Material flow accounts (env_ac_mfa)

Reference Metadata in Single Integrated Metadata Structure (SIMS)

Compiling agency: Eurostat, the statistical office of the European Union


Eurostat metadata
Reference metadata
1. Contact
2. Metadata update
3. Statistical presentation
4. Unit of measure
5. Reference Period
6. Institutional Mandate
7. Confidentiality
8. Release policy
9. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment
Related Metadata
Annexes
Footnotes
National metadata



For any question on data and metadata, please contact: Eurostat user support

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1. Contact Top
1.1. Contact organisation

Eurostat, the statistical office of the European Union

1.2. Contact organisation unit

E2: Environmental statistics and accounts; sustainable development

1.5. Contact mail address

L-2920 Luxembourg, LUXEMBOURG


2. Metadata update Top
2.1. Metadata last certified 18/06/2024
2.2. Metadata last posted 18/06/2024
2.3. Metadata last update 18/06/2024


3. Statistical presentation Top
3.1. Data description

Economy-wide material flow accounts (EW-MFA) provide an aggregate overview, in thousand tonnes per year, of the material flows into and out of an economy. EW-MFA cover solid, gaseous, and liquid materials, except for bulk flows of water and air. Like the system of national accounts, EW-MFA constitute a multi-purpose information system. The detailed material flows provide a rich empirical database for numerous analytical purposes. Further, EW-MFA are used to derive various material flow indicators.

 

This metadata refers to the following six datasets based on Eurostat’s EW-MFA data collection:

  • Material flow accounts (env_ac_mfa): this dataset provides certain flow aggregates in a  detailed breakdown by materials as mandatorily requested according to Regulation (EU) 691/2011, namely domestic extraction of materials, physical imports, and physical exports – and derived indicators such as e.g. domestic material consumption (DMC).
  • Material flow accounts - domestic processed output (env_ac_mfadpo): this dataset provides a material flow aggregate termed 'domestic processed output' in a breakdown by detailed materials.
  • Material flow accounts - balancing items (env_ac_mfabi): this dataset provides balancing items which are required to articulate a consistent material input-output balance of a national economy.
  • Resource productivity (env_ac_rp): this dataset provides ratios of gross domestic product (GDP) over domestic material consumption (DMC) in various units of measure (see also item 4 of metadata). The term 'resource productivity' designates an indicator that reflects the GDP generated per unit of resources used by the economy. This is typically a macro-economic concept that can be presented alongside labour or capital productivity.
  • Material import dependency (env_ac_mid): this dataset provides the ratio of imports (IMP) over direct material inputs (DMI) in percentage. The term 'material import dependency' shows the extent to which an economy relies upon imports in order to meet its material needs. Material import dependency cannot be negative or higher than 100%. Values equal to 100% indicate that there are no domestic extractions.
  • Material flow accounts - main indicators (env_ac_mfain): this dataset provides highly aggregated indicators derived from EW-MFA:

- domestic extraction (DE): DE indicates the total amount of material extracted by resident units from the natural environment for further processing in the economy;

- imports (IMP): imports of products in their simple mass weight;

- exports (EXP): exports of products in their simple mass weight;

- physical trade balance (PTB): physical imports minus physical exports;

- direct material input (DMI): DMI indicates the direct input of material into the economy. DMI includes all materials which are of economic value and which are available for use in production and consumption activities and it is calculated as the sum of domestic extraction plus physical imports: DMI = DE + IMP;

- domestic material consumption (DMC): DMC indicates the total amount of material actually consumed domestically by resident units (‘apparent consumption’). DMC of a given economy can be calculated as direct material input minus physical exports: DMC = DMI – EXP. In general, DMC is additive across countries. However, this feature does not apply to Eurostat's EW-MFA dataset due to the methodology for calculating physical trade for the aggregated EU economy (see point 18.5 of metadata);

- domestic processed output (DPO): DPO indicates the amounts of solid, liquid and gaseous materials (excluding water and respiratory carbon dioxide) supplied by the national economy and taken up by the natural environment, particularly by the atmosphere;

- balancing items (BI): balancing items enable the balancing of material input and output related to a national economy. Two groupings of balancing items are distinguishable: first, BI to be added to material input, such as oxygen for combustion processes and respiration, and nitrogen; secondly, BI to be added to material output, such as water vapour from combustion and gases from respiration. 'Total BI' designates the difference between 'BI: input side' and 'BI: output side', i.e. 'BI (input -output)';

- net additions to stock (NAS): NAS is a measure for the ‘physical growth of the economy’. Materials in form of buildings, infrastructures, durable goods such as e.g. cars, industry machinery, or household appliances are added to the economy’s material stock each year (gross additions), and old materials are removed from stock as buildings are demolished, and durable goods disposed of (removals). NAS is approximated using the following equation: NAS = DMC - DPO + BI (input-output).

