1.1. Contact organisation
National Statistics Office (NSO)
1.2. Contact organisation unit
Unit B3: Environment, Agriculture and Fisheries Statistics
1.3. Contact name
Confidential because of GDPR
1.4. Contact person function
Confidential because of GDPR
1.5. Contact mail address
National Statistics Office (NSO), Unit B3: Environment, Agriculture and Fisheries Statistics, Lascaris, Valletta VLT2000, Malta
1.6. Contact email address
Confidential because of GDPR
1.7. Contact phone number
Confidential because of GDPR
1.8. Contact fax number
Confidential because of GDPR
2.1. Metadata last certified
21 May 2025
2.2. Metadata last posted
3 June 2025
2.3. Metadata last update
21 May 2025
3.1. Data description
The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures and agro-environmental aspects that look at the impact of agriculture on the environment.
The data are used by public, researchers, farmers and policy-makers to better understand the state of the farming sector and the impact of agriculture on the environment. The data follow up the 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). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2019/2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
3.2. Classification system
Data are arranged in tables using many classifications. Please find below information on most classifications.
The classifications of variables are available in Annex III of Regulation (EU) 2018/1091 and in Commission Implementing Regulation (EU) 2021/2286.
The farm typology means a uniform classification of the holdings based on their type of farming and their economic size. Both are determined on the basis of the standard gross margin (SGM) (until 2007) or standard output (SO) (from 2010 onward) which is calculated for each crop and animal. The farm type is determined by the relative contribution of the different productions to the total standard gross margin or the standard output of the holding.
The territorial classification uses the NUTS classification to break down the regional data. The regional data is available at NUTS level 2.
3.3. Coverage - sector
The statistics cover agricultural holdings undertaking agricultural activities as listed in item 3.5 below and meeting the minimum coverage requirements (thresholds) as listed in item 3.6 below.
3.4. Statistical concepts and definitions
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2023 are set in Commission Implementing Regulation (EU) 2021/2286.
The following groups of variables are collected in 2023:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module “Irrigation”: availability of irrigation, irrigation methods, sources of irrigation water, technical parameters of the irrigation equipment, crops irrigated during a 12 months period;
- for the module “Soil management practices”: tillage methods, soil cover on arable land, crop rotation on arable land, ecological focus area;
- for the module “Machinery and equipment”: internet facilities, basic machinery, use of precision farming, machinery for livestock management, storage for agricultural products, equipment used for production of renewable energy on agricultural holdings.
3.5. Statistical unit
See sub-category below.
3.5.1. Definition of agricultural holding
The agricultural holding is a single unit, both technically and economically, that has a single management and that undertakes economic activities in agriculture in accordance with Regulation (EC) No 1893/2006 belonging to groups:
- A.01.1: Growing of non-perennial crops;
- A.01.2: Growing of perennial crops;
- A.01.3: Plant propagation;
- A.01.4: Animal production or;
- A.01.5: Mixed farming.
Regarding activities of class A.01.49, only the activities “Raising and breeding of semi-domesticated or other live animals” (with the exception of raising of insects) and “Bee-keeping and production of honey and beeswax” are included.
3.6. Statistical population
See sub-categories below.
3.6.1. Population covered by the core data sent to Eurostat (main frame and if applicable frame extension)
The thresholds of agricultural holdings are available in the annex.
Annexes:
3.6.1. Thresholds of agricultural holdings
3.6.1.1. Raised thresholds compared to Regulation (EU) 2018/1091
No3.6.1.2. Lowered and/or additional thresholds compared to Regulation (EU) 2018/1091
Yes3.6.2. Population covered by the data sent to Eurostat for the modules “Labour force and other gainful activities”, “Rural development” and “Machinery and equipment”
The same population of agricultural holdings defined in item 3.6.1.
3.6.3. Population covered by the data sent to Eurostat for the module “Animal housing and manure management”
Restricted from publication
3.6.4. Population covered by the data sent to Eurostat for the module “Irrigation”
The subset of agricultural holdings defined in item 3.6.2 with irrigable area.
3.6.5. Population covered by the data sent to Eurostat for the module “Soil management practices”
The subset of agricultural holdings defined in item 3.6.2 with arable land.
3.6.6. Population covered by the data sent to Eurostat for the module “Orchard”
Not applicable for our country, according to Article 7(5) of Regulation (EU) 2018/1091.
3.6.7. Population covered by the data sent to Eurostat for the module “Vineyard”
Restricted from publication
3.7. Reference area
See sub-categories below.
3.7.1. Geographical area covered
The entire territory of the country.
3.7.2. Inclusion of special territories
Not applicable.
3.7.3. Criteria used to establish the geographical location of the holding
The residence of the farmer (manager) not further than 5 km straight from the farm3.7.4. Additional information reference area
Not available.
3.8. Coverage - Time
Farm structure statistics in our country cover the period from 2001 onwards. Older time series are described in the previous quality reports (national methodological reports).
3.9. Base period
The 2023 data are processed (by Eurostat) with 2020 standard output coefficients (calculated as a 5-year average of the period 2018-2022). For more information, you can consult the definition of the standard output.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
See sub-categories below.
5.1. Reference period for land variables
The use of land refers to the 12-month period ending on 31 August 2023. In the case of successive crops from the same piece of land, the land use refers to a crop that is harvested during the reference year, regardless of when the crop in question is sown.
5.2. Reference period for variables on irrigation and soil management practices
For variables on irrigation and soil management practices, the 12-month period ending on 31 August within the reference year 2023.
5.3. Reference day for variables on livestock and animal housing
For the livestock variables, the reference day 30 September within the reference year 2023. The animal housing variables are not applicable for 2023.
5.4. Reference period for variables on manure management
The manure management variables are not applicable for 2023.
