Accurate data is crucial for the effective monitoring of macroeconomic imbalances within the Macroeconomic Imbalance Procedure (MIP), which is part of the European Semester - a framework for the coordination of economic and social policies across the European Union (EU). The European Statistical System (ESS), composed of Eurostat and the national statistical institutes (NSIs) and other national authorities (ONAs), as well as the European System of Central Banks (ESCB), composed of the European Central Bank (ECB) and the national central banks (NCBs), contribute within their respective spheres of competence to the harmonised production of data used in the context of the MIP: they provide the necessary expertise to guarantee the statistical quality of indicators and their availability, in a continuous effort to reflect economic and social development. It is of the utmost importance that statistics underlying the MIP procedure remain fit for purpose in this highly relevant policy context where imbalances are identified and countries' progress monitored based on the best possible data quality. Close cooperation on quality assurance of statistics underlying the MIP is ensured via the implementation of the Memorandum of Understanding (MoU) signed between Eurostat and the ECB DG Statistics in November 2016.1

This 12th joint annual quality report presents a transparent description and assessment of the quality of the statistics underlying the MIP indicators. This report benefited from comments of the Committee for Monetary, Financial and Balance of Payments statistics (CMFB).2 It concludes that the macroeconomic statistics produced by the ESS and the ESCB are of sufficient coverage, comparability (across countries), accuracy and timeliness to ensure an effective macroeconomic surveillance and therefore to support the MIP, whilst describing areas for further improvement in each of these dimensions.

When looking at the quality of MIP statistics, the following main features are worth highlighting:

In the EU, a regular and comprehensive quality assessment of national Gross Domestic Product (GDP) is in operation in the frame of Gross National Income (GNI) being used for own resources purposes, of which GDP constitutes the predominant part. In addition, the results of the annual quality reporting exercise under the European System of Accounts (ESA 2010) methodology were published in November 2025.3

For balance of payments and international investment position (BOP/IIP) statistics, the ECB and Eurostat assess regularly the quality of the data in the context of the respective legal framework.

Moreover, joint ECB and Eurostat dedicated country visits take place to assess in detail the quality of BOP/IIP and FAs for MIP purposes.4 Asymmetries in bilateral flows and stocks remain a concern.

Eurostat and the ECB recommend that countries enhance their efforts to reduce asymmetries. This includes actively participating in the Foreign Direct Investment (FDI) network and the FDI Asymmetry Resolution Mechanism meetings organised by the ECB. The valuation and recording of FDI transactions, positions, and income require further work to ensure adequate and harmonised implementation of the current statistical guidance. Moreover, Eurostat has been sponsoring an Asymmetries Resolution Mechanism for international trade in services since 2022.

Eurostat’s annual quality reporting on national and regional accounts cover the components of the unit labour costs indicator and generally indicate only a few gaps in completeness and timeliness of regular transmissions.

The quality of the government finance statistics (GFS) is assessed in the context of an enhanced quality assurance mechanism around the Excessive Deficit Procedure (EDP); in case of quality concerns, Eurostat expresses reservations on data reported in official EDP notifications.5

Financial accounts statistics (FA) data quality is assessed by the ECB and Eurostat on a regular basis following the respective legal framework.6 Certain areas of improvement have been identified in several countries, including coverage and data sources for Other Financial Institutions (OFIs), elimination of some national inconsistencies between the annual and quarterly datasets, and the reduction of (vertical) discrepancies with non-financial sector accounts.

Moreover, additional efforts are also needed to address the ongoing inconsistencies between BOP/IIP and the “Rest of the World” (ROW) account. Eurostat and the ECB regularly present joint reports on the consistency of the two datasets to the CMFB. The most recent joint ECB-Eurostat

“BOP-NA ROW consistency report” was presented to the CMFB plenary in January 2026 and published on the CMFB website in February 2026.7 This report highlights cross-cutting and transversal issues where efforts need to continue to reduce inconsistencies, with the aim of further enhancing the quality and international comparability of macroeconomic statistics. The goal is to significantly reduce and eventually eliminate these discrepancies.

For housing price statistics, following the adoption in 2023 of the Commission Implementing Regulation (EU) 2023/14708, two country monitoring visits took place in 2024 and two more in 2025. The compliance monitoring reports for the first three visits were made available in 2025, and the fourth will be made available in 2026 on the quality section of Eurostat’s thematic website for housing price statistics.9 In terms of data availability, one country does not deliver data as required by Commission Regulations (EU) 2016/792 and 2023/1470. To address this data gap within the MIP

exercise, Eurostat continues to use an index published by this country’s National Central Bank, that does not fully comply with the standards set in the abovementioned regulations.10

The overall accuracy of labour market statistics is considered as high, while it may vary across countries due to differences in response rates. These differences, being within the acceptable range, do not jeopardise overall accuracy and comparability. The principle legal acts which the EU Labour Force Survey (EU-LFS) is based on are Regulation (EU) 2019/1700 on a common framework for European statistics relating to persons and households, and the Commission Implementing Regulation (EU) 2019/2240 that specifies the implementation rules, technical items and content.

Furthermore, the Commission Implementing Regulation (EU) 2019/2180 specifies the detailed arrangements and content for the quality reports pursuant to Regulation (EU) 2019/1700.

This report presents various quality issues related to statistics underlying the MIP. Part 2 of the document provides a background over the MIP quality assurance underlying the MIP. Part 3 contains more in-depth information by statistical domain, including scoreboard indicators and relevant quality criteria: institutional issues, the compilation process, and the quality of the statistical output, focusing on its accuracy, reliability and comparability across countries and across time. Annexes 1 and 2 list the MIP scoreboard and auxiliary indicators.

1 Memorandum of Understanding between Eurostat and the ECB-DG Statistics on the quality assurance of statistics underlying the MIP.

2 Council Decision 2006/856/EC of 13 November 2006 establishing a Committee on monetary, financial and balance of payments statistics, OJ L 332, 30.11.2006, p. 21.

3 Quality report on National and Regional Accounts (europa.eu).

      4 Latvia in 2025 and Italy in the beginning of 2026 were visited in this context.

5 Eurostat thematic section on GFS/EDP statistics. Eurostat dedicated section on GFS/EDP statistics, Eurostat thematic section on GFS/EDP statistics.

6 Also joint ECB and Eurostat dedicated country visits take place to assess in detail the quality of BOP/IIP and FAs for MIP purposes; Latvia in 2025 and Italy in the beginning of 2026 were visited in this context.

7 2025 Joint ECB-Eurostat annual report on the consistency of National Accounts and Balance of Payments concerning quarterly financial and non-financial accounts.

8 Commission Implementing Regulation (EU) 2023/1470 of 17 July 2023 laying down the methodological and technical specifications in accordance with Regulation (EU) 2016/792 of the European Parliament and of the Council as regards the house price index and the owner-occupied housing price index, and amending Commission Regulation (EU) 2020/1148 (Text with EEA relevance)

9 Eurostat thematic section on housing price statistics.

10 For instance, contrary to the requirements of the legal framework in this domain, the residential property index produced by the Bank of Greece is not based on transaction prices of dwellings. Furthermore, as it relies on appraisal reports of residential properties used in loan agreements, it does not fully capture the entire spectrum of dwelling purchases, as required by the regulation and is therefore not comparable with the indices of the other Member States.

2.1    Background and legal basis

The MIP headline indicators are derived from macroeconomic and financial statistics produced by the ESS and the ESCB, mostly based on data collected under European Union legislation. This encompasses balance of payments statistics, international investment positions, national accounts, financial accounts, EDP and government finance statistics, prices, and labour market statistics, where statistical legislation provides for regular domain-specific quality reports, often accompanied by inventories describing sources and methods applied in data collection. This report finds that these statistics are of sufficient coverage, accuracy and timeliness to ensure an effective multilateral macroeconomic surveillance within the context of the MIP.

The ESS, composed of Eurostat and the NSIs and other national authorities11, and the ESCB, composed of the ECB and the NCBs, operate under separate legal frameworks reflecting their respective governance structures and cooperate closely when designing their respective statistical programmes. Both systems12 have long produced macroeconomic and financial statistics within their respective spheres of competence, applying statistical quality assurance mechanisms to ensure that these statistics are in line with international statistical standards and reliable and comparable across EU Member States. Such statistics have been the basis for economic and monetary policy decisions of the Union over many years and are also used by international organisations like the IMF and the OECD in their surveillance reports.

Ensuring the quality of these statistics is a central contribution of the ESS and the ESCB. The two systems share similar principles related to statistical processes, outputs, and institutional environment. These principles are reflected in the European Statistics Code of Practice and the ESCB Public Commitment on European Statistics respectively, aligning with UN, IMF and OECD standards.

The assessment presented in this ESS-ESCB Quality Assessment Report reflects essential quantitative and qualitative information from the comprehensive quality assurance frameworks for macroeconomic statistics of the ESS and the ESCB, in particular from domain-specific quality reports. As MIP indicators derive from available macroeconomic and financial statistics, this report focuses on the quality of these statistics. Accordingly, the report also outlines areas of the underlying statistics that may need further quality enhancements.13

2.2   Quality and cost-effectiveness 

By striking the right balance between different quality dimensions, the ESS and the ESCB aim to produce fit for purpose macroeconomic and financial statistics in a cost-effective manner. To strike this balance, statisticians, in close liaison with users and reporting agents and prior to developing new statistics or imposing additional reporting requirements, have to undertake a 'merit and cost evaluation' considering the trade-offs between the timeliness, accuracy, reliability, detail and cost of macroeconomic statistics.