3.2. Classification system

EW-MFA record physical flows of materials in a breakdown by type of flow and in a breakdown by type of material.

Type of flows are e.g. domestic extraction (i.e. natural input flows into economy), domestic processed output (i.e. residual flows towards environment), imports and exports (i.e. product flows between resident units and non-residents).

The breakdown by type of material employs a classification of materials which is addressed in this section. The classification of materials MF.1 to MF.6 is mentioned in the legal base of EW-MFA, namely Regulation (2011) 691, Annex III.

The EW-MFA classification of materials is hierarchical with main material flow categories (1-digit level); i.e. MF.1 to MF.8. Each main category is further broken down, maximal down to 4-digit-level (see also the EW-MFA data structure in Annexes):

  • 1-digit: material category;
  • 2-digit: material class;
  • 3-digit: material group;
  • 4-digit: material sub-group.

The type of material corresponds in a certain way to the type of flow. Most material categories have a one-to-one correspondence to a certain type of flow. The Annex presents these correspondences by cross-tabling the type of material (rows) with the type of flow (columns A, B, D, F and G, which also correspond to the respective EW-MFA questionnaire tables).

The first four material categories MF.1 to MF.4 were initially designed for characterising domestic extraction of materials. The material categories MF.1 to MF.4 are also applied to physical imports and exports. The material categories MF.5 and MF.6 apply to physical imports and physical exports. Material category MF.7 applies exclusively to domestic processed output; while MF.8 solely applies to balancing items.

The classification of MF.1 'biomass', MF.2 'metal ores', MF.3 'non-metallic mineral', and MF.4 'fossil energy materials/carriers' is based pragmatically on the statistical data sources employed to compile domestic extraction for these type of materials, e.g. agriculture, forestry, fishery, and energy statistics. A notable particularity of EW-MFA is the attribution of type of material to physical imports and physical exports. Physical imports and exports are flows of products for which one commonly employs product classifications such as e.g. the Classification of Products by Activity (CPA) or Combined Nomenclature (CN). In EW-MFA traded products are presented by type of material and not by product classification. For this, each CN code is assigned to one and only one MF class. For raw products (e.g. output from mining) this assignment to one and only one MF class is straightforward. However, the further processed the goods are the more they are composed of more than one material. The material-wise assignment of semi-manufactured and finished goods is ambiguous.

Domestic processed outputs are hierarchically classified. Five categories are distinguished at 2-digit level:

  • MF.7.1 Emissions to air;
  • MF.7.2 Waste disposal to the environment;
  • MF.7.3 Emissions to water;
  • MF.7.4 Dissipative use of products;
  • MF.7.5 Dissipative losses.

The final category (MF.8) is for the balancing items on the input and output side. Balancing items are a particularity of EW-MFA. They are only introduced for balancing purposes, i.e. needed to establish a material balance for the entire national economy, and are not to be included in the indicators derived from the accounts. Balancing items include two categories: items to be added to material inputs such as oxygen for combustion processes and respiration, and nitrogen; items to be added to material outputs such as water vapour from combustion and gases from respiration. On the input side balancing items constitute natural inputs; on the output side balancing items constitute residuals.

3.3. Coverage - sector

The data refer to national economies as defined in the system of national accounts.

3.4. Statistical concepts and definitions

Conceptually economy-wide material flow accounts (EW-MFA) belong to the international system of environmental economic accounting (SEEA-Central Framework). Furthermore, EW-MFA is one of several physical modules of Eurostat's programme on European environmental economic accounts. It is covered by Regulation (EU) No. 691/2011 on European environmental economic accounts.

EW-MFA are closely related to concepts and definitions of national accounts. Most notably they follow the residence principle, i.e. they record material flows related to resident unit's activities, regardless where those occur geographically.

Further methodological guidelines are provided in various publications by Eurostat (see Eurostat website > Environment > Methodology, heading: 'Material flows and resource productivity').

3.5. Statistical unit

Statistical units differ, depending on the different data sources (e.g. agriculture, forestry and fishery statistics, production statistics, geological surveys, energy statistics, international trade in goods etc.) used to compile EW-MFA.

3.6. Statistical population

EW-MFA include all materials (excluding water and air) crossing the system boundary of the national economy of the reporting country. The latter is demarcated by the conventions of the national accounting system (resident units). In Eurostat's EW-MFA material inputs to the economy cover extractions of natural resources (excluding water and air) from the natural environment and imports of material products (goods) from the rest of the world economy (ROW). Material outputs are disposals of materials to the natural environment and exports of material products and waste to the ROW.

