All these people sign a declaration that they undertake to comply with the rules relating to the application of the Principle of Statistical Confidentiality.

Face to face interviews:

• The statistical units are pre-informed about all aspects related to the survey, in particular about the confidentiality of the information provided.
• For security reasons, interviewers always display the respective identification / credentials to the respondent and then inform them about the Principle of Statistical Confidentiality and inform them that the data collection is intended solely for statistical purposes.

CN - National coordinating body;

CR - Regional coordinating body;

TL - Local technical staff member.

Holdings that undertake only activities other than the ones listed in Annex I of Regulation (EC) No 1166/2008 (e.g. forests, fur animals other than rabbits, fish ponds, reeds) where not included in the national definition

• existence, on September 1st 2016, or production in the crop year 2015/2016, of at least:

As the survey progressed, a number of agricultural holdings in the list of producers might be considered as non-existent or in no enquiry conditions. This included, in particular, those that were incorporated into other holdings, whose agricultural area or animal houses went on to have another type of (non-agricultural) utilisation, those that, despite maintaining some sort of agricultural activity, lost the enquiry limits, or those that were double-counted in the list of producers.

The situations behind are the following:

1. 171 holdings have fallow land /permanent grassland no longer in production purposes, but have the land in good agricultural and environmental conditions;
2. 13 holdings with only kitchen gardens. These holdings were sampled because they had  some SO characteristics;
3. 2 holdings with any agricultural activities (corresponding to 20 population holdings).

There are various reference periods, depending on the variable to be collected:

Chronogram of the main operation activities
The main activities of this statistical operation, from the preparation to the dissemination of results, are recorded in the chronogram shown in 3-1. Calendar (overview of work progress) (in annex).

The FSS data collection was split in two periods: September-October 2016 for the web data collection; from November 2016 to May 2017 for the face-to-face data collection. Data collection also included critical appraisal, recording, validation and analysis.
Collected data was subject to a critical appraisal according to the guidelines defined in the control manual (document provided to field chain and containing, for each question, the procedures to be adopted for a preliminary control of data collection, especially identifying compulsory questions, relationships among variables, etc.). In turn, the consistency of collected data should be analysed in line with the provisions of the Instruction Manual and its alignment with local circumstances.

This statistical operation involved over 200 staff across the whole country (Mainland and Islands), and was based on compliance with pre-defined data collection procedures aimed at organising, managing, monitoring and controlling data collection.

The FSS face-to-face data collection model focused on the collection services, with the coordination and technical support structure and coordination upstream, and field teams downstream. 3-2. FSS – Organisational structure (in annex) shows the organisational structure of the statistical operation.

The responsibilities are allocated as follows:

Interviewer: data recording, validation, critical appraisal, analysis and confirmation/correction in computer-readable format.

Local technical staff member (Portuguese acronym: TL)
- guiding and monitoring data collection, recording, validation and analysis,
- ensuring the organisational logistics and administrative management at their section level,
- ensuring information sessions to interviewers,
- ensuring,  in cooperation with the regional coordinating body, the allocation of the different intervening parties to the SAGR chain and the distribution of work to the interviewers,
- managing the questionnaire transfer, notably by reallocating questionnaires at the level of the collection section and between this section and other sections of the region or of other regions,
- contributing to overcome the difficulties shown by the interviewers and assessing the quality of the information provided by them, being able to hand them back certified questionnaires,
- preparing meetings and drafting periodical monitoring reports on the work.

Regional coordinating body (Portuguese acronym: CR)

- recruiting, selecting and training human resources, effectively establishing shared intervention in terms of operational management,
- coordinating the operation in each region, being responsible for compliance with the respective budget (upon final validation of collection structure expenses),
- guiding and monitoring data collection, recording, validation and analysis at regional level,
- ensuring  information sessions for the interviewers, and overcoming difficulties these considered to be insurmountable,
- preparing periodical monitoring reports on the work at regional level, as well as a regional report on the operation.

National coordinating body (Portuguese acronym: CN) - composed of representatives of the Economic Statistics Department and the Data Collection Department – organisational units of Statistics Portugal:

- defining the organisational and logistical structure of the statistical operation,
- monitoring works, thereby gauging the need to intervene in order to solve critical situations.
It also assumed responsibility for the project’s budget control.

Structure of the field chain

The collection structure was initially sized based on the number of agricultural holdings forming the farm register, the size of the geographical area of intervention of teams, and, at the upper levels of the chain of collection, the profile and availability of human resources.

Geographical distribution/organisation

The field structure was composed of 7 services distributed across the country, 32 staff supervising a team incorporating 216 interviewers.

