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Survey on the Structure of Agricultural Operations

• 1Contact
  • 1.1Contact organisation
    National Statistics Institute of Spain
    
  • 1.5Contact mail address

    Avenida de Manoteras 50-52 - 28050 Madrid

    
    
• 2Metadata update
  • 2.1Metadata last certified
    13/02/2025
  • 2.2Metadata last posted
    26/02/2025
  • 2.3Metadata last update
    13/02/2025
• 3Statistical presentation
  • 3.1Data description

    The data describe the structure of farms by providing general characteristics of farms and farmers, as well as information on their land, livestock and labour force.  They also describe production methods, rural development measures and agri-environmental aspects analysing the impact of agriculture on the environment.

    The data are used by the public, researchers, farmers and policy makers to better understand the situation of the agricultural sector and the impact of agriculture on the environment. The data monitor changes in the agricultural sector and provide a basis for decision-making in the Common Agricultural Policy (CAP) and other European Union policies.

    The statistical unit is the agricultural holding (farm). Aggregated results are disseminated by means of statistical tables. Data are presented at different geographical levels and by periods.
    The data collections are organised in accordance with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The Regulation covers data collections in 2020 (the agricultural census), 2023 and 2026. The data are as comparable and consistent as possible with other European countries.

    The Farm Structure Survey 2023 has the following objectives:

    • To evaluate the situation of the agricultural sector in Spain and to monitor the structural evolution of agricultural holdings, achieving comparable results among all EU Member States.
    • To update the framework or directory of agricultural holdings that is used to carry out the sample designs of the sectorial agricultural surveys and as a source of information for the compilation of the Economic Accounts of Agriculture.
    • To comply with the legal regulations of the European Union.
    • To serve as a basis for the formulation, implementation, monitoring and evaluation of agricultural policies, especially the Common Agricultural Policy (CAP), as well as environmental policies on climate change adaptation and mitigation and land use.
    • Monitoring several Sustainable Development Goals (SDGs) and measuring the impact of these policies on the female farm labour force.

    The EEA2023 is structured in two blocks:

    • A main block detailing the main characteristics to be collected (annex III of Regulation (EU) 2018/1091).
    • Another complementary block relating to the modular variables to be collected on labour, rural development, irrigation, soil management practices, orchards, machinery and equipment (Annex IV of the Regulation) and waste generation.

    In the main block the characteristics are integrated into the following three sections:

    • General variables of the agricultural holding relating to the holder, geographical location, legal personality and head of the holding and tenure regime of the Utilised Agricultural Area (UAA).
    • Variables relating to the land: UAA in the open air, UAA under glass or high accessible shelter, areas by crop, area of other land, ecological area and total irrigable area.
    • Livestock variables: Heads of livestock by species and organic livestock.

    In the block relating to the modules, the characteristics to be investigated are integrated in:

    • Module concerning labour and other gainful activities: Farm management, family and non-family labour and other gainful activities related and not directly related to the farm.
    • Rural development module: Agricultural holdings with rural development measures.
    • Irrigation module: Irrigation practices and area of irrigated crops during the agricultural year.
    • Soil management practices module: Tillage methods, soil cover on agricultural land, crop rotation on arable land and on the area of ecological interest.
    • Module on fruit trees: Area, age and density of plantations for pome fruits (apple and pear), stone fruits (peaches, nectarines and apricots), citrus fruits (oranges, small citrus fruits and lemons), olives and table and sultana grapes.
    • Machinery and equipment module: Internet facilities, basic machinery, differentiating between the farm's own machinery and machinery used by several farms, the use of precision farming, machinery for livestock management, storage of agricultural products and equipment used for renewable energy production.
    • Waste generation module: generation of manure and slurry, generation of hazardous and non-hazardous waste, food waste and final destination of the waste generated.

     

  • 3.2Classification system
    • Autonomous Communities
      01   Andalucía
      02   Aragón
      03   Asturias, Principado de
      04   Balears, Illes
      05   Canarias
      06   Cantabria
      07   Castilla y León
      08   Castilla - La Mancha
      09   Cataluña
      10   Comunitat Valenciana
      11   Extremadura
      12   Galicia
      13   Madrid, Comunidad de
      14   Murcia, Región de
      15   Navarra, Comunidad Foral de
      16   País Vasco
      17   Rioja, La
  • 3.3Sector coverage

    The population researched by the Farm Structure Survey comprises all agricultural and livestock holdings existing in the national territory, in the reference period, regardless of the natural or legal person acting as owner and the destination given to agricultural production, that meet one of the following criteria, in accordance with the thresholds established in Annex I of Regulation (EU) 2018/1091 of the European Parliament and of the Council of 18 July 2018 on integrated statistics on agricultural holdings:

    • All agricultural holdings with at least 5 ha of Utilised Agricultural Area (UAA).
    • All agricultural holdings with at least 2 ha of Arable Land.
    • All agricultural holdings with at least 0.5 ha of Potatoes.
    • All agricultural holdings having at least 0.5 ha of Fresh Vegetables and Strawberries.
    • All agricultural holdings with at least 0.2 ha of Aromatic, medicinal and culinary plants, flowers and ornamental plants, seeds and seedlings, and nurseries¹.
    • All agricultural holdings with at least 0.3 ha of Fruit trees, berries, nuts, citrus fruits, other permanent crops, excluding nurseries, excluding vineyards and excluding olive trees.
    • All agricultural holdings with at least 0.1 ha of Vineyards.
    • All agricultural holdings with at least 0.3 ha of olive trees.
    • All agricultural holdings with at least 100 m2 of Greenhouses.
    • All agricultural holdings with at least 100 m2 of cultivated mushrooms.
    • All agricultural holdings with at least 1.7 Livestock Units (LU).

    These criteria are independent, i.e. at least one of them has to be fulfilled for the holding to be considered as belonging to the target population.

    Purely forestry holdings are excluded from the survey if they do not meet the above-mentioned conditions, as they refer to purely agricultural holdings. However, when the holding under investigation has some forest cover, this is included in the questionnaire.

    To avoid placing an unnecessary burden on agricultural holdings and national administrations, Regulation 2018/1091 requires each Member State to provide data on agricultural holdings covering 98% of the utilised agricultural area (UAA) (excluding kitchen gardens) and 98% of the livestock units (LU).

     

    [1] This refers to outdoor crops only; for example, in the case of medicinal plants grown under glass, the threshold to be used is that of greenhouses.