5.5. Reference period for variables on labour force
The 12-month period ending on 31 August within the reference year 2023.
5.6. Reference period for variables on rural development measures
The three-year period ending on 31 December 2023.
5.7. Reference day for all other variables
The reference day 30 September within the reference year 2023.
6.1. Institutional Mandate - legal acts and other agreements
See sub-categories below.
6.1.1. National legal acts and other agreements
Legal act6.1.2. Name of national legal acts and other agreements
Malta Statistics Authority Act 2000
6.1.3. Link to national legal acts and other agreements
See information at this website (legislation).
6.1.4. Year of entry into force of national legal acts and other agreements
2000
6.1.5. Legal obligations for respondents
Yes6.2. Institutional Mandate - data sharing
The Malta Statistics Authority Act gives power to the NSO to collect data from administrative sources.
7.1. Confidentiality - policy
The NSO requests information for the compilation of official statistics according to the articles of the MSA Act – Chapter 422 and the Data Protection Act – Chapter 586 of the Laws of Malta implementing the General Data Protection Regulation (GDPR).
In accordance with the provisions of the MSA Act, Article 40 stipulates the restrictions on the use of information while Article 41 stipulates the prohibition of disclosure of information. Furthermore, Section IX of the Act (Offences and Penalties) lays down the measures to be taken in case of unlawful exercise of any officer of statistics regarding confidentiality of data.
Since its inception, the NSO has always assured that all data collected remains confidential and that it is used for statistical purposes only according to the articles and derogations stipulated in the laws quoted above. The Office is obliged to protect the identity of the data providers and refrain from divulging any data to third parties that might lead to the identification of persons or entities.
Upon employment, all NSO employees are informed of the rules and duties pertaining to confidential information and its treatment. In accordance with the provisions of the MSA Act, before commencing work, every employee is required to take an oath of secrecy whose text is included in the same Act.
An internal policy on anonymisation is in place to ascertain that adequate methods are used for the protection of data which the office collects and shares with the public in its capacity as the National Statistics Office. The policy is meant to safeguard confidentiality of both personal and business data entrusted to the NSO. The document provides guidance for all NSO employees who process data on a daily basis as to how anonymisation methods should be applied. The policy applies to all confidential, restricted and internal information, regardless of form (paper or electronic documents, applications and databases) that is received, processed, stored and disseminated by the NSO.
7.2. Confidentiality - data treatment
See sub-categories below.
7.2.1. Aggregated data
See sub-categories below.
7.2.1.1. Rules used to identify confidential cells
No rules applied7.2.1.2. Methods to protect data in confidential cells
No methods applied7.2.1.3. Description of rules and methods
Not applicable.
7.2.2. Microdata
See sub-categories below.
7.2.2.1. Use of EU methodology for microdata dissemination
Yes7.2.2.2. Methods of perturbation
Recoding of variablesRemoval of variables
Reduction of information
Merging categories
Rounding
Micro-aggregation
7.2.2.3. Description of methodology
The methodology is described in the dedicated section of Eurostat's website: Microdata.
8.1. Release calendar
For IFS 2023, the publication of the results was not included in the advance release calendar due to other workload that was not anticipated. This will be settled for IFS 2026 for which the date when the results will be made available will be included in the release calendar, 6 months before the release date.
8.2. Release calendar access
Not applicable.
8.3. Release policy - user access
An internal policy on dissemination is in place to govern the dissemination of official statistics in an impartial, independent and timely manner, making them available simultaneously to all users. The NSO’s primary channel for the dissemination of official statistics is the NSO website. Tailored requests for statistical information may also be submitted through the NSO website.
8.3.1. Use of quality rating system
No8.3.1.1. Description of the quality rating system
Not applicable.
Data on Integrated Farm Statistics is disseminated every 3-4 years.
10.1. Dissemination format - News release
See sub-categories below.
10.1.1. Publication of news releases
No10.1.2. Link to news releases
Not applicable.
10.2. Dissemination format - Publications
See sub-categories below.
10.2.1. Production of paper publications
No10.2.2. Production of on-line publications
No10.2.3. Title, publisher, year and link
Not applicable.
10.3. Dissemination format - online database
See sub-categories below.
10.3.1. Data tables - consultations
Not applicable.
10.3.2. Accessibility of online database
No10.3.3. Link to online database
Not applicable.
10.4. Dissemination format - microdata access
See sub-category below.
10.4.1. Accessibility of microdata
Yes10.5. Dissemination format - other
The main results have been uploaded on the NSO website as part of the agriculture statistics indicators in agriculture.
10.5.1. Metadata - consultations
Not requested.
10.6. Documentation on methodology
See sub-categories below.
10.6.1. Metadata completeness - rate
Not requested.
10.6.2. Availability of national reference metadata
No10.6.3. Title, publisher, year and link to national reference metadata
Not applicable.
10.6.4. Availability of national handbook on methodology
No10.6.5. Title, publisher, year and link to handbook
Not applicable.
10.6.6. Availability of national methodological papers
No10.6.7. Title, publisher, year and link to methodological papers
Not applicable.
10.7. Quality management - documentation
Not available.
11.1. Quality assurance
See sub-categories below.
11.1.1. Quality management system
Yes11.1.2. Quality assurance and assessment procedures
Use of best practicesQuality guidelines
Self-assessment
Peer review
11.1.3. Description of the quality management system and procedures
The NSO ensures the accuracy of data released to the public and prepares clear methodological notes which explain the processes involved in the collection and production of official statistics.
The NSO has developed an internal Quality Management Framework (QMF) which is built on common requirements of the ESS Code of Practice (ESS CoP). A document was prepared to include a set of general quality guidelines spanning over all statistical domains. Assuring methodological soundness is an integral part of the QMF, nonetheless, the document spans also on other areas related to institutional aspects.
