Economic accounts for agriculture (aact)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Ministry of Agriculture, Fisheries and Food

Time Dimension: 2017-50

Data Provider: ES6

Data Flow: COSAEA_NEQ_5


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: EUROPEAN STATISTICAL DATA SUPPORT

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1. Contact Top
1.1. Contact organisation

Ministry of Agriculture, Fisheries and Food

1.2. Contact organisation unit

Subdireccion General de Analisis, Coordinación y Estadistica

1.5. Contact mail address

Paseo de Infanta Isabel, 1, MADRID (28014)


2. Statistical presentation Top
2.1. Data description

Main characteristics

2.1.1 Describe shortly the main characteristics of the statistics  

The Economic Accounts for Agriculture (EAA) provide detailed information on income in the agricultural sector. The purpose is to analyse the production process of the agricultural industry and the primary income generated by this production. The accounts are therefore based on the industry concept. The EAA accounts are detailed data on value of output (producer prices and basic prices), intermediate consumption, subsidies and taxes, consumption of fixed capital, rent and interests, capital formation etc. The values are in current as well as in constant prices. Agricultural Labour Input (ALI) and Unit Values (UV) are an integrated part of the overall concept of Economic Accounts for Agriculture.


Reference period

2.1.2 Reference period of the data collection 

2017

2.1.3 Is the reference period based on the calendar year starting January 1st and ending December 31st? Yes
2.1.4 If No, please specify


National legislation

2.1.5 Is there a national legislation covering these statistics?  Yes
If Yes, please answer all the following questions.  
2.1.6 Name of the national legislation 

EAA statistic is included in the National Statistical Plan 2017‐2020, approved by Royal Decree 410/2016, of October 3 (operation nº7459).

The collection, processing and dissemination of data from statistical operations for state purposes is governed by the provisions of Law 12/1989, of May 9, on the Public Statistical Function (LFEP) and the Fourth Additional Provision of the Law 4/1990, of June 29. In the LFEP it is established that the National Statistical Plan (PEN) is the main ordering instrument of the statistical activity of the General State Administration and contains the statistics to be prepared in the four-year period by the services of the State Administration or any other entities dependent on it, and those that must be carried out in whole or in part with the participation of the Autonomous Communities and Local Corporations by virtue of cooperation agreements with the State statistical services or, where appropriate, in execution of the provisions of the laws.

2.1.7 Link to the national legislation 

https://www.boe.es/boe/dias/2016/11/18/pdfs/BOE-A-2016-10773.pdf

2.1.8 Responsible organisation for the national legislation 

Nacional Statistical Institution

2.1.9 Year of entry into force of the national legislation 

2017

2.1.10 Please indicate which variables required under EU regulation are not covered by national legislation, if any.

None

2.1.11 Please indicate which national definitions differ from those in the EU regulation, if any. 

None

2.1.12 Is there a legal obligation for respondents to reply?  Yes


Additional comments on data description

2.2. Classification system

The EAA is an integral part of the European system of accounts and therefore for their compilation the Eurostat's general classification of economic activities, NACE Rev. 2, is used.

2.3. Coverage - sector

EAA cover the Agricultural industry and inseparable, non-agricultural secondary activities

2.4. Statistical concepts and definitions

One of the principal objectives of the EAA is to measure agricultural income and changes therein.
The three agricultural income indicators can be described as follows:
Indicator A: index of the real income of factors in agriculture per AWU
Indicator B: index of real net agricultural entrepreneurial income, per non-salaried AWU
Indicator C: net entrepreneurial income of agriculture

2.5. Statistical unit

In order to analyse flows generated by the production process and the use of goods and services, it is necessary to select units which emphasise relationships of a technical-economic kind. This requirement means that as a rule institutional units must be partitioned into smaller and more homogeneous units with regard to the kind of production. Local kind-of-activity units (local KAUs) are intended to meet this requirement as a first but practically-oriented operational approach

2.6. Statistical population

The agricultural holding, which is the unit currently used for statistical studies of agriculture (censuses, surveys of the structure of agricultural holdings), is the local KAU most appropriate to the agricultural industry. In addition to agricultural holdings, the agricultural industry comprises units made up of groups of producers (e.g. cooperatives) which produce wine and olive oil and specialised units which provide machines, material and labour for the performance of contract work.

