.7 3.7 3.6 3.73.4 Ratio of net interest income to total income 3.6 3.6 3.8 3.73.5 Ratio of trading and foreign exchange gains/losses to total income 3.5 3.4 3.4 3.43.6 Ratio of operating costs to net interest income 3.3 3.6 3.6 3.63.7 Ratio of staff costs to operating costs 3.0 3.4 3.5 3.4
3.8 Spread between reference lending and deposit rates 3.5 3.5 3.7 3.6
3.9 Share of assets of the three largest depository corporations in total assets of depository corporations 2.9 3.2 2.9 3.0
4. Liquidity
4.1 Distribution of three-month local currency interbank rates for different depository corporations 2.7 3.0 2.9 2.9
4.2 Average interbank bid-ask spread for three-month local currency deposits 3.0 2.9 2.9 2.9
4.3 Ratio of liquid assets to total assets 3.3 3.6 3.5 3.5 4.4 Ratio of liquid assets to liquid liabilities 3.3 3.7 3.7 3.6 4.5 Average maturity of assets 3.2 3.3 3.6 3.4 4.6 Average maturity of liabilities 3.2 3.3 3.6 3.4
4.7 Average daily turnover in the Treasury bill (or central bank bill) market 2.3 2.7 3.1 2.7
Appendix IV
83
Type of User___________________________________________________________________________________________________________________________________Policy/Research Private Sector Average___________________________________ ____________________________________ _______________________________________
Industrial Emerging Developing Average Industrial Emerging Developing Average Industrial Emerging Developing World Total
3.9 3.9 3.2 3.7 3.4 3.8 3.5 3.6 3.7 3.9 3.6 3.83.4 3.6 3.2 3.4 3.6 3.6 3.3 3.5 3.6 3.6 3.5 3.63.2 3.6 3.1 3.3 3.1 3.3 3.1 3.2 3.2 3.6 3.4 3.42.9 3.0 2.8 2.9 2.7 2.9 3.1 2.9 2.9 3.1 3.1 3.0
3.6 3.6 2.9 3.4 3.1 3.1 3.2 3.1 3.3 3.4 3.1 3.3
3.1 3.4 3.5 3.4 3.0 3.1 3.5 3.1 2.9 3.3 3.3 3.2
3.1 3.5 3.2 3.3 3.4 3.4 3.5 3.4 3.2 3.5 3.4 3.42.8 3.2 3.0 3.0 2.9 2.7 2.5 2.7 2.7 3.0 2.6 2.82.8 3.2 2.9 3.0 2.8 2.7 2.5 2.7 2.7 2.9 2.6 2.8
3.6 3.8 3.5 3.6 3.4 3.4 3.7 3.5 3.5 3.6 3.5 3.63.5 3.5 3.1 3.4 3.2 2.9 3.0 3.0 3.3 3.3 3.1 3.23.4 3.4 3.1 3.3 3.2 2.9 3.0 3.0 3.3 3.2 3.2 3.2
3.4 3.6 3.6 3.6 3.2 3.7 3.0 3.4 3.3 3.6 3.6 3.53.2 3.2 2.7 3.1 3.2 3.4 2.8 3.2 3.2 3.2 2.8 3.13.0 3.7 3.3 3.4 2.9 3.5 2.8 3.1 3.0 3.6 3.5 3.43.2 3.5 3.5 3.4 3.1 3.3 3.5 3.2 3.2 3.6 3.6 3.5
3.9 4.0 3.8 3.9 3.7 3.9 3.7 3.8 3.9 3.9 3.8 3.93.8 3.9 3.6 3.8 3.7 3.7 3.7 3.7 3.8 3.8 3.8 3.8
3.8 3.7 3.3 3.6 3.1 3.4 3.4 3.3 3.4 3.5 3.3 3.43.3 3.5 3.2 3.4 2.9 3.2 3.1 3.1 3.1 3.4 3.2 3.33.3 3.5 3.1 3.3 2.8 3.3 2.7 3.0 3.2 3.4 3.0 3.23.2 3.5 2.6 3.2 3.2 3.5 2.7 3.3 3.2 3.4 2.9 3.2
3.5 3.2 2.9 3.2 3.1 2.9 2.5 2.9 3.2 3.0 2.8 3.03.3 2.9 2.8 3.0 2.9 2.7 2.3 2.7 3.1 2.8 2.7 2.83.1 3.0 2.8 3.0 2.9 2.8 2.3 2.7 3.0 2.8 2.8 2.9
3.1 2.6 2.6 2.8 2.8 2.7 2.0 2.6 2.8 2.7 2.5 2.7
2.5 2.7 2.7 2.6 1.9 2.9 3.1 2.6 2.4 2.7 2.9 2.7
3.5 3.8 3.5 3.6 3.1 3.7 3.6 3.5 3.5 3.8 3.6 3.63.6 3.9 3.5 3.7 2.9 3.7 3.6 3.4 3.5 3.8 3.6 3.63.2 3.7 3.1 3.4 3.0 3.6 3.4 3.3 3.3 3.6 3.6 3.53.1 3.4 2.8 3.2 2.9 3.4 3.3 3.2 3.2 3.4 3.3 3.33.0 3.6 3.5 3.4 2.6 3.5 3.3 3.1 3.0 3.6 3.6 3.42.7 3.4 3.0 3.1 2.5 3.3 3.3 3.0 2.8 3.4 3.4 3.2
3.4 3.7 3.5 3.5 3.2 3.6 2.9 3.3 3.4 3.6 3.5 3.5
2.6 3.2 2.9 2.9 2.5 2.9 2.8 2.7 2.7 3.1 2.9 2.9
2.6 3.1 2.9 2.9 2.9 3.1 2.4 2.9 2.7 3.1 2.8 2.92.6 3.1 2.7 2.8 3.0 3.2 2.3 2.9 2.9 3.0 2.7 2.9
3.1 3.7 3.8 3.5 3.3 3.6 3.3 3.4 3.2 3.6 3.5 3.52.9 3.7 3.9 3.5 3.4 3.7 3.3 3.5 3.2 3.7 3.7 3.62.9 3.7 3.7 3.4 3.0 3.3 3.4 3.2 3.0 3.4 3.6 3.42.9 3.7 3.7 3.4 3.0 3.3 3.4 3.2 3.0 3.4 3.6 3.4
2.1 3.2 3.3 2.9 2.5 3.2 2.7 2.8 2.3 3.0 3.1 2.8
APPENDIX IV
84
Table A4.3 (concluded)
______________________________________________________________Supervisors________________________________________
Industrial Emerging Developing Average
4.8 Average bid-ask spread in the Treasury bill (or central bank bill) market 2.3 2.8 2.9 2.7 4.9 Ratio of central bank credit to depository corporations to depository
corporations’ total liabilities 2.6 3.1 2.9 2.9
4.10 Ratio of customer deposits to total (noninterbank) loans 3.1 3.2 3.5 3.3 4.11 Ratio of customer foreign currency deposits to total (noninterbank)
foreign currency loans 2.6 3.1 3.0 3.0
5. Sensitivity to market risks
5.1 Ratio of gross foreign currency assets to own funds 2.7 3.2 3.2 3.1 5.2 Ratio of net foreign currency position to own funds 3.3 3.7 3.5 3.5
5.3 Average interest rate repricing period for assets 3.0 3.2 3.1 3.1 5.4 Average interest rate repricing period for liabilities 2.9 3.1 3.1 3.1
5.5 Duration of assets 3.0 3.2 3.0 3.15.6 Duration of liabilities 3.0 3.1 3.1 3.1
5.7 Ratio of gross equity position to own funds 2.9 2.9 2.8 2.9 5.8 Ratio of net equity position to own funds 2.9 2.9 2.9 2.9
5.9 Ratio of gross position in commodities to own funds 2.3 2.3 2.1 2.2 5.10 Ratio of net position in commodities to own funds 2.3 2.3 2.3 2.3
Appendix IV
85
Type of User___________________________________________________________________________________________________________________________________Policy/Research Private Sector Average___________________________________ ____________________________________ _______________________________________
Industrial Emerging Developing Average Industrial Emerging Developing Average Industrial Emerging Developing World Total
2.2 3.3 3.2 2.9 2.5 3.2 2.7 2.8 2.3 3.0 3.0 2.8
2.6 3.1 2.6 2.8 2.6 3.0 2.6 2.8 2.6 3.1 2.8 2.9
2.9 3.4 3.0 3.2 2.6 3.2 3.0 2.9 2.9 3.3 3.3 3.2
2.4 3.2 2.8 2.9 2.9 3.1 2.3 2.8 2.6 3.1 2.9 2.9
2.6 3.3 3.2 3.1 2.9 3.1 3.3 3.0 2.7 3.2 3.2 3.12.9 3.5 3.5 3.3 3.1 3.5 3.3 3.3 3.1 3.6 3.5 3.4
2.8 3.4 2.8 3.0 2.6 3.3 2.8 2.9 2.8 3.3 3.0 3.02.8 3.4 2.8 3.0 2.6 3.3 2.8 2.9 2.8 3.2 3.0 3.0
2.9 3.6 3.0 3.3 3.0 3.4 3.0 3.2 3.0 3.4 3.0 3.22.9 3.6 3.0 3.3 3.1 3.3 3.0 3.2 3.0 3.3 3.0 3.2
2.7 3.1 3.3 3.0 2.7 2.9 2.8 2.8 2.8 3.0 3.0 2.92.8 3.1 3.4 3.1 2.7 2.8 3.0 2.8 2.8 3.0 3.1 3.0
2.3 2.7 2.7 2.6 2.3 2.5 2.5 2.4 2.3 2.5 2.4 2.42.4 2.7 2.8 2.6 2.3 2.5 2.5 2.4 2.3 2.5 2.5 2.4
APPENDIX IV
86
Table A4.4. Compilation and Dissemination of FSIs by Type of Economy
Industrial Countries___________________________________________Total Number Percent Number Percent
in Compiling of Disseminating ofGroup FSIs Total FSIs Total
1. Capital adequacy
1.1 Basel capital adequacy ratio 21 20 95 15 71a. Basel tier I capital (net of deductions) 21 19 90 13 62b. Basel tier II capital (net of deductions) 21 19 90 12 57c. Basel tier III capital (net of deductions) 21 15 71 8 38d. Risk-weighted assets 21 19 90 12 57
1.2 Distribution of capital adequacy ratios 21 8 38 3 14a. Number of institutions with Basel capital ratios, falling into specified ranges 21 8 38 3 14b. Assets of institutions within each range 21 12 57 6 29c. Assets by type of depository corporation
c.1 Headquartered in the country 21 13 62 5 24of which: internationally active 21 7 33 2 10of which: state-owned or -controlled 21 7 33 3 14
c.2 Headquartered in other countries 21 11 52 2 10
1.3 Ratio of total on-balance-sheet assets to own funds 21 13 62 6 29a. Total on-balance-sheet assets 21 20 95 13 62b. Own funds (equity capital and reserves) 21 20 95 13 62
2. Asset quality
(a) Lending institution
2.1 Distribution of on-balance-sheet assets by Basel risk-weight category 21 17 81 7 33a. Assets per Basel risk-weight category 21 17 81 7 33
2.2 Ratio of total gross asset position in financial derivatives to own funds 21 9 43 4 19a. Total gross asset position in derivatives 21 15 71 6 29b. of which: off-balance-sheet position 21 14 67 4 19
2.3 Ratio of total gross liability position in financial derivatives to own funds 21 7 33 4 19a. Total gross liability position in derivatives 21 14 67 6 29b. of which: off-balance-sheet position 21 12 57 4 19
2.4 Distribution of loans by sector 21 21 100 17 81a. Loans by national accounts sectors 21 20 95 17 81
of which:a.1. Loans for investment in commercial real estate 21 13 62 9 43a.2. Loans for investment in residential real estate 21 17 81 15 71a.3. Loans to other key sectors (specify) 21 14 67 10 48
b. Total loans 21 19 90 19 90
2.5 Distribution of credit extended by sector 21 11 52 7 33a. Credit by national account sectors 21 13 62 9 43b. Total credit 21 18 86 13 62