Every five to seven years, the NSO participates in a Peer Review exercise through which the compliance of its operations with principles of the ESS CoP is assessed by an expert team. Peer Reviews are indeed part of the European Statistical System (ESS) strategy to implement the ESS CoP. Each NSI is expected to provide information as requested by a standard self-assessment questionnaire. Following this, an expert team visits the office to meet NSI representatives and main stakeholders. Peer Reviews result in a compliance report and the listing of a set of Improvement Actions that need to be followed up by the NSI. The last round of Peer Reviews has been carried out in 2022.
11.1.4. Improvements in quality procedures
All information related to the Peer Review (including outcome) is available here: Peer review report.
11.2. Quality management - assessment
Not available.
12.1. Relevance - User Needs
The main user of the IFS data is the Directorate for Agriculture within the Ministry for Agriculture, Fisheries and Animal Rights (MAFA).
12.1.1. Main groups of variables collected only for national purposes
In the IFS 2023, the following data has been collected for national purposes only:
- the percentage of the production that has been consumed by the agricultural holding's family members and the share that has been sold.
- detailed data has been collected on each and every parcel of land.
- whether the manager is training someone that may be interested to take over once the manager retires.
12.1.2. Unmet user needs
All user needs were met.
12.1.3. Plans for satisfying unmet user needs
Not applicable.
12.2. Relevance - User Satisfaction
The last user satisfaction survey was held in 2022 with the aim to collect information about key users’ satisfaction with statistical output.
The NSO keeps a record of the number of news releases and publications that are disseminated on its website, the users to whom statistical products are provided; as well as the number of requests that are processed every year.
News releases and tailor-made statistical outputs were assessed on account of their quality, timeliness, and on their ability to meet users’ needs.
12.2.1. User satisfaction survey
Yes12.2.2. Year of user satisfaction survey
2022
12.2.3. Satisfaction level
Satisfied12.3. Completeness
Information on not collected, not-significant and not-existent variables is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
12.3.1. Data completeness - rate
Not applicable for Integrated Farm Statistics as the not collected variables, not-significant variables and not-existent variables are completed with 0.
13.1. Accuracy - overall
See categories below.
13.2. Sampling error
See sub-categories below.
13.2.1. Sampling error - indicators
Please find the relative standard errors on Eurostat’s website, at the Circabc website.
13.2.2. Reasons for non-compliant precision requirements in relation to Regulation (EU) 2018/1091
There are no cases where estimated RSEs are above thresholds.
13.2.3. Reference on method of estimation
See in annex.
Annexes:
13.2.3. Methodology used to calculate relative standard errors
13.2.4. Impact of sampling error on data quality
Unknown13.3. Non-sampling error
See sub-categories below.
13.3.1. Coverage error
See sub-categories below.
13.3.1.1. Over-coverage - rate
The over-coverage rate is available on Eurostat’s website, at the Circabc website.
The over-coverage rate is unweighted.
The over-coverage rate is calculated as the share of ineligible holdings to the holdings designated for the core data collection. The ineligible holdings include those holdings with unknown eligibility status that are not imputed nor re-weighted for (therefore considered ineligible).
The over-coverage rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.
13.3.1.1.1. Types of holdings included in the frame but not belonging to the population of the core (main frame and if applicable frame extension)
Temporarily out of production during the reference periodCeased activities
Merged to another unit
13.3.1.1.2. Actions to minimize the over-coverage error
Maintain of ineligible units in the records, recalculating weights of all units by considering the corrected population13.3.1.1.3. Additional information over-coverage error
Not available.
13.3.1.2. Common units - proportion
Not requested.
13.3.1.3. Under-coverage error
See sub-categories below.
13.3.1.3.1. Under-coverage rate
The estimated rate is 0.
13.3.1.3.2. Types of holdings belonging to the population of the core but not included in the frame (main frame and if applicable frame extension)
None13.3.1.3.3. Actions to minimise the under-coverage error
Prior to the IFS 2023, the NSO has merged all the existent registers available at the Ministry for Agriculture, Fisheries and Animal Rights (MAFA) with the statistical farm register.
13.3.1.3.4. Additional information under-coverage error
Not available.
13.3.1.4. Misclassification error
No13.3.1.4.1. Actions to minimise the misclassification error
Not applicable.
13.3.1.5. Contact error
No13.3.1.5.1. Actions to minimise the contact error
All the registers that been merged together prior to the data collection have also been merged with our population database to try to have the latest contact telephone number of the farmers.
13.3.1.6. Impact of coverage error on data quality
None13.3.2. Measurement error
See sub-categories below.
13.3.2.1. List of variables mostly affected by measurement errors
- Family farm labour force directly employed by the farm on a regular basis (male and female) - FLF_D_RFAM_M_PCXX and FLF_D_RFAM_F_PCXX
- Non-family farm labour force, directly employed by the farm on a regular basis (male and female) - FLF_D_RNFAM_M_PCXX and FLF_D_RNFAM_F_PCXX
- Volume of water - WTRVOL_M3
13.3.2.2. Causes of measurement errors
Respondents’ inability to provide accurate answers13.3.2.3. Actions to minimise the measurement error
Pre-testing questionnaireExplanatory notes or handbooks for enumerators or respondents
Training of enumerators
13.3.2.4. Impact of measurement error on data quality
Low13.3.2.5. Additional information measurement error
A thorough check of completed questionnaires is an integral part of the processing system. Data control started at the collection stage. Since we have opted for the CAPI, we have included a number of in-built validations directly in the system. Besides, we have tested the system prior to the launch of the data collection. Apart from this, all interviewers were instructed to interview not more than five holdings and submit the data to be able to identify any mistakes undertaken during the interviewing stage. This exercise helped the interviewer to reduce the number of errors in the remaining questionnaires. Once the interviewers submitted the questionnaires through the system, a number of validations were run on the data and, in cases where information was not clear, the interviewer was contacted again to verify the data given by the farmer. In such instances, the interviewer could update the data and resend the respective questionnaire.
