1. DANMARKS NATIONALBANK Presentation of Danish quarterly financial accounts

2. Agenda 1.Introduction / Tue 2.Compilation system, sources and data gaps / Martin 3.Internal use of financial accounts a.Usage in Systemic Risk Council / Martin b.Usage in Economics Department / Paul 4.Other items?

3. The National Bank of Denmark Act (1936) § 1. ”Danmarks Nationalbank […] shall as the Central Bank of this country […] maintain a safe and secure currency system in this country, and facilitate and regulate the traffic of money and the extension of credit.” § 14a. ”The Bank collects, compile and disseminates statistical information within its competence and is allowed to use this information when necessary in order for the Bank’s fulfillment of its tasks.” § 14a, cont. ”The Bank can request that individuals [red.] pass on information they posses to the Bank […] if it is necessary for the Bank to receive the information for the fulfillment of its tasks [see §1].”

4. Stable financial system Safe payments Stable prices / exchange rates Nationalbankens main targets

5. Organisation

6. Statistics Department

7. Overview of financial statistics produced by Danmarks Nationalbank Financial Statistics in Danmarks Nationalbank

8. Agenda 1.Introduction / Tue 2.Compilation system, sources and data gaps / Martin 3.Internal use of financial accounts a.Usage in Systemic Risk Council / Martin b.Usage in Economics Department / Paul 4.Other items?

9. Danish quarterly financial accounts Quarterly statistic on all sectorial balance sheets and financial flows. Publish data and press release with a highlighted development. Relevant for financial and conjunctural analysis of Danish economy. Quarterly release, 4th quarter 2012: Non-financial companies’ transactions

10. Dimensions of financial accounts Sectors: Non-financial companies (S.1100) Danmarks Nationalbank (S.1210) Other monetary financial institutions (S.1220) Other financial intermediaries (S.1230) Financial auxiliaries (S.1240) Insurance corporations and pension funds (S.1250) General government (S.1300) Households and NPISH (S.1415) Rest of the world (S.2000) Instruments: Monetary gold and SDR (AF.1) Currency and deposits (AF.2): Currency (AF.21) Transferable deposits (AF.22) Other deposits (AF.29) Securities other than shares (AF.3): Short-term securities other than shares (AF.31) Long-term securities other than shares (AF.32) Financial derivatives (AF.34) Loans (F.4): Short-term loans (AF.41) Long-term loans (AF.42) shares and other equities (AF.5): Quoted shares (AF.511) Unquoted shares (AF.512) Other equity (AF.513) Mutual fund shares (AF.52) Insurance technical reserves (AF.6): Net equity of households in life insurance reserves (AF.611) Net equity of households in pension funds reserves (AF.612) Pprepayments of insurance premiums and reserves for outstanding claims (AF.62) Other accounts receivables/payable (AF.7) Trade credits and advances (AF.71) Other accounts receivalbe/payable, excl. trade credits (AF.79) Accounts: Stock (AF) Transactions (FT) Revaluations (RE) Other volume changes (OVC)

11. Example: Other MFIs short-term loans to non- financial companies ACCOUNT ASSET SECTOR LIABILITY SECTOR INSTRUMENTQUARTER AFFTREOVC S.1220 S.1100AF.412012Q1 243900 2012Q2 2531000 2012Q3 237-1600

12. A world of counterparties Our system compiles sectorial accounts at detailed ”counter party”-level. Our ”cube” must not have empty cells (almost). Ensures ”horizontal” consistency: ∑ assets = ∑ liabilities).

13. Compilation from primary sources MFI BOP/IIP IF SEC FA Financial accounts receives ”partial” cubes from primary statistics. All primary statistics’ cubes are combined to fill out empty cells. Ensures overall consistency between all financial statistics. Different data for one cell leads to reconciliation between sources.

14. Dataflow in compilation system SOURCE DATA RECONCILIATED DATA PUBDB ECB, etc. PUBDB Pivot tables for analysis Publica tion MFI IF BOP/IIP SEC ICPF Other financial intermediaries etc. (yearly company accounts) Government financial statistics (GFS)

15. Financial accounts in a National accounts perspective Non-financial Net lending/ net borrowing Financial Domestic sectors, S.1For., S.2 BOP MFI Securities IIP BOP/SEC/MFI (property inc.) SEC/MFI (interest income) Accounts, Financial auth., other sources Statistical discrepancies Ensures ”vertical” consistency

16. To sum up: Compilation 1.The different sources are prioritised for each instrument and sector on a sector-by-sector level (SAS programming). 2.Correction of flows so that the identity is satisfied: Ultimo = Primo + Transactions + Revaluation + Other changes 3.Correction to net-lending in the non-financial accounts (compiled by Statistics Denmark) 4.Data analysis and validation Primary tool: Balancing matrix for checking consistency across primary statistics (Excel VBA tools)