The frequency of the statistical production, which is in most cases regulated, has also to be taken into account: high-frequency macroeconomic statistics ensure the appropriate timeliness but are generally compiled with less detail not to overburden respondents, while more detailed statistics become available less frequently and with a longer time-lag.

Another usual arbitrage is between the degree of reliability and accuracy on the one hand, and timeliness of publication on the other hand: the shorter the length of time for collecting, computing and controlling the statistical output before publication, the less accurate and reliable the statistics will be, assuming all other things equal. Revisions have to be considered a normal phenomenon to increase progressively the quality of data, in particular its accuracy. Revisions are also regularly analysed in order to improve source data, statistical processes and methods. Benchmark revisions, like the one implemented in 2024, are crucial occasions to review these sources, processes and methods in a coordinated way across domains (national accounts, financial accounts, and balance of payments).

Moreover, the quality is also linked to the compilation methods that are available and used. Data derived from business accounting or administrative sources, which are closely related to the phenomena under observation, may often lend itself as the most solid primary data for certain purposes, if deviations from statistical standards are appropriately addressed. In other cases, surveys can be appropriate or even unavoidable in certain statistical areas, which are by definition less exhaustive, but the risk of error is mitigated by statistical techniques to the largest extent possible.

While a more extensive use of censuses instead of sample surveys might enhance the accuracy and reliability of certain statistics, it would also increase the costs and the reporting burden, in particular for small and medium-sized enterprises. For example, the reporting obligations on cross-border transactions (for balance of payments purposes) may only be imposed for transactions or positions above certain thresholds to limit the reporting burden; this is however expected to affect only marginally the accuracy and reliability of the final output. In addition, the estimate of some variables may only be achieved through modelling, with a need for some expert judgment.

The accuracy and reliability of macroeconomic statistics are also influenced by the level of qualified human and financial resources involved in the statistical work. For example, as quality checks typically require contacting the reporting entities to confirm the provided statistical information, the lack of resources may limit the scale of this task, with a possible impact on the accuracy and reliability of the statistics. Experience in some countries points to the impact of economic globalisation on macroeconomic statistics and the difficulties in collecting data from multinational enterprises. The sharing of information and data between statisticians is legally challenging and still difficult in practice, while globalisation of large economic groups is accelerating.

In short, the quality framework must take account of the wider statistical context in which these data are produced; a context in which timeliness, reliability, accuracy, and other quality parameters must be carefully balanced in the choice of collection and compilation methods. Otherwise, Member States could be obliged to adjust their collection and compilation methods in a manner that can no longer be considered balanced or cost-effective for the wider set of statistics from which the MIP relevant data are derived.

2.3   The three-level structure of the ESS-ESCB quality framework  

The ESS-ESCB quality assurance framework follows a three-level structure.

The first level (level 1, the present document) provides key messages on the quality assurance of MIP statistics, in particular on their reliability and comparability, to the Council and the European

Parliament, policy makers and the public at large. This level draws on the information gathered in the next two levels.

The second level consists of domain-specific quality reports produced by Eurostat and the ECB DG Statistics, summarising the main findings for the euro area and/or the EU Member States. These reports assess the underlying compilation process and its robustness, describe its legal basis and evaluate whether the statistics are in line with international statistical standards and comparable.

They reflect comprehensive expert assessments on whether the statistics are fit for each of the broader purposes for which they are intended. The quality assessment is based on, among other sources, the input coming from national, domain-specific quality reports. For national accounts, after the adoption of an implementing act14, an annual quality reporting by Member States started in 2017, including data underlying the MIP indicators, too.

ECB DG Statistics and Eurostat, with the support of the CMFB, worked with the objective of harmonising the quality reporting on BOP/IIP and FA. While - due to the different data coverage and legislation - it is currently not possible to have one common level 2 report, its structure, the indicators and the findings included in the Eurostat and the ECB reports are harmonised, including a special section (box) focusing on the quality assessment of the data used for MIP purposes.

On the third level, depending on the domain, national quality reports (self-assessments) are produced by the institution compiling the national statistics. Most of these reports are voluntarily published by Members States on the CMFB’s website and/or on the website of the national statistics compiler.15

By focusing the quality assurance on the underlying macroeconomic and financial statistics that are used for multiple purposes, rather than on MIP indicators only, data quality is ensured regardless of possible adjustments to the scoreboard indicators.

2.4    The Memorandum of Understanding between Eurostat and the European Central Bank/DG Statistics 

On 7th November 2016, Eurostat and DG Statistics of the ECB signed a Memorandum of Understanding on the quality assurance of statistics underlying the MIP.16 Within its scope are two statistical domains where many Member States have designated their National Central Banks for producing the datasets, or major parts of it:

• Balance of payments and international investment position statistics

• Financial accounts

The Memorandum of Understanding establishes a mutual recognition of the respective ESS and ESCB quality assurance frameworks. Furthermore, it sets out the steps to be taken during the MIP indicators production process - based on a timetable to be agreed annually by Eurostat and the ECB/DG Statistics - and establishes that, with the support of NSIs and NCBs, Eurostat and the ECB/DG Statistics may undertake analysis of the output quality and consistency of the datasets with related statistical domains, including joint visits to Member States.

Eurostat and ECB/DG Statistics have been fully implementing the MoU since its agreement, including regular comparisons of the relevant data in the Eurostat and ECB databases and their harmonisation, the implementation of the three levels quality reporting system and joint visits by Eurostat and the ECB/DG Statistics to countries. Country visits started in 2017 with Greece and Belgium, followed by Luxembourg and Poland in 2018, Germany, Ireland and Malta in 2019, France in 2020, Finland in 2022 (virtual visit), Cyprus and the Netherlands in 2023, Croatia and Bulgaria in 2024, Latvia in 2025, and Italy in the beginning of 2026. The purpose of the visits is to assess the quality of financial accounts and BOP data underlying the MIP indicators. Visits are carried out on the basis of a well-established framework and have demonstrated their potential for identifying concrete actions for the improvement of the quality of MIP underlying statistics. Progress on the conclusions of the visits is then reviewed on an annual basis, and in 2025 this procedure was successfully closed for both Belgium and Greece.

11 List of National statistical institutes (NSI) and other national authorities.

12 The institutional framework for the production of European statistics is set out in the Treaty of the European Union (TFEU) and in Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics, OJ L 87, 31.3.2009, p. 164, and in Council Regulation (EC) No 2533/98 of 23 November 1998 concerning the collection of statistical information by the European Central Bank, OJ L 318, 27.11.1998, p. 8.

13 Within the reporting structure monitoring the quality of statistics underlying the MIP, this ESS-ESCB Quality Assessment Report isaccompanied andcomplemented by domainspecificquality reports prepared on anational level by the Member States and on an EU/euro arealevel by Eurostat andthe ECB.

 14 Commission Implementing Regulation (EU) No 724/2014 of 26 June 2014 on the interchange standard for the transmission of data required under Regulation (EU) No 549/2013 of the European Parliament and of the Council on the European system of national and regional accounts in the European Union Text with EEA relevance.

15 MIP quality section on the CMFB website.

16 Memorandum of Understanding between Eurostat and the ECB-DG Statistics on the quality assurance of statistics underlying the MIP.

A quality assessment supporting the MIP exercise should focus on scrutinising the relevant quality criteria for the MIP process. These criteria should be embraced in the three main blocks clustering the quality principles of the European Statistics Code of Practice and the ESCB Public Commitment on European Statistics.

Given that MIP indicators are designed to 'identify imbalances' and to develop 'multilateral policy recommendations', a 'fit-for-purpose' quality assessment for the MIP should give prominence to the criteria assessing:

• the institutional environment, such as the legal basis supporting the collection of the statistics, the quality assurance mechanisms in place and the policy uses of the underlying statistics;

• the robustness of the statistical / compilation process; analysing whether the important parts of the statistics are supported by comprehensive collection of raw data or by sound estimation methods supplemented when necessary by expert judgement; and

• the quality of the statistical output; focusing on the accuracy and the comparability of the underlying statistical output across countries and across time. Accuracy and reliability17 are relevant because policy makers would need an assessment on whether the reported value portrays the reality by applying the concepts and rules defined in international statistical standards. In particular, reliability needs to be assessed in the sense whether statistics are also consistent over time or if revisions may result in final values of the indicators diverging substantially from the value reported when the policy assessment of imbalances was undertaken. Comparability (and coherence)18 requires judging whether the statistics for all EU Member States abide by the international statistical standards or European regulations and identifying major deviations.

3.1    Gross domestic product

Given that many of the MIP indicators are compiled relative to GDP, it is important to assess the quality of GDP statistics to ensure the quality of MIP indicators compiled by relating domain-specific statistics or indicators to GDP.

Institutional issues

i) Legal basis

European national accounts are compiled according to the harmonised accounting concepts, definitions, classifications, methodology and calculating rules described in Regulation (EU) No 549/2013, which covers the European System of Accounts (hereinafter referred to as “ESA 2010”)19, and amended by Regulation (EU) No 2023/734.20 The ESA 2010 Transmission Programme (Annex B of the Regulation) specify at which level of detail and timeliness that the data should be provided. The revised Transmission Programme (2023/734) entered into force on 1 September 2024.

ii) Quality assurance mechanisms

As Gross National Income (GNI) under Regulation (EU) No 2019/516 (hereinafter referred to as “GNI Regulation”)21 is used for administrative purposes, the countries are obliged to give detailed inventories of the sources and methods (GNI Inventories) used to produce GNI aggregates and their components in accordance with ESA 2010 to the Commission. GDP and the transaction flows in it form a major part of GNI22 and are therefore included in the GNI Inventories, thus being a source for assessing GDP quality. The verification of GNI Inventories is supplemented by Eurostat information visits to Member States to verify the quality of GNI aggregates and their components and their compliance with ESA 2010. National accounts experts from other EU Member States may attend the GNI information visits as observers. Eurostat's GNI verification activities are checked annually by the European Court of Auditors. The above-mentioned administrative and policy uses force both the European Union and the Member States themselves to verify the GDP and GNI calculations.