The above measures were taken in order to minimise as much as possible the measurement errors.
13.3.3. Non response error
See sub-categories below.
13.3.3.1. Unit non-response - rate
See item 13.3.1.1.
The unit non-response rate is unweighted.
The unit non-response rate is calculated as the share of eligible non-respondent holdings to the eligible holdings. The eligible holdings include those holdings with unknown eligibility status which are imputed or re-weighted for (therefore considered eligible).
The unit non-response rate is calculated over the holdings in the main frame and if applicable frame extension, for which core data are sent to Eurostat.
13.3.3.1.1. Reasons for unit non-response
Failure to make contact with the unitRefusal to participate
13.3.3.1.2. Actions to minimise or address unit non-response
Follow-up interviewsReminders
Weighting
13.3.3.1.3. Unit non-response analysis
Not available.
13.3.3.2. Item non-response - rate
There were no partly completed questionnaires. The respondents are asked all the questions by the interviewers, and they replied to every question.
13.3.3.2.1. Variables with the highest item non-response rate
Not applicable.
13.3.3.2.2. Reasons for item non-response
Not applicable13.3.3.2.3. Actions to minimise or address item non-response
None13.3.3.3. Impact of non-response error on data quality
None13.3.3.4. Additional information non-response error
Not available.
13.3.4. Processing error
See sub-categories below.
13.3.4.1. Sources of processing errors
Data entry13.3.4.2. Imputation methods
None13.3.4.3. Actions to correct or minimise processing errors
When the data collected from the IFS 2023 resulted in discrepancies, the relevant participants were contacted again in order to confirm the data provided.
No processing errors were found as a result of thoroughly checking the data during the input stage and also through the inbuilt validations in the system.
13.3.4.4. Tools and staff authorised to make corrections
Interviewers could directly correct the questionnaire on the tablet and add a remark explaining the changes they were making. Once the correction was completed, the interviewer resubmitted the questionnaire to the office.
Apart from the interviewers, only the Head of Unit was able to make corrections to the data submitted by the interviewer during the validation stage. When staff members identified a query, they consulted with the interviewer or farmer for clarification and then provided the Head of Unit with the updated data along with the reason. The Head of Unit personally updated the data in the database.
13.3.4.5. Impact of processing error on data quality
Low13.3.4.6. Additional information processing error
Not available.
13.3.5. Model assumption error
Not applicable.
14.1. Timeliness
See sub-categories below.
14.1.1. Time lag - first result
Not applicable, because only final results are published.
14.1.2. Time lag - final result
12 months.
14.2. Punctuality
See sub-categories below.
14.2.1. Punctuality - delivery and publication
See sub-categories below.
14.2.1.1. Punctuality - delivery
Not requested.
14.2.1.2. Punctuality - publication
Not applicable as there is no release calendar for IFS. The data was published as part of the agriculture statistics indicators available on the NSO website following the data transmission to Eurostat.
15.1. Comparability - geographical
See sub-categories below.
15.1.1. Asymmetry for mirror flow statistics - coefficient
Not applicable, because there are no mirror flows in Integrated Farm Statistics.
15.1.2. Definition of agricultural holding
See sub-categories below.
15.1.2.1. Deviations from Regulation (EU) 2018/1091
The data sent to Eurostat and the published data regarding agricultural holdings respect the definition set in Regulation (EU) 2018/1091 with the exception that those agricultural holdings having only agricultural land that is kept in good agricultural and environmental condition were excluded.
15.1.2.2. Reasons for deviations
Agricultural holdings having only fallow land were excluded from the population of the IFS 2023, as they do not form part of the main frame.
15.1.3. Thresholds of agricultural holdings
See sub-categories below.
15.1.3.1. Proofs that the EU coverage requirements are met
For the sample, the population consisted of all the holdings meeting at least one of the physical thresholds listed in Annex II of Regulation (EU) 2018/1091 together with the frame extension.
Of the 1 375 agricultural holdings that were sent to Eurostat, a total of 974 agricultural holdings met at least one of the physical thresholds listed in Annex II of Regulation (EU) 2018/1091. The remaining 401 agricultural holdings form part of the frame extension.
15.1.3.2. Differences between the national thresholds and the thresholds used for the data sent to Eurostat
The thresholds applied for the national data collection are the same as those applied for the data sent to Eurostat.
15.1.3.3. Reasons for differences
Not applicable.
15.1.4. Definitions and classifications of variables
See sub-categories below.
15.1.4.1. Deviations from Regulation (EU) 2018/1091 and EU handbook
The data that is sent to Eurostat and published data is with the same definitions and classification of variables included in Regulation (EU) 2018/1091, Commission Implementing Regulation (EU) 2021/2286, and EU handbook.
15.1.4.1.1. The number of working hours and days in a year corresponding to a full-time job
The information is available on Eurostat’s website, at the Circabc website.
The number of working hours and days in a year for a full-time job correspond to one annual working unit (AWU) in the country. One annual work unit corresponds to the work performed by one person who is occupied on an agricultural holding on a full-time basis. Annual working units are used to calculate the farm work on the agricultural holdings.
15.1.4.1.2. Point chosen in the Annual work unit (AWU) percentage band to calculate the AWU of holders, managers, family and non-family regular workers
See item 15.1.4.1.1.
15.1.4.1.3. AWU for workers of certain age groups
See item 15.1.4.1.1.
15.1.4.1.4. Livestock coefficients
For livestock coefficients, we used those included in Regulation (EU) 2018/1091.