2.7. Reference area
2.7.1 Geographical area covered

The geographical scope is the entire national territory with the exception of the autonomous cities of Ceuta and Melilla.

 

2.7.2 Which special Member State territories are included?

The territory is composed by 17 Autonomous Regions, Canary and Balearic Islands included  

2.8. Coverage - Time

1990-2017

2.9. Base period

Not applicable


3. Statistical processing Top
3.1. Source data

Overall summary

3.1.1 Total number of different data sources used

28

The breakdown is as follows: 
3.1.2 Total number of sources of the type "Census"

6

3.1.3 Total number of sources of the type "Sample survey"

4

3.1.4 Total number of sources of the type "Administrative source"

13

3.1.5 Total number of sources of the type "Experts"

0

3.1.6 Total number of sources of the type "Other sources"

5


Census

If there is a specific census conducted in your country to collect data exclusively for the EAA please describe it in this part. For other data sources please use table 3.1 in the annexed Excel file. If metadata already exist just provide the name of the data source. 
3.1.7 Name/Title
3.1.8 Name of Organisation responsible
3.1.9 Main scope
3.1.10 List used to build the frame
3.1.11 Any possible threshold values
3.1.12 Population size
3.1.13 Additional comments


Sample survey

If there is a specific survey conducted in your country to collect data exclusively for the EAA please describe it in this part. For other data sources please use table 3.1. If metadata already exist just provide the name of the data source.(e.g. FSS, Crop production, Animal production, Prices in Agriculture) 
3.1.14 Name/Title
3.1.15 Name of Organisation responsible
3.1.16 Main scope
3.1.17 List used to build the frame
3.1.18 Any possible threshold values
3.1.19 Population size
3.1.20 Sample size
3.1.21 Sampling basis
3.1.22 If Other, please specify
3.1.23 Type of sample design
3.1.24 If Other, please specify
3.1.25 If Stratified, number of strata
3.1.26 If Stratified, stratification criteria
3.1.27 If Other, please specify
3.1.28 Additional comments


Administrative source

If there is a specific administrative source in your country witch provide data exclusively for the EAA please describe it in this part. For other administrative sources please use table 3.1. If metadata already exist just provide the name of the data source. 
3.1.29 Name/Title
3.1.30 Name of Organisation responsible
3.1.31 Contact information (email and phone)
3.1.32 Main administrative scope
3.1.33 Geospatial Coverage
3.1.34 Update frequency
3.1.35 Legal basis
3.1.36 Are you able to access directly to the micro data?
3.1.37 Are you able to check the plausibility of the data, namely by contacting directly the units?
3.1.38 How would you assess the proximity of the definitions and concepts (including statistical units) used in the administrative source with those required in the EU regulation?
3.1.39 Please list the main differences between the administrative source and the statistical definitions and concepts
3.1.40 Is a different threshold used in the administrative source and statistical data?
3.1.41 If Yes, please specify
3.1.42 Additional comments


Experts

If there is a specific expert source in your country witch provide data exclusively for the EAA please describe it in this part. For other expert sources please use table 3.1. If metadata already exist just provide the name of the data source.
3.1.43 Name/Title
3.1.44 Primary purpose
3.1.45 Legal basis
3.1.46 Update frequency
3.1.47 Expert data supplier
3.1.48 If Other, please specify
3.1.49 How would you assess the quality of those data?
3.1.50 Additional comments


Other sources

If there is more than one other statistical activity, please describe the main one below and the additional ones in table 3.1 of the annexed Excel file 
3.1.51 Name/Title
3.1.52 Name of Organisation
3.1.53 Primary purpose
3.1.54 Data type
3.1.55 If Other, please specify
3.1.56 How would you assess the quality of those data?
3.1.57 Additional comments

 

3.2. Frequency of data collection

Not applicable, since there are no specific sources conducted to collect data exclusively for EAA.