Monitoring of country's compliance with the requirements of the ESA 2010 transmission programme has also been enhanced, and further work on improvement of validation procedures is being taken forward with Member States.

Provisions for quality reporting and assessment of the ESA 2010 data, including GDP, are established by Art. 4, Regulation (EU) No 549/2013. The adoption of the Commission Implementing Regulation (EU) No 2016/2304 of 19 December 201623 enabled the introduction of the first quality reporting exercise by Member States in 2017. The annual quality reporting covers all ESS quality criteria.

Member States provide annual quality reports to Eurostat by the end of May each year, covering the data transmitted during the previous year. Eurostat makes public its own assessment based on the country reports. The latest annual quality report was published in November 2025.24

iii) Policy uses

As GDP is the key variable to measure economic development, it is also used in policy decision making at the European Commission, ECB, and for budgetary policy purposes in the Member States. Annual GDP and GNI statistics are used in the European Union for various administrative purposes. GNI is the largest revenue source for the EU budget. In addition, Member States' GDP data are also used for administrative purposes in the Excessive Deficit Procedure (EDP) as general government debt and deficit are proportioned to GDP in the EDP criteria. Furthermore, regional GDP per capita is used in the decisions for the funding from the European Union Structural Funds to the regions of the Member States.

Compilation process

GDP is compiled by Member States using an ample and comprehensive set of primary data sources. The national statistical authorities collect themselves the majority of the basic data, the quality of which is defined by national and European regulations, by using both statistical surveys and administrative records (such as taxation records), and bookkeeping data from both governmental bodies and enterprises. Data consistency is enforced at the economy-wide level by the fact that GDP is calculated using the production, expenditure and income approaches which should lead to the same result.

Quality assessment of output

i) Accuracy and reliability

There is a comprehensive system for verification of GNI data and the annual reports on the quality of GNI data are available for all countries. This includes the GNI Expert Group to issue annual opinions on the appropriateness of the GNI data submitted by the Member States for own resources purposes.

Article 5(1) of the GNI Regulation provides for the Commission to verify the sources, their uses and the methods in the GNI Inventories based on a verification model drawn up in close cooperation with the GNI Expert Group and based on the principles of peer review and cost-effectiveness and with respect to reliability, comparability and exhaustiveness. A document that includes the transmitted data and reports on quality of GNI data sent each year before 1 October to Eurostat is presented in November to the GNI Expert Group for discussion and examination. The annual GNI data and the opinion of the GNI Expert Group are transmitted to DG Budget for the purpose of budgetary calculations. The verification of sources and methods for GNI in the 2020-2024 cycle was finalized. Eurostat placed GNI reservations in December 2024. The deadline set for the Member States to finalise the work on reservations is September 2026 in most cases.

Moreover, the practical validation of GDP data puts emphasis on consistency requirements. When quarterly and annual data are submitted to Eurostat, it is important to ensure that these figures are consistent. Small differences may be tolerated, but not major ones. Consistency between annual data and the sum of the data for the four individual quarters for certain key EU aggregates are analysed in the context of the ESA 2010 quality reporting exercise with generally very small inconsistencies limited to different vintages or rounding. The consistency of aggregates and breakdowns is also monitored and usually well fulfilled.

- Revisions

Member States may have routine revisions of GDP data every year when updated surveys or administrative data become available, replacing preliminary estimates. When the final annual source data of the reference year are available and GDP calculations are based on the balanced supply and use tables by the product groups, the revisions in the annual GDPs of the Member States are generally small. Most Member States make available online information on national revision policies. For own resources purposes, the GNI figures become time-barred after four years. However, where revisions are likely to have a material effect, the Commission issues reservations which means that GNI data remain open for possible revision. Similarly, EDP related reclassifications and methodological improvements might also lead to GDP revisions.

Benchmark revisions, on the other hand, are coordinated major European revisions, taking place at least once every five years to incorporate new data sources and major changes in international statistical methodology. Since 2014 all Member States have carried out benchmark revisions in national accounts, the latest being in 2024, except in Luxembourg which postponed its revision to 2027. The 2024 benchmark revision hence covered countries that account for 99% of the euro area and 99% of the EU in terms of GDP. Countries implemented an updated classification for household expenditure breakdowns (COICOP 2018) and other transmission improvements, according to the revised Transmission Programme 2023/734, unless temporary derogations were agreed. As a key aspect of benchmark implementation is communication, Eurostat set up a sub-page on data revision25 on its ESA 2010 website to support the coordinated ESS communication strategy on the 2024 benchmark revision.

ii) Comparability

Comparability is ensured by the application of common definitions and requirements (ESA 2010). While the aim is to improve the quality of statistics, the level of comparability between Member States however may also depend on the comparability/level of development in the basic data used as input for the GDP compilation, and hence the level of efforts needed to ensure alignment with the ESA 2010 and BPM6 definitions at macro level.

3.2    External imbalances and competitiveness

Macroeconomic imbalances remain a serious concern, requiring decisive, comprehensive and coordinated policy action. For a better analysis of a country's economic external and domestic situation, the MIP scoreboard indicators for this purpose are grouped into: i) external imbalances and competitiveness, and ii) internal imbalances.

The MIP scoreboard indicators on external imbalances and competitiveness are calculated from BOP/IIP, real effective exchange rate statistics and NA, and covers the following indicators:

• Current account balance (CA) as % of GDP, 3 year average

• Net international investment position (NIIP) as % of GDP

• Real effective exchange rate (REER), 42 trading partners, HICP/CPI deflators, 3 year % change

• Export performance against advanced economies, 3 year % change

• Nominal unit labour cost (per hour worked), 3 year % change

3.2.1    Balance of payments and international investment position indicators

The following headline indicators based on BOP/IIP are included in the MIP scoreboard:

• Current account balance (CA) as % of GDP, 3 year average

• Net international investment position (NIIP) as % of GDP

• Export performance against advanced economies, 3 year % change

Institutional issues

i) Legal basis

BOP/IIP indicators are provided to the ECB on the basis of Guideline ECB/2011/2326, as amended27

(hereinafter “Guideline ECB/2011/23”) and to Eurostat on the basis of Regulation (EC) No 184/2005.28

These legal acts do not impose back data requirements in compliance with the BPM6 statistical standard. Therefore, long time series are provided on a voluntary basis by Member States. In the last MIP scoreboard the relevant series for the compilation of the indicators were available for all Member States for at least 10 years as per the requirements within the MIP.

ii) Quality assurance mechanisms

Since 2017 several actions for the improvement of the quality of the BOP/IIP datasets have been jointly undertaken by Eurostat and ECB, mostly in the context of the implementation of the Memorandum of Understanding (MoU). This has also further strengthened the close cooperation between the two institutions and between the ESS and the ESCB.

A biennial report from the Executive Board of the ECB to the Governing Council on the quality of the external statistics (ES) data is required by Article 6 of the amending Guideline ECB/2020/52. The report follows the principles of the “Public commitment on European Statistics by the ESCB”29 and includes an extensive quantitative assessment of the statistical output. The ECB report is submitted to the Working Group ES and the Statistics Committee (STC) via written procedures and approved by the Executive Board before being submitted to the ECB Governing Council and published on the ECB website.

The European Commission (Eurostat) produces a biennial quality report (produced in years when the ECB is not producing its report and vice versa) on the basis of Article 4(3) of Regulation (EC) No 184/2005. This report is reviewed with the assistance of the European Statistical System Committee referred to in Article 11 of Regulation 184/2005, amended by Article 4(4) of Regulation (EU) 2016/1013.30 The quality assessment of this report is conducted in accordance with the principles established by Commission Regulation (EC) No 1055/200831 and Commission Regulation 1227/2010. It verifies compliance of the BOP data reported by EU Member States with all the quality criteria and the Regulation on European statistics (Article 12(1) of Regulation (EC) No 223/2009, as amended). The Eurostat report is a condensed analysis of the results of national quality reports pre-filled by Eurostat and completed by Member States: it is presented to the BOP Working Group, publicly disseminated on Eurostat's website, and sent to the European Parliament and the Council for information.

iii) Policy uses

BOP/IIP data are broadly used for monetary and economic analysis throughout the world, i.e. not only for European policy purposes, but generally by all economic analysts looking into external imbalances/relationships and competitiveness in a context of increasingly mobile financial flows. In particular, these data are used to explain changes in monetary developments, thereby supporting the preparation and explanation of monetary policy decisions. BOP/IIP statistics are also broadly used in the European Systemic Risk Board (ESRB) Risk Dashboard for various European Commission policy purposes, and IMF work

Compilation process

At national level, the compilation of BOP/IIP is usually a competence of either the NCB or the NSI, sometimes both. By nature, BOP/IIP statistics are rather eclectic as regards data sources, relying on micro (e.g. the Centralised Securities Database - CSDB) and macro data sets, direct reporting and counterpart information, statistical surveys and administrative data sets (e.g. for the general government sector). National compilation systems also seek synergies with worldwide exercises, such as the IMF CPIS and CDIS surveys. Several statistical methods and compilation assumptions are used, including the derivation of transactions from changes in stocks, taking into account price and exchange rate revaluations.