15.1.4.1.5. Livestock included in “Other livestock n.e.c.”
There are no differences between the types of livestock included under the heading “Other livestock n.e.c.” and the types of livestock that should be included according to the EU handbook.
15.1.4.2. Reasons for deviations
Not applicable.
15.1.5. Reference periods/days
See sub-categories below.
15.1.5.1. Deviations from Regulation (EU) 2018/1091
The data that is sent to Eurostat and published data is in compliance with the reference periods/days set in Regulation (EU) 2018/1091.
15.1.5.2. Reasons for deviations
Not applicable.
15.1.6. Common land
The concept of common land does not exist15.1.6.1. Collection of common land data
Not applicable15.1.6.2. Reasons if common land exists and data are not collected
Not applicable.
15.1.6.3. Methods to record data on common land
Not applicable15.1.6.4. Source of collected data on common land
Not applicable15.1.6.5. Description of methods to record data on common land
Not applicable.
15.1.6.6. Possible problems in relation to the collection of data on common land and proposals for future data collections
Not applicable.
15.1.7. National standards and rules for certification of organic products
See sub-categories below.
15.1.7.1. Deviations from Council Regulation (EC) No 834/2007
No, there are not any deviations from Council Regulation (EC) No 834/2007.
15.1.7.2. Reasons for deviations
Not applicable.
15.1.8. Differences in methods across regions within the country
No differences.
15.2. Comparability - over time
See sub-categories below.
15.2.1. Length of comparable time series
1 reference year.
15.2.2. Definition of agricultural holding
See sub-categories below.
15.2.2.1. Changes since the last data transmission to Eurostat
There have been sufficient changes to warrant the designation of a break in series15.2.2.2. Description of changes
For 2023, agricultural holdings having only fallow land were excluded from the population, as they do not form part of the main frame.
15.2.3. Thresholds of agricultural holdings
See sub-categories below.
15.2.3.1. Changes in the thresholds of holdings for which core data are sent to Eurostat since the last data transmission
There have been sufficient changes to warrant the designation of a break in series15.2.3.2. Description of changes
In 2023, agricultural holdings having only fallow land were excluded from the population, as they do not form part of the main frame. Therefore, the holdings with standard output equal to 0 euro were excluded from the frame.
15.2.4. Geographical coverage
See sub-categories below.
15.2.4.1. Change in the geographical coverage since the last data transmission to Eurostat
There have been no changes15.2.4.2. Description of changes
Not applicable.
15.2.5. Definitions and classifications of variables
See sub-categories below.
15.2.5.1. Changes since the last data transmission to Eurostat
There have been no changes15.2.5.2. Description of changes
There are no changes as both 2020 and 2023 are data collection years covered by the same Regulation (EU) 2018/1091.
15.2.6. Reference periods/days
See sub-categories below.
15.2.6.1. Changes since the last data transmission to Eurostat
There have been no changes15.2.6.2. Description of changes
Not applicable.
15.2.7. Common land
See sub-categories below.
15.2.7.1. Changes in the methods to record common land since the last data transmission to Eurostat
There have been no changes15.2.7.2. Description of changes
Not applicable.
15.2.8. Explanations for major trends of main variables compared to the last data transmission to Eurostat
With regards to the number of holdings by legal personality, comparing 2023 with 2020, data shows a shift from other family farm personalities (FARM_FAM, FARM_SPOU, FARM_SPOUFAM) to FARM_HLD.
In 2023 the share of holdings without livestock increased remarkably compared to 2020.
By watching the evolution 2023 vs 2020 of the number of holdings by SO_EURO class it can be noticed that those having no turnover disappeared in 2023. This break in the time series happened because: for 2023, those holdings having only kitchen gardens and SO=0 were not taken into consideration for the population of the IFS 2023 while for the census they were included holding having kitchen gardens and also Q0000T (fallow land) > 0. In 2023 the new threshold on SO_EURO was included.
This change in threshold had an effect on the farm typology classification with the consequent shrink of number of holdings falling in FT90_SO.
Number of holdings having benefitted of rural development measures in 2023 decreased by 15 percentage points between 2020 and 2023.
15.2.9. Maintain of statistical identifiers over time
Yes15.3. Coherence - cross domain
See sub-categories below.
15.3.1. Coherence - sub annual and annual statistics
Not applicable to Integrated Farm Statistics, because there are no sub annual data collections in agriculture.
15.3.2. Coherence - National Accounts
Not applicable, because Integrated Farm Statistics have no relevance for national accounts.
15.3.3. Coherence at micro level with data collections in other domains in agriculture
See sub-categories below.
15.3.3.1. Analysis of coherence at micro level
Yes15.3.3.2. Results of analysis at micro level
No analysis has been made for crop statistics since we use the data collected in the Integrated Farm Statistics.
Regarding animal statistics, we have compared the data collected directly from the farmer for the specific reference date with the data used for the animal statistics that was compiled from the administrative source. Basically, there were no big changes between the two datasets.
15.3.4. Coherence at macro level with data collections in other domains in agriculture
See sub-categories below.
15.3.4.1. Analysis of coherence at macro level
Yes15.3.4.2. Results of analysis at macro level
Coherence cross-domain: IFS vs ORGANIC CROP PRODUCTION
IFS 2023 data resulted much lower than the organic crop production for ARAT_ORG, PECRT_ORG and UAAXK0000_ORG. The difference between IFS and organic crop production is due to the fact that in the IFS not all the certified organic holdings are selected and interviewed. For the sample of IFS, the organic area is not one of the stratification variables.
15.4. Coherence - internal
The data are internally consistent. This is ensured by the application of a wide range of validation rules.
See sub-categories below.
16.1. Coordination of data collections in agricultural statistics
For the IFS 2023 that was carried out between October 2023 and January 2024, we did not coordinate questionnaires of different data collections.