As the collection stage of the operation progressed, the national coordinating body sent to the different regional coordinating bodies the current status of the collection on a weekly basis. This included, per collection service, information on the number of questionnaires collected, still to collect, their status and certification.

SOURCE: Agricultural surveys (vegetable, orchard, floriculture, etc.)

Responsibility: Statistics Portugal

Coverage: All agricultural holders with specific productions

Geographical scope: Mainland, Autonomous Region of the Azores, Autonomous Region of Madeira

Reference point: 2009 to 2015

SOURCE: Statistical units file

Responsibility: Statistics Portugal

Coverage: All companies and self-employed people

Geographical scope: Mainland, Autonomous Region of the Azores, Autonomous Region of Madeira 

Reference point: online (2016)

For administrative sources, see item 4.1 below

In addition, use was made of other sources:
- of files with specific information from the Autonomous Region of Madeira and,
- on an ad hoc basis, of information scattered in files from other statistical surveys of the Economic Statistics Department, notably the inquiry populations of statistical operations targeted at poultry farms and nurseries.

The type of frame is a list frame.

The list of producers became available at April 2016.

In the process of updating and rendering the different available sources compatible, Statistics Portugal used a tool developed in QualityStage, a data quality management application. This application supported the implementation of processes within the scope of the standardisation and consolidation of names and addresses.
Based on the use of the QualityStage tool, a sequential process was established to compare sources, two by two. After the definition of survival criteria, this gave rise to provisional lists of producers.
The provisional result is compared with a new source, until a final consolidated list of producers is obtained.  

It was deemed necessary to define survival rules for the “selection” of the producer who subsists given a group of “potentially” equal producers; essentially, the rules are related to the quality/timeliness associated with each source.
In the 2016 process the list was updated with the latest data obtained from the Financing Institute for Agriculture and Fisheries, the Autonomous Region of Madeira, and also available in the Economic Statistics Department.
Following implementation of the QualityStage software and definition of survival rules for producers, a provisional list was obtained, which was subject to various types of analyses, as a result of the enhancement, improvement and update of information:
(a) Spelling correction of names, addresses and cities, undetectable in the standardisation made by the software application;
(b) Construction of Access queries to detect and eliminate possible double counting that may persist: same names/District/Municipality/Commune (DT/MN/FREG)/Tax identification number; names/telephone/ DT/MN/FREG/address; etc.
(c) Comparison with data from the statistical units file to complement registers with missing information, in particular names, incomplete or unknown addresses, DT/MN/FREG/4 and 7-digit postal_code;
(d) Update of the DT/MN/FREG code of the holding and the producer with current territorial referencing (Portuguese acronym: REFTER) codes, ensuring completion of all fields;
(e) Assignment of cities of the Portuguese Mail Services (CTT) when there is a common 7-digit DT/MN/FREG/postal_code key between the two bases of comparison;
(f) Completion of not valid postal codes through the DT/MN/FREG link with the CTT table for which there is a direct match;
(g) Replacement of legal person identification numbers started with 8xx by new numbers, started with 1xx or 2xx;
(h) Filtering of telephone characters and elimination of telephones without 9 digits;
(i) Elimination of the completion of the address field, whenever the address and city fields were exactly alike.

The sample was selected independently in each stratum by sequential simple random selection without replacement. That is, within each stratum holdings were sorted by the random number associated with them and were selected for the sample the first agricultural holdings.

In order to obtain good results for some variables, with significative importance at national level, but concentrated in a relatively small number of holdings, it was adopted a stratification “in cascade”. Some strata were built that contained all the holdings of the region with a non-zero value or above a certain value for those variables. It’s called stratification “in cascade”, because the holdings with values of the concerning variables above certain limits were progressively isolated.

All the remaining holdings, not belonging to these special strata, were stratified by size classes of UAA.

The stratification and the variables used can be found in annex: 3.1-3.2. The stratification variables and the sampling stage.

The total sample size was 27575 holdings, corresponding to a sampling fraction of approximately 9,1%. This sample size was considered adequate in order to get, for each region (NUTS II), a sufficient precision for the most important variables. 

Later adjustments to sample size were made to improve the accuracy of some indicators considered relevant.

See annex: 3.1-3.5 Neyman allocation.

