Back Matter

Back Matter

Paul Hilbers, Alfredo Leone, Mahinder Gill, and Owen Evens
Published Date:
April 2000
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Appendix I Existing Data Collection Frameworks

This appendix reviews the frameworks for the collection of MPIs already in place in international and regional organizations to ascertain the types of data generally available, to identify gaps or weaknesses in coverage, and to assess the potential for exchange of data and cooperation in collection of MPIs.

International Monetary Fund

The IMF collects and disseminates a wide variety of macrostatisics, but does not systematically collect financial microdata. The IMF’s monetary statistics comprise a very extensive database on banking institutions. These data are potentially very important for macroprudential analysis because many MPIs and the monetary statistics compiled by the IMF are derived from the same data sources—central bank and commercial bank balance sheets. The data have a monthly periodicity and are provided to the IMF as soon as possible after the reference date. An analytical presentation of monetary data is published in International Financial Statistics. The published data only highlight a limited number of monetary and credit aggregates. These aggregates are presented in a modified balance sheet format that does not present total assets, total liabilities, and detailed capital account information, and thus does not provide the structural information needed for macroprudential analysis. Also, the monetary statistics have not been constructed under standard accounting rules, such as for valuation or provisioning, which detracts from their usefulness for macroprudential purposes. Similarly, data on bank income, expenses, and profitability, which are used in many MPIs, are not collected.

A number of changes to the methodology for compiling these monetary statistics, which will bring about greater standardization and harmonization between countries, will be introduced when the IMF’s new Manual on Monetary and Financial Statistics is published. The manual recommends that all countries apply the statistical standards presented in the System of National Accounts, 1993, which will result in standard statistical accounting treatments, definitions of the financial sector, and classifications and treatments of financial instruments. The manual also provides for compilation of aggregate balance sheets for the domestic banking sector, which in most countries would be the only aggregate statistics on the financial positions and condition of financial institutions. Implementation of the standards in the manual would aid countries in producing MPIs in a number of ways, including by providing a framework for the classification and the measurement of financial derivatives, and recording assets at their fair market value. The framework of the manual was not designed with MPIs in mind, but it could be extended—after some conceptual work is done—to accommodate further information on MPIs, such as on asset quality, credit concentration, capital adequacy, and relations with foreign affiliates. Perhaps half of the proposed MPIs could be integrated into the monetary statistics framework, with varying degrees of difficulty.

Bank for International Settlements

The BIS publishes international banking statistics in the form of a semiannual consolidated report of statistics on the amount, maturity, and sectoral and nationality distribution of international bank lending. These data are available to the public through the BIS website ( The data are also included in a joint BIS/IMF/OECD/World Bank quarterly statistical release on external debt, which was recently introduced in order to facilitate timely access to a single set of debt indicators. These data are also analyzed in depth in the BIS International Banking and Financial Market Developments, which also presents discussions of conceptual and statistical issues related to the data, as needed.

The BIS staff, partly in support of the Committee on the Global Financial System and its predecessor, the Euro-Currency Standing Committee, have carried out work following the financial crises in the early 1990s with a view to identifying indicators of financial risk, and data have been collected as needed to support these analyses.

European Central Bank

The ECB has initiated an MPI project that has identified the EMU monetary statistics as a source of macroprudential information. The EMU countries compile a harmonized set of monetary statistics to provide the statistical basis for the operation of the EMU single monetary policy.90 The statistics are compiled on a timely basis according to statistical standards based on the European System of Accounts, 1995 (ESA95).91 Because universal banking prevails in Europe, the EMU monetary data cover most of the EMU financial sector.

The EMU monetary statistics are presented in a straightforward balance sheet format, with a reasonable amount of detail on financial instruments and counterparty sector. The data compiled for each country cover each institution’s activity within the country, and separate information is provided on positions with other countries within the EMU and with nonresidents of the EMU. This statistical construction permits the European System of Central Banks (ESCB) to produce a comprehensive picture of the financial positions of domestic financial institutions vis-á-vis residents of the country and residents of the EMU. Although there are some limitations to the data because the reporting system was designed primarily to serve monetary statistics purposes, the EMU monetary statistics framework is comprehensive and methodologically strong. The framework is also being enhanced to better incorporate the needs of macroprudential analysis.