3.3. Data collection

Census

If there is a specific census conducted in your country to collect data exclusively for the EAA please describe the method of data collection in this part. For other data sources please use table 3.3. If metadata alredy exist just provide the name of the data source. 
3.3.1 Name/Title
3.3.2 Methods of data collection
3.3.3 If Other, please specify
3.3.4 If face-to-face or telephone interview, which method is used?
3.3.5 Data entry method, if paper questionnaires?
3.3.6 Please annex the questionnaire used (if very long: please provide the hyperlink)
3.3.7 Additional comments


Sample survey

If there is a specific survay conducted in your country to collect data exclusively for the EAA please describe the method of data collection in this part.For other data sources please use table 3.3. If metadata alredy exist just provide the name of the data source. 
3.3.8 Name/Title
3.3.9 Methods of data collection
3.3.10 If Other, please specify
3.3.11 If face-to-face or telephone interview, which method is used?
3.3.12 Data entry method, if paper questionnaires?
3.3.13 Please annex the questionnaire used (if very long: please provide the hyperlink)
3.3.14 Additional comments


Administrative source

If there is a specific administrative source in your country to collect data exclusively for the EAA please describe the metod of data collection in this part.For other data sources please use table 3.3. If metadata alredy exist just provide the name of the data source. 
3.3.15 Name/Title
3.3.16 Extraction date
3.3.17 How easy is it to get access to the data?
3.3.18 Data transfer method
3.3.19 Additional comments


Experts

If there is a specific expert source in your country witch provide data exclusively for the EAA please describe the metod of data collection in this part. For other expert sources please use table 3.3. If metadata alredy exist just provide the name of the data source.
3.3.20 Name/Title
3.3.21 Methods of data collection
3.3.22 Additional comments
3.4. Data validation
3.4.1 Which kind of data validation measures are in place? Manual
3.4.2 What do they target? Outliers
3.4.3 If Other, please specify
3.5. Data compilation
3.5.1 Describe the data compilation process

EAA are calculate in our own application sofware. We have a second software intended to download the data in the first one, agricultural production and prices are compile in the application directly as data bases and the rest of information are download in the application from excel files. The compilation of data is made at the level of detail provincial. All the process is automatic there is no manual introduction of information.

Our software produces EAA simultaneously at three levels: provincial (NUT III) and by agregation NUT II and national.

3.5.2 Additional comments
3.6. Adjustment

Intermediate consumption of seeds and planting stock: OEVV (2nd other source in the Annex) only provide information on certified seeds and plants, hence these data need to be increased to cover the standard seeds and plants too, which is done according the estimations of the level of certified seed consumed regarding the total seeds used in agriculture and the levels of normal planting dose applied by farmers. 

Fertilizers: Statistics of Consumption of Fertilizers in Agriculture (7th administrative source in the Annex) provide the fertilizers consumed in agriculture by product and province. This statistic has a bias in certain provinces that has to be adjusted according the normal ratios of agricultural consumption obtained from RECAN for these territories. 

Electricity: MITECO (5th census in the Annex) provide the electricity consumed in agriculture by province. This statistic has a bias in certain provinces that has to be adjusted according the normal ratios of agricultural consumption obtained from RECAN for these territories. 

Plant protection products: AEPLA (3rd other source in the Annex) provide the value of the plant production products sold to the farmers by the companies included in in the association. Although AEPLA includes practically all the company relevant in the sector, these data need to be adjusted to cover the total companies of the sector which is done according the AEPLA estimations of its level of the market representation. 

Animal feed: The Survey of Manufacturers of Compound Feeds, Additives and Premixes (6th census in the Annex) provides the animal feed produced by the manufacturing industry by type of animal feed. These data sometimes show deviations in their evolution from the previous year that do not coincide with the theoretical evolution of livestock consumption. These deviations should be corrected according to calculation models based on the census and the volume of animals slaughtered. 

GFCF in machinery: The Monthly Statistics of Agricultural Machinery Registration (10th administrative source in the Annex) provides information on agricultural machinery recorded during the calendar year. This registration is mandatory for tractors, self-propelled harvesters and plant protection treatment machinery, but the information of the rest of the machines must be increased according to the registration index estimated by the Subdirectorate of Agricultural Production Means of MAPA.


