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Implementing ‘quality assurance procedures’ in monetary and financial statistics (MFS)

ECB-PUBLIC. Violetta Damia Jean-Marc Israël European Central Bank Directorate General Statistics Monetary and Financial statistics Division. Implementing ‘quality assurance procedures’ in monetary and financial statistics (MFS). Q2014 - European conference on quality in statistics

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Implementing ‘quality assurance procedures’ in monetary and financial statistics (MFS)

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  1. ECB-PUBLIC Violetta Damia Jean-Marc Israël European Central Bank Directorate General Statistics Monetary and Financial statistics Division Implementing ‘quality assurance procedures’ in monetary and financial statistics (MFS) Q2014 - European conference on quality in statistics Vienna, 3 June 2014

  2. ECB-PUBLIC [Please select] Overview 1 MFS - Quality assurance procedures 2 Example 1. Enhancing MFS methodological soundness 3 Example 2. Revision analysis 4 Example 3. “Top-down” analysis for balance sheet data 5 Foreseen initiatives for 2014-2015 Implementing ‘quality assurance procedures’ in monetary and financial statistics

  3. Input: data collected from reporting agents by the NCBs and reported to the ECB • methodologically sound data • in line with internationally accepted standards and classifications • ECB regulations & Guidelines set common harmonised standards • according to a fixed and agreed timetable Throughput: several quality checks on the national contributions received • completeness, internal and intra-period consistency • external consistency • Revision studies • Plausibility checks Output: data accessibility & dissemination policy • press releases • ECB Statistical Data Warehouse and on the ECB’s website MFS - Quality assurance procedures (1) ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  4. MFS - Quality assurance procedures (2) ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  5. Development of MFS ~ meeting user requirements & in line with international statistical standards – also input to other stat. domains Until recently, several deviations with international statistical standards • reporting units and sectors, counterpart sectors or sub-sectors, financial instruments, etc. • other specific issues, e.g. the valuation principles applied, the treatment of accrued interest, and the treatment of non-performing loans. Additional requirements from users • substantial amendment of five ECB Regulations and Guideline on MFS (ECB/2014/15) Regulations ECB/2013/33 on MFI balance sheet statistics, ECB/2013/34 on MFI interest rate statistics, ECB/2013/39 on Post Office Giro Institutions, ECB/2013/38 on Investment Funds and ECB/2013/40 on Financial Vehicle Corporations  1st reporting in in Jan. 2015 with data for Dec. 2014 – publication in mid-2015 Example 1. Enhancing MFS methodological soundness ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  6. To evaluate the reliability of first releases Special features • data can be revised at any release • “ordinary revisions” vs. “exceptional” revisions (the latter related to to reclassifications and improved reporting procedures) Revisions of the monthly monetary aggregates and components  differences between the revised period-on-period growth rates at a pre-determined lag and the first release  estimation of bias Example 2. Revision analysis (1) ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  7. Revisions to the month-on-month growth rates of M3 to better identify the timing of a given revision Example 2. Revision analysis (2) ECB-PUBLIC Figure 2: Revision of M3 growth rate (2013) (No of occurrences (Y-axis), hundredths of a percentage point (Y-axis)) Revisions to the components of M3 at lag t+3 to understand the largest contributions to the overall M3 revisions Implementing ‘quality assurance procedures’ in monetary and financial statistics

  8. Traditionally, a “bottom-up approach” is followed for consistency and plausibility of aggregated series  focus on raw series • vertical checks (TRUE/FALSE type of check) • horizontal checks (based on statistical significance) if developments are correct in raw series, they must be correct in derived aggregates New “top-down approach” for analysis and identification of possible special developments  focus on aggregated series decomposition of the aggregate into its main underlying components and identification of the raw series responsible of the development Example 3. “Top-down” analysis for balance sheet data (1) ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  9. 2-steps procedure Step 1: run horizontal checks on selected aggregate series • better statistical modelling of aggregates • special development in raw series usually matters when impact on aggregate is significant • MFI balance sheet statistics: run checks on country consolidated balance sheet Step 2: Decompose the special development into components • reverse engineer the set of raw series responsible for development • ECB aggregation framework allows for identification of series dependencies in the aggregation tree • User defined threshold, user friendly graphical output Example 3. “Top-down” analysis for balance sheet data (2) ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  10. Advantages: • significantly reduce the number of processed series • answers to typical questions such as “is development widespread?; “which are the sectors responsible for it?”, etc • combine checking for outliers with economic interpretation • Step 2 can also be used independently of horizontal checks Example 3. “Top-down” analysis for balance sheet data (3) ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  11. Example 3. “Top-down” analysis for balance sheet data (4) ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  12. Several work-streams are in the pipeline to increase MFS availability, and enhance the input to other statistical domains A new Regulation on assets and liabilities of Insurance Corporations A new Regulation on high frequencydata on money market activity (MMSRR) The development of an “Analytical Credit dataset” (AnaCredit) across the ESCB the provision of necessary data for the ECB’s financial stability analysis of the euro area and to cover the European Systemic Risk Board (ESRB) needs Foreseen initiatives for 2014-2015 ECB-PUBLIC Implementing ‘quality assurance procedures’ in monetary and financial statistics

  13. ECB-PUBLIC Thank you very much for your attention! Implementing ‘quality assurance procedures’ in monetary and financial statistics

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