Unclassified COM/STD/DAF(2016)22 COM/STD/DAF(2016)22 Unclassified Organisation de Coopération et de Développement Économiques Organisation for Economic Co-operation and Development 08-Nov-2016 English - Or. English Directorate for Financial and Enterprise Affairs Statistics Directorate Working Party on Financial Statistics TAILORING NATIONAL FINANCIAL ACCOUNTS TO THE USER S NEEDS USING ADMINISTRATIVE AND LARGE GRANULAR DATASETS JOINT MEETING To be held on 25-27 October 2016 OECD Conference Centre Beginning at 2:00 pm on the first day This document has been prepared by Filipa Lima - Banco de Portugal and will be presented under item 23 of the draft agenda The complete document is only available in PDF format English - Or. English JT03404784 Complete document available on OLIS in its original format This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.
COM/STD/DAF(2016)22 2
Tailoring national financial accounts to the user s needs using administrative and large granular datasets Filipa Lima Deputy Head Statistics Department, Banco de Portugal Joint Meeting of the WPFS/WPNA Paris, 24-28 October 2016
Outline I. Introduction II. III. IV. The use of administrative and large granular databases by BdP A tailored approach to national financial accounts Some applications to national accounts V. Final remarks 2 OECD, Joint Meeting of the WPFS/WPNA, October 2016
I. Introduction The aftermath of the financial crises characterised by different and new data needs - More detailed and with faster availability Banco de Portugal experience with the financial crises and the Financial Assistance Programme (2011 2014): - Make extensive use of administrative and large granular databases Tailor national financial accounts (NFA) to users needs, allowing to see the details without losing sight of the big picture 3 OECD, Joint Meeting of the WPFS/WPNA, October 2016
II. The use of administrative and large granular databases Main large granular databases used by the BdP Statistics Department Central Credit Register (CCR) Central Balance-Sheet Database (CBSD) Securities Statistics Integrated System (SSIS) Balance of Payments (BoP) / other 4 OECD, Joint Meeting of the WPFS/WPNA, October 2016
II. The use of administrative and large granular databases Central Credit Register 5 OECD, Joint Meeting of the WPFS/WPNA, October 2016
II. The use of administrative and large granular databases Central Balance Sheet Database IES Informação Empresarial Simplificada (Simplified Business Information) A successful institutional cooperation (2007) Annual report of almost 100% of corporations Format: totally automatic Timeliness: 6.5 months Level of detail: + 3 000 items 6 OECD, Joint Meeting of the WPFS/WPNA, October 2016
Securities Statistics Integrated System II. The use of administrative and large granular databases Flows and stocks (monthly) Own portfolios (ISIN code) SSIS Securityby-security Investorby-investor Equity and debt securities Custodians 7 OECD, Joint Meeting of the WPFS/WPNA, October 2016
II. The use of administrative and large granular databases Balance of Payments / other Banks own operations clients operations* * without statistical classification own operations Companies other sources (e.g. payments data) 8 OECD, Joint Meeting of the WPFS/WPNA, October 2016
II. The use of administrative and large granular databases National financial accounts: financial assets and liabilities, by sector and financial instrument GOAL SSIS CCR SSIS FEASIBLE Currency and deposits Securities Loans Shares and other equity Insurance technical reserves NFC FC GG HH+NPISH RoW A L A L A L A L A L Other accounts CBSD BSI FEASIBLE BOP/IIP 9 OECD, Joint Meeting of the WPFS/WPNA, October 2016
III. A tailored approach to national financial accounts a) Non-financial sector indebtedness Monthly data @ T+45 days New chapter to the Statistical Bulletin Securities (SSIS) CBSD Statistical databases External operations (BoP / IIP) Domestic loans (CCR) Firm size and activity sector (NACE) Debt new dimensions of analysis Private vs. state-owned Type of instrument Loans Debt securities Trade credits By creditor 10 OECD, Joint Meeting of the WPFS/WPNA, October 2016
III. A tailored approach to national financial accounts a) Non-financial sector indebtedness Breakdown by creditor Dec-07 Dec-15 10% 19% 12% General Government External financing 66% 4% 9% 54% 6% 20% 2% 29% 34% 36% Public corporations External financing GG financing 63% 14% 1% 8% 5% 22% 25% 1% 4% Private companies Banks financing External financing 30% 50% 6% 27% 43% 11 OECD, Joint Meeting of the WPFS/WPNA, October 2016
III. A tailored approach to national financial accounts b) Flow of funds 2011 2014 Financial Assistance Programme to Portugal 2011 FC Decrease of financing needs HH NFC Net funds channelled from rest of the world to general government Financial sector deleveraging Net flows from the financial sector to rest of the world intensify deleveraging intensified, Eurosystem funding lost momentum HH FC 2012 NFC GG RoW Private sector reduces financing needs Households: lower consumption NFC: sharp contraction of investment GG RoW FC 2014 Rest of the world shifts from net lender to net borrower Mirrored in current account surplus from 2012 onwards HH NFC 12 OECD, Joint Meeting of the WPFS/WPNA, October 2016 GG RoW
2001 Jan 2001 Jul 2002 Jan 2002 Jul 2003 Jan 2003 Jul 2004 Jan 2004 Jul 2005 Jan 2005 Jul 2006 Jan 2006 Jul 2007 Jan 2007 Jul 2008 Jan 2008 Jul 2009 Jan 2009 Jul 2010 Jan 2010 Jul 2011 Jan 2011 Jul 2012 Jan 2012 Jul 2013 Jan 2013 Jul 2014 Jan 2014 Jul 2015 Jan 2015 Jul 2016 Jan Value (millions of Euro) 2002 Mar 2002 Set 2003 Mar 2003 Set 2004 Mar 2004 Set 2005 Mar 2005 Set 2006 Mar 2006 Set 2007 Mar 2007 Set 2008 Mar 2008 Set 2009 Mar 2009 Set 2010 Mar 2010 Set 2011 Mar 2011 Set 2012 Mar 2012 Set 2013 Mar 2013 Set 2014 Mar 2014 Set 2015 Mar 2015 Set 2016 Mar IV. Some applications to national accounts 25% 20% 15% 10% 5% 0% -5% -10% Nondurable private consumption vs. ATM/POS data (y-oy growth rates) Non-durable goods and services ATM/POS 1800 1600 1400 1200 1000 800 600 400 200 0 Travel (BoP) and the use of cards issued abroad (in Portugal) 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% MA(12) 13 Withdrawals and purchases with cards issued abroad (A) "Travel" BoP (B) MA(12) of (A)/(B)
IV. Final remarks Key Success Factors Metadata Links across domains Governance model Mix of flexible solutions Common IT platform 14 OECD, Joint Meeting of the WPFS/WPNA, October 2016
IV. Final remarks Weaknesses and Threatens of large granular datasets More demanding in terms of IT Human resources Data management more demanding microdatabase trap : the risk to drown in detailed data and lose focus of the macro perspective 15 OECD, Joint Meeting of the WPFS/WPNA, October 2016
Thank you for your attention! Questions? Filipa Lima slima@bportugal.pt 16 OECD, Joint Meeting of the WPFS/WPNA, October 2016