4. Quality management Top
4.1. Quality assurance
4.1.1 Is there a quality management system used in the organisation? No
4.1.2 If yes, how is it implemented?
4.1.3 Has a peer review been carried out? No
4.1.4 If Yes, which were the main conclusions?
4.1.5 What quality improvements are foreseen? Other
4.1.6 If Other, please specify

The improvement in quality is an ongoing process, all the statistical sources and methodologies for capturing and processing information are reviewed whenever problems are detected or better procedures or sources are encountered.

On the other hand we expected to receive new reinforcements in our team of EAA hence we will probably increase the efforts in quality improvements

4.1.7 Additional comments

The quality of this statistic is ensured by controls established, both in the information collection and in the subsequent data processing: 

- Comparison of statistical data up to the level of provincial geographic detail with respect to the preceding historical series.

- Sending to the Autonomous Communities in order to contrast of results in each and every one of the items calculated in the operation.

- Review of arithmetic correction in item aggregation.

- Review of the accuracy of the capture of the statistical data that make up the operation.

- Crossing of information sources when there are other sources available, e.g.: National Agrarian Accounting Network (RECAN), technical-agronomic information, etc. 

All the outliers detected are check with the source of information and in case of error the data are corrected attending agronomical and technical criteria.

4.2. Quality management - assessment

Development since the last quality report

4.2.1 Overall quality Improvement
4.2.2 Relevance Stable
4.2.3 Accuracy and reliability Improvement
4.2.4 Timeliness and punctuality Stable
4.2.5 Comparability Stable
4.2.6 Coherence Improvement
4.2.7 Additional comments

Since the last QR the best improvement has been the automation of compilation process resulting in a better accuracy and reliability. Our current software compiles regions NUT III, which implies a complete coherence between National and Regional accounts


5. Relevance Top
5.1. Relevance - User Needs
5.1.1 If certain user needs are not met, please specify which and why

All user needs were met

 

 

5.1.2 Please specify any plans to satisfy needs more completely in the future
5.1.3 Additional comments
5.2. Relevance - User Satisfaction
5.2.1 Has a user satisfaction survey been conducted? Yes
If Yes, please answer all the following questions 
5.2.2 Year of the user satisfaction survey

2015

5.2.3 How satisfied were the users? Highly satisfied
5.2.4 Additional comments

Relevance: More than 85% of the participants rated it as positive or very positive

Accuracy: More than 80% of the participants rated it as positive or very positive

Opportunity: More than 70% of the participants rated it as positive or very positive

Coherence: More than 80% of the participants rated it as positive or very positive

Geographical comparability: Almost the 60% of the participants rated it as positive or very positive.

Temporal comparability: Almost the 75% of the participants rated it as positive or very positive.



Annexes:
MAPA statistics user satisfaction survey
5.3. Completeness
5.3.1 Data completeness - rate

All the items included in the list of data transmission have been sent

 

 

5.3.2 If not complete, which characteristics are missing?
5.3.3 Additional comments


6. Accuracy and reliability Top
6.1. Accuracy - overall
6.1.1 How good is the accuracy? Good
6.1.2 What are the main factors lowering the accuracy? Other
6.1.3 If Other, please specify

Lack of specific statistics focused on certain items.

6.1.4 Additional comments
6.2. Sampling error

Not applicable. There are not any direct surveys for the Spanish EAA

6.2.1. Sampling error - indicators

Not applicable. 

6.3. Non-sampling error

Not applicable. 

6.3.1. Coverage error

Not applicable. 

6.3.1.1. Over-coverage - rate

Not applicable. 

6.3.1.2. Common units - proportion

Not applicable. 

6.3.2. Measurement error

Not applicable. 

6.3.3. Non response error

Not applicable. 

6.3.3.1. Unit non-response - rate

Not applicable. 

6.3.3.2. Item non-response - rate

Not applicable. 

6.3.4. Processing error

Not applicable. 

6.3.4.1. Imputation - rate

Not applicable. 

6.3.5. Model assumption error

Not applicable. 

6.4. Seasonal adjustment

Not applicable. 

6.5. Data revision - policy

Ordinary revision scheme: Is intended to incorporate new updated statistical information to the EAA, at the pace that the different statistical sources are being consolidated.

