Abstract

13.1 This chapter provides an overview of the use of FSI data in macroprudential analysis. It begins with a brief review of approaches to financial stability analysis, macroprudential frameworks and macroprudential policies, and the role that FSIs can play in the supporting analysis. It continues with a more detailed discussion of the potential and current use of FSIs in macroprudential analysis, and a brief overview of related analytical approaches that commonly employ FSIs as inputs or outputs. The chapter concludes with a summary of key points.

I. Introduction

13.1 This chapter provides an overview of the use of FSI data in macroprudential analysis. It begins with a brief review of approaches to financial stability analysis, macroprudential frameworks and macroprudential policies, and the role that FSIs can play in the supporting analysis. It continues with a more detailed discussion of the potential and current use of FSIs in macroprudential analysis, and a brief overview of related analytical approaches that commonly employ FSIs as inputs or outputs. The chapter concludes with a summary of key points.

13.2 One of the lessons from the Global Financial Crisis (GFC) was the need to put in place macroprudential frameworks which provide a system-wide perspective on risk (Borio 2014). In retrospect, it was clear that the build-up of imbalances in the financial system had not been adequately identified and measured in the period leading up to the crisis.

13.3 Macroprudential frameworks complement the traditional microprudential focus on individual institutions to contribute to financial stability. While many central banks, the Bank for International Settlements and the IMF, had included elements of a macro-prudential perspective in assessing financial stability prior to the GFC,1 this work took on a new prominence in the subsequent reform agenda. Increasingly, an explicit mandate for financial stability has come to be seen as an essential supplement to the traditional central bank mandate for price stability (Goodhart, 2014), although there is no single accepted definition of financial stability (Vlahović, 2014).

13.4 The macroprudential literature is still young, and as with financial stability, there is no common definition of macroprudential policy and its elements. One working definition in fairly widespread use is that macroprudential policy is the use of primarily prudential tools to limit systemic risk.2 Efforts have focused on pragmatic approaches to a comprehensive framework for identifying and monitoring systemic risk despite the absence of theoretical consensus. The toolkit of macroprudential policy instruments is a work in progress, with no current consensus on optimal tools, calibration or triggers for use.

13.5 In this relatively new and developing field, despite variations in specific definitions and approaches, there has been convergence around four key elements of a macroprudential framework: (i) the objective of limiting systemic risk; (ii) a scope of analysis including the financial sector as a whole and its interaction with the real economy; (iii) a set of macro-prudential tools and guidelines for their use including interactions with monetary policy; and (iv) the need for a macroprudential authority with a clear mandate, appropriate powers, and accountability. Macro-prudential policies do not function in isolation from other elements of the financial stability framework and macroeconomic policies. Thus, the macroprudential framework supplements but does not replace a sound foundation for microprudential oversight and monetary and fiscal policies.

13.6 FSIs can play a central role an analytical framework that addresses the financial sector as a whole and its interaction with real economy (Figure 13.1). This begins with monitoring of markets and broader macro-economic conditions to identify potential shocks in the time dimension. In addition to financial market data, macro indicators such the difference between the credit-to-GDP ratio and its long-run trend (the credit-to-GDP gap), and other variables, some FSIs (growth of credit to the private sector, real estate prices) can provide insights into the potential emergence of asset price imbalances.

Figure 13.1
Figure 13.1

Analytic Framework for Financial Stability

Source: Adapted from IMF 2003.Note: BIS = Bank for International Settlements.

13.7 FSIs are also useful in monitoring the condition of the household and corporate sectors, potentially identifying vulnerabilities before they are reflected in financial sector performance. Excessive leverage, stressed debt-service levels, and exposure to foreign currency risk could be useful indicators of imbalances, which can help trigger the use of macroprudential tools.