3.7. Reference area

European Union (as aggregate and for each Member State); EFTA countries; EU candidate countries, UK.

3.8. Coverage - Time

Dataset 'material flow accounts' (env_ac_mfa): data are annual and may start with the year 1990 (EU aggregate since 2000).

Dataset 'material flow accounts - domestic processed output' (env_ac_mfadpo): data are annual and may start with the year 1990 (EU aggregate since 2000).

Dataset 'material flow accounts - balancing items' (env_ac_mfabi): data are annual and may start with the year 1990 (EU aggregate since 2000).

Dataset 'material flow accounts - main indicators' (env_ac_mfain): data are annual and may start with the year 1990 (EU aggregate since 2000).

Dataset 'resource productivity' (env_ac_rp): data are annual and may start with the year 2000 (EU aggregate since 2000).

Dataset 'material import dependency' (env_ac_mid): data are annual and may start with the year 1990 (EU aggregate since 2000).

3.9. Base period

Index series are provided for the reference year 2000 (see below item 4 "Unit of measure").


4. Unit of measure Top

The datasets 'material flow accounts' (env_ac_mfa) and 'material flow accounts - main indicators' (env_ac_mfain) provide data in thousand tonnes, tonnes per capita (using the demographic indicator 'Average population - total') and Indices (2000=100).

 

The datasets 'material flow accounts - domestic processed output' (env_ac_mfadpo) and 'material flow accounts - balancing items' (env_ac_mfabi) provide data in thousand tonnes, tonnes per capita (using the demographic indicator 'Average population - total').

 

Various units are employed for the data set 'resource productivity' (env_ac_rp) depending on which type of GDP (current price or volume figures) has been used for calculating the ratio:

  • 'Euro per Kilogram' (GDP in current prices), to be used to analyse a single country at one point in time (for one particular year);
  • 'PPS per Kilogram' (GDP in current prices expressed in Purchasing Power Standards). Purchasing Power Standards are fictive 'currency' units that remove differences in purchasing power, hence eliminate differences in price levels across countries; to be used when comparing across countries at one point in time;
  • 'Euro 2015-based chain linked volumes per kilogram' (GDP in chain-linked volumes normalised to 2015 prices). Volume figures show the development of aggregates excluding inflation; to be used when comparing over time (various years) one single country;
  • 'Index, 2000=100' (based on GDP in chain-linked volumes normalised to 2000 prices).

 

The dataset 'material import dependency' (env_ac_mid) provides data in percentage (physical imports in relation to direct material inputs (DMI); see item 3.1 above).


5. Reference Period Top

The data refer to the calendar years.


6. Institutional Mandate Top
6.1. Institutional Mandate - legal acts and other agreements

Economy-wide material flow accounts (EW-MFA) are legally covered by Regulation (EU) 691/2011 on European Environmental Economic Accounts.

6.2. Institutional Mandate - data sharing

Not applicable.


7. Confidentiality Top
7.1. Confidentiality - policy

Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.

7.2. Confidentiality - data treatment

Confidential data are flagged 'c)' and not published. For aggregates of confidential data, Eurostat's rules for confidentiality are respected. 

 


8. Release policy Top
8.1. Release calendar

The deadline for the annual EW-MFA questionnaire is 30 April (T = deadline).  Data are published ca. 3 months later, around end of June, including early estimates for the flow types domestic extraction, imports, and exports.

8.2. Release calendar access

Not applicable.

8.3. Release policy - user access

In line with the Community legal framework and the European Statistics Code of Practice Eurostat disseminates European statistics on Eurostat's website (see item 10 - 'Accessibility and clarity') respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users.


9. Frequency of dissemination Top

See above item 8.1.


10. Accessibility and clarity Top
10.1. Dissemination format - News release

A news release on resource productivity is published every year in July via the Eurostat web site.

10.2. Dissemination format - Publications

Statistics explained articles: Material flow accounts and resource productivity, Physical imports and exports, Resource productivity statistics.

10.3. Dissemination format - online database

Please consult data on Eurostat's online database: Material flows and resource productivity (env_mrp)

10.3.1. Data tables - consultations

Consultations of Eurostat online database 'EUROBASE' – data sets

This quality performance indicator presents the number of consultations of online data sets taking into account the following parameters:

- DATASETS = 'env_ac_mfa', 'env_ac_mfadpo', 'env_ac_mfabi', 'env_ac_mfain', 'env_ac_rp'

- REFERENCE PERIOD = 2018, 2019, 2020, 2021 and 2022 monthly

   

 

10.4. Dissemination format - microdata access

Not applicable.

10.5. Dissemination format - other

See point 3.1 of metadata.