  • 3.4Statistical concepts and definitions
    • Agricultural holding
      This is a unit, from the technical and economic perspective, with a single management, and which, within the Spanish economic territory, carries out agricultural activities, both as a main activity and a secondary activity. In addition, the holding may have other complementary (not agricultural) activities.
      Said unit, on being a single unit from the technical and economic perspective, is characterised by a common use of labour and of means of production (machinery, land, installations, fertiliser, etc.). This implies that, if the plots of the holding are in two or more municipalities, they may not be very far from each other geographically.
      The listing of agricultural and livestock activities is based on division 01 of the European Union Classification of Economic Activities (NACE, Rev.2), with some exceptions specified in Annex IV. In particular, it includes those holdings that maintain their land, which are no longer used for production purposes, in good agricultural and environmental conditions, in accordance with Council Regulation (EC) Number 1782/2003.
      With the 2003 reform of the Common Agricultural Policy (CAP), the maintenance of the land in good agrarian and environmental conditions was introduced as an agricultural activity (Article 2 of said Regulation). Aside from this activity, farmers must not have any other agricultural activity in order to access the single-payment scheme.
      Therefore, the agricultural holding may be defined as a unit with an agrarian nature (set of land and/or livestock), under a single management, located in a given geographical location, and which uses the same production methods.
    • Holder of the holding
      The holder of the holding is designated as the individual or legal entity that, acting freely and autonomously, takes on the risk of an agricultural holding, managing it themselves or through someone else. In particular, the holder is considered to be:
      - The owner, when said person directly manages the land, though s/he has granted all or part of the decision-making power to a holding manager.
      - The tenant.
      - The sharecropper.
      - Any who, freely and autonomously, manage and take on the risk of a holding, regardless of the tenancy regime.
      A holder that, as such, may exercise a triple role with regard to the holding of which s/he has technical-economic responsibility:
      a) Takes on the responsibility of the economic or financial running of the holding and the risk of results.
      b) Adopts the main technical decisions surrounding the use of available means and exercise administrative control over the holding transactions.
      c) Oversees the daily management of the holding work and makes common decisions on the less important issues.
    • Holding manager
      The holding manager is the person responsible for the current and daily management of the agricultural holding.
      The holding manager coincides, in general, with the holder. If the two do not coincide, the holding manager may be a member of the holder's family or another wage earner.
    • Livestock
      This includes the production animals belonging to the holding or bred by it at 30 September 2013, including those being moved and livestock on an integration or contract basis. Integration basis is considered to be all types of contract that imply a dependence on supplies, animals, fodder and on sale. It therefore includes the vertical integration with private companies, and the horizontal or cooperative integration.
    • Livestock units
      Livestock data is expressed by number of head or in livestock units (LU), which are obtained by applying a coefficient to each species and type, in order to group different species into one common unit. Beehives that do not become LU are exempt.
    • Total area of the holding
      The total area of the holding is made up of the area of all the plots included therein: the area that is the property of the holder, the area rented out for working and the area worked and governed by other types of tenancy agreement. Areas owned by the holder, but granted to third persons, are excluded.
      The total area of the holding includes cultivated land, lands for permanent pastures and other lands.
    • Utilised Agricultural Area (UAA)
      The utilised agricultural area is the whole of the cultivated areas of land, and land used as permanent pastures. The cultivated land includes herbaceous, fallow lands, kitchen gardens and permanent crops.
    • Work units
      The data on work in the holding is expressed in the number of working days, the percentage of worktime or Annual Working Units (AWU); one AWU is equivalent to the work carried out by one person on a full-time basis over one year.
  • 3.5Statistical unit

    The agricultural holding is a unit, both technical and economic, which has a single management and which carries out economic activities in agriculture according to Regulation (EC) No 1893/2006 belonging to groupings:

    A.01.1: Non-perennial crops
    A.01.2: Perennial crops
    A.01.3: Plant propagation A.01.4: Animal production
    A.01.4: Animal production
    A.01.5: Mixed farming

    The ‘maintenance of agricultural land in good agricultural and environmental condition’ of group A.01.6 within the economic territory of the Union, either as a principal or secondary activity.
    For the activities in class A.01.49, only the activities of ‘Raising of semi-domesticated or other live animals’ (except insect farming) and ‘Beekeeping and production of honey and beeswax’ are included.

  • 3.6Statistical population

    The population investigated in the survey comprises all agricultural and livestock holdings existing in the national territory, on 30 September 2023, regardless of the natural or legal person acting as owner and the destination given to agricultural production, that meet any of the threshold criteria established above.

    This population of holdings constitutes the main framework for the modules Labour and other gainful activities, Rural development and Machinery.

    The survey population for the Irrigation module is a subset of the population of the agricultural holdings defined above with irrigable land, for the Soil Management Practices module a subset with arable land area, and for the Fruit Crops module a subset with fruit orchard area.

  • 3.7Reference area

    The entire national territory is included, including the Canary Islands, Balearic Islands, Ceuta and Melilla.

    The agricultural holding will be geo-referenced according to the largest parcel of the holding.

  • 3.8Time coverage

    As of the accession of Spain to the European Community on 1 January 1986, as a full member, the INE joined the Community programme of surveys on the structure of agricultural holdings. This programme makes it necessary to modify the dates of the agricultural census which, according to successive Council Regulations, must be carried out in years ending in nine or zero. This was the case for the 1989, 1999, 2009 and 2020 censuses. It is determined that surveys will be carried out every three years in the intercensal periods, being in 2023 and 2026.

    The older time series are described in the previous quality reports (national methodological reports).

  • 3.9Base period

    Data for 2023 are processed (by Eurostat) with 2020 standard production coefficients (calculated as a 5-year average of the period 2018-2022). 
    For more information, please refer to the definition of standard production.

• 4Unit of measure
  • 4.1Unit of measure

    Unit of measurement of area

    The unit of measurement used for the area of the agricultural holding and crops is the hectare (10,000 m2), except in the case of cultivated mushrooms, which is the square metre (m2).

    Livestock units of measurement

    Data on livestock holdings can be expressed in:

    Heads of livestock

    Livestock data can be expressed in number of heads of animals of the different types of livestock.

    Heads of livestock are given on a reference day within the reference period (30 September 2023 is used for the survey), as the number of livestock in a year may fluctuate.

    For some types of animals (e.g. poultry), there may be a period between production cycles when livestock housing is empty due to temporary interruptions in the production cycle (e.g. regular sanitary cleaning of animal housing, disease outbreaks or similar reasons) or there are fewer animals on the holding. The livestock on these holdings shall correspond to the number of animals just before the health cleaning (provided that they no longer exist on any other holding).

    Livestock units

    Livestock units (LU) is a standard unit of measurement that allows the aggregation of various categories of livestock of different species and ages according to convention, through the use of specific coefficients established on the basis of nutritional or feed requirements of each type of animal, to allow a comparison.