Quality assessment of output

i) Accuracy and reliability

While BOP/IIP compilation in EU Member States is based on BPM6, challenges persist in measuring some components, particularly reinvested earnings on FDI and valuation of unlisted shares and other equity. Member States are encouraged to review and align their methods for compiling reinvested earnings of FDI with the relevant methodology (consistent with ESA 2010). Significant progress has been made in ensuring adequate data coverage and quality for SPEs.

Recent quality assessments confirm that these improvements increasingly support the stability and internal consistency of BOP/IIP data used for EU aggregates and MIP indicators. However, some components remain subject to higher revisions particularly direct investment income and selected financial account components, where comprehensive annual information and methodological refinements are available with a longer delay.

- Revisions

Revisions continue to affect individual parts of BOP/IIP to varying degrees, with ongoing efforts to improve consistency and reduce discrepancies across statistical domains. Given that a benchmark revision took place in 2024, the revisions were rather limited in nature in 2025. However, national compilers continued to improve data sources, mainly focused on strengthening the coverage and compilation of direct investment, portfolio investment and the services accounts. Methodological upgrades to FDI were reported through improved coverage of fellow enterprises (Netherlands), reclassification of trade credits (Greece), and new calculations of reinvested earnings (Austria), while portfolio investment statistics were reinforced via the integration of ECB securities holdings and

third-party holdings data (Finland, Greece). Improvements in services statistics included supplementation of surveys with administrative sources such as VIES data as well as increasing the sample size (Finland). In addition, new data collections were introduced (e.g. crypto-asset service provider reporting in Estonia), survey designs were strengthened through the introduction of reporting thresholds in enterprise surveys to balance reporting burden and quality (Poland), and targeted technical revisions were implemented to address internal consistency issues (Malta), collectively contributing to more robust and comprehensive BOP/IIP statistics.

Since the last review period, routine revisions for Hungary, Luxembourg and Sweden affected the position of the MIP current account indicator relative to the relevant threshold for reference period 2023. The revisions did not change the analytical interpretation of the international investment position indicator for reference 2023 for any of the countries.

For BOP, direct investment income remains the most extensively revised series. As source data are typically available only on an annual basis, revisions to higher-frequency data are practically unavoidable. Other key drivers of revisions in BOP/IIP statistics included:

• Improved coverage, particularly for SPEs.

• Implementation of new data sources and production systems by national compilers.

• Major economic events affecting BOP/IIP.

• Revisions in related statistical domains.

ii) Comparability

Intra-EU asymmetries continue to be a relevant quality concern and will most likely persist given the increasingly multi-territorial presence of enterprises that require innovative and complex collection and estimation methods. Experience with the European FDI Network shows that data exchange can help to solve asymmetries, provided that all affected Member States participate actively and follow up bilaterally on the identified counterpart cases.

Eurostat-led work on services asymmetries and the Early Warning System, and the ECB-led quarterly Asymmetry Resolution Mechanism in FDI continue to support a more targeted follow-up on the most material asymmetries affecting EU aggregates. These initiatives complement other bilateral and multilateral reconciliation channels and help prioritise investigations where the expected impact on EU aggregates is the highest.

Despite the conceptual consistency ensured by BPM6 and ESA 2010, discrepancies between BOP/IIP statistics and NA-ROW accounts persist in several countries. The most significant remaining inconsistencies for the largest contributors typically concern goods, services and income items on the current and capital account side, and equity and residual “other” components on the financial account side. Given their weight in EU aggregates and their sensitivity to methodological choices and source changes, these items remain priority areas for joint Eurostat–ECB work. The Eurostat–ECB annual consistency report confirms that sizeable discrepancies remain even after the September 2024 benchmark revision and therefore calls on countries with large remaining differences to establish dedicated, regular coordination arrangements between national accounts and BOP compilers.

The Harmonised European Revision Policy is being implemented on a voluntary basis for national accounts, financial accounts and balance of payments statistics, reinforcing the EU-wide commitment to improve cross-domain coherence.

Progress in reducing asymmetries and improving BOP–ROW consistency ultimately depends on continued engagement by the countries with the largest absolute and relative discrepancies, and on timely exchange of metadata and reconciliation evidence. Asymmetries have also been highlighted as an area to investigate in the context of multi-country supply-use and input-output work (e.g. FIGARO), where improved bilateral consistency supports more robust integrated globalisation analysis.

Finally, while BPM6 and ESA 2010 provide a consistent conceptual framework, discrepancies still arise due to different vintages, revision policies, data sources, and practical implementation choices. Maintaining and institutionalising cross-domain reconciliation practices remains essential, and countries are encouraged to build on the results of the CMFB-related consistency work and other Eurostat and ECB initiatives.

3.2.2 Real effective exchange rate statistics

The following headline indicator based on real effective exchange rate statistics is included in the MIP scoreboard:

• Real effective exchange rate (REER), 42 trading partners, HICP/CPI deflators, 3 year % change

Institutional issues

i) Legal basis

Real effective exchange rates (REERs) data used in the MIP are compiled by the European Commission based on a widely recognized standard methodology implemented by DG ECFIN: Reports on Price and Cost Competitiveness. REER datasets, together with the underlying nominal effective exchange rates (NEER), are published on the website of DG ECFIN32, and also disseminated in Eurostat’s database.33 REERs are not directly based on a legal act, but they are based on national data (exchange rates, trade data and deflators) that are mostly compiled and collected based on specific legal acts. REERs are derived indicators and therefore their quality is mostly a function of the quality in underlying data sets.

ii) Quality assurance mechanisms

The data underlying the calculation of REERs is as far as possible collected from reliable institutional sources, compiled by the ECB, the IMF and Eurostat. However, for some of the non-EU member states the data from institutional sources is complemented by a private data provider. Exchange rates, trade data and deflators are subject to quality reporting in their respective domains. DG ECFIN has produced a comprehensive quality report on its REER statistics together with an assessment of how they compare to the REER time series compiled by four international institutions (ECB, OECD, IMF and BIS)34.

iii) Policy uses

Both NEER and REER are widely used measures of price and cost competitiveness. NEERs describe changes in the average overall value of a currency with reference to a given base period and a given group of reference countries. The REERs identify relative evolutions in the prices or production costs of domestically produced goods compared to the prices or production costs of goods produced by competitor countries, when expressed in a common currency.

Compilation process

Nominal effective exchange rates are calculated as trade-weighted geometric averages of the bilateral exchange rates against the currencies of competing countries. The real effective exchange rates or the “relative price and cost indicators” are calculated as the adjusted NEERs with trade-weighted price or cost deflators.

The EU27 and euro-area aggregates are calculated by taking as weights each country's share of extra-EU or extra-EMU trade. Double export weights are used to calculate REER, reflecting not only competition in the home markets of the various competitors, but also competition in export markets elsewhere.

Quality assessment of output

i) Accuracy and reliability

The quality of the REER indicators depends on the quality of the underlying sources, in particular those used for constructing export weights and deflators.

The REERs used in the MIP are based on a harmonised index of consumer prices (or national CPI where appropriate) relative to a panel of the most important trading partners. The REER used in the MIP exercise is computed against a panel of 42 other countries. The Commission may consider extending the basket of trading partners further when data of sufficient quality for additional emerging countries become available.

Generally, the full dataset is updated monthly. Changes in methodology are rare but could happen in the future, should new countries be added to the basket of trading partners (when sufficiently reliable data are available for such countries).

ii) Comparability

Due to the use of index numbers vis-à-vis a base period, the usual caution must be used for any geographical comparison. The comparability over time of the data can be considered as very high, and methodological changes may occur but have a limited effect on the overall pattern of REER indicators. Each time these occur, recalculations under the new definitions are performed for the whole time series to ensure consistent time series without breaks. The changes are mainly the result of including new trading partners in the trade-weighted index, and/or new countries in the euro area.

3.2.3 Nominal unit labour cost

The following headline indicator based on national accounts data is included in the MIP scoreboard:

• Nominal unit labour cost (NULC) index (per hour worked), 3 year % change

Institutional issues

i) Legal basis

There is no specific legal basis for the calculation of unit labour costs per se, but it is derived from several components which themselves are collected under the overarching framework of the national accounts. According to the Eurostat MIP scoreboard presentation35, “Nominal unit labour cost compares remuneration (compensation per hour worked) and productivity (GDP in volume per hour worked) to show how the remuneration of employees is related to the productivity of labour. An increase means that the average compensation per hour worked grew more than labour productivity. The total hours worked data covers both employees and self-employed, while remuneration covers wages and salaries and employers' social contributions. The unit labour cost indicator is compiled using national accounts data”.

ii) Quality assurance mechanisms

Quality is assured by the strict application of ESA 2010 concepts and a thorough validation of country data. Data are collected from reliable sources applying high standards to methodology and ensuring high comparability. In addition, Eurostat conducts an annual compliance exercise for all Member States. As stipulated in the Commission Implementing Regulation 2016/2304, Eurostat established regular quality reporting on national and regional accounts, which cover the components of the MIP ULC indicator and generally indicate only a few gaps in completeness and timeliness of regular transmissions.

iii) Policy uses

Unit labour cost, which is defined as the cost of labour per unit of output, is a common measure of the external competitiveness of a country. Labour being a major input of production, its compensation directly affects the costs and prices of outputs, thus having a bearing on export market share and growth potential. It allows the comparison and analysis of cost competitiveness across countries.

However, specific developments, such as notably an impact of globalisation on GDP figures, due to the relocation of business within multinational enterprises, may have to be taken into account when interpreting productivity figures of certain countries (e.g. for Ireland).