10.5.1. Metadata - consultations

Consultations of Eurostat online database 'EUROBASE' - metadata

This quality performance indicator presents the number of consultations of online metadata taking into account the following parameters:

- METADATA = 'ENV_AC_MFA_ESMS.htm' and 'ENV_AC_MFA_SIMS.htm'

- REFERENCE PERIOD = 2018, 2019, 2020, 2021. 2022 and 2023 monthly

 

  

 

10.6. Documentation on methodology

Information (e.g. manuals, electronic questionnaires) is available on Eurostat's website.

10.6.1. Metadata completeness - rate

Metadata completeness - rate

This quality performance indicator presents the ‘ratio of completeness’ by country. It is defined as the number of metadata elements provided by countries in relation to the total number of metadata elements applicable.

The following parameters are taken into account:

- GEO = EU, Member States

- REFERENCE PERIOD = 2023 data collection cycle

- DEADLINE = 30 April 2023 (metadata received); 30 July 2023 (metadata already published)

- INDIC = National metadata file (SIMS)

- Ratio of completeness = number of metadata elements provided / total number of metadata elements applicable

The total number of metadata elements applicable include the following:

- Statistical outputs concepts - 2.1, 2.2, 2.3, 3.1,3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4, 7.1, 8.1, 8.2, 8.3, 9

- Statistical processes concepts - 5, 6.1, 6.2, 7.2, 17.1, 17.2, 18.1.1, 18.1.2, 18.2, 18.3, 18.4, 18.5.1, 18.5.2, 18.5.3, 18.5.4, 18.5.5, 18.5.6, 18.6

- Quality concepts - 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7, 11.1, 11.2, 12.1, 12.2, 12.3, 13.1, 13.2, 13.3, 14.1, 14.2, 15.1, 15.2, 15.3, 15.4, 16

 

Countries           

Ratio of completeness

(before Eurostat's validation)

Ratio of completeness disseminated

(after Eurostat's validation)

EU - Average completeness rate 98% 100%
Austria 100% 100%
Belgium 100% 100%
Bulgaria 100% 100%
Cyprus 100% 100%
Czechia 98% 100%
Germany  97% 100%
Denmark  100% 100%
Estonia  98% 100%
Greece 98% 100%
Spain  100% 100%
Finland  98% 100%
France 95% 100%
Croatia 97% 100%
Hungary  100% 100%
Ireland  98% 100%
Italy  98% 100%
Lithuania  98% 100%
Luxembourg 97% 100%
Latvia  98% 100%
Malta  100% 100%
Netherlands  98% 100%
Poland  98% 100%
Portugal  98% 100%
Romania  98% 100%
Sweden  97% 100%
Slovenia  98% 100%
Slovakia  100% 100%
10.7. Quality management - documentation

With this metadata file at hand Eurostat provides an overall evaluation of EW-MFA data quality based on national quality reports sent by Member States.


11. Quality management Top
11.1. Quality assurance

To ensure quality of EW-MFA data Eurostat implemented the following quality assurance elements:

1) Methodological guidelines to assist countries in compiling and providing internationally harmonised EW-MFA;

2) A wide range of validation procedures to check the quality of data received. The validation procedures check:

  • completeness;
  • symbols;
  • internal consistency;
  • correctness of footnotes and confidentiality;
  • plausibility of reported time series (annual change rates);
  • plausibility of revisions;
  • external consistency (cross-domain plausibility).

3) Gap-filling of missing statistical information (see also item 18.5).

11.2. Quality management - assessment

Quality management is good. Validation procedures, estimation of missing statistical data (gap-filling) and quality reporting are in place. The working group on environmental accounts, encompassing representatives of all Member States, Eurostat and other stakeholders, discusses quality improvements.

EW-MFA is a relatively mature data collection, which started in 2013 according to Regulation 691/2011. Data quality could still be improved in particular for some quantitative important elements, which need to be estimated (e.g. sand and gravel extraction, grazed biomass).

Each year around June/July Eurostat produces and publishes early estimates of the domestic extraction of materials for the preceding year (e.g. in June 2018 for reference year 2017). Each year, Eurostat provides a report that assesses the quality of the early estimates by analysing the estimation error.

Please find the most recent reports (PDF) annexed here:



Annexes:
MFA_quality_early_estimates_refYear_2017_report
MFA_quality_early_estimates_refYear_2018_report
MFA_quality_early_estimates_refYear_2019_report
MFA_quality_early_estimates_refYear_2020_report
MFA_quality_early_estimates_refYear_2021_report


12. Relevance Top
12.1. Relevance - User Needs

Users of economy-wide material flow accounts (EW-MFA) and derived indicators include policy makers in environmental ministries, environmental organisations, researchers, students and interested citizens.

More information on the policy context can be found here.

