Robert Obrzut, Eurostat,

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Presentation transcript:

Robert Obrzut, Eurostat, robert.obrzut@ec.europa.eu Why consistency matters – The impact of the consistency debate on increased accuracy and coordination within the national accounts and between national accounts and balance of payments statistics of the EU Robert Obrzut, Eurostat, robert.obrzut@ec.europa.eu 29 June 2018 Session 10

Contents Why consistency matters – motivational introduction Dimensions and concepts Data evidence – external and internal aspects Causes for inconsistencies (Eurostat survey) Determining the critical threshold Major obstacles and outlook

Contradictory balances in the main items Non-financial Component a/c BOP balance ROW balance Germany Capital account +3.5 -1.1 France (2017) Services +17.9 -14.6 Poland Secondary income -1.4 +2.5 FA transactions BOP assets ROW liabilities BOP liabilities ROW assets Denmark +23.3 -0.7 Finland +21.7 -6.1 Sweden +8.4 -91.0 +24.2 -90.1 FA stocks IIP net assets ROW net liabilities Luxembourg +22.0 -50.0 Balances in bill. €, by concerned Member State, 2016, Apr. 2018 (billion EUR)

The integrated nature of the accounts Methodological standards BPM6 and ESA2010/SNA2008 Fully integrated concept – full comparability (Theoretically) no methodological differences Statistical domains (non-financial & financial) Sector accounts, incl. ROW BOP NA main aggregates Government finance statistics (GFS) Data evidence External aspect: BOP-ROW Internal aspect: Sector accounts – main aggregates/GFS

Dimensions of consistency in the accounts Main/balancing items GDP, B9, B9F Sector accounts "anchor"

Prominence of external and internal aspects ASA – Annual sector accounts; ANA – Annual National accounts (main aggregates); GFS – government finance statistics; Oct. 2017 (million EUR)

External aspect: BOP-ROW discrepancies Non-financial accounts – 14 MS consistent Mean absolute percentage deviation (B9), by country, 2014-2016, Apr. 2018

External aspect: BOP-ROW discrepancies Component exposure in the non-financial a/c Absolute discrepancies, non-financial accounts, sum of EU-28, 2010-2017, Apr. 2018 (million EUR)

Internal aspect: cross-domain discrepancies in NA Sector accounts – main aggregates and GFS Mean absolute differences, by country, 2010-2016, Oct. 2017 (million EUR)

Causes for inconsistent accounts Eurostat compiler surveys 2015 and 2017 Analysing BOP-ROW inconsistencies in the non-financial accounts Main causes Revision and vintage effects Methodological differences Organisational & management aspects Sequential versus twinning processes Integrated accounts versus autonomous production systems (cost of coordination)

Determining the critical threshold Identity of data sets versus tolerance bands (? in % of GDP) Mechanistic approach to NA cross-domain inconsistencies Sensitivity analysis for GDP and B9 0% - max. 21 MS concerned (B9); 1% - max. 12 MS concerned (B9) 0.3% threshold chosen Emphasising integrated data models and harmonised production & revision calendars Risk of diverging publication practices inf Eurostat and country statistics Organic approach to BOP-ROW inconsistencies Methodological differences Different revision practices Different institutional frameworks

Conclusions Obstacles Institutional autonomies (historically grown) Resource restrictions on human/IT capacities Need for flexibility in adjustment practices Confidentiality of micro data Practical ways forward Based on identified causes rather than symptoms Increasing data standardisation Securities reference databases from micro data (CSDB) Standardised enterprise identifiers (LEI) Mirror data comparisons (intl. services, FDI network) Interinstitutional technical cooperation

Why consistency matters Thank you very much / Dziękuję bardzo Robert Obrzut, Eurostat, robert.obrzut@ec.europa.eu