2.6 Distribution of credit by country or region 21 16 76 12 57a. Loans by country or region 21 18 86 13 62
2.7 Ratio of credit to related entities to total credit 21 6 29 2 10a. Credit to related entities 21 13 62 3 14
2.8 Ratio of total large loans to own funds 21 6 29 0 0a. Total large loans (specify size range) 21 12 57 1 5
2.9 Ratio of gross nonperforming loans to total assets 21 13 62 9 43a. Gross nonperforming loans 21 19 90 12 57
2.10 Ratio of nonperforming loans net of provisions to total assets 21 12 57 8 38a. Nonperforming loans net of provisions 21 18 86 11 52
(b) Borrowing institution
2.11 Ratio of corporate debt to own funds (“debt-equity ratio”) 21 9 43 7 33a. Total corporate debt 21 16 76 12 57b. Corporations’ own funds 21 15 71 12 57
Appendix IV
87
Emerging Countries Developing Countries World Total_____________________________________ _______________________________________ _________________________________________Total Number Percent Number Percent Total Number Percent Number Percent Total Number Percent Number Percent
in Compiling of Disseminating of in Compiling of Disseminating of in Compiling of Disseminating ofGroup FSIs Total FSIs Total Group FSIs Total FSIs Total Group FSIs Total FSIs Total
44 38 86 27 61 28 27 96 11 39 93 85 91 53 5744 37 84 21 48 28 25 89 10 36 93 81 87 44 4744 36 82 21 48 28 24 86 10 36 93 79 85 43 4644 14 32 9 20 28 7 25 4 14 93 36 39 21 2344 41 93 24 55 28 24 86 11 39 93 84 90 47 51
44 7 16 3 7 28 6 21 5 18 93 21 23 11 1244 7 16 3 7 28 6 21 5 18 93 21 23 11 1244 15 34 8 18 28 10 36 4 14 93 37 40 18 19
44 13 30 6 14 28 8 29 3 11 93 34 37 14 1544 11 25 6 14 28 4 14 1 4 93 22 24 9 1044 14 32 7 16 28 6 21 2 7 93 27 29 12 1344 12 27 7 16 28 3 11 0 0 93 26 28 9 10
44 17 39 9 20 28 4 14 2 7 93 34 37 17 1844 38 86 31 70 28 19 68 11 39 93 77 83 55 5944 38 86 30 68 28 19 68 11 39 93 77 83 54 58
44 39 89 17 39 28 21 75 9 32 93 77 83 33 3544 39 89 17 39 28 21 75 9 32 93 77 83 33 35
44 5 11 1 2 28 1 4 0 0 93 15 16 5 544 14 32 8 18 28 3 11 1 4 93 32 34 15 1644 14 32 6 14 28 3 11 1 4 93 31 33 11 12
44 5 11 1 2 28 1 4 0 0 93 13 14 5 544 14 32 8 18 28 2 7 0 0 93 30 32 14 1544 15 34 7 16 28 2 7 0 0 93 29 31 11 12
44 34 77 27 61 28 21 75 16 57 93 76 82 60 6544 29 66 23 52 28 19 68 14 50 93 68 73 54 58
44 14 32 10 23 28 14 50 11 39 93 41 44 30 3244 19 43 13 30 28 15 54 12 43 93 51 55 40 4344 24 55 20 45 28 15 54 10 36 93 53 57 40 4344 36 82 33 75 28 22 79 17 61 93 77 83 69 74
44 22 50 17 39 28 13 46 11 39 93 46 49 35 3844 24 55 18 41 28 16 57 14 50 93 53 57 41 4444 33 75 28 64 28 22 79 18 64 93 73 78 59 63
44 19 43 12 27 28 7 25 4 14 93 42 45 28 3044 22 50 15 34 28 8 29 5 18 93 48 52 33 35
44 12 27 3 7 28 8 29 2 7 93 26 28 7 844 32 73 10 23 28 18 64 8 29 93 63 68 21 23
44 15 34 7 16 28 8 29 1 4 93 29 31 8 944 26 59 11 25 28 14 50 8 29 93 52 56 20 22
44 20 45 14 32 28 9 32 5 18 93 42 45 28 3044 39 89 26 59 28 22 79 13 46 93 80 86 51 55
44 17 39 8 18 28 10 36 6 21 93 39 42 22 2444 31 70 18 41 28 21 75 13 46 93 70 75 42 45
44 5 11 2 5 28 3 11 0 0 93 17 18 9 1044 14 32 11 25 28 8 29 4 14 93 38 41 27 2944 13 30 10 23 28 6 21 3 11 93 34 37 25 27
APPENDIX IV
88
Table A4.4 (continued)
Industrial Countries___________________________________________Total Number Percent Number Percent
in Compiling of Disseminating ofGroup FSIs Total FSIs Total
2.12 Ratio of corporate profits to equity 21 8 38 6 29a. Corporate pre-tax profits 21 15 71 12 57b. Corporate post-tax profits 21 14 67 11 52
2.13 Ratio of corporate debt service costs to profits 21 9 43 7 33a. Corporate debt service costs 21 15 71 11 52
2.14 Corporate net foreign currency exposure 21 1 5 0 0a. Gross foreign currency assets 21 5 24 3 14b. Gross foreign currency liabilities 21 5 24 3 14c. Net off-balance-sheet foreign currency positions (nominal value) not
included above 21 2 10 0 0
2.15 Ratio of household debt to GDP 21 8 38 5 24a. Household total debt 21 17 81 13 62b. of which: mortgage debt 21 13 62 10 48c. of which: debt to depository corporations 21 14 67 13 62
2.16 Number of applications for protection from creditors 21 9 43 8 38
3. Profitability and competitiveness
3.1 Rate of change in the number of depository corporations 21 14 67 11 52a. Difference between number of institutions at beginning and end of period 21 19 90 15 71b. of which: due to mergers and acquisitions 21 17 81 10 48c. of which: due to withdrawals of licenses or closing of units 21 17 81 12 57
3.2 Ratios of profits to period-average assets (ROA) 21 13 62 10 48a. Pretax, after provisions profits 21 19 90 16 76b. Posttax profits 21 20 95 16 76c. Total period-average on-balance-sheet assets 21 18 86 13 62
3.3 Ratios of profits to period-average equity (ROE) 21 14 67 11 52a. Pretax, after provisions profits 21 19 90 15 71b. Posttax profits 21 20 95 16 76c. Period-average equity 21 18 86 13 62
3.4 Ratio of net interest income to profits 21 13 62 8 38a. Net interest income 21 20 95 16 76
3.5 Ratio of trading and foreign currency gains/losses to profits 21 11 52 7 33a. Gains/losses in securities and foreign currencies 21 18 86 13 62
3.6 Ratio of operating costs to net interest income 21 13 62 8 38a. Operating costs 21 20 95 16 76
3.7 Ratio of staff costs to operating costs 21 12 57 8 38a. Staff costs 21 19 90 14 67
3.8 Spreads between reference lending and deposit rates 21 8 38 5 24a. Reference lending rate (specify rate) 21 13 62 13 62b. Reference deposit rate (specify rate) 21 13 62 13 62
3.9 Share of assets of the three largest depository corporations in total assets of depository corporations 21 12 57 5 24
a. Assets of the three largest depository corporations 21 19 90 7 33
4. Liquidity
4.1 Distribution of three-month local currency interbank rates for different banks 21 3 14 1 5
4.2 Average interbank bid-ask spread for three-month local currency interbank deposits 21 6 29 3 14
4.3 Ratio of liquid assets to total assets 21 10 48 5 24a. Liquid assets 21 18 86 7 33
4.4 Ratio of liquid assets to liquid liabilities 21 11 52 5 24a. Liquid liabilities 21 18 86 7 33
Appendix IV
89
Emerging Countries Developing Countries World Total_____________________________________ _______________________________________ _________________________________________Total Number Percent Number Percent Total Number Percent Number Percent Total Number Percent Number Percent
in Compiling of Disseminating of in Compiling of Disseminating of in Compiling of Disseminating ofGroup FSIs Total FSIs Total Group FSIs Total FSIs Total Group FSIs Total FSIs Total
44 4 9 2 5 28 3 11 1 4 93 15 16 9 1044 17 39 11 25 28 10 36 5 18 93 42 45 28 3044 16 36 10 23 28 9 32 4 14 93 39 42 25 27
44 3 7 1 2 28 1 4 1 4 93 13 14 9 1044 11 25 4 9 28 5 18 4 14 93 31 33 19 20
44 3 7 2 5 28 2 7 0 0 93 6 6 2 244 11 25 7 16 28 11 39 6 21 93 27 29 16 1744 11 25 7 16 28 10 36 5 18 93 26 28 15 16
44 9 20 5 11 28 7 25 4 14 93 18 19 9 10
44 4 9 2 5 28 1 4 0 0 93 13 14 7 844 11 25 8 18 28 5 18 0 0 93 33 35 21 2344 9 20 6 14 28 3 11 0 0 93 25 27 16 1744 13 30 10 23 28 2 7 0 0 93 29 31 23 25
44 3 7 1 2 28 1 4 1 4 93 13 14 10 11
44 13 30 9 20 28 8 29 8 29 93 35 38 28 3044 26 59 22 50 28 14 50 12 43 93 59 63 49 5344 26 59 20 45 28 15 54 13 46 93 58 62 43 4644 26 59 20 45 28 15 54 12 43 93 58 62 44 47
44 19 43 15 34 28 10 36 4 14 93 42 45 29 3144 38 86 27 61 28 23 82 14 50 93 80 86 57 6144 40 91 29 66 28 21 75 13 46 93 81 87 58 6244 39 89 22 50 28 18 64 10 36 93 75 81 45 48
44 20 45 16 36 28 10 36 4 14 93 44 47 31 3344 36 82 25 57 28 22 79 12 43 93 77 83 52 5644 40 91 29 66 28 21 75 11 39 93 81 87 56 6044 38 86 23 52 28 18 64 10 36 93 74 80 46 49
44 18 41 12 27 28 8 29 3 11 93 39 42 23 2544 39 89 27 61 28 23 82 11 39 93 82 88 54 58
44 14 32 8 18 28 5 18 1 4 93 30 32 16 1744 29 66 20 45 28 17 61 8 29 93 64 69 41 44
44 17 39 10 23 28 8 29 3 11 93 38 41 21 2344 39 89 25 57 28 22 79 12 43 93 81 87 53 57
44 17 39 10 23 28 8 29 3 11 93 37 40 21 2344 37 84 24 55 28 22 79 12 43 93 78 84 50 54
44 8 18 7 16 28 9 32 4 14 93 25 27 16 1744 29 66 25 57 28 13 46 9 32 93 55 59 47 5144 27 61 24 55 28 13 46 9 32 93 53 57 46 49