    The coefficients used are adopted in accordance with Annex I of Regulation (EU) 2018/1091.

    Number of hives

    For bees, the unit adopted is the number of hives.

    Units of measurement of work

    Data on work on the holding are expressed in number of working days, in percentage of working time or in annual work units (AWU); an AWU is equivalent to the work done by a full-time person over a year.

    The annual work unit (AWU) is equivalent to the work done by a full-time person over a year, i.e. the total hours worked divided by the average annual hours worked in full-time jobs in the country.

    For the purposes of the survey, a full working day is defined as 1,800 hours (8 hours per day for 225 working days).

    The following table gives the equivalences between AWU brackets, hours worked per year and full-time working days:

    Porcentaje (%)	UTA	Horas al año	Jornadas completas al año
    = 100	>=1	>=1800	>=225
    >=75 a <100	>=0,75 a <1	>=1350 a <1800	De 169 a 224
    >=50 a <75	>=0,50 a <0,75	>=900 a <1350	De 113 a 168
    >=25 a <50	>=0,25 a <0,50	>=450 a <900	De 57 a 112
    > 0 a <25	> 0 a <0,25	> 0 a <450	De 1 a 57
    0	0	0	0

    Volume of water used

    The measure used to account for the volume of water used on the holding for irrigation is the cubic metre (m3).        

    Date and time

    The date and time shall follow the ISO 8601 standard. The main feature of the standard is that the date/time information is ordered so that the largest time term (the year) is placed to the left and successive smaller terms are placed to the right of the previous term (date elements can be separated by ‘-’ and time elements by ‘:’ to improve human readability.

    The standard also sets a reference calendar such as the Gregorian calendar.

    The standard also prescribes at least a four-digit year (YYYYY).

    For the representation of the month and year, the order shall be: YYYYY-MM.

    Other conventional units of measurement

    The following conventional units are also used:

    Standard Production (SP)

    The output of an agricultural characteristic is the monetary value of the gross production at the farm gate price.

    Standard output (ST) is the value of the output corresponding to the average situation in a certain region for each agricultural characteristic.

    The total standard output (ST) of the holding is obtained as the result of adding the product of each value obtained from the characteristics of the holding, for each standard output of these characteristics.

    Output means the sum of the value of the main product(s) and of the secondary product(s). The values are calculated by multiplying the output per unit by the farm gate price excluding VAT, product taxes and direct payments.

    The standard outputs correspond to a production period of 12 months (crop year from 1 October 2022 to 30 September 2023). For plant and animal products for which the duration of the period is longer or shorter than 12 months, an SP corresponding to the annual increase or production of 12 months will be calculated.

    SPs are provided by the Ministry of Agriculture, Fisheries and Food. They are determined using average basic data calculated over a reference period of five years. They are updated from time to time in line with economic trends.

    The total standard output (TEP) of the holding is the sum of the values obtained for each characteristic by multiplying the standard outputs per unit by the corresponding number of units.

     

• 5Reference period
  • 5.1Reference period

    According to the type of data the reference periods are defined as follows:

    • For the characteristics related to land, labour, irrigation, soil management practices and fruit trees the reference period is the crop year 2023, comprised between 1 October 2022 and 30 September 2023.
    • For the livestock and machinery and equipment variables, the reference date shall be 30 September 2023.
    • For rural development measures the reference period is three years ending on 31 December 2023 (from 1 January 2021 to 31 December 2023).

    Data referring to the period: Annual A: 2023

• 6Institutional mandate
  • 6.1Legal acts and other agreements

    The compilation and dissemination of the data are governed by the Statistical Law No. 12/1989 "Public Statistical Function" of May 9, 1989, and Law No. 4/1990 of June 29 on “National Budget of State for the year 1990" amended by Law No. 13/1996 "Fiscal, administrative and social measures" of December 30, 1996, makes compulsory all statistics included in the National Statistics Plan. The National Statistical Plan 2009-2012 was approved by the Royal Decree 1663/2008. It contains the statistics that must be developed in the four year period by the State General Administration's services or any other entity dependent on it. All statistics included in the National Statistics Plan are statistics for state purposes and are obligatory. The National Statistics Plan 2021-2024, approved by Royal Decree 1110/2020, of 15  December, is the Plan currently implemented. This statistical operation has governmental purposes, and it is included in the National Statistics Plan 2021-2024. (Statistics of the State Administration).

    
    

    The INE conducts this survey with reference to 2023 within the framework of Regulation (EU) 2018/1091 of the European Parliament and of the Council, of 18 July 2018, on integrated statistics on agricultural holdings, which requires basic information and additional information to be collected by sample.

    And at national level, Royal Decree 97/2022 of 1 February, approving the Annual Programme 2022 of the National Statistical Plan 2021-2024, establishes among the statistical operations owned by the INE the compilation of the survey on the structure of agricultural holdings, with operation code number 8002), in accordance with current legislation applicable to the compilation of statistics at state level.

    In order to reduce the burden on respondents, national statistical institutes and other national authorities should have access to administrative data to the extent that they are necessary for the development, production and dissemination of European statistics, in accordance with Article 17a of Regulation (EC) No 223/2009.

    As regards the geo-coding of agricultural holdings, the system of statistical units referred to in Annex III to Directive 2007/2/EC of the European Parliament and of the Council should be used.

  • 6.2Data sharing
    The exchanges of information needed to elaborate statistics between the INE and the rest of the State statistical offices (Ministerial Departments, independent bodies and administrative bodies depending on the State General Administration), or between these offices and the Autonomic statistical offices, are regulated in the LFEP (Law of the Public Statistic Function). This law also regulates the mechanisms of statistical coordination, and concludes cooperation agreements between the different offices when necessary.
    

    The data has been obtained in collaboration with the Basque Statistics Institute (EUSTAT) in the territorial scope of its community, in accordance with the agreement signed between the INE and EUSTAT.

• 7Confidentiality
  • 7.1Confidentiality - policy

    The Statistical Law No. 12/1989 specifies that the INE cannot publish, or make otherwise available, individual data or statistics that would enable the identification of data for any individual person or entity. Regulation (EC) No 223/2009 on European statistics 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

    
    
  • 7.2Confidentiality - data treatment
    INE provides information on the protection of confidentiality at all stages of the statistical process: INE questionnaires for the operations in the national statistical plan include a legal clause protecting data under statistical confidentiality. Notices prior to data collection announcing a statistical operation notify respondents that data are subject to statistical confidentiality at all stages. For data processing, INE employees have available the INE data protection handbook, which specifies the steps that should be taken at each stage of processing to ensure reporting units' individual data are protected. The microdata files provided to users are anonymised.
    