The Banking Supervision Committee of the ESCB has initiated a project to identify MPIs for the EU banking sector, and has established a Working Group on Macroprudential Analysis to that end (see Section IV). The ECB has recently completed a “gaps exercise” to inquire about the availability of data at the EU national central banks needed to calculate MPIs from existing data sources. A selection has been made of indicators to follow and data sources to use. The ECB and national central banks are now putting into place mechanisms for compiling the data. Most of the balance sheet data sought will be taken directly from monetary statistics: monthly balance sheets for the banking sector, supplemented by quarterly information that provides greater detail on borrowing from and lending to nonbank financial institutions, corporations, and households (including a split between consumer credit and mortgage lending). There is also information on particular types of lending, deposit rates, and interest rate spreads. Data collection at this stage is limited to the banking sector. In addition to the collection of data through the monetary statistics system, other data are being gathered from national supervisory sources within the Banking Supervision Committee. This exercise draws also on data collection carried out in other supervisory forums, notably the “Groupe de Contact” (composed of representatives of the supervisory authorities of the countries in the European Economic Area). Subsequent actions will depend on the results of the exercise.

EMU member countries also prepare financial accounts that detail financial assets and liabilities of all major sectors of an economy, and the ECB and Eurostat jointly prepare the Monetary Union Financial Accounts (MUFA). The statistical standards for financial accounts are based on ESA95 and thus are harmonized with the standards for monetary statistics, so that it is possible to embed the analysis of the banking sector within the statistical framework for financial activity for the entire economy and its key components. The specific importance of financial accounts for MPIs is that relationships between the financial sector and its creditor and debtor sectors are made explicit in a way that allows tracking of the influence of macroeconomic trends on the condition of the financial sector. The sectoral accounts also permit analysis of the financial strength or vulnerabilities of the various sectors, thus supporting the analysis of transmission of financial strains between the rest of the economy and the banking sector.

World Bank

As noted in Section IV, the World Bank is involved in the analysis of financial sector soundness, including through its joint work with the IMF under the FSAP. The Financial Sector Liaison Committee of the World Bank and the IMF is currently discussing options for the joint development of a financial sector database for internal use that will include qualitative information, macroeconomic time series, and aggregated microprudential information. Most of the statistical data will be drawn from databases maintained by other institutions, but will also include information gathered during the FSAP missions and other consultations with member countries. The World Bank also makes use of macroprudential information in risk assessment models used in conjunction with its lending operations.

Organization for Economic Cooperation and Development

The OECD collects a wide range of financial sector data from its member countries for use in its regular analysis of national and international financial conditions, as presented in its Financial Market Trench and numerous other analytical and statistical reports. The OECD does not presently collect specific MPIs, but uses a broad range of macro- and microstatistics and qualitative information in its assessments of countries’ financial situations. However, two OECD publications are of particular interest for macroprudential purposes.

  • Bank Profitability presents data on (1) bank income, expenditure, and profitability; (2) balance sheets, with substantial detail; (3) capital adequacy; (4) supplemental data on the number of institutions and employment; and (5) some limited information on the overall structure of the financial system. A number of countries provide data disaggregated by major type of bank. Data are available for all OECD member countries, using a standard set of tables that have a rather detailed breakdown. The data are subject to a number of limitations, however, mostly the result of diversity in national coverage.92 Data have an annual periodicity, and the latest data in the 1999 report are from 1997 for all but a few countries.
  • Financial Accounts of OECD Countries presents standard tables with annual data on flows of funds and balance sheets of most OECD countries. Detail is given by type of financial instrument and counterparty sector, and sometimes with links to gross saving and investment in the national accounts. These data are compiled in accordance with SNA standards and thus provide links between the financial sector and the overall national economy. This multi-sector by financial instrument framework is potentially useful for macroprudential analysis by permitting examination of the concentration of lending by sector and the transmission of financial stress across sectors. Although adherence to SNA standards imparts some comparability of data across countries, the foreword warns that the “extreme diversity that characterizes the financial institutions of the member countries and the financial instruments they use may limit the comparability of the statistics.”. Data users are advised to refer to a methodological supplement for information on standard concepts, calculation methods, and individual country notes. Other limitations are the restricted country coverage, availability of only annual data, and the long lags in the production of data by some countries.
Appendix II Special Data Dissemination Standard and General Data Dissemination System