The data are widely used for many purposes and publications, such as the assessment by the Commission of the functioning of the labour market within the Europe 2020 Joint Assessment Framework or the annual Competitiveness report, the ECB's Economic Bulletin, and Annual Report, and by other International Organisations such as the IMF and the OECD (the latter uses ECB data for the publication of whole economy European ULCs). ULCs are mentioned explicitly as “other factors” which need to be analysed in the assessment of Convergence in the EU.

Compilation process

The formulae for ULC, compensation per hour worked by employee and labour productivity are the following:

ULC = Compensation per hour worked by employees / Labour productivity

Compensation per hour worked by employee = Compensation of employees / number of hours worked by employees, domestic concept;

Labour productivity = GDP at market prices, chain-linked volumes reference year 2015 / number of total hours worked, domestic concept.

Quality assessment of output

i) Accuracy and reliability

Overall, the underlying data used in the compilation of the ULC are robust and harmonised across the EU, particularly at the whole economy level. Breakdowns by economic activity are also published using available data on gross value added, employment and compensation of employees by industries. It is methodologically more appropriate to use hours worked instead of number of persons to calculate the unit labour costs, given the differences in hours worked per person in the countries. The quality of the input data is considered to be equivalent.

- Revisions

Nominal unit labour cost data are usually revised to reflect data changes in its components. Revisions may stem from implementation of new compilation standards (e.g. ESA 2010), periodic benchmarking on population census results, and changes in the labour force survey methodology. GDP can be revised in relation to an improved recording of global business activities, addressing issues raised in the context of the GNI or EDP verification process, as well as other methodological or technical improvements. These methodological and statistical changes may lead to some breaks in the data series if back estimations are not done for all underlying series.

ii) Comparability

Cross-national comparability is very high due to the use of a common national accounts framework and the standardized ULC formulae to derive the statistics, but also owing to continuous efforts to enhance harmonization of the definition, coverage, and methodological treatment of the components comprising this labour cost indicator. The prevalence of this approach has been sought in due consideration of the use of different sources for the primary data of labour input (household surveys, business surveys administrative records, etc.), the importance of adjustments for alignment with national accounts concepts and statistical conversion techniques (e.g. from jobs to persons and to full-time equivalents). In this context, it may be noted that Poland flagged a break in its time series (in 2019).

3.3 Internal imbalance

The internal imbalances cover MIP indicators derived from government finance statistics, financial accounts, house price statistics and labour market statistics, and includes the following indicators:

• General government gross debt as % of GDP

• Household debt including NPISH as % of GDP, consolidated

• NFC debt as % of GDP, consolidated

• Household credit flow including NPISH as % of GDP, consolidated;

• NFC credit flow excluding FDI as % of GDP, consolidated

• Nominal house price index, 1 year % change

• Unemployment rate as % of labour force aged 15-64 years;

• Labour force participation rate as % of population aged 15-64 years, 3 year change in pp

3.3.1 Goverment finance statistics

The following headline indicator based on government finance statistics is included in the MIP scoreboard:

• General government gross debt (GGGD) as % of GDP

Institutional issues

i) Legal basis

For the purpose of the Excessive Deficit Procedure (EDP) in the Economic and monetary union (EMU), as well as for the Growth and Stability Pact, Protocol 12, annexed to the Treaty on the Functioning of the European Union, provides a definition of government debt: "Debt means total gross debt at nominal value outstanding at the end of the year and consolidated between and within the sub-sectors of general government". This definition is supplemented by Council Regulation (EC) No 479/200936 specifying the components of government debt with reference to the definitions of financial liabilities in ESA 2010 and that the nominal value corresponds to the face value of liabilities.

In this context, the stock of government debt in the Excessive Deficit Procedure (EDP debt) is equal to the consolidated sum of liabilities at face value, at the end of year N, of all units classified within the general government sector (S.13) in the following categories: currency and deposits (AF.2) + debt securities (AF.3) + loans (AF.4).

The Council Regulation requires all EU countries to report EDP data twice a year (before 1 April and 1 October) to Eurostat. The Council Regulation also requires that Member States transmit to Eurostat inventories to describe the sources and methods used for compiling the reported data.37

ii) Quality assurance mechanisms

Council Regulation (EC) 479/2009 stipulates that the “Commission (Eurostat) shall regularly assess the quality both of actual data reported by Member States and of the underlying government sector accounts compiled according to ESA 2010' and that the 'Commission (Eurostat) shall report regularly to the European Parliament and to the Council on the quality of the actual data reported by Member States. The report shall address the overall assessment of the actual data reported by Member States as regards to the compliance with accounting rules, completeness, reliability, timeliness, and consistency of the data.”

EDP data is thoroughly verified by Eurostat. This assessment concerns factors that explain the general government deficit / surplus and changes in general government debt. Member States notify EDP data to Eurostat twice a year, by transmitting "EDP notification tables" as well as supplementary information included in the "Questionnaire related to the EDP notification" and the "Supplementary tables for reporting government interventions to support financial institutions". The notification is followed by a period of bilateral clarification between Eurostat and Member States. In addition to that, Eurostat maintains an overview of EDP relevant issues in Member States through regular "EDP dialogue visits".

iii) Policy uses

The general government debt plays an important role in the framework of the Stability and Growth Pact (SGP). The SGP contains two arms – the preventive arm and the corrective arm. The preventive arm seeks to ensure sound budgetary policies over the medium term by setting parameters for Member States' fiscal planning and policies during normal economic times. The corrective arm ensures that Member States adopt appropriate policy responses to correct excessive deficits (and/or debts).

The corrective arm is made operational by the Excessive Deficit Procedure (EDP), a procedure to correct excessive deficits that occur when one or both of the rules - that the deficit must not exceed 3% of GDP and public debt must not exceed 60% of GDP (or, if exceed, decrease sufficiently towards 60%) as defined in the Treaty on the Functioning of the EU - are breached. Non-compliance with either the preventive or corrective arm of the Pact can lead to the imposition of sanctions for euro area countries. In the case of the corrective arm, this can involve annual fines for euro area Member States and, for all countries, possible suspension of Cohesion Fund financing until the excessive deficit is corrected.

Compilation process

The data are mainly compiled from public accounts, other administrative data and questionnaires. A limited amount of indirect data is also used for the compilation of financial accounts, but generally not for the compilation of general government gross debt at face value. The detailed sources and methods for each Member State can be found on the Eurostat website within the published EDP inventories.

Quality assessment of output

i) Accuracy and reliability

In recent reports sent to the European Parliament on the fiscal data reported by Member States, Eurostat noted the good overall quality of the reporting of fiscal data. Improvement is still expected with respect to the coverage and quality information on trade credits and in the consistency with the quarterly financial accounts for general government as well as for the work to update the EDP inventories. In general, consistency with the underlying general government sector data (GFS data reported in ESA tables 2, 25, 27, 28) remained very high, including for quarterly government debt.

- Revisions

In general, EDP statistics take on board updated, more detailed and more accurate data sources without delay. Methodological improvements and correction of errors should similarly not be delayed.

ii) Comparability

In general, Member States continuously provide good quality information, both in EDP notification tables and in other relevant statistical returns. Moreover, Eurostat is closely monitoring the system for the reporting of the Recovery and Resilience Facility as well as measures to mitigate the impact of high energy prices.

3.3.2 Financial accounts statistics

Four of the MIP headline indicators are based on annual financial accounts data:

• Household debt (incl. NPISH), consolidated, as % of GDP

• NFC debt, consolidated, as % of GDP

• Household credit flow (incl. NPISH), consolidated, as % of debt stocks (t-1)

• NFC credit flow (excl. FDI), consolidated, as % of debt stocks excl. FDI (t-1)

Financial accounts are an area of shared responsibility between the ESS and the ESCB.

Institutional issues

i) Legal basis

Quarterly financial accounts are mostly compiled by NCBs and transmitted to the ECB based on the ECB Guideline ECB/2013/24 (henceforth the “MUFA Guideline”)38, which foresees compliance with the principles and definitions of the ESA 2010 and the information breakdowns necessary to meet the ESCB’s needs.

Annual financial accounts are compiled according to the requirements of ESA 2010, in terms of principles and definitions, as well as information detail. Annual financial accounts data are transmitted to Eurostat in the framework of the ESA transmission programme (Annex B of ESA 2010). From September 2024, an updated version of the transmission programme entered into force, which includes the transmission of a sub-set of annual financial accounts four months after the end of the reference period.

ii) Quality assurance mechanisms

Since 2017, several actions for the improvement of the quality of financial accounts data have been jointly undertaken by Eurostat and ECB, mostly in the context of the implementation of the Memorandum of Understanding (MoU). This has also further strengthened the close cooperation between the two institutions and between the ESS and the ESCB.

A biennial quality report on the quarterly financial accounts is required by Article 7 of the MUFA Guideline. It follows the principles of the ECB Statistics Quality Framework (SQF).39 It assesses the quality of the data according to the following dimensions: relevance, accuracy, timeliness punctuality, accessibility and clarity, comparability and coherence. Furthermore, a special section (box) focuses on the quality assessment of the data used for MIP purposes. The ECB report is made available to the public on the ECB website.40

Based on the Commission Implementing Regulation No 2016/2304 of 19 December 2016 specifying the modalities, structure, periodicity, and assessment indicators of the quality reports which countries must provide in accordance with Article 4 of Regulation (EU) No 549/2013 (ESA 2010), Eurostat continued to publish regular quality reports on ESA 2010 transmissions. Annual financial accounts data are also covered in the Eurostat summary report on the quality of ESA 2010 data transmitted in 2024, which was published in November 2025.41

The quality reporting framework for financial accounts is further complemented by the national level 3 quality or ‘self-assessment’ reports that provide metadata on financial accounts, including descriptions on the compilation practices, sources and methods. Since September 2025, these reports are also considered to be the structural metadata of the annual financial accounts, as requested from the ESA 2010 regulation on a mandatory basis. The reports of all EU countries are available on the dedicated section of the CMFB website.42

The quarterly financial accounts data transmissions are regularly checked for completeness, internal consistency, as well as for external consistency with related statistics (e.g. non-financial sector accounts, money and banking statistics, investment funds statistics, insurance corporation statistics and BOP statistics).