16.2. Efficiency gains since the last data transmission to Eurostat
Further automation16.2.1. Additional information efficiency gains
For the IFS 2023, we used the CAPI method for data collection and therefore information was transferred every day and there was no need to do data entry from our side since the data was being received directly in our system.
16.3. Average duration of farm interview (in minutes)
See sub-categories below.
16.3.1. Core
Not available.
16.3.2. Module ‘Labour force and other gainful activities‘
Not available.
16.3.3. Module ‘Rural development’
Not available.
16.3.4. Module ‘Animal housing and manure management’
Restricted from publication
16.3.5. Module ‘Irrigation’
Not available.
16.3.6. Module ‘Soil management practices’
Not available.
16.3.7. Module ‘Machinery and equipment’
Not available.
16.3.8. Module ‘Orchard’
Not applicable, because data was not collected.
16.3.9. Module ‘Vineyard’
Restricted from publication
17.1. Data revision - policy
The NSO has a data revision policy for the statistical data that is produced. It is available in the following website: Revisions of Official Statistics Policy.
Revisions are classified into minor revisions, unplanned revisions or major revisions. These are included in the advance release calendar on the NSO website.
17.2. Data revision - practice
The IFS 2023 data is final upon publication, with no planned or unexpected revisions at this time.
17.2.1. Data revision - average size
Not requested.
18.1. Source data
See sub-categories below.
18.1.1. Sampling design & Procedure frame
See sub-categories below.
18.1.1.1. Type of frame
List frame18.1.1.2. Name of frame
Statistical Farm Register
18.1.1.3. Update frequency
Annual18.1.2. Core data collection on the main frame
See sub-categories below.
18.1.2.1. Coverage of agricultural holdings
Sample18.1.2.2. Sampling design
The sampling design used was the stratified one-stage random sampling in which there was no use of systematic sampling. The stratification variables were:
- District (Malta and Gozo) at NUTS 3
- Category (Main Frame and Frame Extension)
- Economic size class (12 categories)
The allocation of the overall sample size was based on a stratified random sampling (based on margin of error relative to the mean).
18.1.2.2.1. Name of sampling design
Stratified one-stage random sampling18.1.2.2.2. Stratification criteria
Unit sizeUnit location
18.1.2.2.3. Use of systematic sampling
No18.1.2.2.4. Full coverage strata
For those strata that had few holdings, all were selected in the sample. Moreover, following the data collection, there were a number of holdings that were given a weight of 1 as they were affecting the end result. The rest of the holdings in that particular strata were re-weighted.
18.1.2.2.5. Method of determination of the overall sample size
The overall sample was mainly based on precision of estimates in each stratum.
18.1.2.2.6. Method of allocation of the overall sample size
Other18.1.3. Core data collection on the frame extension
See sub-categories below.
18.1.3.1. Coverage of agricultural holdings
Sample18.1.3.2. Sampling design
The sampling design used was the stratified one-stage random sampling in which there was no use of systematic sampling. The stratification variables were:
- District (Malta and Gozo) at NUTS 3
- Category (Main Frame and Frame Extension)
- Economic size class (12 categories)
The allocation of the overall sample size was based on a stratified random sampling (based on margin of error relative to the mean).
18.1.3.2.1. Name of sampling design
Stratified one-stage random sampling18.1.3.2.2. Stratification criteria
Unit sizeUnit location
18.1.3.2.3. Use of systematic sampling
No18.1.3.2.4. Full coverage strata
For those strata that had few holdings, all were selected in the sample. Moreover, following the data collection, there were a number of holdings that were given a weight of 1 as they were affecting the end result. The rest of the holdings in that particular strata were re-weighted.
18.1.3.2.5. Method of determination of the overall sample size
The overall sample was mainly based on precision of estimates in each stratum.
18.1.3.2.6. Method of allocation of the overall sample size
Other18.1.4. Module “Labour force and other gainful activities”
See sub-categories below.
18.1.4.1. Coverage of agricultural holdings
Sample18.1.4.2. Sampling design
The sampling design used was the stratified one-stage random sampling in which there was no use of systematic sampling. The stratification variables were:
- District (Malta and Gozo) at NUTS 3
- Category (Main Frame and Frame Extension)
- Economic size class (12 categories)
The allocation of the overall sample size was based on a stratified random sampling (based on margin of error relative to the mean).
18.1.4.2.1. Name of sampling design
Stratified one-stage random sampling18.1.4.2.2. Stratification criteria
Unit sizeUnit location
18.1.4.2.3. Use of systematic sampling
No18.1.4.2.4. Full coverage strata
For those strata that had few holdings, all were selected in the sample. Moreover, following the data collection, there were a number of holdings that were given a weight of 1 as they were affecting the end result. The rest of the holdings in that particular strata were re-weighted.
18.1.4.2.5. Method of determination of the overall sample size
The overall sample was mainly based on precision of estimates in each stratum.
18.1.4.2.6. Method of allocation of the overall sample size
Other18.1.4.2.7. If sampled from the core sample, the sampling and calibration strategy
Not applicable18.1.5. Module “Rural development”
See sub-categories below.
18.1.5.1. Coverage of agricultural holdings
Sample18.1.5.2. Sampling design
The sampling design used was the stratified one-stage random sampling in which there was no use of systematic sampling. The stratification variables were:
- District (Malta and Gozo) at NUTS 3
- Category (Main Frame and Frame Extension)
- Economic size class (12 categories)
The allocation of the overall sample size was based on a stratified random sampling (based on margin of error relative to the mean).
18.1.5.2.1. Name of sampling design
Stratified one-stage random sampling18.1.5.2.2. Stratification criteria
Unit sizeUnit location
18.1.5.2.3. Use of systematic sampling
No18.1.5.2.4. Full coverage strata
For those strata that had few holdings, all were selected in the sample. Moreover, following the data collection, there were a number of holdings that were given a weight of 1 as they were affecting the end result. The rest of the holdings in that particular strata were re-weighted.