Recent financial crises have given rise to increased efforts by the international community to foster macroeconomic stability and financial system soundness. Transparency in the functioning of world capital markets and of countries’ financial policies is being promoted. The IMF has taken numerous steps to enhance transparency and openness, including the establishment and recent strengthening of disclosure standards to guide countries in a number of areas, including data dissemination. The need for these standards, first highlighted by the Mexican financial crisis in 1994895, was underscored by the recent financial crises in Asia and elsewhere. The Special Data Dissemination Standard, complete with an electronic bulletin board—and in a growing number of cases, electronic links that enable users to move between the metadata and the actual data—has been in place since March 1996. The General Data Dissemination System was established in December 1997.

Special Data Dissemination Standard

Countries subscribing to the SDDS undertake to follow good practices in four dimensions:

  • Data—coverage, periodicity, and timeliness:
  • Access by the public—dissemination of advance release calendars, and simultaneous release of the data;
  • Integrity—disclosure of information on laws governing the compilation and release of the data, access to the data by other government officials prior to release, ministerial commentary accompanying the release of the data, revision policy, and advance notice of major changes in methodology; and
  • Quality—dissemination of documentation on methodology and sources, and dissemination of detailed data that support statistical cross-checks.

Under the SDDS, data dissemination practices are described for a total of 20 data categories covering the real, fiscal, financial, and external sectors as well as for population, and are posted on the Dissemination Standards Bulletin Board. To date, 47 countries—representing a mix of industrial, emerging market, and transition economies—have voluntarily subscribed to the SDDS. Countries are also required to establish an Internet site containing the actual data disseminated under the SDDS, called a national summary data page that is hyperlinked to the DSBB.

The SDDS has led to wider availability and enhanced timeliness of published data and greater use of advance data release calendars. In light of the recent financial crises, the IMF has also taken steps to strengthen the SDDS, particularly in the areas of international reserves and external debt. The new reserves template is more comprehensive than the existing prescription, with subscribers having until March 31, 2000, to meet the new requirements. Improvements in external debt data are also taking place.

General Data Dissemination System

The GDDS, like the SDDS, was developed in close collaboration with a wide range of producers and users of statistics. The primary focus of the GDDS is on improvement in data quality. This stands in contrast with the SDDS, where the focus is on dissemination in countries that generally already meet high data quality standards. Against this background, the GDDS is one of the most important strategic projects for the IMF in the area of statistics, where a long-standing objective has been the improvement of data and statistical practices among the membership. It is hoped that the GDDS will also be a valuable resource for bilateral and multilateral providers of technical assistance, and that the GDDS can provide the basis for enhanced cooperation with other providers of technical assistance. The GDDS’s purposes are (1) to encourage member countries to improve data quality; (2) to provide a framework for evaluating needs for data improvement and setting priorities in this respect; and (3) to guide member countries in the dissemination to the public of comprehensive, timely, accessible, and reliable economic, financial, and sociodemographic statistics. The framework takes into account, across the broad range of countries, the diversity of their economies and the developmental requirements of their statistical systems.

Dissemination Standards Bulletin Board

The DSBB website (, which is maintained by the IMF, serves as a toot for market analysts and others who track economic growth, inflation, and other economic and financial developments in countries around the world. The aim of the DSBB is to strengthen the availability of timely and comprehensive information on economic and financial statistics and to contribute to the pursuit of sound macroeconomic policies and improved functioning of financial markets.