The EAA are annual statistics that are updated according the following timetable: 

First estimate: 30 November of the current year n

Second estimate: 30 January of the following year n+1

Semi-definitive data: 30 September year n+1

Definitive data: September n+2 

Extraordinary revisions: Revisions put in practice when there are mayor changes on EAA methodology, error are detected o new statistics sources or methods for specific items are developed.

6.6. Data revision - practice
6.6.1 Data revision - average size
6.6.2 Were data revisions due to conceptual changes (e.g. new definitions)  carried out since the last quality report? Yes
6.6.3 What was the main reason for the revisions?

Incorporation of information not available on previous dates from several statistical sources, updating of information in other sources. Integration of information from Autonomous Regions in the process of generation the integrated calculation EAA-EAAR

6.6.4 How do you evaluate the impact of the revisions? Important
6.6.5 Additional comments


7. Timeliness and punctuality Top
7.1. Timeliness
7.1.1 When were  the first  results for the reference period published?

20Th December 2017 (1st Estimate EAA 2017)

7.1.2 When were  the final results for the reference period published?

Semidefinitive data: 17/12/2018

Final results: 23/12/2019

7.1.3 Reasons for possible long production times?

According methodology on EAA, most of agricultural subsidies are calculated applying the accrual principle. We record the real amount of subsides paid to the farmers according the CAP rights includes by farmers in their yearly applying forms.

The deadline for the CAP payments follow the regulations of EAGF and EAFRD, so the payment period for applications made in a specific year N goes from October 16Th year N to October 15th year N+1. Therefore it is impossible to obtain a complete information about the amount of subsidies until the payments period is closed and the official information is available and this happens along the year N+2.

Other statistics sources are not available until year N+2 like: statistic on electricity, seeds and planting stock (information delay usually until August N+2), and RECAN which only provide provisional data in March N+2.

Other sources are affected by revisions even in the year N+2 like ALI and GDP deflector. 

Finally, our information system generate regional accounts by the principle “bottom up”, this means that definitive EAA has to match with the sum of the all the regional accounts and these can only be consolidated after a long and intensive period of exchange of information with the autonomous regions, so it is unavoidable that the consolidation of regional accounts impact EAA final data.

7.2. Punctuality
7.2.1 Were data released nationally according to a pre-announced schedule (Release Calendar)? Yes
7.2.2 If Yes, were data released on the target date? Yes
7.2.3 If No, reasons for delays?
7.2.4 Number of days between the national release date of data and the target date


8. Coherence and comparability Top
8.1. Comparability - geographical

To be assessed by Eurostat

8.1.1. Asymmetry for mirror flow statistics - coefficient
8.2. Comparability - over time
8.2.1 Length of comparable time series

990-2006; 2007-2008; 2009-2010; 2014-2017

8.2.2 Have there been major breaks in the time series? Yes
8.2.3 If Yes, please specify the year of break and the reason

2007: Following Eurostat guidelines we change the methodology for calculation GFCF in animals from net method to gross method, similar approach we applied to GFCF in plantations. 

2009: Following Eurostat guidelines we removed the production of Meadows and straw from “099000 Other crop products. Other” to “039000 Other forage plants”, also we start to record meadows “grazed”. 

2014: Change from SEC 1995 to SEC 2010. This involved changes classification criteria: Small tools from fixed capital consumption on “21100 Equipment” to intermediate consumption on “19070 Maintenance of materials” and land improvements from “non-produced non-financial asset” to GFCF as produced asset.

8.2.4 Additional comments
8.3. Coherence - cross domain
8.3.1 With which other national data sources have the data been compared?

National Agrarian Accounting Network (RECAN)

8.3.2 Describe briefly the results of comparisons

We found meaningful differences in the large aggregates obtained by elevation of the RECAN ratios compared to the EAA. Analyzing in detail by subsector, the differences are even more important than in the aggregate data of agricultural output, even in sectors for which the EAA have little margin for error due to the existence of administrative data. 

In this sense, it should be noted that the data obtained from RECAN show a bias in favour of production from less intensive holdings in the use of labour force. In particular, an overweight of the farms dedicated to the production of cereals is observed over those oriented to the production of vegetables. This involves lower salaried labor force input in RECAN. 