13.8 The Core FSIs for deposit-takers provide a good overview of the resilience of the deposit-taking sector to potential shocks. Earnings-related FSIs provide an indication of the ability to internally generate capital, while the capital-related FSIs provide insights into the magnitude of losses that can be borne by system without falling into crisis. Liquidity FSIs similarly quantify the ability of the system to deal with market disruption over varying time horizons.

13.9 The FSIs have not played a major role in the other two elements of the analytical framework: analysis of macrofinancial linkages and surveillance of macro-economic conditions. The first is targeted at understanding and assessing the various means by which shocks to the financial sector can result in a feedback loop to the real sectors, and contagion effects within the financial sector. The second is focused on monitoring the impact of these macrofinancial linkages on broader macroeconomic conditions, in the face of significant shock.

II. Macroprudential Policies

13.10 Macroprudential and microprudential approaches can be compared and understood using a number of criteria that reflect the inherent differences in focusing on risk in the financial system as a whole versus risk in individual institutions (Table 13.1). A systemic focus requires a broader analytical approach to identify the potential risks, assess resilience, and to calibrate and trigger the use of macroprudential tools. Macroprudential policies have to consider the build up of risks over time (the time dimension) as well as risks arising from the interlinkages among individual institutions—or financial markets—of potential systemic importance.

Table 13.1

Comparison Between Macroprudential and Microprudential Policies

Source: Borio (2003).

13.11 Taking steps to address excessive leverage or debt-service stress in the household or corporate sector and asset price imbalances can result in an orderly deceleration rather than a shock to the financial system. Similarly, taking a macro perspective on credit growth and liquidity may provide insights into needed interventions that may not be evident when only the condition of individual banks is considered.

13.12 Following the Global Financial Crisis, emphasis was placed on identification and supervision of systemically important financial institutions (SIFIs) whose size, behavior, and condition can affect the overall macroprudential environment—providing one type of bridge between micro- and macro- supervision and policy. The FSIs do not play a major role in identifying and assessing the important structural considerations arising from the presence of SIFIs within a financial sector.

13.13 There are three objectives to be met in operationalizing macroeconomic policies: (i) increasing resilience to aggregate shocks by building buffers; (ii) containing the buildup of systemic vulnerabilities; and (iii) controlling structural vulnerabilities.3 FSIs can play a useful role in the macroprudential analysis that supports achieving the first two of these objectives, both of which address the time dimension of macroprudential policies.4

III. Macroprudential Analysis

13.14 Macroprudential analysis incorporates a range of approaches and indicators to measure systemic risks in both the time and structural dimensions. Indicators include aggregate balance sheet and income statement-derived ratios; market-based indicators such as asset prices, spreads or market liquidity measures; broad macro indicators such as ratios of credit to GDP; and other quantitative and qualitative information available to country authorities. Stress testing and network analysis (measuring the relationships among potentially systemically important institutions) are examples of this additional quantitative information. Assessments of credit underwriting standards and the adequacy of banks’ risk management processes are examples of qualitative information that may be incorporated into macroprudential analysis.

13.15 The need to capture systemic risks in the context of the financial cycle (time dimension) has led to greater use of macroeconomic variables, market data such as asset prices, measures of the linkages between the real and financial sector and monitoring of interactions between macroprudential policy with monetary policy (Table 13.2).5 These macropruden-tial indicators, which include a number of the Additional FSIs and in some cases, can be derived using Core FSIs, potentially can be used to trigger and calibrate macroprudential tools to mitigate the build-up of imbalances in the financial sector. This emphasizes the importance of compiling the Additional FSIs in order to identify the build-up of risks outside the financial sector. Once buildup of systemic risks has been detected, the practical question then becomes what macroprudential tools are available, and when should they be deployed. Once deployed, when should the tools be further tightened or relaxed in response to changing circumstances? FSIs and other inputs can be used to trigger the deployment of macroprudential tools, as discussed next.

Table 13.2

Macroprudential Indicators, Policy Tools and Financial Soundness Indicators

Source: Adapted from IMF Staff Guidance Note on Macroprudential Policy (2014) and Table 1.1 in this Guide.