The DSBB describes the statistical practices of the SDDS-participating countries in the collection, compilation, and dissemination of key macroeconomic indicators. DSBB users also have access to actual country data on the national summary data pages, A project is under way to enhance the DSBB website with regard to (1) presentation and functionality; (2) tools for metadata management; (3) provision of a database for data that are accessible on or via the DSBB; and (4) marketing of the DSBB.


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The FSAP was launched jointly with the World Bank on a pilot basis in May 1999. The program is designed to identify financial system strengths and vulnerabilities and to help develop appropriate policy responses. The FSSA reports, which locus on financial system issues of significance for macroeconomic performance and policies, are prepared on the basis of the FSAP by IMF staff for discussion in the IMF Executive Board, within the context or Article IV surveillance. In the World Bank, the FSAP reports provide the foundations for the formulation of financial sector development strategies.


Observation lags should be short to allow timely monitoring. Stress testing these indicators could provide an early warning regarding vulnerabilities.


The IMF’s FSSAs combine the analysis or MPIs with a comprehensive review of these qualitative aspects (see Section V).


For example, whereas in one country an indicator may be constructed using a narrow monetary aggregate, in another country a broad aggregate may be more meaningful.


On an aggregate basis for the financial system as a whole, however, some or the indicators that are useful for individual institutions may not be applicable and meaningful. Problems of aggregation and measurement are discussed further in Section VI.


Actual (observed) capital adequacy ratios are lagged indicators of banking problems—by the time capital adequacy ratios show a decline, financial institutions generally have already been experiencing serious problems.


Tier 1 capital consists of permanent shareholders’ equity and disclosed 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 or subordinated short-term debt (over two years). Sec BIS (1988, 1996).


The analysis of financial sector stability may sometimes require information on the condition of individual large banks because of their market power or the possibility of contagion to other firms; sec, for example, Downes, Marston, and Olker (1999). A specific problem for macroprudcnlial analysis is how to integrate (1) microinformation on specific firms, which is highly affected by accounting and supervisory standards and lire structure of the firm’s global operations; (2) information on the structure of the industry (e.g., concentration, foreign ownership, public sector institutions, overconcentrated lending); and (3) national macroeconomic information. This process might involve using measures of dispersion, concentration, large-bank group analysis, or multivariate analysis.


Among other factors, differential reserve requirements in some countries create incentives for foreign currency-denominated intermediation by making if relatively more competitive than intermediation denominated in domestic currency.


Foreign currency-denominated lending is often measured as a percentage of total lending. Aggregate figures on foreign currency lending are usually available, but in countries where only a few institutions have access to foreign exchange, the lending patterns of these particular institutions may merit individual attention.


Adequate loan classification and accounting standards are essential for the ratio of nonperforming loans to total loans to be meaningful. The utility of this ratio may also be diminished in an environment in which banks lend to roll over loans that otherwise would become nonperforming—a practice also described as “evcrgreening”.


Some countries allow the netting of the collateral value against the impaired loan in calculating the provisions for loan losses. Different rules in this respect may make cross-country comparison of provisioning data difficult. Under some circumstances, when netting is allowed, provisioning ratios may become meaningless due to difficulties with valuing and liquidating collateral (e.g., real estate collateral subsequent to a real estate bubble).


One advantage of these ratios as MPIs is their easy availability from prudential returns.


Even though This ratio is usually low on an aggregate basis, risk can be significant in countries with small numbers of large conglomerates.


Therefore, it has similar drawbacks. Nevertheless, it can be a useful indicator where loan valuation may be regarded as adequate.


Corporate debt-equity ratios depend, in part, on countries’ legal definitions of debt and equity, and, therefore, are not easily comparable across economies.


Few countries have reliable disclosure laws, however, so that data on corporate debt to equity ratios may have to be obtained from bank supervisors, if they collect bank information on their clients’ credit quality and on large borrowers or credit concentration, or by observing shifts in lending practices.


Care should he taken to identify cyclical movements in corporate sector profitability.


See the literature survey in Section III for details.


The latter indicator can be influenced by the quality of bankruptcy and related legislation.


For comparisons between countries, pretax profits should be used to eliminate the effects of different national taxation practices.


