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Chapter 5 G20 Data Gaps Initiative II: Meeting the Policy Challenge

Author(s):
Li Lian Ong, and Andreas A. Jobst
Published Date:
September 2020
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Author(s)
Robert Heath and Evrim Bese Goksu

This chapter is based on IMF Working Paper 16/43 (Heath and Bese Goksu 2016).

The G20 Data Gaps Initiative (DGI), which aimed at addressing the information needs that were revealed by the 2007–08 global financial crisis, concluded its first phase and started a second phase (DGI-2) with the endorsement of G20 Finance Ministers and Central Bank Governors in September 2015. The DGI-2 recommendations maintain the continuity of DGI-1 but, reflecting the evolving policy needs, focus more on datasets that support the monitoring of risks in the financial sector and the analysis of the interlinkages across the economic and financial systems. This chapter presents the DGI as an overarching initiative, bringing together various statistical frameworks for a complete picture of the economic and financial system to support the work of policymakers.

1. INTRODUCTION

A widely accepted old lesson is that “Good data and good analysis are the lifeblood of effective surveillance and policy responses at both national and international levels” (FSB and IMF 2009). Indeed, reliable, comprehensive, and timely information is essential to assess the risks and vulnerabilities facing economies, as policymaking relies on a correct assessment of such risks and vulnerabilities.

In 2007–08 the problems in the financial systems of a number of advanced economies, including the United States, spilled across borders to affect the rest of the world. As the financial sector was at the center of the crisis, the G20 economies supported a number of actions for the reform of the financial sector regulatory framework. Even though a lack of data was not the main reason for the crisis, it would have been possible to detect risk build-ups had the right data been available at the right time. Further, better data might also have enhanced the robustness and credibility of stress test analysis conducted by the authorities around the crisis, helping to support market confidence. To this end, the identification and addressing of information gaps were among the action items for the reform of the financial sector leading to the G20 Data Gaps Initiative (DGI). This chapter explains how the DGI is meeting policy needs.

2. RESPONDING TO POLICY NEEDS: THE DGI

How the Evolution of Economic Thinking over Time Affected Statistics

Recognizing the need to strengthen economic and financial data following a crisis is not new. As the economic and financial systems evolve as a consequence of market developments and financial innovation, information needs change. Looking back in history, crisis events have always acted as triggers to question the nature, quality, and availability of data needed for policymaking.

The Great Depression of the 1930s is a good example of fundamental advances in economic statistics. As policymakers began to more actively manage the economy and particularly aggregate demand, the intellectual and policy focus came to be concentrated on demand and supply factors in the economy, and on transactions rather than stocks. As a result, the System of National Accounts (SNA), which still remains the overarching framework of macroeconomic statistics, was developed in the late 1940s (UN 1953), and the first IMF Balance of Payments Manual (IMF 1948) was published around the same time.

The capital liberalization trend which started in the 1980s brought new opportunities for investment but also new risks and vulnerabilities, domestically and across borders, leading to a growing policy focus on financial stability (Heath 2015). These developments have necessitated a rethinking of macroprudential and monetary policies (IMF 2015g) and also the related statistical frameworks.

When the Mexican crisis occurred in 1994–95, international capital flows and a lack of relevant information were central. The IMF responded with the establishment of two key standards for the dissemination of a core set of economic and financial data: the Special Data Dissemination Standard (SDDS) and the General Data Dissemination System (GDDS). The SDDS was intended for countries with access to international capital markets while the GDDS focused on countries that needed to develop their statistical systems.

In 1997–98 the Asian crisis revealed the need for better information on reserve and reserve-related activities, as forward sales of foreign currency contracts by the Bank of Thailand were seen as having masked the true pressure on international reserves. As a result, a reserves template was developed and the SDDS was strengthened by the addition of requirements on reserves and foreign currency liquidity data.

Due to the global imbalances and the associated discrepancies in income flows at the global level, the first IMF Coordinated Portfolio Investment Survey (CPIS) was launched at end 1997 to improve statistics of holdings of portfolio investment assets in the form of equity and long-term and short-term debt securities. The strengthening of Bank for International Settlements’s (BIS) International Banking Statistics (IBS) and the increasing adoption by countries of the IMF’s Balance of Payments Manual has been prevalent throughout the past two decades.

The Global Financial Crisis of 2007–08 and the DGI

The financial crisis, which started in 2007 with problems in the US subprime market, spread to the rest of the world and became the most severe global crisis since the Great Depression. One difference between the global financial crisis and earlier postwar crises was that the crisis struck at the heart of the global financial system and spread throughout the global economy. This required global efforts for recovery. As one element of the global response, in October 2009 the G20 Finance Ministers and Central Bank Governors (FM-CBG) endorsed a DGI led by the Financial Stability Board (FSB) Secretariat and the IMF staff. The DGI was launched as an overarching initiative of 20 recommendations to address information gaps revealed by the global financial crisis.

Since its launch, considerable progress has been made toward closing those gaps (FSB and IMF 2015). Given this progress, in September 2015, at its sixth year, the G20 FM-CBG closed the first phase (DGI-1) and opened a second act of the DGI (DGI-2).

The success of the DGI is mainly attributable to a strong policy support, a common sense of ownership by the G20 economies, and the close cooperation among relevant parties. The InterAgency Group on Economic and Financial Statistics (IAG)1 has been acting as the global facilitator and coordinator of the exercise, liaising with other groups and initiatives. The IMF staff has been monitoring the implementation of the DGI recommendations by G20 economies on an annual basis and reporting, together with the FSB Secretariat, the progress made to the G20 FMCBG. Six progress reports were provided to the G20 FMCBG in DGI-1, with the third progress report under DGI-2 provided in September 2018 (http://www.imf.org/external/ns/cs.aspx?id=290).

In 2009, many of the recommendations were written as aspirations, as the implications of the crisis for regulatory and financial policy going forward were unclear. They were drafted following extensive consultations with compilers and users, including a users’ conference in July 2009,2 and structured around four themes: build-up of risk in the financial sector, cross-border financial vulnerabilities, vulnerability of domestic economies to shocks, and communication of official statistics.

As time progressed, the implications of the crisis for regulatory and macroprudential policy, and hence the data needs, have become more clearly established. Reflecting this, the DGI-2 recommendations focus on datasets that support the stability of the financial system both domestically and internationally. Nonetheless, as the 20 recommendations in DGI-1 have stood the test of time, DGI-2 represents an evolution and not a rethinking of the DGI project. DGI-2 aims to strengthen and consolidate the progress made in DGI-1, achieve the potential for data provision embodied in the initiative, and promote high-quality statistics for policy use (see Figure 5.1). The DGI-2 recommendations are set out in Appendix 5.1.

Data Gaps Intitiative Recommendations

Source: Author.

*Indicates priority areas identified by the G20 economies and international agencies in 2015.

The intention of this chapter is to demonstrate how DGI-2 is integral to meeting the emerging policy needs, both regulatory and macro-financial. To this end, the DGI-2 recommendations are more specific than those of DGI-1, with some identified as global priorities (see Figure 5.1) based on consultations with users and compilers in 2015. G20 economies have committed to action plans that take national circumstances into account, but are based on the targets set for each recommendation. The objective is to advance the statistical agenda agreed to by the G20 economies and endorsed by the G20 FMCBG at the global level. This agenda is designed to help make national and international financial systems more stable in a world of increased financial interconnectedness. An earlier working paper that set out the analytical justifcation for the DGI-1 recommendations remains relevant for DGI-2 (Heath 2013).

