ECB欧洲央行-ESS---ESCB-quality-assessment-report-on-statistics-underlying-the-Macroeconomic-Imbalance-Procedure-_annual-report-for-2018__34页_548kb

ESS-ESCB Quality Assessment Report on MIP Statistics (2019)

I. Executive Summary

The Macroeconomic Imbalance Procedure (MIP) is a key component of the European Semester, providing a framework for coordinated economic policy across the EU. The European Statistical System (ESS) and the European System of Central Banks (ESCB), particularly Eurostat and the European Central Bank (ECB), are responsible for producing the macroeconomic and financial statistics underpinning the MIP. These statistics are essential for identifying imbalances and monitoring progress in Member States.

This report evaluates the quality, coverage, comparability, and timeliness of the statistics used in the MIP. It highlights the importance of statistical quality assurance and the Memorandum of Understanding (MoU) between Eurostat and the ECB to ensure data consistency and reliability. The report concludes that the statistics are generally of sufficient quality to support effective macroeconomic surveillance, but there are areas for improvement.

II. General Considerations on Statistical Quality

II.1 Macroeconomic Statistics - Core of MIP Indicators

• MIP indicators are based on macroeconomic and financial statistics from the ESS and ESCB.
• These statistics are derived from EU legislation and are used for economic and monetary policy decisions.
• The ESS and ESCB ensure comparability, accuracy, and reliability across EU Member States.
• The quality of the underlying data is crucial for the effectiveness of MIP.

II.2 European Law and Quality Assurance

• EU legislation includes quality assurance frameworks for macroeconomic statistics.
• The ESS-ESCB quality framework is structured into three levels:
  1. Level 1 (this report): Focuses on communication of quality issues to policymakers.
  2. Level 2: Domain-specific quality reports by Eurostat and ECB.
  3. Level 3: National self-assessments of statistical quality.
• Legal basis and international standards are central to ensuring data quality.

II.3 High Quality and Cost-Effective Statistics

• The ESS and ESCB aim to produce fit for purpose statistics in a cost-effective manner.
• A balance between timeliness and detail is essential.
• Revisions are a normal part of the process to improve data accuracy and reliability.
• Collection methods (surveys, administrative data, estimation) affect data quality.
• Human and financial resources are key to ensuring accurate data checks and processing.

III. Main Observations

III.1 GDP Statistics

• GDP is a core indicator for MIP, and its quality is critical.
• The ESA 2010 methodology ensures international consistency and comparability.
• Reservations exist for several countries, including:
  • Croatia: Two specific reservations.
  • Bulgaria: One specific reservation.
  • Greece: Five specific reservations.
  • France: One general reservation.
• Revisions in 2018 were mainly due to ESA 2010 and BPM6 improvements.
• Benchmarking revisions were implemented in some countries, such as Croatia, to improve data accuracy.

III.2 Balance of Payments (BoP) and International Investment Position (IIP)

• BoP and IIP statistics are compiled under BPM6.
• Asymmetries in bilateral flows and stocks remain a challenge.
• Confidentiality is a major obstacle to resolving these issues.
• SPEs (Special Purpose Entities) coverage is still inadequate in some countries.
• Discrepancies between BoP/IIP and the "Rest of the World" sector in financial accounts are significant in countries like France, Sweden, Netherlands, and Ireland.

III.3 Nominal Unit Labour Cost (NULC)

• NULC data are robust and harmonised across the EU.
• However, time series breaks and conceptual differences (e.g., national vs. domestic concept) persist in some countries.
• Ireland, Poland, and Romania flagged breaks in time series in 2018.
• Croatia still uses the national concept for employment data.
• Timeliness issues were noted in Poland and Denmark.

III.4 Housing Price Statistics

• The 2013 legal framework improved the accuracy and comparability of housing price data.
• ELSTAT (Greece) does not deliver data as required by Commission Regulation (EU) No 93/2013.
• Eurostat continues to use the Greek central bank's Residential Property Price Index for MIP purposes.

III.5 Financial Accounts Statistics

• Financial accounts data are compiled from sector-specific sources.
• Revisions are common, particularly in private sector credit and debt.
• Improvements are needed in:
  • Coverage of liabilities of other financial institutions.
  • Reconciliation of the "Rest of the World" sector with BoP/IIP data.
  • Reduction of discrepancies with non-financial sector accounts.
  • Clarification of consolidated vs. non-consolidated data.
• Several countries, including Bulgaria, Czech Republic, Denmark, Ireland, and Slovakia, need to improve annual and quarterly data consistency.

III.6 Government Finance Statistics

• Quality is ensured through enhanced mechanisms related to the Excessive Deficit Procedure (EDP).
• Eurostat expresses reservations on data reported in EDP notifications if quality concerns are identified.

III.7 Labour Market Statistics

• Overall accuracy and comparability are considered high.
• Data are used for MIP monitoring and are generally reliable.

IV. Conclusion

• The statistics underpinning the MIP are of sufficient quality for effective surveillance.
• Improvements are needed in areas such as globalisation impacts, SPEs coverage, data consistency, and timeliness.
• Cooperation between Eurostat and the ECB, as well as between ESS and ESCB, is essential.
• Globalisation and multinational enterprises continue to pose data collection and interpretation challenges.
• Impact assessments and case studies are recommended before introducing new compulsory statistical requirements.