18.1.5.2.5. Method of determination of the overall sample size
The overall sample was mainly based on precision of estimates in each stratum.
18.1.5.2.6. Method of allocation of the overall sample size
Other18.1.5.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.6. Module “Animal housing and manure management module”
Restricted from publication
18.1.6.1. Coverage of agricultural holdings
Restricted from publication
18.1.6.2. Sampling design
Restricted from publication
18.1.6.2.1. Name of sampling design
Restricted from publication
18.1.6.2.2. Stratification criteria
Restricted from publication
18.1.6.2.3. Use of systematic sampling
Restricted from publication
18.1.6.2.4. Full coverage strata
Restricted from publication
18.1.6.2.5. Method of determination of the overall sample size
Restricted from publication
18.1.6.2.6. Method of allocation of the overall sample size
Restricted from publication
18.1.6.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication
18.1.7. Module ‘Irrigation’
See sub-categories below.
18.1.7.1. Coverage of agricultural holdings
Sample18.1.7.2. Sampling design
The sampling design used was the stratified one-stage random sampling in which there was no use of systematic sampling. The stratification variables were:
- District (Malta and Gozo) at NUTS 3
- Category (Main Frame and Frame Extension)
- Economic size class (12 categories)
The allocation of the overall sample size was based on a Stratified Random Sampling (based on margin of error relative to the mean).
18.1.7.2.1. Name of sampling design
Stratified one-stage random sampling18.1.7.2.2. Stratification criteria
Unit sizeUnit location
18.1.7.2.3. Use of systematic sampling
No18.1.7.2.4. Full coverage strata
For those strata that had few holdings, all were selected in the sample. Moreover, following the data collection, there were a number of holdings that were given a weight of 1 as they were affecting the end result. The rest of the holdings in that particular strata were re-weighted.
18.1.7.2.5. Method of determination of the overall sample size
The overall sample was mainly based on precision of estimates in each stratum.
18.1.7.2.6. Method of allocation of the overall sample size
Other18.1.7.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.8. Module ‘Soil management practices’
See sub-categories below.
18.1.8.1. Coverage of agricultural holdings
Sample18.1.8.2. Sampling design
The sampling design used was the stratified one-stage random sampling in which there was no use of systematic sampling. The stratification variables were:
- District (Malta and Gozo) at NUTS 3
- Category (Main Frame and Frame Extension)
- Economic size class (12 categories)
The allocation of the overall sample size was based on a stratified random sampling (based on margin of error relative to the mean).
18.1.8.2.1. Name of sampling design
Stratified one-stage random sampling18.1.8.2.2. Stratification criteria
Unit sizeUnit location
18.1.8.2.3. Use of systematic sampling
No18.1.8.2.4. Full coverage strata
For those strata that had few holdings, all were selected in the sample. Moreover, following the data collection, there were a number of holdings that were given a weight of 1 as they were affecting the end result. The rest of the holdings in that particular strata were re-weighted.
18.1.8.2.5. Method of determination of the overall sample size
The overall sample was mainly based on precision of estimates in each stratum.
18.1.8.2.6. Method of allocation of the overall sample size
Other18.1.8.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.9. Module ‘Machinery and equipment’
See sub-categories below.
18.1.9.1. Coverage of agricultural holdings
Sample18.1.9.2. Sampling design
The sampling design used was the stratified one-stage random sampling in which there was no use of systematic sampling. The stratification variables were:
- District (Malta and Gozo) at NUTS 3
- Category (Main Frame and Frame Extension)
- Economic size class (12 categories)
The allocation of the overall sample size was based on a stratified random sampling (based on margin of error relative to the mean).
18.1.9.2.1. Name of sampling design
Stratified one-stage random sampling18.1.9.2.2. Stratification criteria
Unit sizeUnit location
18.1.9.2.3. Use of systematic sampling
No18.1.9.2.4. Full coverage strata
For those strata that had few holdings, all were selected in the sample. Moreover, following the data collection, there were a number of holdings that were given a weight of 1 as they were affecting the end result. The rest of the holdings in that particular strata were re-weighted.
18.1.9.2.5. Method of determination of the overall sample size
The overall sample was mainly based on precision of estimates in each stratum.
18.1.9.2.6. Method of allocation of the overall sample size
Other18.1.9.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.10. Module ‘Orchard’
See sub-categories below.
18.1.10.1. Coverage of agricultural holdings
Not applicable18.1.10.2. Sampling design
Not applicable.
18.1.10.2.1. Name of sampling design
Not applicable18.1.10.2.2. Stratification criteria
Not applicable18.1.10.2.3. Use of systematic sampling
Not applicable18.1.10.2.4. Full coverage strata
Not applicable.
18.1.10.2.5. Method of determination of the overall sample size
Not applicable.
18.1.10.2.6. Method of allocation of the overall sample size
Not applicable18.1.10.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Not applicable18.1.11. Module ‘Vineyard’
Restricted from publication
18.1.11.1. Coverage of agricultural holdings
Restricted from publication
18.1.11.2. Sampling design
Restricted from publication
18.1.11.2.1. Name of sampling design
Restricted from publication
18.1.11.2.2. Stratification criteria
Restricted from publication
18.1.11.2.3. Use of systematic sampling
Restricted from publication
18.1.11.2.4. Full coverage strata
Restricted from publication
18.1.11.2.5. Method of determination of the overall sample size
Restricted from publication
18.1.11.2.6. Method of allocation of the overall sample size
Restricted from publication
18.1.11.2.7. If sampled from the core sample, the sampling strategy and calibration strategy
Restricted from publication
18.1.12. Software tool used for sample selection
SPSS
18.1.13. Administrative sources
See sub-categories below.