Evolution of Policy Needs Following the Global Financial Crisis

Regulatory Reform Agenda

Following the global financial crisis, in 2008, the G20 leaders, at their meeting in Washington,3 committed to implementing a fundamental reform of the global financial system to strengthen financial markets and regulatory regimes so as to avoid future crises.4 As part of the reform agenda, the FSB was established in April 2009 as the successor to the Financial Stability Forum and started working as the central locus of coordination to take forward the financial reform program as developed by the relevant bodies. The obligations of members of the FSB included agreeing to undergo periodic peer reviews, using among other inputs IMF/World Bank Financial Sector Assessment Program (FSAP) reports. The G20 leaders noted the importance of global efforts in implementing the global regulatory reform so as to protect against adverse cross-border, regional, and global developments affecting international financial stability.

The components of the G20 regulatory reform agenda complement each other with an ultimate goal of strengthening the international financial system. The DGI has been an important element of this agenda as the regulatory reform agenda items mostly require better data. The collection of data on Global Systemically Important Banks’ (G-SIBs) exposures and funding dependencies is among the steps towards addressing the “too-big-to-fail” issue by reducing the probability and impact of G-SIBs’ failing. The FSB work on developing standards and processes for global data collection and aggregation on securities financing transactions aims to improve transparency in securitization toward the main goal of reducing risks related to the shadow banking system. Over-the-counter (OTC) derivatives markets including credit default swaps (CDS) were brought under greater scrutiny toward the main goal of making derivatives markets safer following the global crisis. The DGI supported this goal by improving information in CDS markets. A number of other G20 initiatives have strong links with the DGI project, including the FSB work on strengthening the oversight and regulation of the shadow banking system and on the work on global legal entity identifiers5 that contribute to the robustness of the data frameworks with a more micro focus. The changing global regulatory reforms—particularly the implementation of Basel III—was also taken into consideration in the development of the DGI.

Global Flow of Funds

Through the use of internationally agreed-upon statistical standards, data on cross-border financial exposures (International Banking Statistics, Coordinated Portfolio Investment Survey, and Coordinated Direct Investment Survey) can be linked with domestic sectoral accounts data to build up a comprehensive picture of financial interconnections domestically and across borders, with a link back to the real economy through the sectoral accounts. This work is known as the “Global Flow of Funds” (GFF) (Errico and others 2014). The GFF project is mainly aimed at constructing a matrix that identifies interlinkages among domestic sectors and with counterpart countries (and possibly counterpart country sectors) to build up a picture of bilateral financial exposures and support analysis of potential sources of contagion.

The concept of the GFF was first outlined in the Second Progress Report on the G20 Data Gaps Initiative and initiated in 2013 as part of a broader IMF initiative aimed at strengthening the analysis of interconnectedness across borders, global liquidity flows, and global financial interdependencies. In the longer term, the GFF matrix is intended to support regular monitoring of bilateral cross-border financial positions through a framework that highlight risks to national and international financial stability. The IMF staff is working toward developing a GFF matrix, starting with the largest global economies.

Surveillance Agenda

The importance of closing the data gaps hampering the surveillance of financial systems was also highlighted as part of the IMF’s 2014 Triennial Surveillance Review (TSR).6 The 2014 TSR emphasized that due to growing interconnectedness across borders, financial market shocks will continue to have significant spillovers via both capital flows and shifts in risk positions. Also, new dimensions to interconnectedness will continue to emerge, such as through the potential short-term adverse spillovers generated by the financial regulatory reforms. To this end, the TSR recommended improving information on balance sheets and enriching flow-of-funds data.

The IMF has overhauled its surveillance to make it more risk based. To this end, the IMF Managing Director’s Action Plan for Strengthening Surveillance following the 2014 TSR (IMF 2014c) underlined that the IMF will revive and adapt the balance sheet approach to facilitate a more in-depth analysis of the impact of shocks and their transmission across sectors, and possibly initiate the global flow of funds to better reflect global interconnections (Box 5.1). This work requires data from the DGI, as it will help support the IMF’s macro-financial work, including in the key exercises and reports (that is, early warning exercise, FSAP, and GFSR).

The DGI Project

The DGI project has allowed for a broad range of users’ needs to be incorporated into the development of economic and financial statistics. Wide user consultation took place as part of the DGI work process in 2015,7 including through the Second IMF Statistical Forum, which constitutes an annual global space where data users, data providers, and policymakers can come together to discuss emerging needs for statistical information to inform policymaking.8

The consultations with users indicated the need for ensuring completeness and comprehensiveness of data that support analysis of interconnections among economies. The importance of the balance sheet approach for understanding sectoral interconnections within the domestic economy was emphasized. Data that are key to assessing fiscal sustainability were agreed to be essential but challenges in implementation were also pointed out. As a result, the following key focus areas common for G20 economies were identified:

  • Disseminating consistent and comparable Financial Soundness Indicators
  • Ensuring regular collection of IBS and the CPIS
  • Providing consistent securities statistics
  • Improving the availability of sectoral accounts data
  • Disseminating timely and comparable general government operations and debt data

The Second IMF Statistical Forum, under the main theme of “Statistics for Policy Making—Identifying Macroeconomic and Financial Vulnerabilities,” emphasized the importance of data quality and comparability; the need for monitoring interconnections and so the importance of sectoral accounts, balance sheets, and international investment position (IIP) data; and the need for better information on nonfinancial corporations, households, and real estate markets.

Consequent to these developments DGI-2 emerged with a focus on: (1) monitoring risk in the financial sector, and (2) vulnerabilities, interconnections, and spillovers. As illustrated in Figure 5.2, the recommendations in DGI-2 can mostly be clustered under these two broad headings. Further, the recommendations are presented as a coherent package that, in their implementation, create positive externalities for both compilation and analysis. The “vulnerabilities, interconnections, and spillovers” category is based on the overarching national accounts system, while the recommendations in the “monitoring risk in the financial system” section cover financial institutions and financial markets, with shadow banking straddling both institutions and markets, as explained in the next section. All recommendations fit together to provide an overall picture of the economy and the financial sector.

Linkages within the DGI-2 Recommendations

Source: Author.

Note: CDIS = Coordinated Direct Investment Survey; CDMs = concentration and distribution measures; CPIS = Coordinated Portfolio Investment Survey; CPPI = Commercial Property Price Indices; DGI = Data Gaps Initiatives; GFS = Government Finance Statistics; G-SIFIs = global systemic financial institutions; FSIs = Financial Soundness Indicators; IBS = International Banking Statistics; IIP = international investment position; PSDS = Public Sector Debt Statistics; R = DGI Recommendation; RPPI = Residential Property Price Indices.

How Does the DGI Help Monitor Risks in the Financial Sector?

Assessing the Soundness of the Banking System

It has been recognized for some time that microanalysis of financial institutions needs to be complemented with a macro focus. To this end, the IMF’s financial soundness indicators (FSIs) were developed in the early 2000s and, while backward looking, are an important component of a macroprudential framework for monitoring and assessing the health and soundness of the overall financial sector (Navajas and Tegeya 2013; and http://www.imf.org/external/np/sta/fsi/eng/fsi.htm). To date, the main focus of the FSIs has been on the banking sector, with additional indicators on banks’ customers as well as on the markets that they operate in.