They are sometimes also used as indicators of management problems.


Liquidity can change rapidly, however, requiring frequent tip-dating of relevant indicators.


In cases where liquid secondary markets exist, one could also look at the ratio of liquid assets to total deposits.


Indicators of maturity structure should distinguish between domestic and foreign liabilities, and indicate the currency denomination of the liabilities.


Most of these indicators can be extracted from prudential returns to supervisory authorities, some directly, others via the capital charges allocated against the particular risks. For exchange-traded instruments, indicators may also be obtained from stock and derivatives exchanges, in particular, from position and margin data. See BIS (1996).


Supervisors often collect information on interest rate risk from individual financial institutions, A commonly used reporting framework is one where a financial institution’s interest-sensitive positions are slotted into time bands, according to the time until the next repricing. Alternatively, interest sensitivity can be determined via duration analysis, weighting and aggregating the durations of individual financial instruments held by a financial institution. See BIS (1997).


For a description of the maturity ladder approach to measuring commodities risk, see BIS (1996).


If shareholders have the perception that the government will bail out troubled financial institutions, however, this data may not adequately reflect the underlying institutional risk.


See Section IV for details. For a recent analysis of rating agencies’ performance, see BIS (1999c), and International Monetary Fund (1999c). Chapter V and Annex V. Since rating agencies generally have to rely on the published accounts of companies being rated, and do not have access to supervisory data, their judgments can be affected by deficiencies in accounting and provisioning standards. On the positive side, rating agencies try to lake into account such deficiencies in their evaluations. They usually update their analysis more frequently than other institutions, and may he in closer and more frequent contact with market participants.


Most commonly, yield spreads are benchmarked against U.S. Treasury yields, and are subdivided into credit and foreign exchange risks.


Bank income under high inflation is often derived from the float on payments, the inflation lax collected on nonremunerated demand deposits, and foreign exchange dealing.


Under fixed exchange rate regimes, by definition, volatility cannot be observed before a devaluation actually occurs, so other indicators have to be used, for example, the volume or foreign exchange intervention by the central bank.


For a summary of financial contagion effects, see International Monetary Fund (1999b), p. 66.


Particularly among academics, investment managers, and analysts participating in the consultative meeting, interest was high in indicators that would permit cross-country studies, that is, indicators that are suitable for comparative analysis.


Work conducted by the IMF is the subject of Section V.


David (1999) provided a very useful reference in writing this section.


In addition, when a bank run occurs, the institution tries to rapidly liquidate assets to meet demand I’or deposit withdrawal. In these circumstances, assets are likely to be sold at a discount and the financial position of the bank may deteriorate further.


For a discussion of adverse selection, see Akerlof (1970).


The range of approaches is illustrated by Demirgüc-Kunl and Detragiache (1998), an econometric study of banking crises in 65 countries; Federal Reserve Bank of Kansas City (1997). conference proceedings covering a wide range of issues beyond quantitative ones, but offering comments on the importance of macro-economic variables: Gavin and Hausmann (1996) and Rojas-Suarez and Weisbrod (1995). both on Latin America; Goldstein and Turner (1996), which contains a comprehensive survey of possible origins of banking crises in emerging countries’, and Goodhart (1995). which focuses on asset market volatility.


The Z-score model uses the linear discriminant analysis method to identify healthy and unhealthy firms, and “Z” represents the composite score used to distinguish between these two groups of firms.


This study includes a recent survey of empirical studies on banking failures.


The Basel Committee’s recent recommendations on capital adequacy (still in the form of a discussion draft) can be found in BIS (1999a).


BIS(1999b) also points out that the way in which undercapitalized banks meet the minimum capital requirement depends on individual cases. Ediz, Michael, and Perraudin (1998) show that banks in the United Kingdom tend to raise their Tier 2 capital first, followed by their Tier 1 capital.