44 17 39 9 20 28 6 21 2 7 93 35 38 16 1744 37 84 16 36 28 11 39 7 25 93 67 72 30 32
44 13 30 7 16 28 7 25 4 14 93 23 25 12 13
44 9 20 6 14 28 3 11 2 7 93 18 19 11 12
44 19 43 9 20 28 8 29 6 21 93 37 40 20 2244 34 77 20 45 28 23 82 14 50 93 75 81 41 44
44 18 41 12 27 28 8 29 5 18 93 37 40 22 2444 33 75 20 45 28 21 75 12 43 93 72 77 39 42
APPENDIX IV
90
Table A4.4 (concluded)
Industrial Countries___________________________________________Total Number Percent Number Percent
in Compiling of Disseminating ofGroup FSIs Total FSIs Total
4.5 Average maturity of assets 21 3 14 0 0a. Average remaining maturity of assets (months) 21 8 38 1 5b. of which: foreign currency assets 21 6 29 1 5c. Average original maturity of assets (months) 21 4 19 1 5d. of which: foreign currency assets 21 4 19 0 0
4.6 Average maturity of liabilities 21 3 14 0 0a. Average remaining maturity of liabilities (months) 21 8 38 1 5b. of which: foreign currency liabilities 21 6 29 1 5c. Average original maturity of liabilities (months) 21 4 19 1 5d. of which: foreign currency liabilities 21 4 19 0 0
4.7 Average daily turnover in the Treasury bill (or central bank bill) market 21 7 33 4 19
4.8 Average bid-ask spread in the Treasury bill (or central bank bill) market 21 3 14 0 0
4.9 Ratio of central bank credit to depository corporations to their total liabilities 21 6 29 4 19a. Total credit from the central bank to depository corporations 21 18 86 14 67b. Total liabilities 21 18 86 14 67
4.10 Ratio of total customer deposits to total (noninterbank) loans 21 11 52 4 19a. Customer (noninterbank) deposits 21 19 90 15 71b. Total (noninterbank) loans 21 19 90 15 71
4.11 Ratio of foreign currency customer deposits to total (noninterbank) foreign currency loans 21 7 33 4 19
a. Customer (noninterbank) foreign currency deposits 21 16 76 12 57b. Customer (noninterbank) foreign currency loans 21 16 76 12 57
5. Sensitivity to market risks
5.1 Ratio of gross foreign currency assets to own funds 21 6 29 2 10a. Gross foreign currency assets 21 16 76 10 48
5.2 Ratio of net foreign currency position to own funds 21 7 33 3 14a. Gross foreign currency assets 21 16 76 10 48b. Gross foreign currency liabilities 21 16 76 9 43c. Net off-balance-sheet foreign currency positions (nominal value) not
included above 21 10 48 2 10
5.3 Average interest rate repricing period for assets 21 6 29 1 5
5.4 Average interest rate repricing period for liabilities 21 6 29 1 5
5.5 Duration of assets 21 5 24 1 5
5.6 Duration of liabilities 21 5 24 0 0
5.7 Ratio of gross positions in equities to own funds 21 8 38 2 10a. Gross holdings of equities 21 17 81 11 52
5.8 Ratio of net positions in equities to own funds 21 6 29 3 14a. Gross holdings of equities 21 17 81 11 52b. Net off-balance-sheet nominal-value position in equities, not included above 21 8 38 2 10
5.9 Ratio of gross position in commodities to own funds 21 3 14 1 5a. Gross asset position in commodities 21 6 29 1 5
5.10 Ratio of net position in commodities to own funds 21 5 24 2 10a. Gross asset position in commodities 21 6 29 1 5b. Net off-balance-sheet nominal-value position in commodities, not included above 21 7 33 2 10
Appendix IV
91
Emerging Countries Developing Countries World Total_____________________________________ _______________________________________ _________________________________________Total Number Percent Number Percent Total Number Percent Number Percent Total Number Percent Number Percent
in Compiling of Disseminating of in Compiling of Disseminating of in Compiling of Disseminating ofGroup FSIs Total FSIs Total Group FSIs Total FSIs Total Group FSIs Total FSIs Total
44 10 23 4 9 28 5 18 1 4 93 18 19 5 544 25 57 11 25 28 13 46 8 29 93 46 49 20 2244 21 48 8 18 28 10 36 7 25 93 37 40 16 1744 19 43 9 20 28 9 32 7 25 93 32 34 17 1844 16 36 7 16 28 9 32 7 25 93 29 31 14 15
44 10 23 4 9 28 5 18 1 4 93 18 19 5 544 26 59 11 25 28 13 46 8 29 93 47 51 20 2244 21 48 7 16 28 10 36 7 25 93 37 40 15 1644 21 48 9 20 28 9 32 7 25 93 34 37 17 1844 16 36 6 14 28 9 32 7 25 93 29 31 13 14
44 20 45 15 34 28 6 21 5 18 93 33 35 24 26
44 15 34 8 18 28 7 25 6 21 93 25 27 14 15
44 8 18 4 9 28 6 21 3 11 93 20 22 11 1244 34 77 24 55 28 15 54 11 39 93 67 72 49 5344 33 75 25 57 28 18 64 14 50 93 69 74 53 57
44 15 34 8 18 28 7 25 2 7 93 33 35 14 1544 37 84 32 73 28 23 82 13 46 93 79 85 60 6544 39 89 32 73 28 25 89 14 50 93 83 89 61 66
44 13 30 6 14 28 4 14 1 4 93 24 26 11 1244 35 80 23 52 28 18 64 10 36 93 69 74 45 4844 35 80 22 50 28 19 68 10 36 93 70 75 44 47
44 14 32 6 14 28 4 14 1 4 93 24 26 9 1044 37 84 20 45 28 19 68 11 39 93 72 77 41 44
44 14 32 7 16 28 4 14 1 4 93 25 27 11 1244 36 82 21 48 28 19 68 10 36 93 71 76 41 4444 36 82 21 48 28 20 71 10 36 93 72 77 40 43
44 25 57 12 27 28 15 54 8 29 93 50 54 22 24
44 9 20 2 5 28 2 7 1 4 93 17 18 4 4
44 9 20 2 5 28 1 4 0 0 93 16 17 3 3
44 11 25 6 14 28 6 21 2 7 93 22 24 9 10
44 10 23 5 11 28 6 21 2 7 93 21 23 7 8
44 8 18 5 11 28 5 18 1 4 93 21 23 8 944 25 57 14 32 28 13 46 7 25 93 55 59 32 34
44 7 16 4 9 28 2 7 1 4 93 15 16 8 944 22 50 13 30 28 12 43 6 21 93 51 55 30 3244 11 25 7 16 28 6 218 4 14 93 25 27 13 14
44 3 7 1 2 28 1 4 0 0 93 7 8 2 244 7 16 5 11 28 2 7 0 0 93 15 16 6 6
44 2 5 1 2 28 1 4 0 0 93 8 9 3 344 6 14 4 9 28 2 7 0 0 93 14 15 5 544 6 14 4 9 28 2 7 0 0 93 15 16 6 6
A t the request of its Executive Board, the IMF isconducting a survey of needs and practices re-
lated to macroprudential indicators (MPIs)—de-fined broadly as indicators of the health and stabil-ity of financial institutions and of their corporateand household counterparties. The purpose of thesurvey is to gather information on the use of macro-prudential data and on country practices in compil-ing and disseminating the data. Survey results willbe used to identify a set of statistical measures thatcan be regularly monitored by national authoritiesin their financial sector assessment work, by theIMF in its surveillance activities, and ultimately bythe private sector.
The survey covers the use, compilation, and dis-semination of aggregate data on the financial sys-tem, and does not cover information on individualinstitutions. The survey is intended to solicit theviews of respondents and is not intended to gatherthe actual numerical data on MPIs. All responses areconfidential. No information will be released in aform that allows public identification of individualcountry responses.
Work by the IMF on MPIs is part of ongoing ef-forts in the international community to strengthenthe architecture of the global financial system.Among the institutions to initiate action in thisarea, the IMF has been called upon to assess finan-cial system soundness as part of its surveillancework—a process now under way as part of the jointWorld Bank-IMF Financial Sector Assessment Pro-gram (FSAP), introduced in May 1999. The abilityto monitor financial soundness presupposes theavailability of valid indicators of the health and sta-bility of financial systems—or MPIs. MPIs allowfor assessments based on objective measures of financial soundness. If comparable across coun-tries—through adherence to internationally agreedprudential, accounting, and statistical standards—they facilitate monitoring at the global level and permit comparisons of national conditions with global benchmarks. If made publicly avail-able, they enhance access to key financial informa-tion and can contribute to strengthening of marketdiscipline.
The focus of this survey is on indicators of thecurrent health of the financial system, which are pri-marily derived by aggregating data on the soundnessof individual financial institutions. For practical pur-poses, the survey limits itself to the depository cor-porations (banking) sector and to their corporate andhousehold counterparties. This focus is appropriatefor a first-time survey in this area, but it is recog-nized that further research is needed on the effects ofnondepository financial institutions and securitiesmarkets on financial stability.