Validation of annual financial accounts transmissions by Eurostat involves a wide range of internal consistency checks, as well as checks on consolidation, negative values, implausible zeroes and comparability with other datasets. Checks on revisions and outliers are also undertaken, as well as monitoring for compliance with the ESA transmission programme.

iii) Policy uses

Private debt indicators allow for an assessment of the private sectors (non-financial corporations and households) vulnerability to changes in the business cycle, inflation and the interest rate. Large credit fluctuations are often associated with potential banking system vulnerabilities, boom and bust cycles in asset markets, house price bubbles, and current account imbalances. Practice suggests that high credit flow is one of the best indicators to predict a crisis incidence early on. It is widely used by the Commission in the economic analysis of the EU Member States.

Quarterly financial accounts are used to supplement the monetary policy analysis of the ECB, because, in particular for households and non-financial corporations, no alternative comprehensive and timely data sources exist. The role of OFIs was recognised in the ECB’s 2020-21 monetary policy strategy review.43 In addition, the quarterly financial accounts are used for financial stability and macro-prudential analysis of individual Member States, and comprehensive debt measures, similar to those of the MIP, are considered by the European Systemic Risk Board (ESRB).

Annual financial accounts are most appropriate for structural analyses, for example of trends in lending and borrowing, in equity participation, in the build-up of asset price bubbles, and in longer term changes in debt positions. They are therefore suitable for the type of structural analysis needed in the MIP, where a long-term perspective is required

Compilation process

The compilation of financial accounts in EU Member States is based on the ESA 2010 methodological framework. Financial accounts data for a large part of the financial corporations (e.g. MFIs, Investment Funds, Insurance Corporations, Pension Funds and Financial Vehicle Corporations engaged in securitisation) are based on statistical Regulations44 directly addressed to the reporting agents: therefore, they use direct statistical sources, which produce high quality and largely harmonized data within the EU. Financial accounts data for the non-financial corporations and

household sectors (referred to as “private” sector in the context of the MIP scoreboard indicators), and part of the financial corporations’ sector related to OFIs, rely less on raw data directly collected from these sectors but on information available to the compiler from their (financial) counterpart sectors and from financial markets’ sources. However, information on securities issues and holdings for all sectors, including for non-financial corporations, are also collected by means of statistical legal acts, including regulations addressed directly to custodians and end-investors, and therefore provide high quality information for these entries in the financial accounts statistics.

For households and NPISH, timely data are generally available from (financial) counterpart sector information and from financial markets’ sources. Compilation of the data for the MIP headline indicators on consolidated non-financial corporations and households (including NPISHs) sectors credit flow and debt is largely based on these harmonised data sources on loans granted (or held) by the financial counterpart sectors and security issues statistics. In addition, for non-financial corporations’ credit flow the FDI are removed; data on FDI is taken from the quarterly financial accounts (QFA) collection of the ECB.

An area where the compilation of the financial accounts data underlying the MIP indicators is affected by limited data sources is the coverage of some financial subsectors (particularly captive financial institutions and OFIs in general, for which source data are not normally comprehensive and timely), which may impact the counterpart data coverage for the household and non-financial corporation sectors.

There is a close alignment of quarterly requirements (ECB Guideline on quarterly financial accounts) and annual requirements (from the ESA 2010 Transmission Programme) in terms of financial instrument and sector detail, although consolidated tables remain more complete for annual data. Annual financial accounts are requested twice per year, 4 and 9 months after the end of the reference year, although some countries report earlier and/or after each quarterly transmission to the ECB. The transmission of data 4 months after the reference year allows for an early compilation of the MIP indicators.

There is an increasing collaboration between the NCBs and NSIs, to integrate the quarterly and the annual financial accounts with the non-financial sector accounts. National compilers are encouraged to improve vertical consistency by implementing the recommendations of the “Report on developing a common approach to improve vertical consistency”45 in their compilation systems. As part of quality assurance, Eurostat and the ECB are monitoring the coherence between these datasets closely.

Quality assessment of output

i) Relevance and data availability, timeliness and punctuality

In annual financial accounts, completeness rates remained very high, being 100% for all Member States except France (transactions in 1995), Ireland (general government subsector detail in historic series) and Denmark (very few missing data for general government subsector before 2019). 

Concerning timeliness, annual financial accounts were transmitted by all Member States on time both at 4 and 9 months after the end of the reference year (apart from Ireland, which has a derogation to make the first transmission 6 months after the reference year instead of 4). In several cases, countries provided a quarterly update of the annual accounts.

- Data sources

Germany is working on a new system to identify OFIs in corporate balance sheet databases and has been able to verify that the largest enterprises are included or can be added manually, so that the coverage in terms of volume is considered significantly above 70%; some work is still needed to ensure full coverage. Poland should improve cross-checking with business registers or use other methods to ensure full coverage of OFIs. In Sweden, it is difficult to determine the coverage for particular OFI sub-sectors, groups of entities or instruments on the basis of existing data sources; meaning that data are incomplete and making the estimation of the missing data impossible.

Several countries do not have comprehensive direct data sources for NFCs, or access to business registers that would facilitate grossing-up techniques to achieve full coverage of intra-NFC loans and other transactions/positions that are not covered by counterpart sector information; Poland is the most prominent case of this situation. Furthermore, for Bulgaria, Czechia, Denmark, Croatia, and Romania, improving timeliness of direct data sources, could reduce revisions.

ii) Accuracy and reliability

- Revisions

Financial accounts are compiled by integrating statistical data from several sources. Differences in the availability and revisions’ practices of the various data sources create revisions. Therefore, all relevant data sources should, as much as possible, follow the HERP. Particular attention is needed to avoid any discontinuity in the time series when doing so (e.g. for time series breaks).

In general, revisions to private sector credit flow and debt are mostly related to non-financial corporation (NFC) loan financing, whereas revisions to household loan financing and NFC debt securities issuance tend to be lower. For consolidated debt of the non-financial sector, revisions were particularly high as a percentage of GDP for Cyprus, Malta and the Netherlands. For consolidated debt of the household sector, high revisions were observed for Ireland and the Netherlands.

iii) Comparability and coherence

The financial accounts are generally consistent with the requirements and conceptual framework of the ESA 2010. However, the financial account statistics are derived statistics that rely on a wide range of data sources. For the part of the accounts which are not covered by harmonised ESCB statistics, sources are not necessarily complete or fully sufficient in terms of conceptual requirements. In such cases source data are supplemented with estimations or residual calculations in order to ensure the completeness of the accounts. One area where the compilation of the financial accounts data underlying the MIP indicators is particularly affected by limited data sources is the OFI sector, for which there are generally no timely and comprehensive source statistics in place. Internal consistency

Member States achieved full internal consistency for annual financial accounts data.

- Vertical discrepancies

In several EU countries, work to ensure a good alignment of financial and non-financial accounts is being carried out, in line with the above-mentioned recommendations published in 2022. At European level, this issue is being addressed in the relevant working fora (the Working Group on Financial Accounts and Government Finance Statistics, the Expert Group on Sector Accounts, and the Task

Force on Annual Financial Accounts).46 The absolute values of vertical discrepancies based on annual data were, for 202447, above 5% of GDP in Greece, Croatia, Romania and Sweden for households (S.14), and in Estonia, Malta and Romania for non-financial corporations (S.11). In addition, vertical discrepancies based on quarterly data were also above 5% of GDP in Ireland for financial corporations (S.12).

3.3.3 Housing price statistics

The following headline indicator is included in the MIP scoreboard:

• House price index (HPI) (2015=100), nominal, 1 year % change

Changes in dwelling prices are measured by Eurostat's (nominal) HPIs.

Institutional issues

i) Legal basis

The legal basis for the compilation of house price indices in the EU is provided by Regulation (EU) 2016/792 of 11 May 2016 on harmonised indices of consumer prices and the house price index.48 This basic act is implemented by Commission Implementing Regulation (EU) 2023/1470 of 17 July 2023.49

With the exception of Greece, the nominal HPIs of EU countries are compiled by National Statistical Institutes, applying a harmonised statistical approach in terms of measurement target, coverage and index calculation. The index provided by Greece is compiled by the Central Bank and does not fully comply with the required standards in this area.

ii) Quality assurance mechanisms

Eurostat and National Statistical Institutes are working to ensure that the statistical practices used to compile national HPIs comply with methodological requirements and that good practices in this field are being followed.

A key element of the quality assurance framework is the annual submission of inventories containing detailed metadata on sources and methods used, providing Eurostat with the essential information to assess reliability and comparability.50

Eurostat implemented a compliance monitoring process in 2024, based on a process agreed with the National Statistical Institutes, to assess the quality of the HPIs, and evaluate how the concepts laid down in the Regulations, the Technical Manual51 and the best practices in the field are applied in each Member State.52 By the end of 2025, three countries had been assessed, and the corresponding

reports were published on Eurostat’s dedicated quality page for housing price statistics.53 The report for a fourth country compliance monitoring assessment is expected to be published in 2026.

iii) Policy uses

HPIs are primarily important for financial-stability related purposes and for macroeconomic analyses and forecasting.