Value-al-Risk is an estimate of the maximum loss on a portfolio with a given (small) probability over a preset horizon. The VaR methodology uses a standard statistical technique usually based on the historical volatility and correlation of portfolio returns to measure market risk (not credit risk)—sec Hendricks (1996), and Dimson and Marsh (1997), While the incorporation of VaR models into capital adequacy regulation could permit a more accurate estimation of risk, it should be noted that there are drawbacks to VaR models. In particular, these models are unable to account for shocks that depart considerably from past experience (e.g., a large devaluation).


These indicators are to be analyzed in their relation to the following intermediate risk targets: aggregate credit risk, interest rate risk, equity price risk, real estate risk, foreign exchange risk, and liquidity risk. The ultimate target variable is the aggregate solvency of the banking system. The analysis under the first category would draw on confidential supervisory data, whereas the analysis under the second would be based largely on public information as well as on available macroeconomic forecasts.


See Section V for details.


As in example, the Reserve Bank of India prepares an annual report on banking trends in India in terms of a statutory requirement under the Banking Regulation Act of 1949. The report covers developments in banking policy, cooperative banking, banks and nonbanking institutions, and provides some information on MPIs, including financial ratios, off-balance sheet exposures, nonperforming loans, and profitability. The Reserve Bank of India, however, does not report the use of these MPIs in any formal framework covering systemic soundness.


The first three reports in this series—called Financial Market Reports—focused on an in-depth presentation of several key aspects of the analysis. Subsequent reports—renamed Financial Stability Reports—have provided updates of the analysis. See Sveriges Riksbank (1999).


Responsibility for the authorization and supervision of individual financial institutions and providers of financial infrastructure rests with the Financial Services Authority.


For a description or the F1MS, see Cole, Cornyn, and Gunther (1995).


For a description of the GMS, see Federal Deposit Insurance Corporation (1997), Vol. I, pp. 496–507. The OCC has been using a variety of computer applications to monitor financial institutions’ risks; see FDIC (1997), Vol. I, p. 512.


The indicators used by private investors need to be differentiated from the so-called market-based indicators, such as stock market and bond indices.


Government support is often assumed in the presence of government guarantees, government or quasi-government ownership or control, high concentration in the banking system, or by precedent


Moody’s Investors Service (1999). Sec also the discussion of market-based indicators in Section II.


The Research Department also runs an ongoing project to analyze, on an experimental basis, the results of early warning system models.


These processes increase opportunities for financial institutions and markets to further develop, but may also expose financial institutions to new and more significant risks, while at the same time pulling pressure on margins through increased competition.


For background on the FSAP and FSSAs, see footnote 1.


National financial systems are subject to threats from internal conditions and external shocks. This section does not cover statistical issues and MPIs related to external shocks because they have already been discussed extensively in the work leading up to the development of the data template on international reserves and foreign currency liquidity. See IMF (1999d).


See Inter-Secretariat Working Group on National Accounts (1993). Financial accounts within the System of National Accounts, 1993 (SNA93) framework include detailed flow of funds accounts (Tables 11.3a. 11.3b), balance sheets and accumulation accounts (Table 13.2), and stocks of financial assets and liabilities analyzed by debtor and creditor (Tables 13.3a, 13.3b). Although few countries will compile these accounts at the level or detail presented in SNA93, the accounts have the flexibility to be focused on analytical or policy questions important to each country while still retaining consistency with the overall framework and international comparability.


A number of MPIs can be drawn directly from the financial balance sheet data used in the forthcoming Monetary and Financial Statistics Manual. An advantage of collecting MPIs through use of a standard framework is that macroprudenlial information will apply common statistical standards, such as a standard statistical definition of residency, which helps integrate the macroprudenlial information into an economywide statistical setting.


Table 4 covers MPIs closely related to the banking sector. Statistical needs for MPIs extend over nonbank financial institutions, securities markets, and nonfinancial corporations, but data outside the banking sector are often less available. Furthermore, the table provides only a first cut at identifying specific statistical problems. The survey of country practices will help identify more precisely the types of problems that exist and their severity.


Netting refers to legal and supervisory procedures that permit gross claims and liabilities between two institutions to be netted into a single asset or liability position.


For example, data based on a national consolidation exclude the foreign currency exposures of a bank’s subsidiaries located in other countries. In contrast, such information is captured within the global consolidation used by supervisors in order to cover the resources and risks to the entire bank.