MPIs are only one of the tools of macroprudentialanalysis. The assessment of financial system sound-ness involves coupling the analysis of MPIs withmacroeconomic data on overall economic condi-tions, information on other financial institutions andmarkets, and qualitative information about the insti-tutional, policy, and regulatory environment. A vari-ety of techniques can be used in macroprudentialanalysis, including stress tests, sensitivity analysis,and other methodologies.
Instructions for Completing the Survey
The survey is being sent to the central banks ofall IMF member countries. The survey has twomajor parts, which are addressed to different orga-nizations in your country. We would like to requestthe assistance of your institution in identifying theappropriate respondents for each part of the survey,forwarding the questionnaires, and collecting theresponses (see below). We would appreciate the return of the completed survey to us by July 28,2000.
Part I: User Questionnaire. This questionnaire isaddressed to (1) financial sector supervisors, (2)analysts and policy officials within the central bankor other government authorities involved in theanalysis of financial system soundness, and (3) fi-nancial market participants and analysts in acade-mia or the private sector. Six copies of the userquestionnaire are provided, for distribution by the
Appendix V Survey on the Use,Compilation, and Disseminationof Macroprudential Indicators
92
Appendix V
central bank. The central bank may find it useful toselect respondents based on their ability to con-tribute to a balanced depiction of the needs forMPIs in the country. In order to protect the confi-dentiality of private sector and academic respon-dents, we would like to request that the centralbank prepare an overview of their responses, whichshould be returned to the IMF.
Part I (a): User Questionnaire: Covers usefulnessof specific MPIs and requirements for frequencyof compilation.
Part I (b): Supplementary Issues: Covers addi-tional questions related to the needs for, andanalysis of, MPIs.
Part II: Compilation and Dissemination Question-naire. This questionnaire is intended for staff withinthe monetary or supervisory authorities, or othergovernment institutions, responsible for the compi-lation of MPIs and components of MPIs, and fortheir dissemination to the public, where appropriate.The selection of the respondents will depend uponthe institutional setup in each country.
Part II (a): Compilation and Dissemination Ques-tionnaire: Covers practices related to the compila-tion and dissemination of MPIs or components ofMPIs.
Part II (b): Supplementary Issues: Covers techni-cal questions on factors affecting the compilationand dissemination of MPIs or components ofMPIs.
Part II (c): Valuation Issues: Covers valuationpractices affecting MPIs or components of MPIs.
Coverage: The survey covers the depository cor-porations subsector, which corresponds roughly tothe banking sector. It includes all major divisionsof depository corporations, including commercialbanks, branches and subsidiaries of foreign banksoperating in your country, money market funds thatissue deposit-like shares, foreign currency and foreign trade banks, international banking facili-ties, investment banks, mortgage banking institu-tions, credit unions, specialized banks, and othersas appropriate. Government-owned or -controlleddepository corporations are included. For the pur-pose of this survey, the central bank is excluded.Mutual funds whose liabilities to investors areclose substitutes for bank deposits should be in-cluded in the survey, but other mutual funds shouldbe excluded.
MPIs and MPI components: The questionnaireslist a number of aggregate indicators that, based onsurveillance and empirical work at the IMF and else-
where, are considered useful for assessing the healthand stability of financial systems. The survey alsogathers information on components of MPIs to as-certain whether the underlying information exists tocompile MPIs that are not now being compiled. Theexact definitions of each indicator or its componentsmay vary from country to country. Respondents arekindly asked to indicate cases where the MPIs usedor available are similar to, but not identical to, thosepresented in the survey.
Special issues pages: The User Questionnaire andthe Compilation and Dissemination Questionnaireeach include a page devoted to a series of questionson special issues related to MPIs.
Additional comments: Respondents may wish toprovide supplemental information important for theanalysis of financial stability conditions in theircountry, important indicators not listed in the sur-vey, special conditions that affect compilation anddissemination of MPIs, and alternatives to the defi-nitions and descriptions of MPIs provided in thesurvey. “Comments” cells for this purpose corre-sponding to each MPI have been created on theUser Questionnaire, Part I (a), and spaces for gen-eral comments are provided at the ends of the UserQuestionnaire Part I (a) and the Compilation andDissemination Questionnaire Part II (a). Othercomments may be entered elsewhere in the spread-sheets by right-clicking your mouse button to select“Insert Comment.”
Optional reports on other financial institutionsand markets: Central banks may also choose toprovide separate reports for other financial institu-tions or markets that are important for the analysisof overall financial stability conditions in theircountries. When doing so, please describe the typesof institutions or markets covered and why they areimportant for macroprudential analysis.
Returning the questionnaire: Responses should besent to the IMF by July 28, 2000:
— by Internet to: [email protected]
— or by mail (diskette or paper copy) to:
MPI SurveyFinancial Institutions Division IIStatistics DepartmentInternational Monetary Fund700 19th Street, N.W.Washington, D.C. 20431, USA
Contacts regarding the survey: IMF staff maycontact you regarding the survey to better under-stand your needs and compilation practices relatedto MPIs, or to clarify your responses.
93
APPENDIX V
MPI Survey: Explanation of TermsDisclaimer: This glossary is provided for the con-
venience of the recipients of this survey. The expla-nations of the terms may not correspond to officialdefinitions or standards.
Bid-Ask Spread. Difference between the prices atwhich a market participant is willing to buy and sella security, such as a Treasury security.
Basel Capital. Capital as defined in the 1988 Capi-tal Accord of the Basel Committee on Banking Su-pervision and subsequent revisions. The Accord de-fines three capital elements. Tier 1 capital consists ofpermanent shareholders’ equity and disclosed re-serves; tier 2 capital consists of undisclosed re-serves, revaluation reserves, general provisions andloan-loss reserves, hybrid debt-equity capital instru-ments, and subordinated long-term debt (over fiveyears); tier 3 capital consists of subordinated short-term debt (over two years).
Basel Capital Adequacy Ratio. The ratio of capital,as defined above, divided by risk-weighted assets.Risk-weighted assets equals the sum of each categoryof asset (and on-balance-sheet equivalents for off-balance-sheet positions) multiplied by a weight repre-senting the credit risk associated with each category.
Basel Capital Deductions. Under the Basel CapitalAccord, supervisors may require depository corpora-tions to deduct certain items—such as investments innon-consolidated financial subsidiaries—from capi-tal in order to calculate capital adequacy ratios.
Capital. Sum of equity capital and reserves. It is theamount by which assets exceed liabilities.
Consolidation. Refers to the elimination of stocksand flows between institutional units when they aregrouped. In particular, a headquarters office and itsbranch offices and subsidiaries would report stockand flow data consolidated in a single statement.Global consolidation refers to the elimination ofstocks and flows occurring across all offices regard-less of their country of location. National consolida-tion refers to the elimination of stocks and flows oc-curring across all offices that are residents of aspecific country.
Credit. Comprises assets for which the counterpartyincurs debt liabilities. Includes loans, securitiesother than shares, and miscellaneous receivables.Equity instruments, financial derivatives, and linesof credit are excluded.
Debt Service. Repayments of principal and intereston mortgages or other outstanding debt.
Depository Corporation. Financial institutionsthat engage in banking-type activities, whether or
not they are called banks or are subject to supervi-sion by a regulatory/supervisory office. The stan-dard statistical definition includes the central bankand other depository corporations, described below,but for the purposes of this survey, the central bankis excluded.
Duration. Weighted average term-to-maturity of anasset’s cash flow, the weights being the present valueof each future cash flow as a percentage of the asset’sfull price.
Equity Capital. Issued and fully paid ordinary shares/common stock and noncumulative perpetual preferredstock (but excluding cumulative preferred stock).
Financial Derivative (or derivative instrument). Con-tract whose value is based on the performance of anunderlying financial asset, index, or other investment.
Global Consolidation. An accounting statement in-cluding all parts of an enterprise regardless of theirlocations worldwide (see Consolidation).
Gross Asset (or Liability) Position in Deriva-tives. The on-balance-sheet value of derivatives inan asset (or liability) position, plus the fair value ofoff-balance-sheet derivatives in an asset (or liabil-ity) position.
Interest Income, Net. Difference between the in-terest income produced by a financial institution’searning assets (loans and investments) and its inter-est expenses.
Loans. Financial assets (1) that are created when acreditor lends funds directly to a debtor; (2) that areevidenced by nonnegotiable documents; or (3) forwhich no security is issued as evidence of the trans-action.
Mortgage. Loans under which the borrower givesthe lender a lien on the property (usually real estate)as collateral for repayment of the loan.
National Consolidation. An accounting statementencompassing all parts of an enterprise within acountry, but excluding branches and subsidiariesoutside the country (see Consolidation).
Net Position. Refers to gross holdings, less grossliabilities, plus net positions under derivatives orother financial commitments in currencies, other fi-nancial instruments, or commodities. For example,a net foreign currency position equals gross foreigncurrency-denominated assets, less gross foreigncurrency-denominated liabilities, plus the net posi-tion under foreign currency financial derivativesand other financial commitments.
Nominal Value of Financial Derivatives. Thestated contract value of the underlying item deliv-ered under a financial derivative. For example, an
94
Appendix V
option that has a nominal value of 100,000 francswill deliver 100,000 francs when exercised.
Nonperforming Loan (NPL). A loan is said to benonperforming when the principal and/or interestpayments on it according to the original terms of theborrower’s loan agreement are past due (e.g., by 90days or more).
Operating Costs. The sum of interest and noninter-est (fees and commissions, trading losses, and salaryand other current costs) expenses.
Other Depository Corporations. Banks (otherthan the central bank) and similar institutions thatcarry out banking functions with the public. A fulldefinition is provided in the System of National Ac-counts 1993. The definition corresponds with mon-etary financial institutions as defined in the Euro-pean System of Account 1995. It includes a varietyof institutions regardless of whether they are calledbanks or are subject to banking supervision, includ-ing commercial banks, branches, and subsidiariesof foreign banks operating in the country, moneymarket funds that issue deposit-like shares, foreigncurrency and foreign trade banks, internationalbanking facilities, investment banks, Islamic banks,mortgage banking institutions, credit unions, spe-
cialized banks, and others as appropriate. Govern-ment-owned or -controlled depository corporationsare included. Mutual funds whose liabilities to in-vestors are close substitutes for bank deposits areincluded, but other mutual funds are excluded.
Own Funds. Equity capital and reserves.
Profits. Sum remaining after all expenses have beenmet or deducted from income. Both pretax and post-tax concepts are used.