From the consultations with compilers and users in 2015, it is clear that FSIs are also increasingly being used by national authorities to establish national benchmarks, perform cross-country analyses, and construct early warning indicators. Such analyses are feeding into financial stability reports to inform policymaking. Further, the IMF includes FSI data in individual economy Article IV consultation reports and in the statistical annex of the GFSR. This policy-related focus of FSIs, both at the national and international level, helped encourage a significant increase in country coverage of FSIs reported to the IMF during DGI-1. At the end of 2018 almost 140 economies reported FSI data to the IMF, including all G20 economies—an increase from 45 economies in 2009.

However, to maintain the usefulness of FSIs as a tool for financial stability assessment, the list of indicators was updated in 2013 to reflect the changes in the financial environment, notably the increased prominence of nonbank financial institutions, and the global regulatory reforms, particularly the implementation of Basel III (see IMF 2013a). The latter revised the definitions of capital and introduced new measures of leverage, liquidity, and funding—all of which are reflected in the updated list of FSIs.

The updated list of FSIs for nonbank financial corporations aims to contribute to the analysis and assessment of the potential impacts of the shadow banking sector on the stability of the financial system. Whereas the previous list only looked at the subsector as a whole, which is comprised of a very heterogeneous set of institutions, the new list includes separate FSIs for money market funds, insurance corporations and pension funds, and other nonbank financial institutions. New FSIs were also introduced for nonfinancial corporations and households (see http://www.imf.org/external/np/sta/fsi/eng/fsi.htm). The DGI-2 places greater emphasis on increasing the frequency and coverage of FSI reporting, particularly for nonbank financial institutions (Appendix 5.1, Recommendation II.2).

The crisis also highlighted the need for taking tail risks into account as a complement to the overall assessment of the financial sector risks through aggregate measures. To this end, to capture the system-wide disturbances that could be caused by the institutions that are at the tail of the distributions, aggregate FSI measures were enhanced by a pilot study on concentration and distribution measures (CDMs). It was considered that expanding FSIs for the financial system with CDMs would allow policymakers and the IMF staff to better capture the performance of the financial sector with greater granularity and in a forward-looking manner.

The pilot project was completed in 2015, with the participation of 35 diverse countries (see Crowley and others 2016). CDMs were compiled for six FSIs of deposit takers: regulatory Tier 1 capital to risk-weighted assets, nonperforming loans to total gross loans, return on assets, return on equity, liquid assets to short-term liabilities, and capital to total assets.9 The data provided important information that was not revealed by averages. For instance, the distributions of minimum values of CDMs,10 which represent the institutions with the most severe risks for any variable, showed substantial variation across countries and over time within countries. The pilot project indicated that regular reporting of CDMs may be feasible and could be a useful tool for monitoring financial sector vulnerabilities. In DGI-2, the IMF is discussing regular collection of CDM data (Appendix 5.1, Recommendation II.3).

Regarding the banking sector, the BIS conducted conceptual work focusing on system-level measures of maturity mismatches (funding gaps) on banks’ international balance sheets, based on BIS IBS (Fender and McGuire 2010). The BIS’s work pointed out that analysis of system-wide bank funding risks and the transmission of shocks across countries require geographically disaggregated data on banks’ balance sheets to capture funding patterns that are location specific, and facilitate targeted assessments of vulnerabilities showing up in the aggregate data. This work helped inform the enhancements to the BIS IBS that were adopted during 2012– 15, thereby improving the usefulness of this dataset for the construction of maturity mismatch and leverage measures. The enhancements to the IBS included improved information on the counterparty, residual maturity, and currency breakdown of banks’ international positions, with improvements made both to the residency-based and consolidated-based (using nationality-based supervisory concepts) statistics. DGI-2 maintains an emphasis on improving the IBS reporting of G20 economies (Appendix 5.1, Recommendation II.11).

Monitoring the Shadow Banks

A shadow banking system is defined by the FSB as a “credit intermediation involving entities and activities outside the regular banking system.” Such institutions could provide alternative sources of funding for market participants in complement to traditional banking but could also carry bank-like risks. Those risks could easily spread through the rest of the system due to complex relationships among these institutions and banks, and hence, they need to be monitored.

Typically, these institutions are highly leveraged and heavily reliant on short-term funding while investing in long-term illiquid assets and hence are exposed to liquidity and maturity risks. During the crisis when such risks materialized, the entire financial system suffered the consequences, thus emphasizing the importance of monitoring such risks.

At the 2011 Summit Meeting in Cannes, the G20 leaders asked the FSB to address the financial stability concerns associated with shadow banking. The FSB strategy has two elements (see FSB 2013):

  • First, the FSB initiated an annual global shadow banking monitoring exercise.
  • Second, the FSB is working to develop policies to strengthen oversight and regulation of the shadow banking system.11

The FSB’s 2015 annual report covered 26 jurisdictions which, as of 2014 (FSB 2015b) constituted 80 percent of global GDP and 90 percent of global financial system assets and is based on balance sheet data of national financial accounts. The annual reports are coordinated collections of data aggregated to a global level to allow for the analysis of global trends and risks in the shadow banking system. For the first time, the 2015 report introduced a new measure of shadow banking based on the economic functions of non-bank financial entities focusing only on those nonbank financial institutions that are involved in significant maturity and liquidity transformation or leverage, and are part of a credit-intermediation chain. This allows policymakers to better focus on the potential risks shadow banking entities may pose. Based on this measure, the global assets of financial entities classified as shadow banking reached $45 trillion at the end of 2016.

Regarding oversight and regulation of the shadow banking system, among the topics covered is that of risks in the securities lending and repurchase markets. The crisis pointed out that short-term deposit-like funding of nonbank entities can easily lead to “runs” in the market if confidence is lost. The use of these collateralized funding (secured financing) techniques can exacerbate such runs and boost leverage, especially when asset prices are buoyant and margins and haircuts on secured financing are low. Therefore, the FSB initiated work to collect and aggregate data on securities financing markets that is now incorporated in DGI-2 (Appendix 5.1, Recommendation II.5). Preparation for official data collection and aggregation started in 2018.

Monitoring the Global Systemically Important Financial Institutions

Due to the significance of global systemically important financial institutions (G-SIFIs) in spreading shocks across borders, and the potential effects of their failure for the global financial system, several measures were taken to improve the resilience of these institutions to limit the moral-hazard effects. Among these measures were the identification of G-SIBs in 2011 by the Basel Committee on Banking Supervision and the introduction of additional loss-absorbency measures for such institutions. Having better data on the bilateral linkages of these institutions as well as their exposures to and funding dependencies on national financial systems was seen as an important prerequisite to understanding the risks associated with these institutions. To this end, the work to construct a data template for G-SIFIs as recommended by the DGI focused initially on G-SIBs.

The end product of this exercise, which was led by the FSB, in close consultation with the IMF, is a set of unique data templates bringing together consistent, granular information on G-SIBs that is useful for both microprudential and macroprudential analysis. Collection of data started with information on G-SIBs’ bilateral linkages as well as some aggregate information based on the institution-level data underlying the consolidated IBS and will continue with the collection of information on G-SIBs’ exposures to and lending from key economies with the granularity of a combination of sector, instrument, currency, and maturity. The data are stored at the International Data Hub established at the BIS and currently are shared among the data-providing national authorities.12 This process has reinforced the exchange of information and coordination among national supervisory authorities. However, given the granularity of the dataset, it brings along confidentiality issues that need to be addressed in the longer term to make better use of this critical information.