In general, it might be difficult to assess the condition of the capital account of national branches of global enterprises because of difficulty in allocating the strengths or weaknesses of the global capital account to individual branches. There might also be a lack of transparency on the allocation of income or expenses on collaborative work between branches in different countries.


In September 1998, the Basel Committee on Banking Supervision and the IOSCO Technical Committee issued a joint report that covers minimum information standards on credit, liquidity, market, and earnings risk that require marked-to-market and notional value data on derivatives by counterparty, maturity, and type or underlying risk; see BIS and IOSCO (1998). The report also suggests that supervisors have access to institutions’ internal VaR estimates.


For example, the Basel Committee on Bunking Supervision has proposed a substantial revision of the risk-based capital ratio.


Important work on the development of standards is being undertaken by the Basel Committee on Banking Supervision, IOSCO, the International Accounting Standards Committee, international statistical organizations, regional organizations, and national supervisors, among others. An important initiative affecting MPIs was the enactment in early 1999 or International Accounting Standard No. 39Financial Instruments: Recognition and Measurement, which mandates that virtually all financial positions be recorded on balance sheet at market value or equivalent and that impairment and loss of market value be reported on an ongoing basis. This standard, where implemented by national authorities, would markedly improve the usefulness of accounting data in the construction of MPIs by providing an accurate and timely depiction of the value of financial institutions’ portfolios. The International Accounting Standards are general standards, however, which may be implemented in somewhat dirieren’ ways in different countries. An important adjunct of this work is the cooperation of the International Accounting Standards Committee with IOSCO to extend standards to cover reporting and valuation of securities.


This fluidity also offers the potential for modification and upgrading of accounting, auditing, supervisory, or statistical standards to better extract macroprudenlial information and to solidify their methodological bases so that MPIs can be soundly constructed and made comparable across countries. Achieving such improvements will require close cooperation between statistical, accounting, and supervisory authorities.


This option has similarities to the ECB’s program of collecting MPI information for the EU and its member countries via its monetary statistics compilation system (see Appendix 1).


They also complement other initiatives undertaken by the IMF to foster macroeconomic stability and financial system soundness through enhanced transparency, such as the development of the Code of Good Practices on Transparency in Monetary and Financial Policies and the Code of Good Practices on Fiscal Transparency.


In subscribing to the SDDS, countries commit to bringing their national statistical practices into alignment with the SUDS requirements for data coverage, periodicity, timeliness, access practices (including data release calendars), integrity, and quality proxies (including summary methodologies). Through the Dissemination Standards Bulletin Board (DSBB), SDDS subscribers provide information about their statistical practices (so-called metadata) for a total of 20 macroeconomic categories, as well as access to actual data. The SDDS countries post at least the two latest data observations for each SDDS data category on their national summary data page to which the DSBB is electronically linked. The DSBB website is


The basic approach taken by IMF staff—subject, of course, to concerns about confidentiality of data for individual institutions—is that information is a public good and that enhanced public availability of information is desirable.


In contrast, in the work on international reserves and, to some extent, on external debt in the SDDS, the IMF look the lead in “pushing the envelope” to promote increased dissemination of reliable, comprehensive, and timely data. In the case of reserves, standards were developed jointly by the IMF and a working group of the CGFS.


EU countries that are not members of the EMU are required to use many of the same statistical standards as the EMU countries.


The ESA 95 standards closely conform with the standards in the IMF’s forthcoming Monetary and Financial Statistics Manual.


“The institutional coverage of the tables has been largely dictated by the availability of data on income and expenditure accounts of banks. As a result of the reporting methods used in OECD countries, the tables are not integrated in the system of national accounts and are, therefore, not compatible with the financial accounts of OECD countries. International comparisons in the Held of income and expenditure accounts of banks are particularly difficult because of considerable differences in OECD countries regarding structural and regulatory features of national banking systems, accounting rules and practices, and reporting methods”. (Organization for Economic Cooperation and Development, 1999, Foreword).

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