12.2. Relevance - User Satisfaction

There are no systematic studies of user satisfaction. Eurostat has regular hearings with European policymakers and contacts with the research community and other stakeholders to monitor the relevance of the statistics produced and identify new priorities.

12.3. Completeness

Data are complete for all Member States and EU aggregates starting from the year 2000.

12.3.1. Data completeness - rate

Data completeness rate, in %

This quality performance indicator presents data completeness rates by geographical entity taking into account the following parameters:

- GEO = EU, Member States

- INDIC_ENV = DE, IMP, EXP

- REFERENCE PERIOD = 5 legally mandatory reference years

Remarks:

- Indicator completeness rate = reported legally mandatory cells / expected mandatory cells

- The range of expected cells encompasses data points for which countries must deliver numeric values based on legal base.

- Data points (cells) with s-flag (Eurostat estimate) are considered as ‘delivered by country’.

 

                                  Number of reported mandatory cells:

Countries:                         

Default cells of the questionnaire

(Tables A, B and D)

First delivery of questionnaire

(deadline: 30 April)

Finally validated questionnaire Data completeness rate of the first delivered questionnaire Data completeness rate of the finally validated questionnaire
EU - Average completeness rate 975 974.93 975 99.99 100
Austria 975 975 975 100 100
Belgium  975 975 975 100 100
Bulgaria 975 975 975 100 100
Cyprus 975 975 975 100 100
Czechia 975 975 975 100 100
Germany  975 975 975 100 100
Denmark  975 975 975 100 100
Estonia  975 975 975 100 100
Greece 975 975 975 100 100
Spain  975 975 975 100 100
Finland  975 974 975 99.90 100
France 975 975 975 100 100
Croatia 975 974 975 99.90 100
Hungary  975 975 975 100 100
Ireland  975 975 975 100 100
Italy  975 975 975 100 100
Lithuania  975 975 975 100 100
Luxembourg 975 975 975 100 100
Latvia  975 975 975 100 100
Malta  975 975 975 100 100
Netherlands  975 975 975 100 100
Poland  975 975 975 100 100
Portugal  975 975 975 100 100
Romania  975 975 975 100 100
Sweden  975 975 975 100 100
Slovenia  975 975 975 100 100
Slovakia  975 975 975 100 100



13. Accuracy Top
13.1. Accuracy - overall

Economy-wide material flow accounts (EW-MFA) are compiled from a wide range of data sources (e.g. agriculture, forestry and fishery statistics, production statistics, geological surveys, energy statistics, foreign trade statistics etc.). The overall accuracy is considered good.

13.2. Sampling error

Not applicable because data are not based on a sample survey.

13.2.1. Sampling error - indicators

Not applicable because data are not based on a sample survey.

13.3. Non-sampling error

Not applicable.

13.3.1. Coverage error

Not applicable.

13.3.1.1. Over-coverage - rate

Not applicable.

13.3.1.2. Common units - proportion

Not applicable.

13.3.2. Measurement error

Not applicable.

13.3.3. Non response error

Not applicable.

13.3.3.1. Unit non-response - rate

Not applicable.

13.3.3.2. Item non-response - rate

Not applicable.

13.3.4. Processing error

Not applicable.

13.3.5. Model assumption error

Not applicable.


14. Timeliness and punctuality Top
14.1. Timeliness

Eurostat collects economy-wide material flow accounts from national statistical institutes (NSI) via an annual questionnaire (see 6.1 for legal base). Reporting deadline for the questionnaire is 30 April of the year T (T = deadline and year into which the deadline falls). The most recent mandatory reference year for which NSI have to report is T-2 years. Only a few NSI report data for one more year (T-1y). For domestic extraction and physical imports and exports, Eurostat produces and publishes early estimates for year T-1y.

14.1.1. Time lag - first result

Not applicable.

14.1.2. Time lag - final result

Not applicable.

14.2. Punctuality

All Member States are currently able to meet the transmission deadline. Eurostat publishes preliminary aggregates using, if necessary, estimates for missing countries.

14.2.1. Punctuality - delivery and publication

 Punctuality of data delivery by country and Eurostat data dissemination

This quality performance indicator presents several metrics related to the punctuality of data delivery and publication taking into account the following parameters:

- GEO = EU, Member States

- INDIC_ENV = DE, IMP, EXP

- REFERENCE PERIOD = 2023 data collection

- DEADLINE FOR DELIVERY = 30 April 2023

- DATE OF DATA DISSEMINATION = 29 June 2023

 

Countries            Punctuality of delivery

Questionnaire for validation 

with country

Questionnaire for validation with Eurostat

(& contractors)