Reference Rate. A specific lending or borrowing rateconsidered representative of overall rates that is usedas a benchmark for evaluating conditions in interestrate markets.
Related Entities. Affiliated enterprises, owners andmanagement of an enterprise, and individuals relatedto owners and managers.
Repricing Period for Interest Rates. The averageperiod (usually expressed in months) until existing fi-nancial instruments are redeemed or until the interestrates on financial instruments are reset or reindexed.
Turnover. Volume of securities traded during a pe-riod (e.g., daily) as a percentage of total securitieslisted on an exchange.
95
APPENDIX V
96
Tabl
e A
5.1.
MP
I S
urve
y —
Par
t I
(a):
Use
r Q
uest
ionn
aire
Is a
ggre
gate
info
rmat
ion
How
freq
uent
ly s
houl
d th
is M
PIC
heck
typ
e of
use
r:Su
perv
isor
——
on t
his
MPI
use
ful?
be c
ompi
led
to m
eet
user
s’ n
eeds
?Po
licy/
Res
earc
h—
—M
arke
t Pa
rtic
ipan
t/O
ther
——
4–
very
use
ful
M–
mon
thly
3–
usef
ulQ
– q
uart
erly
2–
som
etim
es u
sefu
lS
– s
emi-a
nnua
lly1
– no
t us
eful
A–
ann
ually
MPI
X–
no o
pini
onO
– o
ther
(sp
ecify
)C
omm
ents
1.Ca
pita
l ade
quac
y
1.1
Base
l cap
ital a
dequ
acy
ratio
____
____
____
____
____
____
____
____
____
____
____
____
1.1a
Rat
io o
f Bas
el t
ier
I cap
ital t
o ri
sk-w
eigh
ted
asse
ts__
____
____
____
____
____
____
____
____
____
____
____
__1.
1bR
atio
of B
asel
tie
r I +
tie
r II
capi
tal t
o ri
sk-w
eigh
ted
asse
ts__
____
____
____
____
____
____
____
____
____
____
____
__1.
1cR
atio
of B
asel
tie
r I +
II +
III c
apita
l to
risk
-wei
ghte
d as
sets
____
____
____
____
____
____
____
____
____
____
____
____
1.2
Dis
trib
utio
n of
cap
ital a
dequ
acy
ratio
s (n
umbe
r of
inst
itutio
ns
with
in s
peci
fied
capi
tal a
dequ
acy
ratio
ran
ges)
____
____
____
____
____
____
____
____
____
____
____
____
1.3
Rat
io o
f tot
al o
n-ba
lanc
e-sh
eet
asse
ts t
o ow
n fu
nds
____
____
____
____
____
____
____
____
____
____
____
____
2.As
set q
ualit
y
(a)
Lend
ing
inst
itutio
n
2.1
Dis
trib
utio
n of
on-
bala
nce-
shee
t as
sets
,by
Base
l ris
k-w
eigh
t ca
tego
ry__
____
____
____
____
____
____
____
____
____
____
____
__2.
2R
atio
of t
otal
gro
ss a
sset
pos
ition
in fi
nanc
ial d
eriv
ativ
es t
o ow
n fu
nds
____
____
____
____
____
____
____
____
____
____
____
____
2.3
Rat
io o
f tot
al g
ross
liab
ility
pos
ition
in fi
nanc
ial d
eriv
ativ
es t
o ow
n fu
nds
____
____
____
____
____
____
____
____
____
____
____
____
2.4
Dis
trib
utio
n of
loan
s by
sec
tor
____
____
____
____
____
____
____
____
____
____
____
____
2.4a
of w
hich
:for
inve
stm
ent
in c
omm
erci
al r
eal e
stat
e__
____
____
____
____
____
____
____
____
____
____
____
__2.
4bof
whi
ch:f
or in
vest
men
t in
res
iden
tial r
eal e
stat
e__
____
____
____
____
____
____
____
____
____
____
____
__2.
5D
istr
ibut
ion
of c
redi
t ex
tend
ed b
y se
ctor
____
____
____
____
____
____
____
____
____
____
____
____
2.6
Dis
trib
utio
n of
cre
dit
exte
nded
by
coun
try
or r
egio
n__
____
____
____
____
____
____
____
____
____
____
____
__2.
7R
atio
of c
redi
t to
rel
ated
ent
ities
to
tota
l cre
dit
____
____
____
____
____
____
____
____
____
____
____
____
2.8
Rat
io o
f tot
al la
rge
loan
s to
ow
n fu
nds
____
____
____
____
____
____
____
____
____
____
____
____
2.9
Rat
io o
f gro
ss n
onpe
rfor
min
g lo
ans
to t
otal
ass
ets
____
____
____
____
____
____
____
____
____
____
____
____
2.10
Rat
io o
f non
perf
orm
ing
loan
s ne
t of
pro
visi
ons
to t
otal
ass
ets
____
____
____
____
____
____
____
____
____
____
____
____
(b)
Borr
owin
g in
stitu
tion
2.11
Rat
io o
f cor
pora
te d
ebt
to o
wn
fund
s (“
debt
-equ
ity r
atio
”)__
____
____
____
____
____
____
____
____
____
____
____
__2.
12R
atio
of c
orpo
rate
pro
fits
to e
quity
____
____
____
____
____
____
____
____
____
____
____
____
2.13
Rat
io o
f cor
pora
te d
ebt
serv
ice
cost
s to
tot
al c
orpo
rate
inco
me
____
____
____
____
____
____
____
____
____
____
____
____
2.14
Cor
pora
te n
et fo
reig
n cu
rren
cy e
xpos
ure
____
____
____
____
____
____
____
____
____
____
____
____
2.15
Rat
io o
f hou
seho
ld t
otal
deb
t to
GD
P__
____
____
____
____
____
____
____
____
____
____
____
__2.
15a
of w
hich
:mor
tgag
e de
bt t
o G
DP
____
____
____
____
____
____
____
____
____
____
____
____
2.15
bof
whi
ch:d
ebt
owed
to
depo
sito
ry c
orpo
ratio
ns t
o G
DP
____
____
____
____
____
____
____
____
____
____
____
____
2.16
Num
ber
of a
pplic
atio
ns fo
r pr
otec
tion
from
cre
dito
rs__
____
____
____
____
____
____
____
____
____
____
____
__
3.Pr
ofita
bilit
y an
d co
mpe
titive
ness
3.1
Rat
e of
cha
nge
in n
umbe
r of
dep
osito
ry c
orpo
ratio
ns__
____
____
____
____
____
____
____
____
____
____
____
__3.
2R
atio
of p
rofit
s to
per
iod-
aver
age
asse
ts (
ROA
)__
____
____
____
____
____
____
____
____
____
____
____
__3.
3R
atio
of p
rofit
s to
per
iod-
aver
age
equi
ty (
ROE)
____
____
____
____
____
____
____
____
____
____
____
____
3.4
Rat
io o
f net
inte
rest
inco
me
to t
otal
inco
me
____
____
____
____
____
____
____
____
____
____
____
____
3.5
Rat
io o
f tra
ding
and
fore
ign
exch
ange
gai
ns/lo
sses
to
tota
l inc
ome
____
____
____
____
____
____
____
____
____
____
____
____
Appendix V
97
3.6
Rat
io o
f ope
ratin
g co
sts
to n
et in
tere
st in
com
e__
____
____
____
____
____
____
____
____
____
____
____
__3.
7R
atio
of s
taff
cost
s to
ope
ratin
g co
sts
____
____
____
____
____
____
____
____
____
____
____
____
3.8
Spre
ad b
etw
een
refe
renc
e le
ndin
g an
d de
posi
t ra
tes
____
____
____
____
____
____
____
____
____
____
____
____
3.9
Shar
e of
ass
ets
of t
he t
hree
larg
est
depo
sito
ry c
orpo
ratio
ns in
tot
al a
sset
s of
dep
osito
ry c
orpo
ratio
ns__
____
____
____
____
____
____
____
____
____
____
____
__
4.Li
quid
ity
4.1
Dis
trib
utio
n of
thr
ee-m
onth
loca
l-cur
renc
y in
terb
ank
rate
s fo
r di
ffere
nt
depo
sito
ry c
orpo
ratio
ns__
____
____
____
____
____
____
____
____
____
____
____
__4.
2 A
vera
ge in
terb
ank
bid-
ask
spre
ad fo
r th
ree-
mon
th lo
cal-c
urre
ncy
depo
sits
____
____
____
____
____
____
____
____
____
____
____
____
4.3
Rat
io o
f liq
uid
asse
ts t
o to
tal a
sset
s__
____
____
____
____
____
____
____
____
____
____
____
__4.
4 R
atio
of l
iqui
d as
sets
to
liqui
d lia
bilit
ies
____
____
____
____
____
____
____
____
____
____
____
____
4.5
Ave
rage
mat
urity
of a
sset
s__
____
____
____
____
____
____
____
____
____
____
____
__4.
6 A
vera
ge m
atur
ity o
f lia
bilit
ies
____
____
____
____
____
____
____
____
____
____
____
____
4.7
Ave
rage
dai
ly t
urno
ver
in t
he t
reas
ury
bill
(or
cent
ral b
ank
bill)
mar
ket
____
____
____
____
____
____
____
____
____
____
____
____
4.8
Ave
rage
bid
-ask
spr
ead
in t
he t
reas
ury
bill
(or
cent
ral b
ank
bill)
mar
ket
____
____
____
____
____
____
____
____
____
____
____
____
4.9
Rat
io o
f cen
tral
ban
k cr
edit
to d
epos
itory
cor
pora
tions
to
depo
sito
ry
corp
orat
ions
’ tot
al li
abili
ties
____
____
____
____
____
____
____
____
____
____
____
____
4.10
R
atio
of c
usto
mer
dep
osits
to
tota
l (no
nint
erba
nk)
loan
s__
____
____
____
____
____
____
____
____
____
____
____
__4.
11
Rat
io o
f cus
tom
er fo
reig
n cu
rren
cy d
epos
its t
o to
tal (
noni
nter
bank
) fo
reig
n cu
rren
cy lo
ans
____
____
____
____
____
____
____
____
____
____
____
____
5.Se
nsiti
vity
to m
arke
t risk
s
5.1
Rat
io o
f gro
ss fo
reig
n cu
rren
cy a
sset
s to
ow
n fu
nds
____
____
____
____
____
____
____
____
____
____
____
____
5.2
Rat
io o
f net
fore
ign
curr
ency
pos
ition
to
own
fund
s__
____
____
____
____
____
____
____
____
____
____
____
__5.
3 A
vera
ge in
tere
st r
ate
repr
icin
g pe
riod
for
asse
ts__
____
____
____
____
____
____
____
____
____
____
____
__5.
4 A
vera
ge in
tere
st r
ate
repr
icin
g pe
riod
for
liabi
litie
s__
____
____
____
____
____
____
____
____
____
____
____
__5.
5 D
urat
ion
of a
sset
s__
____
____
____
____
____
____
____
____
____
____
____
__5.
6 D
urat
ion
of li
abili
ties
____
____
____
____
____
____
____
____
____
____
____
____
5.7
Rat
io o
f gro
ss e
quity
pos
ition
to
own
fund
s__
____
____
____
____
____
____
____
____
____
____
____
__5.
8 R
atio
of n
et e
quity
pos
ition
to
own
fund
s__
____
____
____
____
____
____
____
____
____
____
____
__5.
9 R
atio
of g
ross
pos
ition
in c
omm
oditi
es t
o ow
n fu
nds
____
____
____
____
____
____
____
____
____
____
____
____
5.10
R
atio
of n
et p
ositi
on in
com
mod
ities
to
own
fund
s__
____
____
____
____
____
____
____
____
____
____
____
__
Add
ition
al C
omm
ents
:Thi
s sp
ace
is fo
r an
y ad
ditio
nal c
omm
ents
you
may
wis
h to
pro
vide
,suc
h as
MPI
s or
top
ics
you
addr
ess
that
are
not
cov
ered
in t
he s
urve
y,M
PIs
defin
eddi
ffere
ntly
tha
n in
the
sur
vey,
or c
once
rns
over
dat
a qu
ality
or
avai
labi
lity.
