Peter van de Ven Head of National Accounts , OECD

1. Balance sheets data according to national accounts: present and future availability, use and abuse Peter van de Ven Head of National Accounts, OECD Strategic Forum Rome, September 22 – 23, 2014

2. On Statistics … • “There are three kinds of lies: lies, damned lies, and statistics” (Benjamin Disraeli)

3. On Statistics … • “There are three kinds of lies: lies, damned lies, and statistics” (Benjamin Disraeli) • “An unsophisticated forecaster uses statistics as a drunken man uses lamp-posts - for support rather than for illumination” (Andrew Lang)

4. Introduction • General overview of availability of balance sheets data • G20 Data Gaps Initiative • Implementation issues • Indicators: use and abuse • Accounting for vulnerabilities and economic sustainability • Going forward: what more do we need? Plea for implementing system of agreed balance sheets, and making full and “appropriate” use of the data

5. Present availability • International standards for national accounts (SNA 2008 and ESA 2010) lay out a full and consistent framework for balance sheets, including transactions • Lot of information is actually already available, first and foremost in relation to quarterly and annual information on financial transactions and positions • Especially in EU, quite some progress has been made in developing quarterly data (nowadays available 90 – 120 days after the end of the quarter) • Also in other OECD-countries

6. G20 Data Gaps Initiative • Economic and financial crisis showed some gaps in the compilation and publication of statistical data, especially in relation to risks and vulnerabilities • In 2009, a set of recommendations has been put forward to address the main data gaps, the so-called G20 Data Gaps Initiative (DGI): • Better capture the build-up of risk in the financial sector • Improve data on international financial network connections • Monitor the vulnerability of domestic economies to shocks • Improve the communication of official statistics 

7. G20 Data Gaps Initiative • Core recommendation from macro-economic perspective: recommendation 15 on institutional sector accounts:“…to develop a strategy to promote the compilation and dissemination of the balance-sheet approach (BSA), flow-of-funds, and sectoral data more generally, starting with the G-20 economies. Data on nonbank financial institutions should be a particular priority. The experience of the ECB and Eurostat within Europe and the OECD should be drawn upon” • Templates for collection of balance sheet data, driven by the example of EU and other OECD-countries, also part of SDDS Plus requirements of IMF

8. Sector details, quarterly

9. Instrument details, quarterly (1/2)

10. Instrument details, quarterly (2/2)

11. Non-financial assets, annually

12. Implementation issues • Measurement of non-financial assets, especially non-produced, non-financial assets (land, natural resources, etc.) • Not all types of risks and vulnerabilities can be captured with agreed templates, e.g. interconnectedness => “from-whom-to-whom” tables or “flow of funds” • Only available in developed countries, not always on a quarterly basis • However, economic and financial crisis has created a momentum for further development • Other (conceptual) issues => later

13. Indicators: use and abuse • From the framework, various indicators can be derived: • Debt to income ratios • Debt to assets ratios • Etc. • Which indicators are the most appropriate? • Example: General Government Gross Debt

14. A Simple Comparison A reasonably sophisticated user has taken a look at various sources: • Eurostat, Tables on Government Finance • IMF, Government Finance Statistics (market value and face value) • IMF, World Economic Outlook • OECD, National Accounts at a Glance • OECD, Economic Outlook

15. Government Debt 2010 Differences between highest and lowest result, in %-points of GDP

16. Coverage of instruments • General definition of gross debt: a specific subset of liabilities … that require payment or payments of interest or principal by the debtor to the creditor at a date or dates in the future (22.104). • All liabilities except shares, equity and financial derivatives • Monetary gold and SDRs • Currency and deposits • Debt securities • Loans • Insurance, pension and standardized guarantee schemes • Other accounts payable

17. Coverage of instruments • However, several other definitions are being used • Maastricht debt: • Currency and deposits • Debt securities • Loans • Sometimes only loans and debt securities are covered • Most substantial impact: pension liabilities

18. Valuation and consolidation • Different valuation concepts: • Market prices (according to SNA) • Nominal value (e.g. Maastricht definition) • Face value • Consolidated versus non-consolidated data • Other differences: differences in sources, lack of alignment to international standards, sometimes even differences due to reporting agency

19. Impact of Excessive Deficit Procedure • Improvement of data according to agreed definition • Inclination to prefer being “exactly wrong” instead of “approximately right” • Focus on single indicators drives poor policy: • Gross Debt and Investments • Pension reforms • Creative accounting: impact on numbers more important than economic rationale (PPPs, sale and lease back constructions, taking over pension liabilities of public corporations) • Single indicators are, almost by definition, a simplification of economic reality

20. Going beyond • Need to account for pension liabilities and contingent liabilities • Need for additional indicators on Net Government Debt => various definitions proposed: • Including liquid assets only • Including similar instruments as the ones on the liabilities side • Including all financial assets (including shares and other equity) • Including financial assets as well as non-financial assets => net worth => also raises the question of which expenditures to be considered as investments • Finally, need for more “story-telling” on the interpretation of government debt data (e.g. the impact of differences in pension arrangements across countries)

21. Accounting for vulnerabilities and economic sustainability • Various forms of vulnerabilities or risks: • Liquidity risk: gross debt to income (after adjusting for liquid assets) • Solvency risk: gross debt to assets • Risk exposures to certain sectors/countries: need for “from-whom-to-whom” tables • Maturity risk, currency risk, etc.: need for more detailed breakdowns • Generally, quite detailed data needed, and some risks may be covered (or actually hidden) • In addition, macro-data may hide risks for certain groups • Question: where to go?

22. Accounting for vulnerabilities and economic sustainability The importance of looking at wealth distribution • Analysing wealth distribution is essential for analysis of vulnerabilities in the household sector Debt to income ratio of indebted households Sources: EFF 2002 (Spain), SCF 2001 (US), SHIW 2002 (Italy), BHPS 2000 (UK)

23. Accounting for vulnerabilities and economic sustainability • Balance sheets are a snapshot of the wealth at a certain moment in time • As such, they may not reflect economic sustainability to the full extent: • Weak versus strong sustainability • Does not say anything about future income generating potential (e.g. debate on ageing society and pension liabilities) • On the other hand, changes in balance sheet positions do provide a sense of sustainability or direction where things are going

24. Going forward: what more do we need? • Better accounting for non-financial assets • Eurostat/OECD Task Force on Measuring Other Non-financial Assets => Guidance on Land • Natural resources (subsoil assets) • Residential and commercial property price indices • Implementation! • Knowledge capital? • Already included: (i) mineral exploration; (ii) software and databases; (iii) entertainment, literary and artistic originals; and (iv) R&D • Human capital?

25. Going forward: what more do we need? • Full accounting for pension entitlements • Supplementary table (2017 in EU) • Accounting for contingent liabilities • Need for much more distributional information • Can we capture risks and vulnerabilities to the full extent? • More generally: which data needs are most prominent?

26. Thank you for your attention!