18.1.13.1. Administrative sources used and the purposes of using them
The information is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
18.1.13.2. Description and quality of the administrative sources
See the Excel file in the annex.
Annexes:
18.1.13.2 Description and quality of administrative sources
18.1.13.3. Difficulties using additional administrative sources not currently used
Other18.1.14. Innovative approaches
The information on the innovative approaches and the quality methods applied is available on Eurostat’s website, at the link: Additional data - Eurostat (europa.eu).
18.2. Frequency of data collection
The Census of Agriculture is conducted every 10 years. Between censuses, the IFS survey is conducted twice, in years n+3 and n+6.
18.3. Data collection
See sub-categories below.
18.3.1. Methods of data collection
Face-to-face, electronic versionTelephone, electronic version
18.3.2. Data entry method, if paper questionnaires
Not applicable18.3.3. Questionnaire
Please find the questionnaire in annex.
Annexes:
18.3.3 Questionnaire
18.4. Data validation
See sub-categories below.
18.4.1. Type of validation checks
Data format checksCompleteness checks
Comparisons with other domains in agricultural statistics
18.4.2. Staff involved in data validation
Staff from central department18.4.3. Tools used for data validation
For the data validation, we used Microsoft Access, SPSS and Excel.
18.5. Data compilation
The design weights for each stratum were calculated as the ratio of the total population size (N) to the sample size (n) of each stratum.
For the non-response holdings, the design weights of the corresponding strata have been adjusted to reflect the non-response.
Moreover, the data analysis identified holdings that significantly affected the end result, due to their collected data and their corresponding weights. In such instances, such holdings were given a weight of 1 and the design weights of the corresponding strata have been adjusted accordingly.
18.5.1. Imputation - rate
Not applicable.
18.5.2. Methods used to derive the extrapolation factor
Design weightNon-response adjustment
Trimming of extreme weights
18.6. Adjustment
Covered under Data compilation.
18.6.1. Seasonal adjustment
Not applicable to Integrated Farm Statistics, because it collects structural data on agriculture.
See sub-categories below.
19.1. List of abbreviations
ARPA – Agricultural and Rural Payment Agency
AWU – Annual working unit
CAP – Common Agricultural Policy
CAPI – Computer Assisted Personal Interview
CoP – Code of Practice
ESS – European Statistical System
EU – European Union
GDPR – General Data Protection Regulation
IACS – Integrated Administration and Control System
IFS – Integrated Farm Statistics
LSU – Livestock unit
MAFA – Ministry for Agriculture, Fisheries and Animal Rights
MCCAA – Malta Competition and Consumer Affairs Authority
MSA – Malta Statistics Authority
NSI – National Statistical Institute
NSO – National Statistics Office
NUTS – Nomenclature of territorial units for statistics
QMF – Quality Management Framework
RSE – Relative standard error
SGM – Standard gross margin
SO – Standard output
VRD – Veterinary Regulation Directorate
19.2. Additional comments
No additional comments.
The data describe the structure of agricultural holdings providing the general characteristics of farms and farmers and information on their land, livestock and labour force. They also describe production methods, rural development measures and agro-environmental aspects that look at the impact of agriculture on the environment.
The data are used by public, researchers, farmers and policy-makers to better understand the state of the farming sector and the impact of agriculture on the environment. The data follow up the 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). The aggregated results are disseminated through statistical tables. The data are presented at different geographical levels and over periods.
The data collections are organised in line with Regulation (EU) 2018/1091 and have a new structure, consisting of a core data set and several modules. The regulation covers the data collections in 2019/2020 (the agricultural census), 2023 and 2026. The data are as comparable and coherent as possible with the other European countries.
21 May 2025
The list of core variables is set in Annex III of Regulation (EU) 2018/1091.
The descriptions of the core variables as well as the lists and descriptions of the variables for the modules collected in 2023 are set in Commission Implementing Regulation (EU) 2021/2286.
The following groups of variables are collected in 2023:
- for core: location of the holding, legal personality of the holding, manager, type of tenure of the utilised agricultural area, variables of land, organic farming, irrigation on cultivated outdoor area, variables of livestock, organic production methods applied to animal production;
- for the module "Labour force and other gainful activities": farm management, family labour force, non-family labour force, other gainful activities directly and not directly related to the agricultural holding;
- for the module "Rural development": support received by agricultural holdings through various rural development measures;
- for the module “Irrigation”: availability of irrigation, irrigation methods, sources of irrigation water, technical parameters of the irrigation equipment, crops irrigated during a 12 months period;
- for the module “Soil management practices”: tillage methods, soil cover on arable land, crop rotation on arable land, ecological focus area;
- for the module “Machinery and equipment”: internet facilities, basic machinery, use of precision farming, machinery for livestock management, storage for agricultural products, equipment used for production of renewable energy on agricultural holdings.
See sub-category below.
See sub-categories below.
See sub-categories below.
See sub-categories below.
See categories below.
Two kinds of units are generally used:
- the units of measurement for the variables (area in hectares, livestock in (1000) heads or LSU (livestock units), labour force in persons or AWU (annual working units), standard output in Euro, places for animal housing etc.) and
- the number of agricultural holdings having these characteristics.
The design weights for each stratum were calculated as the ratio of the total population size (N) to the sample size (n) of each stratum.
For the non-response holdings, the design weights of the corresponding strata have been adjusted to reflect the non-response.
Moreover, the data analysis identified holdings that significantly affected the end result, due to their collected data and their corresponding weights. In such instances, such holdings were given a weight of 1 and the design weights of the corresponding strata have been adjusted accordingly.
See sub-categories below.
Data on Integrated Farm Statistics is disseminated every 3-4 years.
See sub-categories below.
See sub-categories below.
See sub-categories below.