Compilation process

With the exception of Greece, the HPI data are compiled at the national level by the National Statistical Institutes using data collected from administrative sources on dwelling transactions and from other real estate sources. Adjustments for differences over time in the characteristics of the transacted dwellings are made according to a common statistical methodology.

Quality assessment of output

i) Accuracy and reliability

On the basis of the available above-mentioned information (e.g. from the analysis of the aforementioned inventories of sources and methods), it can be judged that the level of statistical quality of the HPIs can be considered adequate.

The accuracy of source data is monitored by assessing the methodological soundness of price and weight sources and the adherence to the methodological recommendations. There is a variety of data sources both for weights and prices (administrative data, construction companies, real estate agents, etc).

- Revisions

The published HPI data may be revised to correct mistakes, to incorporate new or improved data sources or improved calculation methods. The HPI data are released quarterly, and they may include provisional data for the latest quarter. These are usually confirmed or revised to the final figures in the following quarters. Since annual indices are compiled based on quarterly indices, they are revised consistently with quarterly data revisions. Major revisions are normally released with explanatory notes.54

ii) Comparability

Comparability is ensured by the application of common definitions and appropriate methodology, as laid down in the legislation.

Eurostat assesses that the current HPIs are sufficiently accurate and comparable across countries. Existing issues are addressed by Eurostat, and, more widely, in ESS working groups or workshops.

3.3.4 Housing price statistics

The MIP scoreboard includes the following indicators from labour market statistics:

• Unemployment rate, % of labour force aged 15-74

• Labour force participation rate, % of population aged 15-64 years, 3 year change in pp

Institutional issues

i)                         Legal basis

The EU-LFS is based on European legislation since 1973. The principal legal acts, currently in force, are the Regulation (EU) 2019/1700 establishing a common framework for European social statistics relating to persons and households, based on data at individual level collected from samples, and the Commission Implementing Regulation (EU) 2019/2240 that specifies the implementation rules, technical items and content of the EU-LFS. The Commission Implementing Regulation (EU) 2019/2180 specifies the detailed arrangements and content for the quality reports pursuant to Regulation (EU) 2019/1700.

The Regulation (EU) 2019/2240 entered into force in 2021 and introduced major changes in the EU-LFS. Their impact varied among the countries depending on the distance of the previous national situation from the criteria stated in the new legislation. The goal was to achieve a better harmonisation among country results. The new regulation included the obligation for countries to provide break-free series in order to allow the continuity of the analysis and the possibility to calculate LFS-related MIP indicators in a consistent way.

All indicators are based on the definitions stated in the Resolution of the 13th International Conference of Labour Statisticians (ICLS), convened in 1982 by the International Labour Organisation (ILO), and their amendments as decided in the following ICLS occurrences: the labour force is defined as the total number of people employed or unemployed. The employed persons comprise persons aged 15 to 89 who either worked, for at least one hour, in the reference week for pay or profit, including unpaid contributing family workers, or had a work from which they were temporary absent. Unemployed persons comprise persons aged 15 to 74 who meet the following three criteria: were not employed during the reference week, are available to start work within the two weeks following the reference week and have been actively seeking work in the four weeks ending with the reference week, or had already found a job to start within the next three months and are available to start work within the two weeks following the reference week.

The data used to calculate the MIP scoreboard labour market indicators stems from the 'LFS main indicators’ series. The unemployment rate is expressed in percentage of the labour force aged 15-74, while the labour force participation rate is a three-year change in percentage points of the population aged 15-64.

ii) Quality assurance mechanisms

To monitor the quality of the EU-LFS, the following reports are drafted: a) Description of the characteristics of national surveys (annual), b) Quality report (annual).55 Reports are public and available on the website of Eurostat. Those quality reports can be considered as high level, covering the inventory of methodologies, analysis of quality and data comparability.

iii)                         Policy uses

The EU-LFS is the most important source of official statistics on labour markets in the European Union. Some key EU policy initiatives rely on EU-LFS data to monitor progress. For example, the European Pillar of Social Rights Action Plan sets as one of its targets for 2030 to reach a 78 % employment rate in the EU. The LFS-based monthly unemployment rate is an important short-term economic indicator.

Compilation process

The EU-LFS is a quarterly survey used to produce the annual figures underlying MIP headline indicators.

Annual averages of quarterly data, in levels, are produced as simple averages of the quarterly levels. Rates are then calculated from the averaged levels according to their formula.

Quality assessment of output

i) Accuracy and reliability

The overall accuracy of the EU-LFS is high. The survey covers persons in private households to ensure comparable coverage for all countries. While the sampling design is chosen on a country-by-country basis, specific precision requirements must be followed by all countries according to the regulation. Regardless of the sampling method, the data records at Eurostat represent the entire resident population in private households.

The results are subject to the usual types of errors associated with sampling techniques and interviews. Sampling and non-sampling errors are calculated for each country and documented in the publication ‘Quality Report of the European Union Labour Force Survey’.

Two of the most important indicators for the assessment of non-sampling error of the EU-LFS are unit non-response rate and the proxy rate. For the first one, the lower the unit non-response rate is, the more accurate the survey, as the indicator shows the level of the missing information through the ratio of the number of units for which data for no variable have been collected to the total number of units designated for data collection. In particular, the unit non-response rate in 202456 varied among countries from less than 15 % in Austria, Cyprus, Germany, and Romania, to more than 50 % in Sweden, Denmark, Ireland and the Netherlands, and reaching 57.2 % in Sweden. The median country was Czechia with 30.6 %. One cause of such a difference may be that the EU-LFS is not a compulsory survey in all countries, which means that in several countries there is no legal obligation for the citizens to answer the survey, so in general countries in which the survey is not compulsory have higher unit non-response rates. Looking at the development across five years in unit non-response rates, most countries saw an increase in 2024 compared with 2019.

As for the proxy rate, it is defined as the percentage of proxy interviews among all interviews, where a proxy interview is an interview with someone (e.g. one member of the household) other than the person from whom information is being sought, so a lower proxy rate means the survey is more accurate because more information is directly collected from the concerned person. During the five years before 2024, the proxy rate for the EU as a whole improved, although slightly, as it showed a decrease from 33.1 % in 2019 to 29.4% in 2024.57 By country, the proxy rate in 2024 varied from less than 15 % in Luxembourg, the Netherlands, Sweden, Denmark and Finland (in Luxembourg and the Netherlands it was 0%), to more than 45 % in Spain, Slovakia and Portugal and reaching 48.8 % in Slovenia. In this case, the large difference might be due to the sample unit of the survey: in countries in which the sample unit is the individual person the proxy rate is much lower, while in countries in which the sample unit is the entire household, the proxy rate is higher, since one person can answer to the questions for the other members of the same household. Countries which have individual person sample units are Denmark, Luxembourg, the Netherlands, Finland and Sweden.

EU-LFS figures fulfil the Eurostat requirements concerning reliability.

-   Revisions

Revisions of previously released non-seasonally adjusted data based on EU-LFS are not expected, unless major errors are identified in the data delivered or in their processing. Exceptional revisions to back series may happen e.g. after new estimates of population from a population census, or corrections due to break corrections.

The new Framework Regulation for the production of European statistics relating to persons and households58, covering also the EU-LFS, was approved in 2019 and implemented by NSIs by 2021. More information about the methodology of correction for breaks in time series can be found in EU labour force survey - correction for breaks in time series - Statistics Explained.

ii) Comparability – over time

Regulation (EU) 2019/1700 came into force on 1 January 2021 and induced a break in the EU-LFS time series for several EU Member States. To monitor the evolution of inter alia employment and unemployment despite of the break in the time series, Member States assessed the impact of the break in their country and computed impact factors or break-corrected data for a set of indicators.

Thereby, break-corrected data are available for the EU-LFS main indicators, including those used for MIP.

The spread of COVID-19 across Europe in 2020-2021 led to a halt of field activities, resulting in decreased data collection, higher non-response rates, and changes in interview modes. Despite these challenges, Eurostat provided guidance and support to NSIs through methodological papers. This approach allowed for comparative analysis over time and between countries, enabling users to evaluate the impact of the crisis on the labour market.

iii) Comparability – geographical

Comparability of the EU-LFS across countries is considered as high and is achieved through various regulations ensuring harmonisation of concepts, definitions and methodologies. Regulation (EU) 2019/1700 and its Commission Implementing Regulation (EU) 2019/2240 further enhance the comparability between countries, with namely the input harmonisation of employment and unemployment.

A high level of comparability across the EU-LFS participating countries is explicitly ensured by:

(a) Use of the same definitions for all countries;

(b) Transmission to Eurostat of the same list of variables with the same coding;

(c) Same flow for questions determining the labour status (in line with the recommendations of the International Labour Organisation);

(d) Provision (by Eurostat) of model questions to be applied as closely as possible by countries in their national questionnaire;

(e) Use of common classifications (e.g. NACE for economic activity);

(f) Central processing of data, done by Eurostat.

17 Reliability is defined in principle 12 of the European Statistics Code of Practice and ESCB Public Commitment on European Statistics.

18 Coherence and comparability are defined in principle 14 of the European Statistics Code of Practice and ESCB Public Commitment on European Statistics.

19 Regulation (EU) No 549/2013 of the European Parliament and the Council of 21 May 2013 on the European system of national and regional accounts in the European Union.

20 Regulation (EU) 2023/734 of the European Parliament and of the Council of 15 March 2023 amending Regulation (EU) No 549/2013 on the European system of national and regional accounts in the European Union and repealing 11 legal acts in the field of national accounts.