The objective of the templates is to provide authorities with a clearer view of global financial networks and assist them in their supervisory and macroprudential responsibilities (FSB 2014). Data on G-SIBs supports the IMF’s work in safeguarding international financial stability including through effective multilateral and bilateral surveillance and the encouragement of coherent policy responses across member countries (IMF 2014c). The data permits bank-level information to be used in conjunction with measures of worldwide exposures, substantially improving the ability to detect vulnerabilities that could originate from common exposures and concentrated funding positions so deepening the understanding of the potential source of spillovers. G-SIBs data also improves the tracking of banks’ cross-currency funding and maturity transformation activities. In addition, the data helps to improve understanding of financial innovation, market complexity, and emerging sources of potential systemic risks.

Going beyond the banking industry, the FSB and International Association of Insurance Supervisors have also identified insurance companies of global systemic importance, based on a methodology developed by the International Association of Insurance Supervisors (IAIS 2013). The assessment methodology relates to the methodology developed by the Basel Committee on Banking Supervision for G-SIBs, but also takes into account the specific nature of the insurance sector. In particular, insurance groups that engage in nontraditional or noninsurance activities can be vulnerable to liquidity and market price risks amplifying or contributing to systemic risk (IAIS 2011). Therefore, such nontraditional activities are included as an indicator in the assessment methodology. Following on from these regulatory developments, in DGI-2 the possibility of developing a common data template for global systemically important nonbank financial institutions, starting with insurance companies, is included in DGI-2 (Appendix 5.1, Recommendation II.4).

Understanding Financial Markets

While being an important channel for financing of the real economy, securities markets have also been a key channel for risk transmission, particularly due to the increasing reliance on market-based financing. Therefore, there is consensus on the importance of better information on these markets in order to understand the diversification of funding sources and the exposures of both issuers and creditors, including the nonfinancial sector. Long important in advanced economies, there is evidence of growing security issuance in emerging market economies as the composition of corporate debt has been shifting away from loans and toward bonds (IMF 2015c). At the same time, it is estimated that over the past decade, domestic debt securities markets in emerging market economies have increased from around one third of emerging market economies’ GDP to about one half (Hat-tori and Takáts 2015).

The DGI has addressed this growing policy interest in securities markets by providing conceptual advice through the publication of a Handbook on Securities Statistics (see BIS, ECB, and IMF 2015a) prepared jointly by the BIS, the European Central Bank, and the IMF. The DGI has also addressed this interest by fostering improvements in securities statistics through encouraging G20 economies to report to the BIS database on securities statistics.

Since 2009, the number of economies that report regular and consistent securities statistics to the BIS has increased significantly. Moreover, even though the levels of sophistication of national statistical frameworks are diverse among G20 economies, these countries increasingly recognize the importance of having granular information on these markets, and hence are considering building security-by-security databases.13 Data on securities issuance (and holdings) are also an input into national accounts, balance of payments, and government finance statistics. The initial focus of the DGI-2 is to improve data on issuance of debt securities with key information on the markets, sectors, currency, maturity, and interest rate. Consistent information on holdings of debt securities and from-whom-to-whom data is considered a longer-term objective (Appendix 5.1, Recommendation II.7).

The need to bring light to the opaqueness of the OTC derivatives markets is also a focus of the DGI. In DGI-1 CDS data were expanded both in detail and country coverage, and regular reporting of the expanded datasets was implemented. All economies with significant CDS markets report CDS data to the BIS survey, including more detail on the type and geography of counterparties as well as the underlying instrument (BIS 2017).

In DGI-2, there is recognition of the need to improve data on OTC derivative markets more broadly (Appendix 5.1, Recommendation II.6). In September 2009, G20 leaders agreed to a comprehensive reform agenda to improve transparency in OTC derivatives markets, mitigate systemic risk, and protect against market abuse. They asked the FSB and its relevant members to assess its implementation regularly. The objectives of this reform include reporting of OTC derivative contracts to trade repositories and trading of all standardized contracts on exchanges or electronic trading platforms, where appropriate, with clearing through central counterparties. Non-centrally-cleared contracts are subject to higher capital requirements. This regulatory initiative to clear OTC derivatives through central clearing allows for more standardization of reporting and aggregation both for regulatory and financial-data purposes. In turn, these developments are also increasing interest in the quality of reporting as well as the consistency among the already existing data collections.

How Does the DGI Address the Surveillance Agenda?

As noted elsewhere in this chapter, in the wake of the 2014 TSR, the IMF Managing Director published an Action Plan for Strengthening Surveillance. Among the actions to be taken was that “The Fund will revive and adapt the balance sheet approach to facilitate a more in-depth analysis of the impact of shocks and their transmission across sectors.” This responded to a call from outside experts David Li and Paul Tucker in their external study for the 2014 TSR on risks and spillovers (see IMF 2014b).

Sectoral Analysis

Even though the 2007–08 crisis emerged in the financial sector, given its intermediary role, the problems in the financial sector also affected other economic sectors. Therefore, analysis of balance sheet exposures is essential, given the increasingly interconnected global economy. As it is pointed out in the IMF TSR 2014b, the use of balance sheets to identify sources of vulnerability and the transmission of shocks could have helped detect risks associated with European banks’ reliance on US wholesale funding to finance structured products.

In June 2015, the IMF set out the way forward in a paper for the IMF Executive Board on Balance Sheet Analysis in Surveillance (IMF 2015a). Sectoral accounts and balance sheet data are essential, including from-whom to-whom data, in providing the context for an assessment of the links between the real economy and financial sectors. The sectoral balance sheets of the SNA are seen as the overarching framework for balance sheet analysis as the IMF Executive Board paper makes clear. Further, the paper sets out a data framework for such analysis (IMF 2015a, 23).

Putting the sectoral balance sheets of the SNA in a policy context, the IMF has developed a balance sheet approach, which compiles all of the main balance sheets in an economy using aggregate data by sector. The balance sheet approach is based on the same conceptual principles as the sectoral accounts, providing information on a from-whom-to-whom basis with an additional focus on vulnerabilities arising from maturity and currency mismatches as well as the capital structure of economic sectors. While currently not that many economies compile from-whom-to-whom balance sheet data, balance sheet approach data can be compiled from the IMF’s Standardized Report Forms, IIP, and government balance sheet data—a more limited set of data than needed to compile the sectoral accounts.

The DGI-2 recommendations address key data gaps that act as a constraint on a full-fedged balance sheet analysis. The DGI recommends addressing such gaps through improving G20 economies’ dissemination of sectoral accounts and balance sheets, building on the 2008 System of National Accounts, including for the nonfinancial corporate and household sectors (Annex 5.1, Recommendation II.8). Given the multifaceted character of the datasets, implementation of this recommendation is challenging, and progress has been slow. However, all G20 economies agree on the importance of having such information and have plans in place to make it happen.