FSIs and the Calibration of Macroprudential Tools

13.16 A range of macroprudential tools have been identified (Table 13.2), with the availability and power to use such tools varying from country to country in accordance with national institutional structures and legal frameworks. Options can include restrictions on borrowers, instruments or activities, balance sheet restrictions, or capital or provisioning requirements. Macroprudential tools may have the objective of limiting the buildup of risks, or building additional buffers to enhance resilience. Many macroprudential tools, for example, restrictions on financial sector balance sheets or capital requirements, are in fact micro-prudential tools, but are deployed with a systemic perspective in mind (Gadanecz and Jayaram, 2015).

13.17 There are no broadly applicable standards or gauges to indicate when macroprudential tools should be deployed to address accumulating imbalances in the financial sector, but macroprudential policy cannot rely on rules and must be based on a continuous assessment of evolving risks.6 In this regard, FSI data can contribute to identifying when particular macro-prudential tools may be required, and to the ongoing measurement of their impact and hence decisions on tightening or relaxing. Trends and projections of FSIs can be used, in conjunction with other analysis, to inform the expert judgment exercised by the authorities with mandates for financial stability.

13.18 FSIs can provide insights into the resilience of the financial sector to potential vulnerabilities. Key indicators of resilience are capital as a measure of the capacity to absorb unexpected losses, and liquidity as a measure of capacity to deal with market disruption. The availability of FSIs provides a means for crosscountry comparison and analysis.

13.19 The Core FSIs for deposit takers include total capital to risk-weighted assets, Tier 1 capital to risk-weighted assets and Common Equity Tier 1 capital to risk-weighted assets, all anchored in the international standard established by the Basel Capital Accord. These FSIs provide a view at a point in time, which can be used for trend analysis, of aggregate capital adequacy of the banking sector in a jurisdiction. This can be compared to the Basel standard, and to the ratios of other countries or regional peer groupings, providing a measure of resilience to unexpected losses. Non-performing loans net of provisions to capital provides an additional insight into resilience by identifying the ability of the banking system to absorb unexpected losses (provisions should cover expected losses) on already identified problem loans.

13.20 There originally were two liquidity measures in the Core FSIs for deposit takers—liquid assets to total assets, and liquid assets to short-term liabilities. Unlike capital measures, these FSIs are not anchored in an accepted international standard, but do provide indicators of the potential ability of the banking system to deal with market disruption. The Liquidity Coverage Ratio and Net Stable Funding Ratio, two new a Core FSIs, reflect the introduction in Basel III of an international standard for liquidity, effective January 2018. As with the capital FSIs, this will permit comparison to a clear nominal standard, as well as comparisons to other countries and peer groupings.

13.21 FSIs can also provide insights into the buildup of systemic vulnerabilities, allowing for benchmarking of financial systems in normal times with no stress, to monitor changes over time, and to compare across jurisdictions. The three asset quality Core FSIs address the buildup of credit risk (non-performing loans to total gross loans), risk concentrations (loan concentration by economic activity) within the banking sector and the adequacy of provisioning (provisions to non-performing loans). The liquidity FSIs, in addition to providing measures of resilience as discussed earlier, also provide insights into systemic vulnerabilities, as in the absence of healthy liquidity buffers, the banking sector is vulnerable to liquidity shocks. Net open position in foreign exchange to capital provides a measure of the vulnerability of the banking sector to foreign exchange shocks.

13.22 The Additional FSIs provide some further insights into potential vulnerabilities in the banking sector, and perhaps more importantly include measures of the leverage (debt to equity) and debt-service capacity (earnings to interest and principal expenses) of the nonfinancial corporations sector, and debt-service capacity (debt-service and principal payments to income) of the household sector. Together with the residential and commercial property price indices, these offer the potential to detect vulnerabilities long before they become evident in the earnings, asset quality, and capital indicators of the deposit-taking s e c tor.

