Transcript in monetary and financial statistics

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
Rubric
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
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Rubric
MFS - Quality assurance procedures (1)
ECB-PUBLIC
• 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
Implementing ‘quality assurance procedures’ in monetary and
financial statistics
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Rubric
MFS - Quality assurance procedures (2)
Main MFS statistical products
Main quality elements
Monetary financial institutions balance sheet
statistics
•
•
Monetary financial institutions interest rate
statistics
•
List of monetary financial institutions (MFIs)
Securities issues statistics
•
Payments and securities settlement systems
statistics
•
•
Investment funds balance sheet statistics
•
•
List of investment funds (IFs)
Financial vehicle corporations (FVCs) balance
sheet statistics
Legal basis (Regulation or Guideline)
Data collection (by NCBs from reporting
agents) and coverage (full, modified census or
stratification)
Methodological sources (compliance with int.
statistical standards)
Reporting periodicity and transmission
deadlines
Revision policy
Data quality management (quality checks,
time series analysis, etc.)
Compliance monitoring (~ to legal instrument)
Dissemination (advance release calendar,
press release, availability on the ECB’s
Statistical Data Warehouse and on the ECB’s
website, etc.)
 MFS ‘hotline’ providing assistance to users on
all statistical products.
List of financial vehicle corporations (FVCs)
Implementing ‘quality assurance procedures’ in monetary and
financial statistics
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Rubric
Example 1. Enhancing MFS methodological soundness
ECB-PUBLIC
• 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
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financial statistics
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Rubric
Example 2. Revision analysis (1)
ECB-PUBLIC
• 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
Implementing ‘quality assurance procedures’ in monetary and
financial statistics
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Rubric
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 month-on-month
growth rates of M3 to better
identify the timing of a given
revision
Revisions to the components of M3
at lag t+3 to understand the
largest contributions to the
overall M3 revisions
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Rubric
Example 3. “Top-down” analysis for balance sheet data (1)
ECB-PUBLIC
• 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
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Rubric
Example 3. “Top-down” analysis for balance sheet data (2)
ECB-PUBLIC
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
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Example 3. “Top-down” analysis for balance sheet data (3)
ECB-PUBLIC
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
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financial statistics
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Rubric
Example 3. “Top-down” analysis for balance sheet data (4)
Implementing ‘quality assurance procedures’ in monetary and
financial statistics
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Foreseen initiatives for 2014-2015
ECB-PUBLIC
Several work-streams are in the pipeline to
(1) increase MFS availability, and
(2) enhance the input to other statistical domains
• A new Regulation on assets and liabilities of Insurance Corporations
• A new Regulation on high frequency data 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
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Implementing ‘quality assurance procedures’ in monetary and
financial statistics
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