In a world of capital flow liberalization and fewer credit constraints, widening distributions of income, consumption, saving, and wealth can lead to potential financial vulnerabilities even if the aggregate data look reassuring. Indeed, the importance of good distributional data for households has become increasingly apparent over recent years as policy interest in inequality has increased in both advanced and developing economies in recent decades (see IMF’s Work on Income Inequality at http://www.imf.org/external/np/fad/inequality/index.htm). DGI-2 focuses on the compilation of distributional information (such as information by income quintiles) to complement aggregate figures, consistent with national accounts (Appendix 5.1, Recommendation II.9). To this end, the Organisation for Economic Co-operation and Development (OECD) has carried out conceptual work on distributional information focusing on (1) linking national accounts with distributional information (microdata and macrodata), summarized in two OECD publications (OECD 2013a; OECD 2013b), and (2) the provision of an improved conceptual alignment of income, consumption, and wealth in microsurveys, including a further enhancement of wealth definitions.

Analysis of Fiscal Condition

Significant data gaps also exist in the area of government finance statistics. The support provided by many national authorities to the financial sector following the global financial crisis, along with the onset of recession and fiscal stimulus programs to support demand, led to increases in fiscal deficits and government debt. However, consistent and comparable fiscal data across the G20 economies was lacking, hampering cross-country analysis. Further, monitoring the trends in the fiscal positions of governments was often limited by a lack of frequent and timely harmonized data, including a lack of accrual-based data.

At the international level, there has been significant progress in support of the compilation of government finance statistics. Conceptual work has included publication of the Government Finance Statistics Manual 2014 (GFSM 2014). Further, the IMF Executive Board began addressing the problem of government finance statistics in 2010, and reaf-firmed this in 2013 by requiring the inclusion in staff reports of key elements of the GFSM presentation (see IMF 2013b). The paper also confirmed the intention to establish a Government Finance Statistics Advisory Committee to support the implementation of GFSM and advise on emerging fiscal data issues. The advisory committee met for the first time in March 2015 and agreed to support development of the GFSM 2014 with a number of practical recommendations (see IMF 2015e).

Despite these developments at the international level, progress has lagged behind other recommendations. This is due to factors such as the lack of coverage of state and local governments, the fact that Government Finance Statistics in many countries are not institutionally well established, and, in some instances, the reluctance of authorities to use statistical techniques to fll the data gaps.14 To this end, the DGI-2 remains aimed at addressing the gaps in government finance statistics (Appendix 5.1, Recommendation II.15).

Within the same context, information on the debt levels of the public sector, particularly general government, is crucial to assess the fiscal soundness of government. Under the DGI, the World Bank, the OECD, and the IMF launched a quarterly public sector debt statistics database in 2010 to promote standardized reporting by countries. However, the scope of sector and instrument coverage can differ significantly across countries. This is highly relevant because of the close analytical and policy interest in measures such as gross debt to GDP. If a country “only” covers debt securities and loans for the budgetary central government, comparing these data with a country that covers all debt liabilities including accounts payable and pension obligations for the general government will clearly not be comparing like with like (see Dippelsman, Dziobek, and Gutiérrez Mangas 2012). As a consequence, supported by DGI-2, the World Bank’s public debt database is moving to a presentation of instrument and sectoral coverage on a matrix basis—presenting varying levels of sector and instrument coverage from the narrowest to the broadest (IMF 2015f) (Appendix 5.1, Recommendation II.16).15

Understanding Cross-Border Financial Interconnections

The crisis emphasized the fact that it is not possible to isolate the problems in a single financial system, as shocks propagate rapidly across the financial systems. Indeed, since 2010 the IMF has been identifying jurisdictions with systemically important financial sectors based on a set of relevant and transparent criteria, including size and interconnectedness. Within this identification framework, cross-border interconnectedness is considered an important complementary measure to the size of the economy: it captures the systemic risk that can arise through direct and indirect interlinkages among financial sectors in the global financial system (that is, the risk that failure or malfunction of a national financial system may have severe repercussions on other countries or on overall systemic stability) (IMF 2010).

The 2014 TSR summed up the issue succinctly in its Executive Summary: “Risks and spillovers remain first-order issues for the world economy and should be central to Fund surveillance. Recent reforms have made surveillance more risk-based, helping to better capture global interconnections. Experience so far also points to the need to build a deeper understanding of how risks map across countries, and how spillovers can quickly spread across sectors to expose domestic vulnerabilities” (IMF 2014d).

Four existing datasets that include key information on cross-country financial linkages are the IIP, BIS IBS, IMF CPIS, and IMF Coordinated Direct Investment Survey (CDIS). Together, these datasets provide a comprehensive picture of cross-border financial interconnections. This picture is especially relevant for policymakers, as financial connections strengthen across borders and domestic conditions are affected by financial developments in other economies to which they are closely linked financially. DGI-2 focuses on improving the availability and cross-country comparability of these datasets (Appendix 5.1, Recommendations II.10, 11, 12, and 13).

The well-known IIP is a key data source to understanding the linkages between the domestic economy and the rest of the world by providing information on both external assets and liabilities of the economy with a detailed instrument breakdown. However, the crisis revealed the need for currency and more detailed sector breakdowns, particularly for the other financial corporations sector. Consequently, as part of the DGI, the IIP was enhanced to support these policy needs. Significant progress has also been made in ensuring regular reporting of IIPs along with an increase in frequency of reporting from annual to quarterly. By the end of 2017 all G20 economies reported quarterly IIP data.

The IBS have been a key source of data for many decades, providing information on aggregate assets and liabilities of internationally active banking systems on a quarterly frequency. The CPIS data, while on an annual frequency, provided significant insights into portfolio investment assets. That said, both datasets had limitations in terms of country coverage and granularity. CPIS also needed to be improved in terms of frequency and timeliness. To this end, the DGI supported the enhancements in these datasets.

The IBS was enhanced through (1) expanded coverage of banks’ balance sheets to also include domestic positions in complement to cross-border activities, and (2) improved granularity of data by collecting more information on country and sector of banks’ counterparties, in particular non-bank financial institutions. The enhancements to the IBS will provide users with a more comprehensive picture of the size and scope of internationally active banks’ activities. Hence, it will enable a better analysis of the sources and uses of funds and of the importance of international business for banks of different nationalities (Avdjiev, McGuire, and Wooldridge 2015).

The CPIS started to be collected on a semiannual frequency from June 2013 with a dissemination lag of less than nine months (see IMF 2011). In 2018, all G20 economies reported CPIS data to the IMF on a semiannual basis. Further, there is growing interest in understanding the sector allocation of holders and issuers, in order to match the sectoral analysis in the domestic accounts. At the end of 2017, 16 G20 economies reported the sector of holder data, while among the enhancements made in the DGI were new tables for collecting information on the sector of the issuer of securities, also crossed with sector of the holder of securities. DGI-2 maintains the focus on improving CPIS reporting of G20 economies.

The IMF’s CDIS complements the CPIS and IBS for an analysis of cross-border interconnectedness, as it provides information on direct investment positions broken down by net equity and net debt. The CDIS was brought under the DGI umbrella in its second phase with an aim toward improving the quality of G20 economies direct investment position statistics, both inward and outward.

Foreign currency risk is an important element of an analysis of cross-border interconnections. To this end, particular attention was given, including by the G20 FMCBG (see BIS, FSB, and IMF 2015b) to the improvement of foreign currency exposure information given the potential spillover effects of wealth transfers triggered by sharp movements in exchange rates. Within this context, the IMF focused on improving the compilation of foreign currency exposures data across its statistical domains, particularly through the IIP. The BIS contributes to the analysis of foreign currency exposures through its international debt securities, and its enhanced IBS, which provides the basis for deriving a more detailed picture of internationally active banks’ balance sheets and thus measuring potential currency mismatches more accurately.