13.23 In practice, FSIs are commonly used in the analysis supporting decisions to employ macropru-dential tools. For example, The Hong Kong Monetary Authority (HKMA) relied in part on residential estate prices, then one of the Additional FSIs and now a Core FSI, in the analysis leading to the decision to deploy elements of the macroprudential toolkit in May 2017. In addition to prices exceeding previous peaks, the HKMA was motivated by the rate of turnover in the property market, which suggested that speculation may have been fueling the price increases, and concerns that intense competition by banks was leading to increased risk and lower resilience to shocks.7 The HKMA introduced a 25 percent risk weight as a foor for residential mortgage risk weights, increased from the previous 10 percent, for banks using the internal ratings–based approach to determine their capital adequacy. This increase in the amount of capital required for mortgage loans was complemented by reducing the maximum allowable loan to value ratio and increasing the minimum permissible debt-service ratio.

13.24 The Iceland Financial Supervisory Authority similarly relied in part on residential real estate prices, then an Additional FSI and now a Core FSI, in its July 2017 decision to impose macroprudential restrictions. Other contributing factors were the inadequate supply of new housing, and concern that lenders were relaxing underwriting standards, evidenced by an increase in the average loan to value ratio and amortization period of new mortgage loans.8 This led to the imposition of a loan to value limit of 85 percent in general, and 90 percent for first time homebuyers.

FSIs in Macroprudential Analysis

13.25 FSIs are most relevant for surveillance, providing near-contemporaneous indicators of risk and resilience. The Core FSIs provide a snapshot of the condition of the banking system. Trend analysis of some Core FSIs such as loan concentration by economic activity and liquidity ratios is potentially useful in identifying the build-up of systemic risks, providing insight into when to trigger macroprudential tools, and the tightening or relaxation of these tools once deployed. Some of the Additional FSIs are potentially more useful for their ability to provide insights into developments within a financial cycle, and thus as possible leading indicators of financial distress.

13.26 FSIs are used by the IMF in FSAPs, primarily in initial scoping and preliminary risk-assessment, and as inputs and outputs in stress testing. FSIs are also used in other surveillance, typically in the context of Article IV consultations. Most Article IV reports include the Core FSIs, and often include commentary on the soundness of deposit takers based on these indicators. When FSI data is not included, it is generally because of the lack of availability from the authorities. FSI data facilitates ongoing monitoring to determine whether more detailed review of financial stability is required. In most cases where there is detailed financial stability commentary provided as part of the Article I V, it is based on more in-depth analysis. Typically, this can include stress testing completed by the mission, recent FSAP or technical assistance findings, or asset quality reviews or financial stability reports produced by the authorities.

13.27 Other practical examples of the use of FSIs in financial stability analysis are readily found in country financial stability reports. Financial stability reports almost universally include discussion and analysis of macroprudential indicators, which in many cases overlap with the FSIs (Čihák; 2006, and Čihák et al., 2012). Use of FSIs ranges from being a central component and organizing framework for the analysis to reporting with little or no analysis of the data, to inclusion of some FSIs within broader reporting of macroprudential indicators.

13.28 The Islamic Financial Services Board (IFSB) has developed a parallel set of soundness indicators (called Prudential and Structural Indicators for Islamic Financial Institutions—PSIFIs) that apply to the Islamic banking sector in countries with Islamic banks. The indicators parallel the FSI core and additional indicators whenever feasible, with customization to reflect various differing practices in Islamic banking. Thus, some countries will have two sets of indicators—one covering the entire banking system, and a second covering the Islamic banking subsector, which can permit analysis of relative stability conditions in the two subsectors.

FSIs in the Macroprudential Literature

Financial and currency crises since the 1990s have spurred an extensive literature investigating the causes of crises, building from earlier work using financial ratios to predict distress in individual institutions. A small number of studies within the broader macroprudential analysis literature specifically address the use of FSIs. Recent work has tended not to specifically address FSIs, but rather a wider range of variables including macroeconomic and market-based data. Residential real estate prices, a Core FSI, and some of the Additional FSIs (commercial real estate prices, household and corporate leverage and debt service) are among the commonly used parameters in the quest for robust leading indicators.