Duration of validation - overall Punctuality of Eurostat data dissemination
  calendar days after the deadline calendar days before the deadline working days working days working days number of working days between finishing of validation and dissemination
EU (average) 2 27 8 24 32 26
Austria 0 10 3 5 8 40
Belgium  0 2 2 10 12 30
Bulgaria 0 2 2 15 17 25
Croatia 0 110 13 79 92 25
Cyprus 0 4 17 7 24 20
Czechia 0 104 10 82 92 21
Denmark  0 13 6 8 14 37
Estonia  0 130 11 74 85 40
Finland 0 5 10 15 25 20
France 0 3 4 26 30 13
Germany 0 3 5 13 18 25
Greece 0 2 8 15 23 19
Hungary 0 45 2 23 25 45
Ireland 57 0 1 2 3 3
Italy 0 3 8 12 20 23
Latvia 0 4 1 22 23 21
Lithuania  0 4 34 4 38 6
Luxembourg 0 3 12 20 32 11
Malta 0 68 1 37 38 49
Netherlands 0 2 11 14 25 17
Poland 0 4 5 14 19 25
Portugal 0 130 2 74 76 49
Romania 0 3 22 4 26 17
Slovakia 0 33 10 16 26 36
Slovenia 0 16 2 13 15 37
Spain 0 2 18 9 27 15
Sweden 0 26 8 29 37 20

 

 


15. Coherence and comparability Top
15.1. Comparability - geographical

The comparability across countries is good due to clear statistical concepts and definitions. However, the national data sources used for the compilation of EW-MFA by the national statistical institutes may differ in scope and quality.

15.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable because physical imports and exports as recorded in EW-MFA are not specified by origin and/or destination.

15.2. Comparability - over time

The comparability over time is good due to clear statistical concepts and definitions. Revisions in methodology are usually applied backwards to the entire time series.

15.2.1. Length of comparable time series

Length of comparable time series

This quality performance indicator presents the number of ‘breaks in time series’ taking into account the following parameters:

- GEO = EU Member States

- INDIC_ENV = DE, IMP, EXP

- COUNTING BREAKS IN SERIES = number of b) flag

- REFERENCE PERIOD = up from 2000; one reference year has 195 mandatory cells (data points)

mandatory reference years

 - non-mandatory reference years 

 

                                                                                             reference year:

collection cycle (publication date):     

2000

2001

2002

2003

2004

2005

2006

2007 

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

 

2018

     

2019

2020

2021

2013 data collection 

(published in July 2014)

              181 'ES'                            

2014 data collection

(published in July 2015)

 

138 'AT'; 

1'SK'

    1 'AT'     181 'ES'           2 'FR'                

2015 data collection

(published in July 2016)

 

132 'AT';

1 'SK'

    1 'AT'     181 'ES'           2 'FR'                

2016 data collection

(published in July 2017) 

  1 'SK'     1 'AT'       190 'ES'          2 'FR'                

2017 data collection

(published in July 2018) 

  1 'SK'             181 'ES'             7 'IT'            

2018 data collection

(published in July 2019) 

  1 'SK'           1 'IE' 181 'ES'             7 'IT'   2 'DE'        

2019 data collection

(published in March 2020) 

195 'AT'

4 'BE';

1 'SK'

      186 'BE' 178 'BE'  

185 'BE';

181 'ES';

15 'IT'

        1 'FR'     1 'MT' 2 'DE'        

2020 data collection

(published in March 2021) 

194 'AT';

4 'LV'

1 'SK'            

181 'ES';

15 'IT'

        1 'FR'   2 'CZ'

1 'DE';

1 'MT'

2 'DE'        
 

2021 data collection

(published in March 2022)

195 'AT';

4 'LV'

 1 'SK'            

181 'ES';

15 'IT' 

        1 'FR'   4 'DE' 2 'CZ'   1 'MT'          

2023 data collection

(published in July 2023)

195 'AT';

4 'LV'

 

 1 'SK'             

181 'ES';

15 'IT';

6 'FR' 

     102 'FR'    1 'FR'    3 'DE'

 2 'CZ';

1 'FR'

  1 'MT'  1 'CZ' 1 'CZ'    1 'FR'   

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Comparing three most recent data collection cycles: the number of b)-flag has increased between the 2021 and 2023 data collection cycles due to the change in methodology related to the trade figures for France and it has remained unchanged between the two most recent data collection cycles.    

 

 

15.3. Coherence - cross domain

Eurostat performs cross-domain plausibility checking between EW-MFA data and data from other statistical domains by verifying whether data are in accordance with certain basic criteria that serve to assess the plausibility of the given data.

In the context of 2023 data collection cycle, the following domains have been used for cross-domain plausibility checks:

- PRODCOM (production statistics)

- COMEXT (international trade in goods statistics)

- ENERGY STATISTICS

- AGRICULTURE STATISTICS

- AIR EMISSIONS ACCOUNTS.