All of this indicates that RECAN is not a good tool to extrapolate macro data from the sector, given the high diversification of Spanish agriculture and the limited sample (8,687 farms), something that is especially critic in sectors very heterogeneous like the production of vegetables. Consequently, some caution should be exercised in the handling of both macro data extrapolated by elevation, as well as in the exploitation of average ratios per annual work unit (AWU) for the entire agricultural industry. 

The different purpose with which both operations were designed determines that their results in terms of entrepreneurial income cannot coincide, since the objective of RECAN is to monitor agricultural holdings, while EAA monitors the agricultural sector under a methodology derived from the European System of Accounts 2010.

These different approaches result in the following differences encountered: 

1. In RECAN the statistical unit is agricultural holding, while the statistical unit in EAA is the local kind of activity units (local KAUs) and these includes also the companies dedicated to providing agricultural services (p e.g.: Harvesting of crops, plant protections treatments and other works developed by third parties). 

2. Additionally, the EAA consider the cooperatives in the olive and wine-growing sectors, oriented towards the transformation of the raw materials supplied by their partners, as companies within the agricultural industry, companies not captured by RECAN. 

3. On the other hand, there are methodological differences in certain items:

- (04000) Vegetables and horticultural products: the EAAs include the own account gross fixed capital formation (GFCF) in plantations.

- (11000) Animals: Similarly, the EAAs include the GFCF in livestock. 

4. However, the most significant methodological difference occurs in the accounting of farms oriented to pigs and poultry. The RECAN approaches these sectors from the perspective of the rancher, and in this particular sector most part of the ranchers carried out its work mainly as agents at the service of integrated companies, which supply the feed and piglets or day-old chicks and the ranchers fattens the animals up to the final weight, receiving in change a fee for service rendered. The main income recorded by RECAN in this sector is therefore not the amount of the sale of the animals but rather the payment for the service.

On the contrary, the EAA methodology considers that the livestock farming activity is an agricultural activity that must be accounted for, regardless of whether or not the company is an agricultural holding, therefore, the EAA shows a real value of the cattle sold, which implies that the EAA accounts for an addition value that does not appear in RECAN. These different approaches are responsible for strong differences observed in elevation of pig and poultry production data from RECAN with respect to the EAA results.

 

8.3.3 If no comparisons have been made, explain why
8.3.4 Additional comments
8.4. Coherence - sub annual and annual statistics

Not applicable (EAA do not produce sub annual data).

8.5. Coherence - National Accounts

Use of EAA-data in NA calculations

Are EAA used by NA as data source for Group 01 Degree of implication Please describe briefly the reasons
Output Main source used
In National Accounts EAA require certain adjustments to adapt the information to the requirements of the ESA 2010 in order to eliminate the estimates of wine and oil not produced by agricultural units; to include secondary activities not contemplated in EAA; and to include the self-consumption generated by units not contemplated in EAA.
In Regional Accounts EAA is the main source for years t-3 and t-2, being t the current year
Intermediate consumption Main source used
In National Accounts EAA require certain adjustments to adapt the information to the requirements of the ESA 2010 in order to eliminate the estimates of wine and oil not produced by agricultural units; to include secondary activities not contemplated in EAA.
In Regional Accounts EAA is the main source for years t-3 and t-2, being t the current year
Fixed capital consumption Secondary source used
In National Accounts, the FCC is estimated by the Perpetual Inventory Method (PIM), for which the NA GFCF series are used. EEA data are used as main source in the estimate of GFCF (explained below) .
In Regional Accounts another source by the Ministry of Agriculture is used, because EAA has not regional information for this variable.
Compensation of employees Main source used
In National Accounts, compensation of employees from EAA is used in combination with the labour input.
In Regional Accounts another source (The Statistics Yearbook) by the Ministry of Agriculture is used, because EAA has not regional information for this variable.
Taxes Not used
Subsidies Main source used
In National Account, subsidies on products from EAA are used.
In Regional Account they are used for year t to move from producer prices to basic prices.
Rents Not used
Interest Not used
Gross fixed capital formation Main source used

After making a valuation adjustment, EEA data are used in the estimate of the assets Land improvements (AN.1123) and Cultivated biological resources (AN.115). They are also used in the distribution of the GFCF by assets and by industries.