    The Law on the Public Statistical Function (LFEP) establishes that data protected by Statistical Secrecy are personal data, i.e. data referring to natural or legal persons that either allow the immediate identification of such persons or lead by their structure, content or degree of disaggregation to their indirect identification.

    Published data are anonymised, i.e. they cannot be associated with an identified person.

• 8Release policy
  • 8.1Release calendar

    The advance release calendar that shows the precise release dates for the coming year is disseminated in the last quarter of each year.

    
    
  • 8.2Release calendar access

    The calendar is disseminated on the INEs Internet website (Publications Calendar)

    
    
  • 8.3User access

    The data are released simultaneously according to the advance release calendar to all interested parties by issuing the press release. At the same time, the data are posted on the INE's Internet website (www.ine.es/en) almost immediately after the press release is issued. Also some predefined tailor-made requests are sent to registered users. Some users could receive partial information under embargo as it is publicly described in the European Statistics Code of Practice

    
    
• 9Frequency of dissemination
  • 9.1Frequency of dissemination

    The Farm Structure Survey is disseminated every 3 years in periods between censuses, as laid down in Regulation (EU) 2018/1091, in the years 2023 and 2026.

• 10Accessibility and clarity
  • 10.1News release

    The results of the statistical operations are normally disseminated by using press releases that can be accessed via both the corresponding menu and the Press Releases Section in the web

    
    
  • 10.2Publications

    The dissemination of the survey is carried out by means of a system of tables that are published on the INE website.

    The information disseminated in tables is as follows:

    National structural results and by Autonomous Community:

    Main characteristics of the holdings

    • Farms by size according to utilised agricultural area (UAA) and legal status of the holder
    • Farms by size according to total livestock units (LU) and legal status of the holder
    • Farms by main type of farming (OTE) and legal status of the holder
    • Farms by main ETO and size according to total standard output (PET)

    General distribution of utilised agricultural area (UAA)

    • General distribution of the total area (TS) by legal status of the holder
    • Overall distribution of UAA by size of holding according to UAA
    • Overall distribution of UAA by type of farming OTE
    • Holdings by UAA tenure status and size according to UAA
    • Farms by UAA holding system and legal status of the holder
    • Holdings with open-air irrigation facilities (excluding orchards for own consumption) by size of holding according to UAA
    • Mushroom, mushroom and other cultivated mushroom holdings by legal status of the holder

    Livestock farming

    • Livestock holdings by type of livestock and legal status of operator
    • Livestock holdings by type of livestock and size according to total livestock units (LU)
    • Livestock holdings by type of livestock and technical-economic orientation (OTE)

    Organic agriculture and livestock

    • Farms with organic utilised agricultural area, by legal status of the holder and type of organic certification
    • Overall distribution of organic utilised agricultural area (UAA) by size according to UAA and type of crops and/or pastures
    • Comparison of organic UAA utilised agricultural area compared to total UAA (organic+conventional) by crop and/or grassland types
    • Organic livestock holdings by size according to total livestock units (LU), by livestock type
    • Comparison of organic livestock with total livestock (organic+conventional), by livestock type

    Characteristics of farm managers

    • Farm managers by size according to utilised agricultural area (UAA) of the farm, sex, age and relationship to the holder
    • Farm managers by size according to total livestock units (LUs) of the holding, sex, age and relationship to the holder
    • Farm managers by economic and technical orientation (OTE), sex, age and relationship to the holder
    • Farm managers by size according to total standard production (PET), sex, age and relationship to the holder
    • Farm managers by percentage of total work unit-years (UTA), agricultural training, sex and age
    • Farm managers by experience as manager, agricultural training, sex and age
    • Farm managers by agricultural training, training courses, sex and age

     

     

  • 10.3On-line database

    INEbase is the system the INE uses to store statistical information on the Internet. It contains all the information the INE produces in electronic formats. The primary organisation of the information follows the theme-based classification of the Inventory of Statistical Operations of the State General Administration . The basic unit of INEbase is the statistical operation, defined as the set of activities that lead to obtaining statistical results on a determined sector or subject based on the individually collected data. Also included in the scope of this definition are synthesis preparation.

    
    
  • 10.4Micro-data access
    A lot of statistical operations disseminate public domain anonymized files, available free of charge for downloading in the INE website Microdata Section
    
  • 10.5Other

    There is the possibility of requesting customised information from the INE User Services Area. Limitations on confidentiality or accuracy are taken into account when processing said requests.

    See https://www.ine.es/ss/Satellite?L=0&c=Page&cid=1254735550786&p=1254735550786&pagename=ProductosYServicios%2FPYSLayout&rendermode=previewnoinsitem

  • 10.6Documentation on methodology

    For a detailed description of the methods and concepts used, as well as the questionnaires used for the collection of the Survey on the Structure of Agricultural Holdings, please consult the website: 

    INEbase/ Agriculture and the environment / Agriculture

    AC3=100%

  • 10.7Quality documentation

    In accordance with Article 11 of Regulation (EU) 2018/1091 of the European Parliament and of the Council, and coinciding with the transmission of data, a quality report is provided to Eurostat describing the statistical process, and in particular:

    • metadata describing the methodology used and how the technical specifications were met with respect to those laid down by this Regulation;
    • information on compliance with the minimum requirements for the sampling frames used, including when developing and updating them, in accordance with the provisions of this Regulation.

    This standardised methodological report contains, in fields 10.6 to 17, the elements of what constitutes the ‘User-oriented quality report’ for this operation.

• 11Quality management
  • 11.1Quality assurance

    Quality assurance framework for the INE statistics is based on the ESSCoP, the European Statistics Code of Practice made by EUROSTAT. The ESSCoP is made up of 16 principles, gathered in three areas: Institutional Environment, Processes and Products. Each principle is associated with some indicators which make possible to measure it. In order to evaluate quality, EUROSTAT provides different tools: the indicators mentioned above, Self-assessment based on the DESAP model, peer review, user satisfaction surveys and other proceedings for evaluation.

    
    

    A number of measures have been implemented to help ensure the quality of the process and results. These include the following:

    • Both the questionnaire and definitions are agreed in a working group with the participation of experts.
    • Data collection through a multi-channel medium. CATI, CAWI, CAPI applications are observed with implementation of errors and warnings of incompatibility or inconsistency between survey responses for initial debugging.
    • Editing and imputation after data collection.

    The quality of the process has been guaranteed through the analysis, integration, standardisation and exhaustiveness (completeness) of all the agricultural files referred to in the Regulation, together with a field data collection of the agricultural survey.