15.3.1. Coherence - sub annual and annual statistics

Not applicable; reported EW-MFA data are only annual.

15.3.2. Coherence - National Accounts

The data are coherent with national accounts and environmental-economic accounts.

15.4. Coherence - internal

The internal coherence is very high, ensured by the accounting framework.


16. Cost and Burden Top

Depending on the level of automatisation the costs and burden range from 5 to 40 person-days per country and approx. 200 person-days for Eurostat.


17. Data revision Top
17.1. Data revision - policy

To further specify the general Eurostat revision policy, the following revision policy has been established for economy wide material flow accounts: Every year Eurostat publishes the complete time series, which may lead to revisions of data previously published.

17.2. Data revision - practice

All reported errors (once validated) result in corrections of the disseminated data.

Reported errors are corrected in the disseminated data as soon as the correct data have been validated.

Data may be published even if they are missing for certain countries or flagged as provisional or of low reliability for certain countries. They are replaced with final data once transmitted and validated. European aggregates are updated for consistency with new country data.
Aggregates and components are revised at the same time.

For domestic extraction and physical imports and exports, Eurostat produces and publishes early estimates for year T-1y in July. These data are revised in July of the following year.

17.2.1. Data revision - average size

Average absolute size of DMC revisions by country and year

This quality performance indicator presents the average size of revisions for one important EW-MFA indicator, namely DMC. The following parameters are taken into account:

- GEO = EU, Member States

- INDIC_ENV = DMC

- MATERIAL = MF. TOTAL

- UNIT = Thousand tonnes

- Number of data collection cycles: 10

Remarks:

- For each reference year (columns in below table), the absolute revision size for DMC is calculated between two consecutive collection cycles. This is done for each data collection cycle. Then, the average is calculated over the number of data collection cycles.

- Note that for reference year 2016 the average is built on six data collection cycles. For reference year 2017 the average is built on five data collection cycles and so on.

 

                                                                                                                                                                                                                                                                                reference year:
Countries:                         
2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021
EU (average) 2 187 2 017 2 309 2 265 2 561 3 055 4 278 5 024 5 005 4 439 5 846 7 052 7 200 11 136
Austria 4 373 3 725 3 974 3 765 5 956 5 203 6 628 6 046 6 730 6 946 7 005 5 121 6 861 6 560
Belgium 1 627 1 389 1 786 1 844 929 1 131 3 515 3 265 2 690 9 459 11 385 13 003 13 288 26 610
Bulgaria 56 50 45 100 691 998 1 501 944 2 032 1 648 1 327 1 858 1 887 1 906
Croatia 352 178 99 198 257 303 181 200 27 289 675 617 1 902 452
Cyprus 504 325 292 508 418 486 680 372 288 334 155 78 676 571
Czechia 0 0 1 13 22 222 102 342 728 1 304 1 174 746 3 002 579
Denmark 1 276 1 483 1 647 1 973 1 422 1 675 1 792 2 845 3 648 1 787 2 260 2 923 3 893 4 408
Estonia 613 214 443 402 517 591 1 193 842 1 207 868 1 427 1 034 1 304 2 070
Finland 197 194 6 331 5 604 6 322 10 395 9 655 8 191 12 965 11 260 17 961 25 969 37 763 51 496
France 360 369 392 600 895 1 228 5 030 1 367 3 305 6 288 7 704 9 837 13 341 55 179
Germany 8 605 8 405 9 159 11 295 14 608 13 953 19 120 28 096 27 515 17 349 38 162 40 544 21 550 6 685
Greece 8 923 7 339 5 640 4 822 3 599 3 766 2 625 3 155 3 204 4 738 4 172 6 563 6 898 6 289
Hungary 717 416 374 342 446 784 1 606 3 861 3 543 2 121 1 319 4 910 1 009 11 044
Ireland 5 046 5 506 5 001 4 513 3 118 3 637 4 184 1 929 1 020 2 158 2 970 2 383 1 950 645
Italy 4 941 5 576 3 218 5 784 7 266 8 554 23 469 27 592 17 682 6 476 3 934 7 054 7 484 20 953
Latvia 1 374 1 643 1 924 2 003 2 029 1 900 2 526 2 786 3 831 3 843 46 715 1 527 2 970
Lithuania 0 1 0 1 0 831 865 226 536 588 1 694 162 2 091 1 135
Luxembourg 301 178 150 161 182 231 255 383 683 368 207 313 631 156
Malta 15 15 18 23 23 79 44 104 95 179 409 227 277 336
Netherlands 1 616 1 198 1 423 1 018 1 799 2 074 1 049 1 827 2 205 7 132 10 155 15 453 11 054 36 338
Poland 3 520 3 791 3 457 4 051 5 220 7 271 5 215 5 830 12 991 9 677 17 976 13 409 17 660 6 732
Portugal 1 553 1 670 1 307 2 069 1 341 998 3 610 3 041 1 940 2 522 4 020 2 555 7 830 10 477
Romania 10 825 8 981 13 904 8 076 9 631 12 606 14 490 24 610 18 668 16 170 7 761 20 358 4 114 12 646
Slovakia 211 11 13 189 31 76 920 758 1 713 454 1 455 1 336 631 851
Slovenia 10 9 11 15 13 53 226 24 46 178 153 852 160 2 903
Spain 1 187 849 752 669 1 416 1 844 3 139 4 183 2 061 2 874 11 107 7 452 22 590 9 599
Sweden 846 944 982 1 120 1 009 1 608 1 888 2 839 3 785 2 832 1 228 4 928 3 031 21 067