We
are
also
inte
rest
ed in
vie
ws
rega
rdin
g M
PIs
or t
opic
s th
at a
re n
ot r
elev
ant
for
your
nee
ds o
r th
at a
rese
en a
s im
prac
tical
.
APPENDIX V
98
Tabl
e A
5.2.
MP
I S
urve
y—P
art
I (b
):S
uppl
emen
tary
Iss
ues
1.M
acro
prud
entia
l res
earc
h
Are
you
car
ryin
g ou
t,or
pla
nnin
g,re
sear
ch o
n th
e he
alth
and
sta
bilit
y of
the
fina
ncia
l sys
tem
? Is
thi
s re
sear
ch fo
cuse
d on
the
con
ditio
n of
indi
vidu
al in
stitu
tions
,the
ban
king
sec
tor
as a
who
le,o
r ot
her
sect
ors?
Wha
t an
alyt
ical
or
stat
istic
al fr
amew
orks
are
em
ploy
ed in
thi
s re
sear
ch?
2.Co
vera
ge o
f fin
ancia
l ins
titut
ions
a.O
ther
impo
rtan
t ins
titut
ions
,mar
kets
,and
fina
ncia
l act
ivitie
sIn
add
ition
to
depo
sito
ry c
orpo
ratio
ns,w
hat
othe
r m
arke
ts,i
nstit
utio
ns,a
nd fi
nanc
ial a
ctiv
ities
are
impo
rtan
t in
the
ove
rall
anal
ysis
of t
he s
ound
ness
and
con
ditio
n of
the
fina
ncia
lse
ctor
?
b.Ag
greg
atio
n of
dep
osito
ry in
stitu
tions
With
in t
he d
efin
ition
of
“dep
osito
ry c
orpo
ratio
ns”
used
in t
his
surv
ey,i
s th
ere
a ne
ed fo
r fu
rthe
r di
sagg
rega
tion
or s
peci
al a
naly
sis
of s
peci
fic s
ubse
ctor
s—fo
r ex
ampl
e,fo
rfo
reig
n ba
nks,
inte
rnat
iona
l ban
king
faci
litie
s,in
tern
atio
nally
act
ive
bank
s as
cov
ered
und
er t
he B
asel
sta
ndar
ds,m
utua
l fun
ds,o
r ot
hers
?
c.Sy
stem
ically
impo
rtan
t ins
titut
ions
Wha
t te
chni
ques
are
use
d to
eva
luat
e th
e co
nditi
on o
f sys
tem
ical
ly im
port
ant
inst
itutio
ns in
you
r co
untr
y? H
ow a
re s
yste
mic
ally
impo
rtan
t in
stitu
tions
iden
tifie
d? A
re t
hey
subj
ect
to e
nhan
ced
stat
istic
al r
equi
rem
ents
or
disc
losu
re r
equi
rem
ents
?
Appendix V
99
3.M
PI n
orm
s,be
nchm
arks
,and
thre
shol
ds
Wha
t no
rms
or b
ench
mar
k le
vels
or
rang
es a
re u
sed
for
MPI
s? H
ave
valu
es b
een
iden
tifie
d fo
r w
arni
ng le
vel t
hres
hold
s?
4.Pr
esen
tatio
n of
MPI
s
Plea
se in
dica
te y
our
pref
eren
ces
rega
rdin
g th
e m
ode
for
pres
enta
tion
of M
PIs
(e.g
.,as
sin
gle
poin
t es
timat
es,r
atio
s,gr
owth
rat
es,m
easu
res
of d
ispe
rsio
n,st
anda
rd d
evia
tions
,et
c.).
5.Co
mpo
site
mea
sure
s
Plea
se in
dica
te w
heth
er y
ou u
se,o
r pl
an t
o us
e,co
mpo
site
mea
sure
s of
the
con
ditio
n of
the
fina
ncia
l sys
tem
.Wha
t ty
pes
of in
form
atio
n ar
e us
ed t
o co
nstr
uct
such
mea
sure
s?
6.Bu
sines
s su
rvey
s
Do
you
mak
e us
e of
bus
ines
s su
rvey
res
ults
(ge
nera
l sur
veys
of b
usin
ess
sent
imen
t or
spe
cial
ized
sur
veys
on
finan
cial
inst
itutio
ns)
to s
uppl
emen
t yo
ur a
naly
sis
of M
PIs?
APPENDIX V
100
Table A5.3. MPI Survey—Part II (a): Compilation and Dissemination Questionnaire
Compilation_______________________________________________Periodicity Timeliness
M – monthlyQ – quarterlyS – semi- annuallyA – annually Average number of workingO – other (specify) days after reference period
MPIs and Components X – not compiled X - not compiled
1. Capital adequacy
1.1 Basel capital adequacy ratio ______________________ ______________________a. Basel tier I capital (net of deductions) ______________________ ______________________b. Basel tier II capital (net of deductions) ______________________ ______________________c. Basel tier III capital (net of deductions) ______________________ ______________________d. Risk-weighted assets ______________________ ______________________
1.2 Distribution of capital adequacy ratios ______________________ ______________________a. Number of institutions with Basel capital ratios falling into
specified ranges:Specify range used: —— % to —— %, etc. specify ______________________ ______________________
b. Assets of institutions within each range ______________________ ______________________c. Assets by type of depository corporation: ______________________ ______________________
c.1 Headquartered in the country ______________________ ______________________of which: internationally active ______________________ ______________________of which: state-owned or -controlled ______________________ ______________________
c.2 Headquartered in other countries ______________________ ______________________
1.3 Ratio of total on-balance-sheet assets to own funds ______________________ ______________________a. Total on-balance-sheet assets ______________________ ______________________b. Own funds (equity capital and reserves) ______________________ ______________________
2. Asset quality
(a) Lending institution
2.1 Distribution of on-balance-sheet assets by Basel risk-weight category ______________________ ______________________a. Assets per Basel risk-weight category ______________________ ______________________
2.2 Ratio of total gross asset position in financial derivatives to own funds ______________________ ______________________a. Total gross asset position in derivatives ______________________ ______________________b. of which: off-balance-sheet position ______________________ ______________________
2.3 Ratio of total gross liability position in financial derivatives to own funds ______________________ ______________________a. Total gross liability position in derivatives ______________________ ______________________b. of which: off-balance-sheet position ______________________ ______________________
2.4 Distribution of loans by sector ______________________ ______________________a. Loans by national account sectors ______________________ ______________________
of which: ______________________ ______________________a.1. Loans for investment in commercial real estate ______________________ ______________________a.2. Loans for investment in residential real estate ______________________ ______________________a.3. Loans to other key sectors specify ______________________ ______________________
b. Total loans ______________________ ______________________
2.5 Distribution of credit extended by sector ______________________ ______________________a. Credit by national account sectors ______________________ ______________________b. Total credit ______________________ ______________________
2.6 Distribution of credit by country or region ______________________ ______________________a. Loans by country or region ______________________ ______________________
2.7 Ratio of credit to related entities to total credit ______________________ ______________________a. Credit to related entities ______________________ ______________________
2.8 Ratio of total large loans to own funds ______________________ ______________________a. Total large loans (specify size range) specify ______________________ ______________________
2.9 Ratio of gross nonperforming loans to total assets ______________________ ______________________a. Gross nonperforming loans ______________________ ______________________
2.10 Ratio of nonperforming loans net of provisions to total assets ______________________ ______________________a. Nonperforming loans net of provisions ______________________ ______________________
Appendix V
101
Dissemination Data Sources_________________________________________________ ____________________________________________________Periodicity Timeliness Supervisory Statistical Other (specify)
M – monthlyQ – quarterlyS – semi- annually (Indicate type of consolidation used)A – annually Average number of working G = global consolidationO – other (specify) days after reference period N = national consolidationX – not disseminated X - not disseminated B = both national and global consolidation
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
APPENDIX V
102
Table A5.3 (continued)
Compilation_______________________________________________Periodicity Timeliness
M – monthlyQ – quarterlyS – semi- annuallyA – annually Average number of workingO – other (specify) days after reference period
MPIs and Components X – not compiled X - not compiled
(b) Borrowing institution
2.11 Ratio of corporate debt to own funds (“debt-equity ratio”) ______________________ ______________________a. Total corporate debt ______________________ ______________________b. Corporations’ own funds ______________________ ______________________
2.12 Ratio of corporate profits to equity ______________________ ______________________a. Corporate pre-tax profits ______________________ ______________________b. Corporate post-tax profits ______________________ ______________________
2.13 Ratio of corporate debt service costs to profits ______________________ ______________________a. Corporate debt service costs ______________________ ______________________
2.14 Corporate net foreign currency exposure ______________________ ______________________a. Gross foreign currency assets ______________________ ______________________b. Gross foreign currency liabilities ______________________ ______________________c. Net off-balance-sheet foreign currency positions (nominal value)
not included above ______________________ ______________________
2.15 Ratio of household debt to GDP ______________________ ______________________a. Household total debt ______________________ ______________________b. of which: mortgage debt ______________________ ______________________c. of which: debt to depository corporations ______________________ ______________________
2.16 Number of applications for protection from creditors ______________________ ______________________
3. Profitability and competitiveness
3.1 Rate of change in the number of depository corporations ______________________ ______________________a. Difference between number of institutions at beginning and end of period ______________________ ______________________b. of which: due to mergers and acquisitions ______________________ ______________________c. of which: due to withdrawals of licenses or closing of units ______________________ ______________________
3.2 Ratios of profits to period-average assets (ROA) ______________________ ______________________a. Pretax, after provisions profits ______________________ ______________________b. Posttax profits ______________________ ______________________c. Total period-average on-balance-sheet assets ______________________ ______________________
3.3 Ratios of profits to period-average equity (ROE) ______________________ ______________________a. Pretax, after provisions profits ______________________ ______________________b. Posttax profits ______________________ ______________________c. Period-average equity ______________________ ______________________
3.4 Ratio of net interest income to profits ______________________ ______________________a. Net interest income ______________________ ______________________
3.5 Ratio of trading and foreign-currency gains/losses to profits ______________________ ______________________a. Gains/losses in securities and foreign currencies ______________________ ______________________
3.6 Ratio of operating costs to net interest income ______________________ ______________________a. Operating costs ______________________ ______________________
3.7 Ratio of staff costs to operating costs ______________________ ______________________a. Staff costs ______________________ ______________________
3.8 Spreads between reference lending and deposit rates ______________________ ______________________a. Reference lending rate specify ______________________ ______________________b. Reference deposit rate specify ______________________ ______________________
3.9 Share of assets of the three largest depository corporations in total assets of depository corporations ______________________ ______________________