    Since the beginning of the process, regular meetings have been held with experts, in which the coverage has been studied and the coherence of the survey data with other sources available in the Ministry of Agriculture has been analysed.

    The availability of previous administrative information in the framework has allowed for a control of the coverage, which has contributed to the achievement of a quality survey.

  • 11.2Quality assessment

    The quality of the survey is guaranteed by the evaluation of the results that has been carried out continuously throughout the process.

    The adaptation of the questionnaire to the multi-channel collection method (postal-CAWI, CATI, CAPI), as well as the information contrasts and quality controls carried out during the recording and filtering of data, have made it possible to minimise non-response.

    On the other hand, an attempt has been made to minimise the statistical burden and cost by eliminating questions in the questionnaire and whose information has been obtained from other INE sources.

    The survey on the structure of agricultural holdings is carried out in a coordinated manner in all the countries of the European Union, which allows for homogeneous and comparable information on a European level.

• 12Relevance
  • 12.1User needs

    The data are used by the public, researchers, farmers and policy makers to better understand the state of the agricultural sector and the impact of agriculture on the environment.

    The main user is the European Union's Directorate-General for Agriculture, which needs to have, through Eurostat, comparable statistics across all Member States on the structure of agricultural holdings to determine the development and monitoring of the EU's common agricultural policy (CAP). The Ministry of Agriculture also needs to have these data for the monitoring of this policy at national level.

    The variables investigated and their description are reduced to the list proposed in Commission Implementing Regulation (EU) 2021/2286.

    Users of the survey on the structure of agricultural holdings include:

    • Ministry of Agriculture, Fisheries and Food and other public bodies
    • Agricultural Councils of the Autonomous Communities Companies, Professional Agricultural Organisations and other institutions
    • Researchers and academic institutions
    • Press and specialized media
    • Foreign users (Eurostat, OECD, United Nations, etc.)
  • 12.2User satisfaction

    The INE has carried out general user satisfaction surveys in 2007, 2010, 2013,  2016 and 2019 and it plans to continue doing so every three years. The purpose of these surveys is to find out what users think about the quality of the information of the INE statistics and the extent to which their needs of information are covered. In addition, additional surveys are carried out in order to acknowledge better other fields such as dissemination of the information, quality of some publications...

    On the INE website, in its section Methods and Projects / Quality and Code of Practice / INE quality management / User surveys are available surveys conducted to date.(Click  next link)

     

    
    

    A user satisfaction survey was conducted in 2019. A satisfactory level was achieved.

  • 12.3Completeness

    The 2023 Agricultural Holding Structure Survey meets all the requirements set out in national and international regulations. Of the 463 characteristics that must be provided to Eurostat, and due to the diversity of our agriculture, only four are considered non-significant or non-existent, and are therefore not investigated in the survey that has been carried out in accordance with Regulation (EU) 2018/1091 of the European Parliament and of the Council and Commission Implementing Regulation (EU) 2018/1874.

    This makes the indicator Rate of mandatory statistical results available at 99.14%.

    The 'Rate of mandatory statistical results available', R1=99.14%

    The variables that are not significant or do not exist in our country have been reported to Eurostat:

    • Textile linen, due to low prevalence
    • Christmas trees, due to low prevalence
    • Rural Development aid for complementary national direct payments to Croatia, not applicable
    • Rural Development aid for risk management, not applicable
• 13Accuracy and reliability
  • 13.1Overall accuracy

    The multi-channel collection system (Postal/CAWI, CATI, CAPI), the massive use of administrative records and the quality controls introduced in the recording and cleaning of data have made it possible to minimise non-response and non-sampling errors.

    The measures adopted include:

    • The questionnaire was specifically designed to facilitate self-completion.
    • The questionnaire is accompanied by detailed instructions and a cover letter specifying the mandatory nature of the statistical operation and the protection of data by Statistical Secrecy.
    • A free telephone helpline is available to assist respondents.
    • During the personal interview phase, a letter of invitation will be sent prior to the interview with the date and place of the interview.

    The relative sampling errors of the main agricultural and livestock characteristics are calculated and compliance with the precision requirements established in Annex 5 of the Regulation is analysed.

  • 13.2Sampling error

    All the precision requirements established in Annex 5 of the Regulation are met except:

    • For the Labour module and the variable Permanent grasslands in the Canary Islands. In this case, the RSE exceeds 5%.
    • For the Fruit Trees module and the variable Small citrus fruits in the Valencian Community. In this case, the RSE exceeds 7.5%.
    • For the Fruit Trees module and the variable Lemons in the Region of Murcia. In this case, the RSE exceeds 7.5%.

    The main reason is that the variability of the net sample (farms of the respondents) has exceeded that of the gross sample.

    The formulas are provided in the attached file Methodology used to calculate the relative standard errors.

  • 13.3Non-sampling error

    Types of farms included in the framework but not belonging to the population, it is observed that almost more than 48% are about to cease their activity and 27% are temporarily out of production.

    Actions to minimize the error of overcoverage, update the data using the most recent administrative register:

    • Agricultural register
    • Tax register
    • Population register

    The errors of erroneous classification have been minimized by having updated records.

    Contact errors have been minimized by having updated records.

    The main causes of measurement errors are due to self-completion without help from the interviewer. The questionnaire and the collection method have been improved with the experience acquired in previous censuses and surveys.

    To ensure data consistency and minimize errors, we have used the IRIA data collection application developed by the INE that integrates all phases of data collection and editing. All questionnaires (postal mail, CAWI, CATI, CAPI) were recorded with IRIA.

    During the phases of collecting and recording the mail questionnaires, the data were verified, with a quality control of the recording and a control of the data supplied. In addition, CAWI, CATI and CAPI have their own controls in IRIA.

    IRIA detects errors in the internal consistency of the questionnaires (partial absence of data in a questionnaire, inconsistent data between different variables and control of the range and existence of quantitative variables). It also detects and makes a checklist for outliers, such as crops that are not common in certain regions.

    The post-recording editing was carried out centrally by the Promoter Unit with the help of an external company. After this manual correction of errors and before obtaining the data sets with the final data, all questionnaires were subjected to automatic data imputation processes.

    In the case of basic data, the unitary non-response is 0.64%. Actions to minimise or address unitary non-response:

    Update the record
    Upload additional information: telephone number
    Several telephone calls to the farm owner
    The non-response unit is studied to detect if they are eligible and in these cases imputation methods are applied.

    The characteristics related to the farm owner (year of birth, sex, days of work, year of start as owner, training) are non-response, but individual data is not available for this item.

    For the variables related to the farm manager, imputations have been made, in cases where the data was absent or incorrect: year of birth, sex, days worked, training, year of start of work as manager.