The global financial crisis also revealed the need to understand better the cross-border foreign currency exposures of nonfinancial corporations. The FSB Committee on the Global Financial System16 identified the gaps in information on foreign currency exposures of corporations in a joint workshop in 2014, reporting the outcomes to the G20 FM-CBG. In addition, the FSB conducted in 2014 a peer review of the trade repository reporting of OTC derivatives, covering all types of OTC derivatives, including foreign currency derivatives and other instruments that create foreign currency exposures (FSB 2015a). This work was also reported to the G20. All in all, the DGI-2 supports this work on foreign currency exposures through more explicit incorporation of data on foreign currency exposures in the recommendations (that is, IIP, cross-border exposures of nonbank corporations, and securities statistics).

The increase in foreign exchange derivative exposures of nonfinancial corporations through off-shore entities has been an area of concern, particularly for emerging market economies, as authorities were unaware of the transactions recorded outside their jurisdictions. The DGI framework is contributing to shedding light on this broader area of cross-border exposures and intragroup funding by nonfinancial corporations through their off-shore subsidiaries (Appendix 5.1, Recommendation II.14). Conceptual guidance was provided to clarify nationality, group, and consolidation concepts in DGI-1 (IAG 2015), and going forward, BIS and IMF will continue to improve information on nonfinancial corporations’ cross-border exposures, mainly drawing on their existing data collections. The OECD will also contribute through the development of a framework that links its multinational enterprises data with its foreign direct investment data.

Monitoring the Property Markets

Residential and commercial property price indices are important for the detection and monitoring of asset price bubbles, the compilation of estimates of household and corporate wealth and capital formation, and the assessment of the broader financial stability implications. The relevance of property prices was stressed at the Second IMF Statistical Forum (see Silver 2014), while work at the BIS has highlighted the importance of asset price developments— especially property prices—in driving the so-called financial cycle (see Borio and Drehmann 2009; and Dembiermont 2015).

However, the availability and international comparability of this data was limited before the global financial crisis. As part of the DGI-1, conceptual guidance was provided through the publication of Handbook on Residential Property Price Indices,17 and in 2010 the BIS started to disseminate real estate price statistics on its website. Currently, most G20 countries provide data even though the data provided are often at a development stage and more work is needed to ensure consistency and international comparability.

Over recent years, the importance of good real estate price statistics has become increasingly clear to policymakers, given the link with household consumption and the need to monitor asset prices in an environment of accommodative monetary policies. Consequently, most of the G20 economies have been increasing their efforts to develop good statistics on real estate prices. Residential real estate price is one of the FSIs that is prescribed for adherents to the SDDS Plus. Good real estate price indices can also support the measurement of nonfinancial assets in the sectoral accounts.

Commercial property price indices are at a less-developed stage, both conceptually and in terms of availability of data. However, there is a financial stability interest in the dissemination of this data for monitoring asset bubbles. This is because commercial property is used for banks’ collateralized lending; and commercial property price indices data are important for the valuation of securitized assets. Therefore, work needs to be done to enhance the methodological guidance that is being developed and to encourage the provision of available data to the BIS for public dissemination.

DGI-2 Recommendations II.17 and 18 address the development of property place indices.

The Need to Better Communicate Statistics

The DGI facilitated a new tier of the IMF’s data standards (SDDS Plus) mainly intended for economies with systemically important financial systems to guide IMF member countries on the provision of economic and financial data to the public in support of domestic and international financial stability. Economies adhering to the SDDS Plus are expected to disseminate data in nine categories covering four macro-economic sectors—the real sector, the fiscal sector, the financial sector, and the external sector—all of which were largely drawn from the DGI-1 recommendations. Given the common areas of focus, adhering to the SDDS Plus and implementation of DGI recommendations would contribute to each other. When this book went to press, 18 countries were in adherence with the SDDS Plus.

The IMF also continues to consider the needs of emerging markets and low-income countries. The SDDS aims to enhance the availability of timely and comprehensive statistics and thereby contribute to the pursuit of sound macro-economic policies and the improved functioning of financial markets. In May 2015, the GDDS was enhanced (e-GDDS) to assist countries with relatively less-developed statistical capacity. The emphasis on data dissemination in the e-GDDS will support transparency, encourage statistical development, and help create strong synergies between data dissemination and surveillance. IMF will continue working with member economies, including through capacity development activities, to ensure the availability and dissemination of information.

There was also a need to improve the communication of official statistics, as in some instances users were not fully aware of the available data series to address critical policy issues. As part of the DGI, the Principal Global Indicators (PGI) website (http://www.principalglobalindicators.org), hosted by the IMF, was launched in 2009 as a joint undertaking of the IAG with the aim of facilitating the monitoring of economic and financial developments. The PGI website includes data for the G20 economies and non-G20 members that have systemically important financial sectors and are subject to a five-year mandatory FSAP.18 The PGI website was significantly enhanced as part of the DGI in terms of coverage and timeliness. It currently offers access to an online database with user-selected longer runs of historical data presented in comparable units of measure (growth rates, index numbers, and percent of GDP). Work to strengthen the PGI further will continue in DGI-2 (Appendix 5.1, Recommendation II.19).

As new risks emerge and relationships between institutions, sectors, and countries get more complex, the granularity of data needed to assess those risks become relevant. This brings along the need for compilers of data to collect information at the micro level to help meet user demands. DGI recommendations (that is, G-SIBs data, IBS, CPIS) support the need for more granular data.19 On the other hand, the increasing granularity of data also raises challenges for sharing such information either within economies, across borders, and with international agencies, due to confidentiality concerns. This potentially limits the broader benefits of new or existing data collections including some under the DGI. While this is not an easy problem to tackle, DGI-2 focuses on the issue of confidentiality by encouraging the G20 economies to increase the sharing and accessibility of granular data, if needed, by revisiting existing confidential-ity constraints (Appendix 5.1, Recommendation II.20). Addressing the confidentiality constraints and how they can be overcome as part of the DGI-2 would be a positive step forward.

It is also worth noting that the private sector is working toward improving bank disclosures. To this end, the Enhanced Disclosure Task Force, a private sector group of financial institutions established by the FSB, released a report in 2012 that included seven fundamental principles for enhancing the risk disclosures of banks.20

The need for granular and real-time data to understand in-terconnectedness and spillovers across countries and institutions was also emphasized at the Third IMF Statistical Forum held in Frankfurt in November 2015 (http://www.imf.org/external/np/seminars/eng/2015/statsforum/). The participants urged statistical agencies and policymakers to establish new legal frameworks to support microdata access while preserving confidentiality.

Broader Implications of the DGI

Even though the focus of the DGI has been the G20 economies, it involves a wider range of economies as it builds on widely accepted international statistical frameworks. In particular, the methodological guidance provided as a result of the DGI is for all IMF member economies. Moreover, most recommendations of the DGI build on various statistical initiatives that involve a larger group of economies. Furthermore, as these non-G20-member economies see the merit in this initiative for their own policy work, even without any higher level policy push such as the G-20 FM-CBG, they are working toward implementation of the DGI recommendations.