Craig (2002) provides an early description of the use of FSIs in surveillance, highlighting the usefulness of the Additional FSIs for the nonfinancial corporate and household sectors to detect weakness at a relatively early stage. This can often be before weaknesses are reflected in FSIs of the financial sector that measure risk more directly, such as the non-performing loan ratio. FSI analysis as described was based on trend analysis, peer group comparisons and expert judgment. In a similar vein, Worrell (2004) noted that most FSI analysis uses expert judgment in conjunction with other analytical approaches, referring to the use of FSIs in individual country financial stability reports. He cited as an area for future work quantitative research to identify a statistically robust relationship between a variety of FSIs and financial system distress.

Jarle (2002) describes the use of FSIs by the Norges Bank (Norwegian Central Bank) in financial stability analysis. A key observation was the conclusion from practical experience that a set of FSIs for only the banking sector was too narrow. Even if problems showed up clearly in the banking sector FSIs, it was too late to take appropriate action to mitigate the buildup of systemic risk. This led Norges Bank in 1995 to introduce in its Financial Stability Report a number of additional FSIs for the nonfinancial sectors, facilitating an evaluation of the impact of macroeconomic conditions on the debtservice capacity of the household and non-financial corporate sector, and hence the likely impact on banking sector FSIs.

Čihák and Schaeck (2007) use selected FSIs compiled from FSAP and Article IV missions to explore the relationship between FSIs and banking problems. They conclude that there is evidence to suggest that FSIs provide signals of the buildup of imbalances in the banking sector and are of some benefit in determine the timing of crises. However, the authors stress a number of limitations in the data and the need for additional research.

Babahuga (2007) provides the first empirical work specifically using the FSI dataset. The paper establishes the link between selected FSIs and episodes of financial distress, finding that FSIs fluctuate strongly with the business cycle. Costa Navajas and Thegeya (2013) test the effectiveness of FSIs in predicting banking crises. Model results show correlation between some FSIs and banking crises. The findings are of limited use to policy-makers, however, as the most robust results are for contemporaneous or lagged variables, thus providing no lead time to deploy macroprudential tools to avert or mitigate the crisis. This finding highlights the need to compile the Core FSI residential real estate prices and Additional FSIs such as commerical real estate prices and household and corporate sector leverage and debt service, which have been more prominent in recent financial stability analysis due to their potential predictive ability.

More recent work tends to address FSIs less specifically, typically through incorporation of some FSIs into a broader set of macroprudential indicators. A useful overview of recent work is provided in IFC Bulletin No 46 (2017). While some of the papers do touch on the banking sector variables that underpin the Core FSIs, the bulk of current research: (i) stresses the importance of filling data gaps, particularly with respect to real estate and the household and corporate sector, and the shadow banking sector (this reinforces the importance of compiling the Additional FSIs); (ii) the use of market-based indicators including high frequency data; (iii) more granular analysis of potential vulnerabilities; and (vi) interconnectedness and potential contagion. This recent focus reflects that the Core FSIs on their own have limited predictive ability, but can be useful as monitoring tools and as inputs in a broader analytic approach.

13.29 Many country authorities have developed their own key indicators for financial stability analysis with varying degrees of overlap with the FSIs. While only two of the 27 Basel Committee member jurisdictions publishing financial stability reports routinely include the Core FSIs as a table or appendix (see Annex 13.1), almost all Basel Committee member jurisdictions make use of selected FSIs in three contexts. One is the incorporation of some FSIs—typically real estate prices, corporate and household sector leverage and debt-service—together with other parameters, into scenario-based or modeling approaches to identifying imbalances. The second is the use of some of the Core FSIs for deposit-takers—typically asset quality and sometimes liquidity—together with other indicators in the assessment of financial sector vulnerabilities. The third is to incorporate Core FSIs—usually some of the capital, earnings and liquidity-related ratios— into broader analysis of the resilience of the financial s e c tor.