    The variable Land and Constructions has been imputed in 2,454 farms, in which there was livestock and the surface area of ​​the livestock facilities was not reported. In total there are 49,748 farms with this variable, so the imputation rate is 4.93%.

    The overcoverage rate A2 = 0.94%

    Non-response rate per unit: A4 = 0.64%

    Imputation rate (Buildings): A7 = 4.93%.

• 14Timeliness and punctuality
  • 14.1Timeliness

    According to the Community Regulation and, as the information in the Survey refers to the 2023 agricultural campaign, which in the case of Spain ends on September 30, 2023, the period is 15 months. It is the minimum time required to collect, integrate, clean data and prepare results.

    TP2 = 15 months

  • 14.2Punctuality

    The data is disseminated in accordance with the availability calendar of the structural statistics that the INE prepares and publishes for each year. The data are published on the INE website at the end of February 2025, on the 26th, two months after sending the information to Eurostat.

    TP3=100%

• 15Coherence and Comparability
  • 15.1Comparability - geographical

    Agricultural holdings with a definition other than Regulation (EU) 2018/1091 are not included. There are no differences between the national definition and the EU definition of holding.

    The data are collected, sent to Eurostat and published in accordance with the reference periods/reference days established in Regulation (EU) 2018/1091.

    The processing of this statistic in all its phases is the same for the entire territory. The same methods are used for all autonomous communities. In this way, the results are perfectly comparable at the autonomous community level.

    Spanish legislation has been adopted to European Union legislation. Likewise, the use of the community methodology allows the results to be compared with the rest of the Member States of the European Union.

  • 15.2Comparability - over time

    Since we joined the Community Programme, the methodology has not changed much. The only changes relate to the definition of Annual Work Unit (UTA), the definition of technical-economic guidelines (OTE) and the definition of livestock units (UG).

    For the 2023 survey, UTA is set at 225 full days instead of the 228 days used in 2016.

    The technical-economic guidelines are modified from the 1999 Agricultural Census by replacing the main OTE 11 and 12 with OTE 13 and 14. Later, with the last CAP reform, the new Commission Regulation (EC) No 1242/2008 of 8 December 2008 is approved, which affects the 2009 Agricultural Census and the 2013 Survey.

    With respect to the 2016 survey, the codes of all the technical-economic guidelines corresponding to the 2023 survey have been modified.

    The coefficients used in the calculation of the UG are also modified for the 2023 survey with respect to the used in 2016. No coefficient is established for equine livestock, since only the presence of this type of livestock is required. A coefficient is introduced for ducks, geese and ostriches, and that for other birds is reduced from 0.03 to 0.001.

    For all variables, except for UTA, the CC2 indicator: Number of comparable elements in a time series since its last break is 13, while for UTA this indicator is 12.

  • 15.3Coherence - cross domain

    The results were continuously evaluated during the debugging. During the centralised debugging, the custom-designed application indicated from the source which farm had been included in the farm framework and which collection method was used. The data that the farm had in the framework was displayed. This allowed the debugger to compare the information at the micro level.

    In addition, a comparison was made at the provincial level between the information from the 2020 agricultural census, the data on Annual crop areas and annual crop production according to Regulation (EC) 543/2009 and the EEA2023 data. Differences have been found for the pasture data, due to different classification and definition methodologies. For the rest of the crops the data were more or less consistent.

    The 2023 Agricultural Holding Structure Survey is fully consistent with the 2020 Agricultural Census, as it is the same operation investigated on a sample or exhaustive basis, respectively.

  • 15.4Coherence - internal

    The consistency between the variables is checked at all stages of the Survey's preparation. The results are internally consistent since they are obtained from the same microdata file and are calculated using the same purification and estimation methods.

• 16Cost and burden
  • 16.1Cost and burden

    The estimate of the budgetary credit necessary for the financing of this statistic provided for in the Annual Programme for 2025 amounts to a total of 2,330.27 thousand euros.

    The collection of the 2023 survey has not been coordinated with any survey. The collection questionnaires have been sent to the Ministry of Agriculture, so that it is informed and verifies the need to introduce new variables.

    As was already done for the 2020 census, in the 2023 survey administrative information has been used for the CORE data of approximately 70% of the farms; and the information from the rural development module comes from 100% of the administrative register.

• 17Data revision
  • 17.1Data revision - policy

    The INE of Spain has a policy which regulates the basic aspects of statistical data revision, seeking to ensure process transparency and product quality. This policy is laid out in the document approved by the INE board of directors on 13 March of 2015, which is available on the INE website, in the section "Methods and projects/Quality and Code of Practice/INE’s Quality management/INE’s Revision policy" (link).

    This general policy sets the criteria that the different type of revisions should follow:  routine revision- it is the case of statistics whose production process includes regular revisions-; more extensive revision- when methodological or basic reference source changes take place-; and exceptional revision- for instance, when an error appears in a published statistic-.

    
    

    Only final data are published for the survey and are not subject to revision. If errors are detected and the data needs to be changed, then an explanatory note will be added along with the information in order to warn users that the data has been changed.

  • 17.2Data revision - practice

    Data are published when they are final and are not subject to revision.

    The data have been reviewed throughout the entire process. All data have been reviewed weekly to check for changes made during the week and to compare the provisional results obtained with previous data (latest EEA and Census 2020), and data from the Ministry of Agriculture. To do this, the survey data were downloaded and tabulated for comparison.

• 18Statistical processing
  • 18.1Source data

    Among the work prior to the collection, the one related to the update of the basic framework of agricultural holdings stands out. Below, the administrative and statistical sources used to update the directory are briefly detailed:

    • The Single Application Register (RSU) managed by the Spanish Agricultural Guarantee Fund (FEGA), an autonomous body attached to the Ministry of Agriculture, Fisheries and Food (MAPA). The FEGA is responsible for the management and control of the aid charged to the Agricultural Funds made by the paying agencies. It is considered the most complete source for obtaining agricultural data, and is made up of:
      • The R10 file with information on agricultural plots.
      • The R00 file, with general data from the Single Application of the autonomous communities.
    • The Livestock Farms Register (REGA), of the MAPA, which includes the basic data of livestock farms located in Spain, related to the different species of livestock production animals. This register is used to complete the livestock variables required by the European regulation.
    • The Central Business Directory (DIRCE) prepared by the INE.

    Starting from the directory of agricultural holdings that constitutes the 2020 Agricultural Census, those NIFs that appear in the Single Application Registry of the 2022 agricultural campaign and that were not in the 2020 Agricultural Census directory are added.