Evidently, improved quality of information worldwide is essential to ensure a complete assessment of global macro-financial linkages. With this in mind, a reference note (IMF 2015b) to the IMF paper Balance Sheet Analysis in Fund Surveillance (IMF 2015a), provided a full listing of available balance-sheet-related macro datasets, including their relevance for surveillance, and a summary of data availability for each IMF member. Many of the datasets referenced were those covered by DGI-2. Further, the IMF staff provides increasing support to member countries for the compilation of these datasets through technical assistance and training (see IMF 2016).

DGI and Stress Testing

As explained in IMF 2012, “Stress testing is a technique that measures the vulnerability of a portfolio, an institution, or an entire financial system under different hypothetical events or scenarios. It is a quantitative “what if” exercise, estimating what would happen to capital, profits, cash flows, etc. of individual financial firms or the system as a whole if certain risks were to materialize” (IMF 2012). By increasing the availability, consistency, and comparability of data relevant for financial stability analysis, the DGI supports the use of stress tests to assess a broad range of vulnerabilities (for example, credit risk, market risk, and foreign exchange risk), with increased reliability and more flexibility in the potential range of scenarios tested.

More specifically, the work under the DGI to increase the granularity of data will improve the sensitivity of the stress testing exercises and allow for assessments of vulnerabilities of specific components of the financial system (for example, specific sectors and instruments). Further, improved availability, quality, and consistency of institutions’ own data sets (for example, data on global systemically important banks) could be considered a key input to bottom-up stress tests.

Starting with the financial sector, stress testing exercises using systematically collected and disseminated FSI data can fag issues for follow-up, not only on individual institutions (microprudential) but also on aggregate financial systems (macroprudential). For instance, the nonperforming-loans-to-total-loans ratio, one of the core FSIs, is a widely used indicator for the assessment of potential shocks on credit quality.

Sharp changes in property prices are among the key risk factors used in macroeconomic stress scenarios. The increasing availability of comprehensive data on property prices, along with other data being enhanced through the DGI, including sectoral accounts, would therefore allow for a broader range of stress testing exercises to assess the impact of real estate price changes on the both financial sector and the economy more broadly.

For a more aggregate economy-wide perspective, the availability of sectoral accounts data allows for the construction of many indicators of vulnerability including household debt to income, and the relative shift in activity of financial institutions, such as from banks to nonbank financials, while also providing a tool for analyzing the link between the real and financial economies. Analysis through stress tests of the potential impact of various scenarios, including regulatory reform on financial sector activity, and on the economy more broadly, can be enhanced by a comprehensive set of sectoral accounts.

The often close ties between the government and the financial sector can potentially lead to a negative sovereign-bank feedback loop: financial sector problems can lead to bailouts by government, and the financial sector can have large exposures to governments (such as through security holdings, often encouraged by regulatory policy) that are facing fiscal stresses. The more detailed and comprehensive data for government accounts and securities holdings being promoted under DGI-2 would support stress testing scenarios to monitor such potential negative feedbacks.

With regard to the external sector, the channel through which exposures to the rest of the world will primarily affect the domestic economy is the IIP, be it through transactions; current or financial account; valuation; changes in market prices and exchange rates; or other flows, such as debt write-offs. IIP data—with its integrated system of stocks and flows—can be utilized along with sectoral accounts for stress tests to analyze which sectors might gain and which sectors might lose value during an external shock, and how the loss in value is funded. Indeed, the increased focus on foreign currency data in the DGI-2 further supports such analysis through stress testing

Finally, the extent of the trade and financial links across borders turned out to be deeper and more firmly established than most were aware of during the global financial crisis, including through cross-border bond holdings and banking links and through trade supply lines.21 Various datasets included in the DGI-2 support the stress testing of cross-border financial links, including the IBS, CPIS, and CDIS data.

Besides the few examples provided previously, implementation of the DGI-2, in general, would contribute to the stress testing exercises by improving their sensitivity, increasing their scope, and allowing for more flexibility in the potential range of scenarios tested.

3. Conclusion

The DGI could be considered an overarching initiative covering a wide range of statistical frameworks that are interlinked in support of the common goal of understanding financial markets and instruments and shedding light on interconnectedness.

Making available a comprehensive set of information, as intended by the DGI, in a standardized, frequent, and timely manner is not an easy task, especially while also ensuring that the available data are reliable, of high quality, and properly reflect the changing economic circumstances. This cannot happen overnight, but over time and with a global effort, it is possible. It also requires high-level support, including resources to be secured. Since the global financial crisis, significant efforts have been made by all relevant parties to ensure that the policymakers have access to DGI-related information as a key component of their toolbox. To be able to reap the benefits of the investments made in the DGI, it is important to maintain the pace of work and continue coordination among all players in the global economy.

Appendix 5.1. DGI-2 Recommendations

Recommendation II.1: Mandate of the Data Gaps Initiative (DGI)

The G20 economies to regularly compile comparable and high-quality economic and financial statistics in accordance with international standards and disseminate such statistics in a timely manner. The Inter-Agency Group on Economic and Financial Statistics (IAG) to coordinate and monitor the implementation of the DGI recommendations, and promote the Principal Global Indicators (PGI) website as a global reference database. Staff of the Financial Stability Board (FSB) and IMF to provide annual updates on progress to G20 finance ministers and central bank governors.

Monitoring Risks in the Financial Sector

Recommendation II.2: Financial Soundness Indicators

The G20 economies to report the seven financial soundness indicators (FSIs) expected from Special Data Dissemination Standard Plus adherent economies, on a quarterly frequency. G20 economies are encouraged to report the core and expanded lists of FSIs, with a particular focus on other (nonbank) financial corporations. The IMF to coordinate the work and monitor progress.

Recommendation II.3: Concentration and Distribution Measures

The IMF to investigate the possibility of regular collection of concentration and distribution measures for FSIs. G20 economies to support the work of the IMF.

Recommendation II.4: Data for Global Systemically Important Financial Institutions

The G20 economies to support the International Data Hub at the Bank for International Settlements (BIS) to ensure the regular collection and appropriate sharing of data about global systemically important banks. In addition, the FSB, in close consultation with the IMF and relevant supervisory bodies, to investigate the possibility of a common data template for systemically important nonbank financial institutions starting with insurance companies. This work will take due account of the confidentiality and legal issues.

Recommendation II.5: Shadow Banking

The G20 economies to enhance data collection on the shadow banking system by contributing to the FSB monitoring process, including through the provision of sectoral accounts data. FSB to work on further improvements of the conceptual framework and developing standards and processes for collecting and aggregating consistent data at the global level.

Recommendation II.6: Derivatives

BIS to review the derivatives data collected for the International Banking Statistics (IBS) and the semiannual over-the-counter derivatives statistics survey, and the FSB to develop a mechanism to aggregate and share at global level over-the-counter derivatives data from trade repositories. The G20 economies to support this work as appropriate.

Recommendation II.7: Securities Statistics

G20 economies to provide on a quarterly frequency debt securities issuance data to the BIS consistent with the Handbook on Security Statistics starting with sector, currency, type of interest rate, original maturity and, if feasible, market of issuance. Reporting of holdings of debt securities and the sectoral from-whom-to-whom data prescribed for Special Data Dissemination Standard Plus adherent economies would be a longer-term objective. BIS, with the assistance of the Working Group on Securities Databases, to monitor regular collection and consistency of debt securities data.