13.30 Most European Union countries report the Core and many of the Additional FSIs, and some are reflected in the European Systemic Risk Board dash-board.9 The risk dashboard is a set of quantitative and qualitative indicators of systemic risk in the EU organized in seven categories: (i) interlinkages and composite measures of systemic risk; (ii) macro risk; (iii) credit risk; (iv) funding and liquidity; (v) market risk; (vi) profitability and solvency; and (vii) structural risk.

13.31 This risk dashboard, in common with approaches to macroprudential analysis in most highly developed financial systems, takes advantage of the availability of high-frequency market data, macro indicators, and details of individual exposures in addition to aggregate balance sheet and income statement data for banks and other financial institutions. The closest alignment of the risk dashboard with the FSIs is in the indicators of banking groups’ profitability, solvency, liquidity, and balance sheet structure. These indicators are largely derived from supervisory data and thus bear close resemblance to the Core FSIs, with 6 of 12 included in the risk dashboard: (i) return on equity, (ii) return on assets, (iii) cost to income, (iv) net interest income to operating income, (v) NPLs to total gross loans, and (vi) liquid assets to short-term liabilities.

13.32 As explained in the last section, FSIs can play a more prominent role in macroprudential analysis. And a 2009 review of approaches to detecting systemic risk concluded that FSIs provided mixed results in predicting the global financial crisis, they were still useful in assessing systemic vulnerabilities when combined with other reliable data (GFSR April 2009, Chapter 3).

IV. Related Analytic Approaches

13.33 Macroprudential analysis requires a number of complementary approaches, some of which employ FSIs as inputs or outputs. The most common of these is stress testing, in which outputs are frequently expressed as FSI capital ratios.

13.34 Stress testing can be done at the individual institution level as part of a bank’s own internal risk management processes or as part of microprudential supervisory oversight (Basel Committee, 2017). Stress testing can also be done at the macro level, looking at the sector as a whole using either aggregate data (top-down) or by aggregating the results of stress testing individual institutions (bottom-up).10 Top-down stress testing by the IMF is a common feature of FSAPs and may also be used in other surveillance (Jobst, Ong and Schmieder, 2013).

13.35 Many countries have incorporated stress testing into their macroprudential analysis. FSIs often figure prominently in balance-sheet approaches as inputs (increases in NPL ratios, declines in liquidity ratios) and outputs (capital adequacy ratios). More complex models also often incorporate FSIs among their inputs, and almost invariably have capital adequacy ratios among the outputs.

13.36 Network analysis is a subset or variation on stress testing approaches, which investigates the relationships between individual institutions, or in cross-border network analysis, relationships between financial systems.11 It requires detailed information on bilateral exposures in order to construct a web or network, which can provide insights into the structural dimension of systemic risk. This is done using scenario analysis to assess the impact of default by one or more institutions, or in the case of cross-border analysis, financial distress in one or more jurisdictions, on the other institutions or jurisdictions in the network. While the analysis is based on detailed information on institutional exposures that is not captured in the FSIs, the outputs of network analysis are frequently expressed as FSI capital or liquidity ratios.

V. Challenges to Enhance FSIs for Macroprudential Analysis

13.37 The Core FSIs provide measures of both the buildup of risks (asset quality, credit concentration, liquidity stress, foreign currency exposure, residential real estate prices) and resilience (capital, leverage and liquidity buffers) within the banking system. Additional FSIs for deposit takers provide further insights into risks (risk concentrations, reliance on non-deposit funding, and foreign currency exposures). The Additional FSIs for the non-financial sectors are potentially highly useful in identifying vulnerabilities (high leverage, high debt- service ratios, and real estate prices) before these are evident in the Core FSIs, which more directly measure risk in the financial system. This provides an opportunity for policy-makers to use macroprudential tools to mitigate the risks prior to crystallization into a crisis.