17. The Danish business register: Common grounds Common Danish business register administered by Statistics Denmark. Danmarks Nationalbank has active part in sectorization of financial companies. Ensures consistent sectorization in all financial- and non-financial statistics: NA, FA, SEC, MFI, IF, BOP/IIP, etc…

18. Data gap: Loans between non-financial corporations In the financial accounts cube, data is unconsolidated. Fx interbank lending increase both assets and liabilities of other MFIs. Loans between non-financial corporations was missing. Data not included in any primary source statistic. Liabilities of NFCs excl. equity (old)

19. Data gap, cont. Estimate data on best effort basis. 1.Aggregate all loans in yearly accounts of all non-financial companies. 2.Subtract allready known loans from other sectors. 3.Residual = intercompany loans. 4.Linear interpolation for quarterly data. Uncertain estimate increased private sector debt by 27 pct. of GDP! Liabilities of NFCs excl. equity (new)

20. Analytical improvements: Disaggregation of accounts Disaggregation of households and non-financial corporations at the institutional units (that is, individual household and enterprises). Distributional information necessary for structural wealth analysis. Most micro data is administrative registers with tax information collected directly from banks, employers, etc. Also, we collect detailed loan-by-loan information from mortgage banks.

21. Analytical improvements, cont. Total household sector debt-ratio by country and year, 2010 Note: For Germany 2010: The data refer to 2009. For Norway 1980: The data refer to 1987. Source: Isaksen et. al. (2011): Household balance sheets and debt – an international country study, Danmarks Nationalbank, Monetary Review, 4th quarter, Part 2.

22. Distribution of assets across gross debt intervals, 2010 Analytical improvements, cont. Total assets excl. pensionPension wealth

23. Analytical improvements, cont. Micro data covers most parts of aggregate financial accounts. However, some parts of financial accounts not properly covered by micro data. Ongoing work on detailed micro data from life insurance corporations and pension funds. Comparing household micro- and macro data

24. Agenda 1.Introduction / Tue 2.Compilation system, sources and data gaps / Martin 3.Internal use of financial accounts a.Usage in Systemic Risk Council / Martin b.Usage in Economics Department / Paul 4.Other items?

25. Usage in Systemic Risk Council Newly created Systemic Risk Council to prevent and reduce systemic risk in the financial system. The council affects policy through its recommendations and warnings. The councils chairman is our governor, Lars Rohde, and its secretariat is situated in Danmarks Nationalbank. Financial accounts are used in the secretariat material.

26. Net lending/borrowing position by sector Note: GDP is calculated as four-quarters rolling sum. Source: Danmarks Nationalbank and Statistics Denmark. Development in net lending/borrowing position

27. Other financial intermediaries by branches Note: GDP is calculated as four-quarters rolling sum. Source: Danmarks Nationalbank and Statistics Denmark. Development of other financial intermediaires

28. Total balance sheets of non-financial corporations by instruments Note: GDP is calculated as four-quarters rolling sum. Source: Danmarks Nationalbank and Statistics Denmark. Development of non-financial corporations

29. Agenda 1.Introduction / Tue 2.Compilation system, sources and data gaps / Martin 3.Internal use of financial accounts a.Usage in Systemic Risk Council / Martin b.Usage in Economics Department / Paul 4.Other items?

30. Agenda 1.Introduction / Tue 2.Compilation system, sources and data gaps / Martin 3.Internal use of financial accounts a.Usage in Systemic Risk Council / Martin b.Usage in Economics Department / Paul 4.Other items?

31. Overview A few examples on how we use the financial accounts Development in net lending Credit conditions Financial conditions of the private sector (mainly households and NFC), used as input in our quarterly forecast exercise (separate handout) Financial accounts in our macro-model (to be implemented) Wealth (balance) of the various sectors (households, non-financial, financial, public and abroad) Consumption

32. Sectoral savings surpluses

33. Change in net lending of NFC since 2008 Source: Statistics Denmark Note: Per cent of GDP in 2012

34. Accumulated transactions of NFC since 2008 Source: Statistics Denmark and Danmarks Nationalbank Note: Per cent of GDP in 2012

35. Credit to non-financial firms

36. Financial accounts in our macro-model Five sectors: households, NFC, FC, public, abroad Still working on which instruments (equity, securities other than shares, pensions, other instruments). Both assets and liabilities.

37. Households: consumption function Household wealth Wealth effects in our model for private consumption, but different wealth effects on different assets classes (equity, pension, housing and other).

38. Other sectors Financial position of other sectors (NFC, FC, public, abroad) To be implemented. Equations for stock, flows and re-valuations for each instrument and each sector. For the system to work, we need who-to-who information.