 

Comparing three data collection cycles: The data collection cycle 2023 shows a significant increase of the average absolute revisions of DMC for the three most recent reference years mainly due to revisions of Eurostat's early estimates (see also point 11.2 of metadata). 

 

 


18. Statistical processing Top
18.1. Source data

National statistical institutes (NSI) compile economy-wide material flow accounts (EW-MFA) based on a wide range of statistical data sources (e.g. agriculture, forestry and fishery statistics, production statistics, geological surveys, energy statistics, foreign trade statistics etc.). In some cases, estimation procedures are applied where no data sources are available. Eurostat provides standardised estimation procedures.

18.2. Frequency of data collection

Data are collected annually.

18.3. Data collection

EW-MFA data collection is regulated by Regulation (EU) No. 691/2011 on European environmental economic accounts.

The annual EW-MFA questionnaire is available on Eurostat's website. Eurostat receives the questionnaires via eDAMIS (electronic Data files Administration and Management Information System), the standard tool for the transmission of data and metadata to Eurostat. The system provides a secure environment for the transmission of data and offers logging of all transmissions and sends confirmations of delivery.

18.4. Data validation

Data are extensively checked by Eurostat using comprehensive validation procedures (IT tools). Checks are carried out essentially to ensure that the transmission of the requested data has been carried out satisfactorily, that datasets are complete and error-free.

Where necessary, Eurostat gap-fills missing data using national and international data sources (e.g. foreign trade statistics, agriculture statistics, energy statistics, production statistics etc.).

18.5. Data compilation
  • Methodology for the estimates of the EU aggregates:

Eurostat derives EU aggregates bottom-up, i.e. by summing up country data, except for physical imports and exports., for which a special methodology is applied as described in the following:

Eurostat derives physical trade for the aggregated EU economy (which is extra-EU imports and exports for EU countries) by using Comext database, i.e. Eurostat's reference database for detailed European statistics on international trade in goods (ITGS). Only extra-EU trade is taken into account for the aggregated EU.

 Please note that due to this methodology  the physical imports and physical exports of the aggregated EU do not equal the sum of Member States'  trade figures.

 Adjustment for residence principle: fuel bunkered by resident units abroad (item MF 4.2.3 of the EW-MFA questionnaire Table B IMPORTS): this item of the EW-MFA classification is estimated for the aggregated EU economy. Based on historical data it is assumed to be 8% of the total extra-EU imports extracted from Comext ITGS database. 

Adjustment for residence principle: fuel bunkered by non-resident units domestically (item MF 4.2.3 of the EW-MFA questionnaire Table D EXPORTS): this item is estimated zero for the aggregated EU economy. Comext ITGS exports include already supplies on the territory of the reporting country to ships and aircraft which are destined to leave the territory of this country on-board.

  • Methodology for gap-filling and early estimates:

- Gap-filling T-1 year (June): For physical imports and physical exports, Eurostat performs gap-filling at the most detailed material breakdown for each EU Member State and the aggregated EU. The gap-filling is based on international trade in goods statistics (ITGS).

Early estimates T-1 year (June): For domestic extraction Eurostat makes early estimates for the 4 main material categories for each EU Member State and the aggregated EU. These early estimates are based on statistical modelling (mainly regression-type models). For each of the main material categories a number of potential predictors have been identified which are available by the middle of the year (e.g. gross value added by NACE sections, production volume indices from short-term business statistics, monthly energy statistics etc.). Predictors and prediction models are country and material specific. 

18.5.1. Imputation - rate

Not applicable.

18.6. Adjustment

Not applicable; i.e. in EW-MFA no time series adjustment necessary.

18.6.1. Seasonal adjustment

Not applicable.


19. Comment Top


Related metadata Top


Annexes Top


Footnotes Top