Labour input Not used

Labour Force Survey is used as source of information.


Use of NA-data in EAA calculations

Are NA used as data source for EAA Degree of implication  Please describe briefly the reasons 
Output Not used
Intermediate consumption Not used
Fixed capital consumption Not used
Compensation of employees Not used
Taxes Not used
Subsidies Not used
Rents Not used
Interest Not used
Gross fixed capital formation Not used
Labour input Not used
8.6. Coherence - internal

There is a complete traceability of the linkage of data from the original statistics with the final result in EAA, which ensure a complete internal coherence.


9. Accessibility and clarity Top
9.1. Dissemination format - News release
9.1.1 Do you publish a news release? Yes
9.1.2 If Yes, please provide a link

https://www.mapa.gob.es/es/estadistica/temas/novedades/

9.2. Dissemination format - Publications
9.2.1 Do you produce a paper publication? No
9.2.2 If Yes, is there an English version? No
9.2.3 Do you produce an electronic publication? Yes
9.2.4 If Yes, is there an English version? No
9.2.5 Please provide a link

https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/economia/cuentas-economicas-agricultura/

9.3. Dissemination format - online database
9.3.1 Data tables - consultations

Not available

9.3.2 Is an on-line database accessible to users? No
9.3.3 Please provide a link
9.4. Dissemination format - microdata access
9.4.1 Are micro-data accessible to users? No
9.4.2 Please provide a link
9.5. Dissemination format - other
9.6. Documentation on methodology
9.6.1 Are national reference metadata files available? Yes
9.6.2 Please provide a link

http://www.magrama.gob.es/es/estadistica/temas/estadisticas-agrarias/economia/cuentas-economicas-agricultura/

9.6.3 Are methodological papers available? Yes
9.6.4 Please provide a link

http://www.magrama.gob.es/es/estadistica/temas/estadisticas-agrarias/economia/cuentas-economicas-agricultura/

9.6.5 Is a handbook available? No
9.6.6 Please provide a link
9.7. Quality management - documentation
9.7.1 Metadata completeness - rate
9.7.2 Metadata - consultations
9.7.3 Is a quality report available? No
9.7.4 Please provide a link


10. Cost and Burden Top
10.1 Efficiency gains if compared to the previous quality report Further automation
10.2 If Other, please specify
10.3 Burden reduction measures since the previous quality report Multiple use of the collected data
10.4 If Other, please specify


11. Confidentiality Top
11.1. Confidentiality - policy
11.1.1 Are confidential data transmitted to Eurostat? No
11.1.2 If yes, are they confidential in the sense of Reg. (EC) 223/2009? No
11.1.3 Describe the data confidentiality policy in place

The Law 12/1989, of May 9, on the Public Statistical Function (LFEP) establishes that the Ministry of Agriculture, Food and Environment (MAPA) cannot disseminate, or make available in any way, individual or aggregated data that could lead to the identification of previously unknown data for a person or entity. On the other hand, Regulation (EC) nº 223/2009 of the European Parliament and of the Council, of March 11, 2009, regarding statistics establishes the need to establish common principles and guidelines that guarantee the confidentiality of the data used to prepare European statistics and access to such confidential data, taking into account technical progress and the needs of users in a democratic society

11.2. Confidentiality - data treatment
11.2.1 Describe the procedures for ensuring confidentiality during dissemination

The necessary, physical and administrative measures are taken to ensure that the protection of confidential data is effective, from the collection of data to its publication and storage. Since the publication of results only occurs at the aggregated data level, there are no confidentiality conflicts. If the case is detected that one of the published items corresponds to only one or two local activity units, the data would not be published and its transmission to Eurostat and the INE would be under the principle of guarantee of confidentiality according to Law 12/1989, of May 9, on the Public Statistical Function (LFEP) and Regulation (EC) nº 223/2009 of the European Parliament.

11.2.2 Additional comments


12. Comment Top

We consider that the quality of Spanish EAA, is good. The quality has been greatly improved by automation of the process of data capture. That has contribute to reduce the errors and to increase the internal coherence in process of EAA generation. It also allow us to generate both EAA national and regional simultaneously with subsequently improvement in geographical coherence.


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Annexes Top
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