21 Regulation (EU) 2019/516 of the European Parliament and of the Council of 19 March 2019 on the harmonisation of gross national income at market prices and repealing Council Directive 89/130/EEC, Euratom and Council Regulation (EC, Euratom) No 1287/2003 (GNI Regulation).

22 Since GNI equals GDP minus primary income payable by resident units to non-resident units plus primary income receivable by resident units from the rest of the world (GDP + net primary income received from ROW = GNI), the GNI verification proceduresimplicitly cover the verification of GDP and all its components.

23 Commission Implementing Regulation (EU) 2016/2304 of 19 December 2016 on the modalities, structure, periodicity and assessment indicators of the quality reports on data transmitted pursuant to Regulation (EU) No 549/2013 of the European Parliament and of the Council.

24 Quality report on National and Regional Accounts (europa.eu)..

25 Eurostat thematic section on ESA 2010 - data revision.

26 Guideline of the ECB of 9 December 2011 on the statistical reporting requirements of the European Central Bank in the field of external statistics (ECB/2011/23),  OJ L 65, 3.3.2012, p. 1.

27 Guideline of the ECB of 30 July 2013 amending Guideline ECB/2011/23 on the statistical reporting requirements of the ECB in the field of external statistics (ECB/2013/25),  OJ L 247, 18.9.2013, p. 38.

Guideline (EU) 2016/231 of the ECB of 26 November 2015 amending Guideline ECB/2011/23 on the statistical reporting requirements of the ECB in the field of external statistics (ECB/2015/39), OJ L 41, 18. 2.2016, p. 28.

Guideline (EU) 2018/1151 of the European Central Bank of 2 August 2018 amending Guideline ECB/2011/23 on the statistical reporting requirements of the European Central Bank in the field of external statistics (ECB/2018/19),  OJ L 209, 20.8.2018, p. 2.

Guideline (EU) 2020/1554 of the ECB of 14 October 2020 amending Guideline ECB/2011/23 on the statistical reporting requirements of the ECB in the field of external statistics (ECB/2020/52),  OJ L 354, 26.10.2020, p. 26-33. The Eurosystem central banks shall comply with this Guideline as from 1 July 2021.

Guideline (EU) 2024/2148 of the European Central Bank of 23 July 2024 amending Guideline ECB/2011/23 on the statistical reporting requirements of the European Central Bank in the field of external statistics (ECB/2024/21), OJ L, 7.8.2024.

28 Regulation (EC) No 184/2005 of the European Parliament and of the Council of 12 January 2005 on Community statistics concerning balance of payments, international trade in services and foreign direct investment, OJ L 35, 8.2.2005, p. 23.

29 Available on the ECB’s website.

30 Regulation (EU) 2016/1013 of the European Parliament and of the Council of 8 June 2016 amending Regulation (EC) No 184/2005 on Community statistics concerning balance of payments, international trade in services and foreign direct investment, OJ L 171, 29.06.2016 , p. 144.

31 Commission Regulation (EC) No 1055/2008 of 27 October 2008 implementing Regulation (EC) No 184/2005 of the European Parliament and of the Council, as regards quality criteria and quality reporting for balance of payments statistics, OJ L 283, 28.10.2008, p. 3.

32 See e.g. the European Commission’s quarterly reporting on price and cost competitiveness data.

33 Eurostat database - exchange rates and interest rates

34 See the Report on quality, sources and methods - 2025 and the Comparison of Consumer Price deflated REER.

35 See Eurostat thematic section on the MIP..

36 Council Regulation (EC) No 479/2009 of 25 May 2009 on the application of the Protocol on the excessive deficit procedure annexed to the Treaty establishing the European Community, OJ L 145, 10.6.2009, p. 1.

37 The EDP inventories are available on the Eurostat website.

38 Guideline ECB/2013/24 of 25 July 2013, as amended by Guidelines ECB/2020/51 of 14 October 2020 and ECB/2021/20 of 29 April 2021: consolidated version.

39 ECB Statistics Quality Framework (SQF).

40 ECB sector accounts webpage.

41 Quality report on national and regional accounts – 2024 data transmissions – 2025 edition.

42 MIP quality section on the CMFB website.

43 The importance of the analysis of OFIs was emphasised in “Non-bank financial intermediation in the euro area: implications for monetary policy transmission and key vulnerabilities”, Occasional Paper Series, No 270, ECB, revised December 2021. For further details see, “Other financial institutions explained”.

44 CB Regulations impose statistical reporting obligation on MFIs, Investment funds, financial vehicle corporations engaged in the securitisation of assets (FVCs) and Insurance corporations and Pension funds resident in the euro area:

Regulation (EU) No 1071/2013 of the ECB of 24 September 2013 concerning the balance sheet of the monetary financial institutions sector (recast) (ECB/2013/33), OJ L 297, 7.11.2013, p. 1.

Regulation (EU) no 1073/2013 of the ECB of 18 October 2013 concerning statistics on the assets and liabilities of investment funds (recast) (ECB/2013/38), OJ L 297, 7.11.2013, p. 73.

Regulation (EU) no 1075/2013 of the ECB of 18 October 2013 concerning statistics on the assets and liabilities of financial vehicle corporations engaged in securitisation transactions (recast) (ECB/2013/40),), OJ L 297, 7.11.2013, p. 107.

Regulation (EU) No 1374/2014 of the ECB of 28 November 2014 on statistical reporting requirements for insurance corporations (ECB/2014/50), OJ L 366, 20.12.2014, p. 36.

Regulation (EU) No 2018/231 of the ECB of 26 January 2018 on statistical reporting requirements for pension funds (ECB/2018/2),), OJ L 45, 17.2.2018, p. 3.

45 Report on developing a common approach to improve vertical consistency

48 Regulation (EU) 2016/792 of the European Parliament and of the Council of 11 May 2016 on harmonised indices of consumer prices and the house price index, and repealing Council Regulation (EC) No 2494/95, OJ L 135, 24.5.2016, p. 11–38.

49 Commission Implementing Regulation (EU) 2023/1470 of 17 July 2023 laying down the methodological and technical specifications in accordance with Regulation (EU) 2016/792 of the European Parliament and of the Council as regards the house price index and the owner-occupied housing price index and amending Commission Regulation (EU) 2020/1148 (Text with EEA relevance).

50 HPI metadata are available from Eurostat’s website: House price and sales index (prc_hpi_inx).

51 Technical manual on Owner-Occupied Housing and House Price Indices.

52 This process is described in the following link: Compliance Monitoring for the House Price Index and Owner-Occupied Housing Price Index.

53 Eurostat thematic section on housing price statistics.

54 See ’Country revisions‘ section at Eurostat thematic section on housing price statistics.

55 All these reports are available at Eurostat thematic section on LFS.

56 Preliminary results.

57 Preliminary results.

58 Regulation (EU) 2019/1700 of the European Parliament and of the Council of 10 October 2019 establishing a common framework for European statistics relating to persons and households, based on data at individual level collected from samples, amending Regulations (EC) No 808/2004, (EC) No 452/2008 and (EC) No 1338/2008 of the European Parliament and of the Council, and repealing Regulation (EC) No 1177/2003 of the European Parliament and of the Council and Council Regulation (EC) No 577/98.

• Current account balance as % of GDP, 3 year average (BOP-IIP / NA)

• Net international investment position as % of GDP (BOP-IIP / NA)

• Real effective exchange rate, 42 trading partners, HICP/CPI deflator, 3 year % change

• Export performance against advanced economies, 3 year % change (BOP-IIP)

• Nominal unit labour cost (2015=100) per hour worked, 3 year % change (NA)

• General government gross debt (EDP) as % of GDP (EDP / GFS)

• Household debt (incl. NPISH), consolidated, % of GDP (FA / NA)

• NFC debt, consolidated (FA / NA)

• Household credit flow (incl. NPISH), consolidated, % of debt stock (t-1) (FA / NA)

• NFC credit flow (excl. FDI), consolidated, % of debt stock (t-1) excl. FDI (FA / NA / BOP-IIP)

• House prices index (2015=100), nominal, 1 year % change (Housing price statistics)

• Unemployment rate, % of labour force aged 15-74 (LFS)

• Labour force participation rate, % of total population aged 15-64 years, 3 years change in pp (LFS)

Note: NA: National accounts; BOP: Balance of payments; IIP: International investment position; FA: Financial accounts; EDP / GFS: Excessive deficit procedure / Government finance statistics; LFS: Labour Force Survey .

• Net international investment position excluding non-defaultable instruments – % of GDP

• Net lending-borrowing (current plus capital account) – % of GDP

• Net trade balance of energy products – % of GDP

• Real GDP per capita – EUR

• Gross fixed capital formation – % of GDP

• Gross domestic expenditure on R&D – % of GDP

• Export market share (% of world exports) – 3 year % change

• Labour productivity (per hour worked) – 1 year % change

• Core inflation differential vis-à-vis the euro area – percentage points

• Household debt, consolidated – % of GDI

• Gross non-performing loans, domestic and foreign entities – % of gross loans

• Tier-1 capital ratio of banking sector – % of risk weighted assets

• Return on equity of banking sector – %

• Standardised house price-to-income ratio – % of long-term average (2000-current)

• Building permits – m² per 1000 inhabitants

• Long-term unemployment rate – % of labour force aged 15-74

• Youth unemployment rate – % of labour force aged 15-24

• Employment rate – % of population aged 20-64

• Young people neither in employment nor in education or training – % of population aged 15-29

• People at risk of poverty or social exclusion – % of total population

• People at risk of poverty after social transfers – % of total population

• Severely materially and socially deprived people – % of total population

• People living in households with very low work intensity – % of population aged 0-64