    Likewise, the REGA information is processed as of September 30, 2022, and the information of the NIFs incorporated by the RSU 2022 is completed with livestock data. In addition, the NIFs that appear new in this file and do not appear in the Census directory or in the RSU 2022 are added.

    Regarding the treatment of the DIRCE, all those NIFs with a primary or secondary agricultural activity are selected and all those that are not yet included are incorporated into the framework.

    In updating the directory, it is necessary to carry out certain subsequent transformation processes, in order to reach the concepts required by the Regulation. It is worth highlighting the homogenisation processes relating to the concept of Agricultural Holding:

    According to the information contained in the previous agricultural statistical operations, in more than 90% of the cases the owner of the holding is only the owner of a single agricultural or livestock holding, so the following assumptions are made:

    Each owner is identified by his/her NIF and by the province of the municipality where the holding is assigned. In the case of holdings with land in several provinces, the neighbouring provinces of the same owner are joined together in a single holding.
    The co-owners, identified by the same housing code in the Register, are joined together in a single holding, in the event that their holdings are in the same province or neighbouring province.

    The farm framework of the 2020 Agricultural Census updated by the sources described above is crossed by the latest available register to eliminate all those holders registered as deaths.

  • 18.2Frequency of data collection

    The farm survey is collected every 3 years in periods between censuses, as established in the corresponding Regulation. The current one, (EU) 2018/1091, for the reference year 2023, provides for the collection of basic data and data from the modules “Labour and other gainful activities”, “Rural development”, “Irrigation”, “Land management practices”, “Fruit trees” and “Machinery and equipment” by means of a survey. In addition, variables from the “Waste generation” module will be collected.

  • 18.3Data collection

    The European Regulation allows Member States to use various sources or methods to obtain the variables that make up the survey of agricultural holdings, as long as the information collected meets the quality requirements.

    As mentioned above, two types of variables were collected: basic variables (Annex III of the Regulation), variables of the specific modules to be carried out in the reference year (Annex IV of the Regulation) and the variables of the waste generation module.

    In the collection of the EEA 2023, as was done in the 2020 agricultural census, data from administrative records were massively used to collect the basic variables and the variables of the Rural Development module. However, for farms whose owners do not request CAP aid, it was necessary to collect information on the basic variables provided directly by the managers of the agricultural holdings through questionnaires. The modules on labour, irrigation, soil management practices, fruit trees, machinery and equipment, and waste generation were collected entirely by means of questionnaires.

    Therefore, the collection of the survey information consisted of two parts depending on the source of information used: one part based on administrative sources, and another more traditional part in which the information was collected through surveys (direct collection).

    COLLECTION BASED ON ADMINISTRATIVE RECORDS

    From the information provided by the administrative records mentioned above, the information on the basic variables requested by the regulation was completed. The main administrative records from which the information was obtained are:

    RSU: the agricultural data recorded in RSU were incorporated directly into the surveys, considering the different NIF-PROVINCIA declared as farms.
    REGA, for the holders of the REGA 2023 that coincided with those of the RSU already incorporated, the information corresponding to the livestock was completed, so that the livestock data on the existing farms in RSU with agricultural data was included. The farms that did not have agricultural data for these NIFs were also loaded.
    For the loading of data from these sources, the concept of farm corresponds to the NIF-PROVINCE, and there cannot be more than one farm per NIF and province. In those cases in which a NIF of RSU had farms in bordering provinces, a single farm was considered with the following criteria:

    Only NIFs with farms in two bordering provinces were considered.
    The province and municipality where the largest area was located was maintained as the assigned municipality.
    Bordering provinces were not treated in the REGA source.

    DIRECT COLLECTION OF BASIC VARIABLES AND SPECIFIC MODULES

    The direct collection of information was carried out using a multi-channel method: postal mail, completion via the Internet (CAWI), telephone interviews (CATI) and computer-assisted face-to-face interviews (CAPI), in two different phases:

    Phase 1, where the collection was carried out by CAWI, postal mail and CATI.
    Phase 2, where the collection was carried out by CAPI.
    Phase 2 was carried out later, for the units for which no response was obtained in phase 1.

    Three types of questionnaire were used to carry out these phases. A general questionnaire with the general variables, crops and livestock, another questionnaire with the variables of the modules related to labour, irrigation, soil management practices, fruit trees and machinery and equipment. There was a third questionnaire where the variables of waste generation on the farm were collected.

    Phase 1: CAWI, postal and CATI

    There are two stages:

    1. Completion of the questionnaire online (CAWI) and on paper by post.

    This consisted of sending and requesting letters by regular mail to the owners of the farms included in the study with the keys for completing the questionnaires online (CAWI). If the informant had requested it, the questionnaire was sent on paper, sending it in the prepaid reply envelope that was included in the postal delivery.

    To support the collection, free telephone lines (L900) were set up to answer and resolve the queries of the informants. All the questionnaires received by post were recorded. Those informants who needed some kind of clarification or correction necessary to clean up the data they provided were contacted by telephone. Likewise, two postal complaints were made to the farms that did not complete the information.

    The owners of the farms from which no response was obtained through the MAIL and CAWI channels were assigned to the CATI Phase of telephone interviews.

    2. Computer-Assisted Telephone Interviews (CATI).

    Then, the collection of information began through telephone calls (CATI) for those questionnaires pending collection and for which a contact telephone number was available. However, there is always the possibility of carrying out the survey by telephone during the CAWI completion stage or by mail, provided that the informant has requested it.

    In this phase, the owners (or informants) from whom no response was obtained (either because a telephone number was not obtained or because they could not be interviewed by telephone for various reasons) went on to phase 2 of face-to-face interviews.

    Phase 2: Computer-assisted personal interview (CAPI)

    Information was collected by means of a computer-assisted face-to-face interview (CAPI) from the owners of the agricultural holdings for which the questionnaire completed in Phase 1 was not obtained.

    The information on these holdings was available on portable devices and the corresponding face-to-face interviews were conducted. The data were immediately returned to the central databases via an internet connection.

    The interviews were conducted at the home of the owner or the informant. A letter had previously been sent announcing this visit, and attempts were made to contact them by telephone to confirm the appointment or arrange a new one.

    STAFF INVOLVED IN COLLECTING INFORMATION

    During phase 1, the necessary staff was office staff who carried out telephone calls, recording, debugging, inspection and supervision of the information collected. The basic categories of staff were Interviewers, Inspectors and Graduates in Statistics.

    During phase 2, it depended, to a large extent, on the number of farm owners to be interviewed, but initially there was a hierarchical structure that allowed the collection work to be carried out by face-to-face interview with the appropriate quality and within the planned time.

    The basic categories of staff for phase 2 were analogous to phase 1.