13.38 FSIs have been most widely used as macro-prudential indicators and organizing frameworks in jurisdictions, which introduced their formal approach to financial stability analysis after the introduction of the FSIs. In other jurisdictions there is often overlap between the set of macroprudential indicators used on an ongoing basis and the FSIs. Particularly in jurisdictions where data gaps persist, in the absence of high frequency market data and the detail required for network analysis, the FSIs can play a key role in macroprudential analysis.

13.39 There are several challenges to be overcome to enhance macroprudential analysis using FSIs. First, significant data gaps remain despite the steadily increasing number of countries disseminating FSIs. While many countries provide all or most of the Core FSIs, availability drops of rapidly for the Additional FSIs, particularly those not derived from supervisory data. This frequently reflects capacity constraints in national statistics agencies, and also challenges in domestic coordination between the supervisory authorities or central banks often responsible for the complication of FSIs, and statistics agencies, which may play the leading role in compilation of indicators for the non-financial sectors.

13.40 Integrity of data from supervisory sources is an ongoing concern. The Core FSIs, like all supervisory data, are vulnerable to inadvertent or willful misreporting. This is a particular concern due to evidence that often emerges through FSAPs of under-reporting of adverse loan classifications and provisions (Andrews, 2017). Under-provisioning has the effect of reducing expenses and increasing income, thus distorting the profitability and capital-related FSIs in addition to the impact on asset quality indicators.

13.41 Lack of “forward-lookingness” is a common issue in macroprudential analysis. Many financial stability reports tend to rely on the current levels of some key FSIs, such as capital and asset quality-related indicators, and trend analysis (Čihák, 2006). FSIs are historical data, at best providing a picture of the system as it existed three months earlier. This is a problem familiar to bank supervisors everywhere, which has resulted in ratio-based analysis being augmented by additional data and qualitative assessments to become more forward looking. As with microprudential supervision, in macroprudential analysis data extending beyond the Core FSIs, and judgment, are required to better identify vulnerabilities and lack of resilience while there is still time to take action.

13.42 Some key FSIs can provide a foundation to address the lack of “forward lookingness.” As noted in early work by Norges Bank and the IMF, FSIs for the household and nonfinancial corporate sector potentially can identify vulnerabilities before they are evident in the Core FSIs, providing an opportunity to employ the macroprudential toolkit to mitigate accumulating risks. Asset price data, particularly for real estate, offers similar promise as a leading indicator. The Additional FSI growth of credit to the private sector can be used to calculate the credit to GDP gap, one of the few robust leading indicators of financial

distress.12

13.43 As these and other Additional FSIs become more widely available, they will facilitate analysis of variations from long-term trends that potentially can detect buildup of systemic risk with sufficient lead time for policy-makers to act. There will still be challenges, however, which preclude a simple rules-based approach driven by empirical models. Even when relying on some of the best performing indicators, judgment is still required to determine when to act. For example, some research suggests that the credit to GDP gap tends to continue to rise for some quarters after the onset of the crisis, and price to rent and residential property price gaps tend to peak before the onset of the crisis (Gadanecz and Jayaram, 2015). While the available data may never support rules-based decisions, it can still be extremely useful in informing the expert judgment of the authorities with financial stability mandates.

13.44 In less developed financial systems, improvements in supervisory capacity and data availability will generally need to be given priority to lay the foundation for effective macroprudential policy. 13 A sound microprudential framework can help to address concerns over the integrity of the Core FSIs. Further, in the bank-dominated financial systems common in low-income countries, there will be few sources of systemic risk outside the banking system. Thus, sound microprudential supervision and the capacity and will to act when weaknesses are detected are essential components of a framework for financial stability.