a. Assets of the three largest depository corporations ______________________ ______________________
Appendix V
103
Dissemination Data Sources_________________________________________________ ____________________________________________________Periodicity Timeliness Supervisory Statistical Other (specify)
M – monthlyQ – quarterlyS – semi- annually (Indicate type of consolidation used)A – annually Average number of working G = global consolidationO – other (specify) days after reference period N = national consolidationX – not disseminated X - not disseminated B = both national and global consolidation
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
APPENDIX V
104
Table A5.3 (continued)
Compilation_______________________________________________Periodicity Timeliness
M – monthlyQ – quarterlyS – semi- annuallyA – annually Average number of workingO – other (specify) days after reference period
MPIs and Components X – not compiled X - not compiled
4. Liquidity
4.1 Distribution of three-month local-currency interbank rates for different banks ______________________ ______________________
4.2 Average interbank bid-ask spread for three-month local currency interbank deposits ______________________ ______________________
4.3 Ratio of liquid assets to total assets ______________________ ______________________a. Liquid assets ______________________ ______________________
4.4 Ratio of liquid assets to liquid liabilities ______________________ ______________________a. Liquid liabilities ______________________ ______________________
4.5 Average maturity of assets ______________________ ______________________a. Average remaining maturity of assets (months) ______________________ ______________________b. of which: foreign currency assets ______________________ ______________________c. Average original maturity of assets (months) ______________________ ______________________d. of which: foreign currency assets ______________________ ______________________
4.6 Average maturity of liabilities ______________________ ______________________a. Average remaining maturity of liabilities (months) ______________________ ______________________b. of which: foreign currency liabilities ______________________ ______________________c. Average original maturity of liabilities (months) ______________________ ______________________d. of which: foreign currency liabilities ______________________ ______________________
4.7 Average daily turnover in the Treasury bill (or central bank bill) market ______________________ ______________________
4.8 Average bid-ask spread in the Treasury bil (or central bank bill) market ______________________ ______________________
4.9 Ratio of central bank credit to depository corporations to their total liabilities ______________________ ______________________a. Total credit from the central bank to depository corporations ______________________ ______________________b. Total liabilities ______________________ ______________________
4.10 Ratio of total customer deposits to total (noninterbank) loans ______________________ ______________________a. Customer (noninterbank) deposits ______________________ ______________________b. Total (noninterbank) loans ______________________ ______________________
4.11 Ratio of foreign currency customer deposits to total (noninterbank) foreign currency loans ______________________ ______________________
a. Customer (noninterbank) foreign currency deposits ______________________ ______________________b. Customer (noninterbank) foreign currency loans ______________________ ______________________
5. Sensitivity to market risks
5.1 Ratio of gross foreign currency assets to own funds ______________________ ______________________a. Gross foreign currency assets ______________________ ______________________
5.2 Ratio of net foreign currency position to own funds ______________________ ______________________a. Gross foreign currency assets ______________________ ______________________b. Gross foreign currency liabilities ______________________ ______________________c. Net off-balance-sheet foreign currency positions (nominal value) not
included above ______________________ ______________________
5.3 Average interest rate repricing period for assets ______________________ ______________________
5.4 Average interest rate repricing period for liabilities ______________________ ______________________
5.5 Duration of assets ______________________ ______________________
5.6 Duration of liabilities ______________________ ______________________
5.7 Ratio of gross position in equities to own funds ______________________ ______________________a. Gross holdings of equities ______________________ ______________________
Appendix V
105
Dissemination Data Sources_________________________________________________ ____________________________________________________Periodicity Timeliness Supervisory Statistical Other (specify)
M – monthlyQ – quarterlyS – semi- annually (Indicate type of consolidation used)A – annually Average number of working G = global consolidationO – other (specify) days after reference period N = national consolidationX – not disseminated X - not disseminated B = both national and global consolidation
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
APPENDIX V
106
Table A5.3 (concluded)
Compilation_______________________________________________Periodicity Timeliness
M – monthlyQ – quarterlyS – semi- annuallyA – annually Average number of workingO – other (specify) days after reference period
MPIs and Components X – not compiled X - not compiled
5.8 Ratio of net position in equities to own funds ______________________ ______________________a. Gross holdings of equities ______________________ ______________________b. Net off-balance-sheet nominal-value position in equities not included above ______________________ ______________________
5.9 Ratio of gross position in commodities to own funds ______________________ ______________________a. Gross asset position in commodities ______________________ ______________________
5.10 Ratio of net position in commodities to own funds ______________________ ______________________a. Gross asset position in commodities ______________________ ______________________b. Net off-balance-sheet nominal-value position in commodities,
not included above ______________________ ______________________
Additional Comments:This space is for any additional comments you may wishto provide, such as MPIs or topics you address that are not covered in the survey, MPIs defined differently than in the survey, or concerns over data quality or availability. We are also interested in views regarding MPIs or topics that are not relevant for your needs or that are seen as impractical.
Appendix V
107
Dissemination Data Sources_________________________________________________ ____________________________________________________Periodicity Timeliness Supervisory Statistical Other (specify)
M – monthlyQ – quarterlyS – semi- annually (Indicate type of consolidation used)A – annually Average number of working G = global consolidationO – other (specify) days after reference period N = national consolidationX – not disseminated X - not disseminated B = both national and global consolidation
______________________ ______________________ _______________ _______________ _______________ ______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _____________________________________ ______________________ _______________ _______________ _______________
______________________ ______________________ _______________ _______________ _______________
APPENDIX V
108
Table A5.4. MPI Survey—Part II (b): Supplementary Issues
1. Institutional coveragea. Supervisory responsibility over financial institutionsPlease list the institutions that have supervisory responsibility for various segments of the financial system and financial activities.
b. Institutional coveragePlease specify the institutional coverage for each data source (e.g., supervisory, statistical, other). Coverage of branches andsubsidiaries of foreign financial institutions operating in the country should be described. Also describe coverage of offshorebanking operations.
2. Loan classification and provisioning rulesa. Classification rulesPlease describe the system for grading nonperforming loans.
b. Income recognition/interest accrual rulesPlease describe practices and standards for recognition of income, accrual of interest, or other changes in value.
c. Loan-loss provisioning rulesPlease describe the rules governing the recognition and valuation of provisions.
d. CollateralPlease describe requirements and valuation rules for collateral (including real estate).
3. Capital classification rulesPlease describe the components of tier I, tier II, and (if applicable) tier III capital, and the deductions for each category.
4. Other issuesPlease describe practices for recognition and instrument classification for repurchase agreements, securities lending, bankers’acceptances, and financial derivatives.
5. Real estate lendingPlease describe the categories of lending that are recorded as real estate lending, such as loans for the purpose of real estateconstruction, loans to construction companies, loans collateralized by real estate, mortgage loans, etc. What real estate priceinformation is available?
6. Data disseminationa. Restrictions on dissemination of aggregated dataPlease describe legal and other restrictions on the dissemination of the MPIs and their components to the public.
b. Restrictions on dissemination of individual institutions’ dataPlease describe legal and other restrictions on the disclosure of information on individual financial institutions (including anyrestrictions on provision of information to the IMF).
Appendix V
109
Tabl
e A
5.5.
MP
I S
urve
y—P
art
II (
c):V
alua
tio
n Is
sues Pr
ice
Fore
ign
Cur
renc
y-D
enom
inat
ed In
stru
men
ts__
____
____
____
____
____
____
____
____
____
____
____
____
___
____
____
____
____
____
____
____
____
____
____
____
____
____
_R
efer
ence
pri
ceFr
eque
ncy
of r
eval
uatio
nsC
onve
rsio
n ex
chan
ge r
ate
Freq
uenc
y of
rev
alua
tions
____
____
____
____
____
____
____
____
____
____
____
___
____
____
____
____
____
____
___
____
____
____
____
____
____
H =
his
tori
c co
stE
= m
arke
t ra
te (
end
peri
od)
M =
mar
ket
pric
e/fa
ir v
alue
A =
mar
ket
rate
(pe
r.av
erag
e)L
= lo
wer
of c
ost
or m
arke
tB
= o
n-ba
lanc
e-sh
eet
date
G =
offi
cial
rat
eB
= o
n-ba
lanc
e-sh
eet
date
O =
oth
er (
spec
ify)
O =
oth
er (
spec
ify)
O =
oth
er (
spec
ify)
O =
oth
er (
spec
ify)
1.Su
perv
isor
y D
ata
Sour
ces
a.D
epos
its__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_b.
Loan
s__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_c.
Secu
ritie
s (o
ther
tha
n sh
ares
)__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_d.
Shar
es a
nd o
ther
equ
ity__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_e.
Fina
ncia
l der
ivat
ives
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
f.M
isce
llane
ous
rece
ivab
les/
paya
bles
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
g.N
onfin
anci
al a
sset
s (r
eal e
stat
e an
d ot
her
asse
ts)
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
2.St
atis
tical
Dat
a So
urce
s
a.D
epos
its__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_b.
Loan
s__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_c.
Secu
ritie
s (o
ther
tha
n sh
ares
)__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_d.
Shar
es a
nd o
ther
equ
ity__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_e.