    The Graduates in Statistics organized the collection work for their province/s, carried out the control and inspection of the field work, analyzing and checking the results obtained.

    The Interviewing Agents were in charge of conducting the interviews with the farm owners.

    The Inspectors were responsible for monitoring the work of the interviewing agents. They checked that the established work pace was met, the established rate of appointments and/or visits was met, and they especially monitored the incidents detected by their agents and the correct updating of the directory.

    SURVEY MATERIAL

    During phase 1, the following were available:

    The survey start letters with the keys for completing the questionnaires online as well as the complaint letters.
    The questionnaires for both the basic variables and for the specific modules in the languages ​​used in each autonomous community, for return at the request of the informants. An instruction sheet was sent to accompany them, if necessary, and a paid reply envelope/s so that the holders could send the completed questionnaires.
    During the CATI phase, all the material was integrated into the tools of the work centres.

    During phase 2, portable devices were used to load the farm information to be collected from both the basic information questionnaire and the questionnaire for the specific modules. Call and visit letters, interviewer credentials, control and monitoring reports, etc. were used.

  • 18.4Data validation

    The IRIA (Information Collection and Management Integration) software was the tool used during data collection and validation during this phase.

    There are three types of validation:

    • Validation during data collection: there were checks included in the IRIA application at each of the collection phases (CAWI, postal collection, CATI, CAPI). The checks were presented to the interviewers during the interview itself or at the end of it, depending on the type of error. In the case of postal collection, where the questionnaire was recorded once it had arrived by mail, the checks were detailed at the end of the interview and resolved by telephone calls. Subsequently, the survey inspectors had to accept or reject each of the interviewers' questionnaires, depending on the types of errors they contained and the comments included in them. At the next level, the survey inspector carried out a global inspection of the information collected.
    • Validation in Central Services: once the questionnaires were marked as clean in the collection phase, the Promotion Service carried out the validation of the information, guided mainly by the identification of the observations to be treated, based on the coherence in the evolution of the estimated data, with respect to the results available from previous Surveys or the census. Likewise, the incidents in the collection were monitored. A custom-designed interactive application was used, both for the information collected by administrative means and by questionnaire.
    • Automatic imputation: an automatic imputation process of the information was carried out, using specific programs.
  • 18.5Data compilation

    The application used during the debugging process will allow the detection and listing of coverage errors (duplicates, incorrect identifications, etc.) and internal consistency errors in the questionnaires (partial absence of data in a questionnaire, inconsistent data between different variables and control of the range and existence of quantitative variables). Controls of atypical data are also detected and listed, such as crops that appear in certain regions where they had not previously appeared.

    Prior to obtaining the final data files, all questionnaires will be subjected to an automatic imputation process (PIA) using custom programming. The PIA consists of different units called blocks, each of which performs a specific function, more or less complex. These blocks will be applied sequentially to all farms and, in essence, the function of each of them consists of carrying out three types of operations:

    • Controls to detect inconsistencies.
    • Processes to obtain information from the questionnaire itself when inconsistencies have been detected.
    • Perform imputations if necessary.

    If there are no inconsistencies, the block will not make imputations to the farm examined and it moves on to the next block. If a block applies imputations to a farm, the modified data will already be definitive and therefore, the controls carried out in the successive blocks will always refer to the current state of the data and not to the initial state. Within a block, the logic is analogous. The questions asked after the application of one or more imputations always refer to the current state of the data, even if they have been modified within the process of the block.

    Imputations can be classified into two general types:

    • Imputations that are deduced from the information contained in the questionnaire itself by applying the adopted criteria: they appear, when they affect arithmetic inconsistencies, for example, the balancing of sums, they are carried out as a general rule by assigning new data proportional to those appearing in the questionnaire and whose sum verifies the desired consistency condition.
    • Imputations for which it is necessary to use external information due to the absence of the necessary data in the questionnaire: these are carried out using the information contained in a set of Hot Deck (HD) matrices, designed for this purpose, in which the data of the farms previously processed are stored. This information is stored by classifying it according to the size (total surface area) of the farms and when it is used, in the case of arithmetic inconsistencies, the imputation is made by attributing new data with the same proportional distribution criterion. Naturally, at the beginning of the process, the HD matrices must be initialized and this is done for each province based on criteria of greater probability according to data from previous surveys and the agricultural statistics yearbook.

    The population of the Labor module is slightly larger than the CORE population, because the Labor population is an estimate based on samples, while the CORE population is based on census data. Calibration techniques are applied, using the SAS CALMAR macro, in cases where there are correlations between the general variables (CORE) and those of the modules.
    Thus, for the Labour module, small farms are calibrated by the labour of the farm manager and, in general, for each of the SAU sizes, it is calibrated by the number of farms, hectares of cultivated area and pastures.
    For the Irrigation module, it is calibrated, in each of the SAU sizes, by the farms belonging to this population and, at NUTS 2 level, it is calibrated by the irrigable area of ​​the frame.
    For the Soil Management Practices module, it is calibrated by the area of ​​arable land of the frame, and in the Fruit Trees module by the fruit trees of the frame.

  • 18.6Adjustment

    No seasonal adjustment is required.

• 19Comment
  • 19.1Comment

    List of abbreviations used:

    CA Agricultural Census
    CAPI Computer Assisted Personal Interviewing
    CATI Computer Assisted Telephones Interviewing
    CAWI Computer Aided Web Interviewing
    CE European Community
    DIRCE Central Directory of Companies
    EEA Survey on the Structure of Agricultural Holdings
    ENESA State Entity for Agricultural Insurance
    EUSTAT Basque Institute of Statistics
    FAO United Nations Food and Agriculture Organization
    EAFRD European Agricultural Fund for Rural Development
    FEAGA European Agricultural Guarantee Fund
    FEGA Spanish Agricultural Guarantee Fund
    HA Hectares
    IIA International Institute of Agriculture
    IVA Value Added Tax
    INE National Institute of Statistics
    MAPA Ministry of Agriculture, Fisheries and Food
    NACE Nomenclature of economic activities
    SDG Sustainable Development Goals
    OTE Technical Economic Orientation
    CAP Common Agricultural Policy
    PE Standard Production
    PET Total Standard Production
    REGA Register of Livestock Farms
    REGEPA General Register of Agricultural Production
    REGOE General Register of Ecological Operators
    RSU Single Application Register
    SAU Used Agricultural Area of ​​the farm
    SIGPAC Geographic Information System of Agricultural Plots
    ST Total Area of ​​the farm
    TL Cultivated Land
    EU European Union
    UGT Total Livestock Units
    UTA Annual Work Unit