Vulnerabilities, Interconnections, and Spillovers

Recommendation II.8: Sectoral Accounts

The G20 economies to compile and disseminate, on a quarterly and annual frequency, sectoral accounts flows and balance sheet data, based on the internationally agreed template, including data for the other (nonbank) financial corporations sector, and develop from-whom-to-whom matrices for both transactions and stocks to support balance sheet analysis. The IAG, in collaboration with the Inter-secretariat Working Group on National Accounts, to encourage and monitor the progress by G20 economies.

Recommendation II.9: Household Distributional Information

The IAG, in close collaboration with the G20 economies, to encourage the production and dissemination of distributional information on income, consumption, saving, and wealth, for the household sector. The Organisation for Economic Co-operation and Development (OECD) to coordinate the work in close cooperation with Eurostat and European Central Bank.

Recommendation II.10: International Investment Position (IIP)

The G20 economies to provide quarterly IIP data to the IMF, consistent with the Balance of Payments and International Investment Position Manual, sixth edition, and including the enhancements, such as the currency composition and separate identification of other (nonbank) financial corporations, introduced in that manual. IMF to monitor reporting and the consistency of IIP data, and consider separate identification of nonfinancial corporations, in collaboration with IMF Committee on Balance of Payments Statistics.

Recommendation II.11: International Banking Statistics (IBS)

G20 economies to provide enhanced BIS international banking statistics. BIS to work with all reporting countries to close gaps in the reporting of IBS, to review options for improving the consistency between the consolidated IBS and supervisory data, and to support efforts to make data more widely available.

Recommendation II.12: Coordinated Portfolio Investment Survey

G20 economies to provide, on a semiannual frequency, data for the IMF Coordinated Portfolio Investment Survey, including the sector of holder table and, preferably, also the sector of nonresident issuer table. IMF to monitor the regular reporting and consistency of data, to continue to improve the coverage of significant financial centers, and to investigate the possibility of quarterly reporting.

Recommendation II.13: Coordinated Direct Investment Survey (CDIS)

G20 economies to participate in and improve their reporting of the IMF Coordinated Direct Investment Survey, both inward and outward direct investment. IMF to monitor the progress.

Recommendation II.14: Cross-Border Exposures of Nonbank Corporations

The IAG to improve the consistency and dissemination of data on nonbank corporations’ cross-border exposures, including those through foreign affiliates and intragroup funding, to better analyze the risks and vulnerabilities arising from such exposures including foreign currency mismatches. The work will draw on existing data collections by the BIS and the IMF, and on the development of the OECD framework for foreign direct investment. The G20 economies to support the work of the IAG.

Recommendation II.15: Government Finance Statistics

The G20 economies to disseminate quarterly general government data consistent with the Government Finance Statistics Manual 2014 (GFSM 2014). Adoption of accrual accounting by the G20 economies is encouraged. The IMF to monitor the regular reporting and dissemination of timely, comparable, and high-quality government finance data.

Recommendation II.16: Public Sector Debt Statistics

The G20 economies to provide comprehensive general government debt data with broad instrument coverage to the World Bank/IMF/ OECD Public Sector Debt Database. The World Bank to coordinate the work.

Recommendation II.17: Residential Property Prices

The G20 economies to publish residential property price indices consistent with the Handbook on Residential Property Price Indices and supply these data to the relevant international organizations, including the BIS, Eurostat, and OECD. The IAG in collaboration with the Inter-Secretariat Working Group on Price Statistics to work on a set of common headline residential property price indices; encouraging the production of long time series; developing a list of other housing-related indicators; and disseminating the headline residential property price data via the PGI website.

Recommendation II.18: Commercial Property Prices

The IAG in collaboration with the Inter-Secretariat Working Group on Price Statistics to enhance the methodological guidance on the compilation of Commercial Property Price Indices and encourage dissemination of data on commercial property prices via the BIS website.

Communication of Official Statistics

Recommendation II.19: International Data Cooperation and Communication

The IAG to foster improved international data cooperation among international organizations and support timely standardized transmission of data through internationally agreed formats (for example, Statistical Data and Metadata eXchange) to reduce the burden on reporting economies, and promote outreach to users. The IAG to continue to work with G20 economies to present timely, consistent national data on the PGI website and on the websites of participating international organizations.

Recommendation II.20: Promotion of Data Sharing

The IAG and G20 economies to promote and encourage the exchange of data and metadata among and within G20 economies, and with international agencies, to improve the quality (for example, consistency) of data, and availability for policy use. The G20 economies are also encouraged to increase the sharing and accessibility of granular data, if needed, by revisiting existing confidentiality constraints.

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1

The IAG members are the BIS, European Central Bank, Eurostat, IMF (chair), Organisation for Economic Co-operation and Development, United Nations, and World Bank. The FSB is invited to participate on topics in which it has a direct involvement.

2

Papers from the IMF and Financial Stability Board’s 2009 Users’ Conference on the Financial Crisis and Information Gaps are available at http://www.imf.org/external/np/seminars/eng/2009/usersconf/index.htm.

3

“Declaration Summit on Financial Markets and the World Economy, November 15, 2008.” http://www.un.org/ga/president/63/commission/declarationG20.pdf.

4

The G20 leaders continue to reafrm the importance of this commitment. For instance, at the Antalya summit in November 2015, the leaders stated that “Going forward, we are committed to full and consistent implementation of the global financial regulatory framework in line with the agreed timelines….”

5

A global legal entity identifiers system would uniquely identify parties to financial transactions.

6

The papers contributing to the review, including the overview paper, are available at http://www.imf.org/external/np/spr/triennial/2014/. The TSR involved wide consultation among IMF member countries, academia, and the private sector.

7

Four regional conferences were held, as well as meetings with private sector participants.

8

The Second IMF Statistical Forum was held November 18–19, 2014, at IMF Headquarters in Washington, DC. Proceedings are available at http://www.imf.org/external/np/seminars/eng/2014/statsforum/.

9

The CDMs included the following indicators: (1) minimum, maximum, and mean; (2) weighted standard deviations and skewnesses; and (3) quartiles, and the asset share of the bottom quartile.

10

Maximum values in the case of the nonperforming loan FSIs.

11

The progress on the FSB work on shadow banking is set out in FSB 2015c.

12

The sharing of reports based on G-SIBs’ data with international financial institutions (BIS, FSB, and IMF) under strict confidentiality conditions has been established.

13

The BIS database on international debt securities, which has been developed based on granular information, allowing for the parallel identification of the residency and nationality of debt securities issuers, is an example of a security-by-security database constructed at the international level.

14

In addition, government finance statistics are not always consistent with the relevant data in the national accounts despite the harmonization of international standards across statistical domains.

15

The BIS has published a dataset on credit to the general government sector for 26 advanced and 14 emerging market economies (Dembier-mont and others 2015).

16

The Committee on Global Financial System is the BIS committee of central banks overseeing the collection of the IBS statistics.

17

See Handbook on Residential Property Prices Indices (European Union and others 2013), which was jointly supported by Eurostat and the International Labour Organization, IMF, OECD, UN, and World Bank.

18

Currently, 29 IMF member countries are subject to mandatory financial stability assessments, while for the rest of the membership the “FSAP” is voluntary.

19

Micro, granular data sources can also enhance the accuracy and level of details of “traditional” macro statistics. See Tissot 2015.

20

The report focused on disclosures in risk governance and risk management, capital adequacy and liquidity, funding, market risk, credit risk and other risks. See FSB 2012.

21

The IMF Direction of Trade data can be used to analyze cross-border trade linkages.

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