13.45 It is important to include a range of methodologies in the macroprudential approach, so FSI analysis should be supplemented by stress testing, other quantitative indicators where available, and qualitative assessments using expert judgment. FSIs do not provide insights into the structural dimension of systemic risk, so it is especially important to use other approaches in assessing the potential systemic risks of individual institutions and financial markets infrastructures.

13.46 Use of FSIs for macroprudential analysis has been hampered by lack of availability, particularly for those not derived from supervisory returns. As the additional FSIs for the nonfinancial sectors are particularly useful as leading indicators that can help to trigger and calibrate the use of macroprudential tools, when seeking to fll the data gaps, authorities should give priority to nonfinancial corporations debt to equity, earnings to interest and principle expenses, household debt-service and principal payments to income, and residential and commercial real estate price changes. Following the GFC, the G20 urged countries to give priority to development of multisector balance sheet and accumulation accounts (often described briefy as “flow of funds accounts”), which can be constructed to incorporate relevant macropru-dential information. This is, however, a large statistical undertaking that might be beyond the resources of some countries.

Annex 13.1. Financial Soundness Indicators in the Financial Stability Reports of Members of the Basel Committee

Sources: Published financial stability reports, 2017 unless otherwise noted. Please see bibliography for full citations.Notes: Luxembourg does not publish a financial stability report. D-SIB = domestically systemically important banks. Residential real estate prices was an Additional FSI when 2017 financial stability reports were published. It is now a Core FSI.

Both the Riksbank (Central Bank) and Finansinspektionen, the supervisory authority, publish financial stability reports.

Both the Office of Financial Research and Financial Stability Oversight Council publish financial stability reports.

1

References to macroprudential policy first emerged in the late 1970s and1980s in the work of the Bank for International Settlements, aimed at supporting the safety and soundness of the financial system as a whole, as well as the payments mechanism. Macroprudential policy assumed more importance in the early 2000s, and increased sharply with the onset of the Global Financial Crisis. For additional detail, see Borio (2003), and Galati and Moessner (2011).

2

See IMF-FSB-BIS Elements of Effective Macroprudential Policies: Lessons from International Experience (2016) https://www.imf.org/external/np/g20/pdf/2016/083116.pdf. For a discussion of various working definitions, see Committee on the Global Financial System (2016), Claessens (2014), and Galati and Moessner (2011).

3

IMF Staff Guidance Note on Macroprudential Policy 2014.

4

As aggregate statistics, FSIs provide limited insights into the third objective, which addresses the structural dimension of systemic risk. The concentration and distribution measures discussed in Chapter 12 can help to identify structural issues.

5

Increased focus on macroprudential stability has raised the issue of how stability-oriented macroprudential policy interacts with monetary policy, both of which affect the condition of the banking sector. This has led to hybrid macroprudential/inflation targeting policy stances that recognize the mutual interactions between both types of policy.

6

IMF Staff Guidance Note on Macroprudential Policy (2014).

7

HKMA Press Release, May 19, 2017, http://www.hkma.gov.hk/eng/key-information/press-releases/2017/20170519-5.shtml accessed April 27, 2018.

8

Iceland Financial Supervisory Authority Rules on Maximum Loan-to-Value Ratios for Mortgages, July 2017, https://en.fme.is/media/frettir/FME---LTV-Memorandum-July-2017.pdf accessed April 27, 2018.

9

See the European Systemic Risk Board, November 2017, ESRB risk dashboard.

10

For a useful and easy to use bottom-up stress testing model that has been adapted for use in a number of countries, see Čihák, 2014.

11

For more detailed discussion, see “The Network Analysis Approach” in A Guide to IMF Stress Testing: Models and Methods 2014.

12

For further detail, see Gadanecz and Jayaram (2015), Drehmann and Juselius, (2013), and Staff Guidance Note on Macroprudential Policy—Considerations for Low Income Countries, 2014.

13

IMF Staff Guidance Note on Macroprudential Policy— Considerations for Low Income Countries, 2014.

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