Fina
ncia
l der
ivat
ives
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
f.M
isce
llane
ous
rece
ivab
les/
paya
bles
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
g.N
onfin
anci
al a
sset
s (r
eal e
stat
e an
d ot
her
asse
ts)
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
3.O
ther
Dat
a So
urce
s
a.D
epos
its__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_b.
Loan
s__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_c.
Secu
ritie
s (o
ther
tha
n sh
ares
)__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_d.
Shar
es a
nd o
ther
equ
ity__
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
_e.
Fina
ncia
l der
ivat
ives
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
f.M
isce
llane
ous
rece
ivab
les/
paya
bles
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
g.N
onfin
anci
al a
sset
s (r
eal e
stat
e an
d ot
her
asse
ts)
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
____
____
____
____
____
___
OCCASIONAL PAPERS
Recent Occasional Papers of the International Monetary Fund212. Financial Soundness Indicators: Analytical Aspects and Country Practices, by V. Sundararajan, Charles
Enoch, Armida San José, Paul Hilbers, Russell Krueger, Marina Moretti, and Graham Slack. 2002.
211. Capital Account Liberalization and Financial Sector Stability, by a staff team led by Shogo Ishii and KarlHabermeier. 2002.
210. IMF-Supported Programs in Capital Account Crises, by Atish Ghosh, Timothy Lane, Marianne Schulze-Ghattas, Alesv Bulírv, Javier Hamann, and Alex Mourmouras. 2002.
209. Methodology for Current Account and Exchange Rate Assessments, by Peter Isard, Hamid Faruqee, G.Russell Kincaid, and Martin Fetherston. 2001.
208. Yemen in the 1990s: From Unification to Economic Reform, by Klaus Enders, Sherwyn Williams, NadaChoueiri, Yuri Sobolev, and Jan Walliser. 2001.
207. Malaysia: From Crisis to Recovery, by Kanitta Meesook, Il Houng Lee, Olin Liu, Yougesh Khatri, NataliaTamirisa, Michael Moore, and Mark H. Krysl. 2001.
206. The Dominican Republic: Stabilization, Structural Reform, and Economic Growth, by Alessandro Gius-tiniani, Werner C. Keller, and Randa E. Sab. 2001.
205. Stabilization and Savings Funds for Nonrenewable Resources, by Jeffrey Davis, Rolando Ossowski,James Daniel, and Steven Barnett. 2001.
204. Monetary Union in West Africa (ECOWAS): Is It Desirable and How Could It Be Achieved? by PaulMasson and Catherine Pattillo. 2001.
203. Modern Banking and OTC Derivatives Markets: The Transformation of Global Finance and Its Implicationsfor Systemic Risk, by Garry J. Schinasi, R. Sean Craig, Burkhard Drees, and Charles Kramer. 2000.
202. Adopting Inflation Targeting: Practical Issues for Emerging Market Countries, by Andrea Schaechter,Mark R. Stone, and Mark Zelmer. 2000.
201. Developments and Challenges in the Caribbean Region, by Samuel Itam, Simon Cueva, Erik Lundback,Janet Stotsky, and Stephen Tokarick. 2000.
200. Pension Reform in the Baltics: Issues and Prospects, by Jerald Schiff, Niko Hobdari, Axel Schimmelpfen-nig, and Roman Zytek. 2000.
199. Ghana: Economic Development in a Democratic Environment, by Sérgio Pereira Leite, Anthony Pelle-chio, Luisa Zanforlin, Girma Begashaw, Stefania Fabrizio, and Joachim Harnack. 2000.
198. Setting Up Treasuries in the Baltics, Russia, and Other Countries of the Former Soviet Union: An Assess-ment of IMF Technical Assistance, by Barry H. Potter and Jack Diamond. 2000.
197. Deposit Insurance: Actual and Good Practices, by Gillian G.H. Garcia. 2000.196. Trade and Trade Policies in Eastern and Southern Africa, by a staff team led by Arvind Subramanian, with
Enrique Gelbard, Richard Harmsen, Katrin Elborgh-Woytek, and Piroska Nagy. 2000.195. The Eastern Caribbean Currency Union—Institutions, Performance, and Policy Issues, by Frits van Beek,
José Roberto Rosales, Mayra Zermeño, Ruby Randall, and Jorge Shepherd. 2000.194. Fiscal and Macroeconomic Impact of Privatization, by Jeffrey Davis, Rolando Ossowski, Thomas
Richardson, and Steven Barnett. 2000.193. Exchange Rate Regimes in an Increasingly Integrated World Economy, by Michael Mussa, Paul Masson,
Alexander Swoboda, Esteban Jadresic, Paolo Mauro, and Andy Berg. 2000.192. Macroprudential Indicators of Financial System Soundness, by a staff team led by Owen Evans, Alfredo
M. Leone, Mahinder Gill, and Paul Hilbers. 2000.191. Social Issues in IMF-Supported Programs, by Sanjeev Gupta, Louis Dicks-Mireaux, Ritha Khemani,
Calvin McDonald, and Marijn Verhoeven. 2000.190. Capital Controls: Country Experiences with Their Use and Liberalization, by Akira Ariyoshi, Karl Haber-
meier, Bernard Laurens, Inci Ötker-Robe, Jorge Iván Canales Kriljenko, and Andrei Kirilenko. 2000.189. Current Account and External Sustainability in the Baltics, Russia, and Other Countries of the Former So-
viet Union, by Donal McGettigan. 2000.188. Financial Sector Crisis and Restructuring: Lessons from Asia, by Carl-Johan Lindgren, Tomás J.T.
Baliño, Charles Enoch, Anne-Marie Gulde, Marc Quintyn, and Leslie Teo. 1999.
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Occasional Papers
187. Philippines: Toward Sustainable and Rapid Growth, Recent Developments and the Agenda Ahead, byMarkus Rodlauer, Prakash Loungani, Vivek Arora, Charalambos Christofides, Enrique G. De la Piedra,Piyabha Kongsamut, Kristina Kostial, Victoria Summers, and Athanasios Vamvakidis. 2000.
186. Anticipating Balance of Payments Crises: The Role of Early Warning Systems, by Andrew Berg,Eduardo Borensztein, Gian Maria Milesi-Ferretti, and Catherine Pattillo. 1999.
185. Oman Beyond the Oil Horizon: Policies Toward Sustainable Growth, edited by Ahsan Mansur and VolkerTreichel. 1999.
184. Growth Experience in Transition Countries, 1990–98, by Oleh Havrylyshyn, Thomas Wolf, Julian Beren-gaut, Marta Castello-Branco, Ron van Rooden, and Valerie Mercer-Blackman. 1999.
183. Economic Reforms in Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan, and Uzbekistan, byEmine Gürgen, Harry Snoek, Jon Craig, Jimmy McHugh, Ivailo Izvorski, and Ron van Rooden. 1999.
182. Tax Reform in the Baltics, Russia, and Other Countries of the Former Soviet Union, by a staff team led byLiam Ebrill and Oleh Havrylyshyn. 1999.
181. The Netherlands: Transforming a Market Economy, by C. Maxwell Watson, Bas B. Bakker, Jan KeesMartijn, and Ioannis Halikias. 1999.
180. Revenue Implications of Trade Liberalization, by Liam Ebrill, Janet Stotsky, and Reint Gropp. 1999.179. Disinflation in Transition: 1993–97, by Carlo Cottarelli and Peter Doyle. 1999.178. IMF-Supported Programs in Indonesia, Korea, and Thailand: A Preliminary Assessment, by Timothy Lane,
Atish Ghosh, Javier Hamann, Steven Phillips, Marianne Schulze-Ghattas, and Tsidi Tsikata. 1999.177. Perspectives on Regional Unemployment in Europe, by Paolo Mauro, Eswar Prasad, and Antonio Spilim-
bergo. 1999.176. Back to the Future: Postwar Reconstruction and Stabilization in Lebanon, edited by Sena Eken and
Thomas Helbling. 1999.175. Macroeconomic Developments in the Baltics, Russia, and Other Countries of the Former Soviet Union,
1992–97, by Luis M. Valdivieso. 1998.174. Impact of EMU on Selected Non–European Union Countries, by R. Feldman, K. Nashashibi, R. Nord,
P. Allum, D. Desruelle, K. Enders, R. Kahn, and H. Temprano-Arroyo. 1998.
173. The Baltic Countries: From Economic Stabilization to EU Accession, by Julian Berengaut, AugustoLopez-Claros, Françoise Le Gall, Dennis Jones, Richard Stern, Ann-Margret Westin, Effie Psalida,Pietro Garibaldi. 1998.
172. Capital Account Liberalization: Theoretical and Practical Aspects, by a staff team led by Barry Eichen-green and Michael Mussa, with Giovanni Dell'Ariccia, Enrica Detragiache, Gian Maria Milesi-Ferretti,and Andrew Tweedie. 1998.
171. Monetary Policy in Dollarized Economies, by Tomás Baliño, Adam Bennett, and Eduardo Borensztein.1998.
170. The West African Economic and Monetary Union: Recent Developments and Policy Issues, by a staffteam led by Ernesto Hernández-Catá and comprising Christian A. François, Paul Masson, Pascal Bou-vier, Patrick Peroz, Dominique Desruelle, and Athanasios Vamvakidis. 1998.
169. Financial Sector Development in Sub-Saharan African Countries, by Hassanali Mehran, Piero Ugolini,Jean Phillipe Briffaux, George Iden, Tonny Lybek, Stephen Swaray, and Peter Hayward. 1998.
168. Exit Strategies: Policy Options for Countries Seeking Greater Exchange Rate Flexibility, by a staff teamled by Barry Eichengreen and Paul Masson with Hugh Bredenkamp, Barry Johnston, Javier Hamann,Esteban Jadresic, and Inci Ötker. 1998.
167. Exchange Rate Assessment: Extensions of the Macroeconomic Balance Approach, edited by Peter Isardand Hamid Faruqee. 1998.
166. Hedge Funds and Financial Market Dynamics, by a staff team led by Barry Eichengreen and DonaldMathieson with Bankim Chadha, Anne Jansen, Laura Kodres, and Sunil Sharma. 1998.
165. Algeria: Stabilization and Transition to the Market, by Karim Nashashibi, Patricia Alonso-Gamo, StefaniaBazzoni, Alain Féler, Nicole Laframboise, and Sebastian Paris Horvitz. 1998.
Note: For information on the title and availability of Occasional Papers not listed, please consult the IMF Publications Catalog or contact IMFPublication Services.
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Financial Soundness Indicators:Analytical Aspects and Country Practices
ISBN 1-58906-086-5