Responsibility: Financing Institute for Agriculture and Fisheries (IFAP) - IACS

Coverage: Agricultural holders that actually received aid in the reference year

Geographical scope: Mainland, Autonomous Region of the Azores, Autonomous Region of Madeira

Reference point: Crop year 2015/2016

Legal Basis: Regulation (EU) No 1307/2013 of the European Parliament and of the Council of 17 December 2013 establishing rules for direct payments to farmers under support schemes within the framework of the common agricultural policy and repealing Council Regulation (EC) No 637/2008 and Council Regulation (EC) No 73/2009

Updating frequency: yearly

SOURCE: SNIRA (Animal register)

Responsibility: Financing Institute for Agriculture and Fisheries (IFAP) - IACS

Coverage: livestock keepers at national level

Geographical scope: Mainland, Autonomous Region of the Azores, Autonomous Region of Madeira

Reference point: September 2016

Legal Basis: Council Directive 92/102/EEC of 27 November 1992 on the identification and registration of animals; Commission Regulation (EC) No 1678/98 of 29 July 1998 amending Regulation (EEC) No 3887/92 laying down detailed rules for applying the integrated administration and control system for certain Community aid schemes; Council Regulation (EC) No 21/2004 of 17 December 2003 establishing  a  system  for  the  identification  and  registration  of  ovine  and  caprine  animals  and amending  Regulation  (EC)  No  1782/2003  and  Directives  92/102/EEC  and  64/432/EEC; Commission Regulation (EC) No. 759/2009 amending the Annex to Council Regulation (EC) No. 21/2004 establishing a system for the identification and registration of ovine and caprine animals; Commission Decision 2010/280/EU amending   Decision   2006/968/EC   implementing   Council   Regulation   (EC)   No   21/2004   as   regards guidelines  and  procedures  for  the  electronic  identification  of  ovine  and  caprine  animals.

Updating frequency: on-line (cattle); 3-times a year (pigs); yearly (sheep and goats)

Payments under PAC policy

IFAP (IACS)

SNIRA (Animal register)

IFAP (IACS)

• 1989 - Census
• 1993
• 1995
• 1997
• 1999 - Census
• 2003
• 2005
• 2007
• 2009 - Census
• 2013
• 2016

The data capture and editing on the internet data collection mode was supported by the component WEBINQ, a part of the SIGINQ, the Statistics Portugal integrated approach to survey management systems. In this component (WEBINQ, questionnaires on the web) respondents submit their answers online. Acknowledging the relevance of data capture and editing on the final data quality, WEBINQ follows the new concept "Data Version Stack", which has four main rules: i) there is a single response for each tuple (survey, data reference period, statistical unit); ii) data editing performs a new response version; iii) all versions of the responses are saved; iv) last version goes to data warehouse. Data Version Stack allows the survey manager to track changes and ensure data quality. For more detailed information on this issue, check annex 3.3-2 Data collection - Statistics Portugal Survey Management System Architecture (also available at https://ec.europa.eu/eurostat/cros/system/files/NTTS2013fullPaper_146.pdf).

Face-to-face data collection mode:

A generic management and recording application was developed, standardisable by survey (set of validation items and rules), to support the agricultural direct collection statistical operations.
The application is composed of the following modules:
• Management of the survey. Import of validation items and rules;
• Management of agricultural holdings. Import and consultation of the sample. Formulation of monitoring lists;
• Management of the chain of collection. Assignment of user profiles and allocation of agricultural holdings to interviewers;
• Management of questionnaires. Includes the recording module;
• Payments. Introduction of generic and specific variables to prepare payment slips;
• Data analysis. Totalisers, ad-hoc selections and comparison with external sources;
• Maps;
• Synchronisation (between the interviewers’ laptops and the central database).

A web application was developed with a central environment targeted at survey management and analysis, and a local environment on laptops, targeted at questionnaire recording and validation by interviewers.
Hardware
Hardware used:
• 1 web server/application server (virtual machine, 4 CPU, 4 Gb ram memory)
• 1 database server (16 Gb ram memory)

Software
Software used:
• Java
• Oracle 10 and Oracle Express

Software architecture: see 3.3-2.Physical model of the application in annex.

Strengths of the collection and recording application
• Solution that may be used in other statistical operations;
• Recording by interviewers. Correction of errors by interviewers;
• Validation rules editor. Time saving in the programming and testing of rules;
• Selection editor (ad-hoc queries). Research by users with no need for programming;
• Update of the local online application;
• Advantages inherent in a web application (broadly-based access, central application update, centralised database, online output).

Internet data collection mode:

Prior to the beginning of the collection via Internet, agricultural holders from the sub-sample selected to this collection mode were contacted through circular letters, sent to inform them on the statistical operation, its purposes and the importance of their cooperation. It was also mentioned in the letter that they had been selected to answer using Internet and the necessary procedures to answer using Statistics Portugal’s WEBINQ. After that, agricultural holders were contacted by phone and questioned about their intention to answer via Internet (a valid email was then collected to allow the login to the service and further contacts). During the collection period, agricultural holders that didn’t answer the questionnaire were contacted by email, remembering the need to do it and reinforcing that, if not, they would be later contacted by an interviewer that would visit the holding to get the required data.

Face-to-face data collection mode:

Promoting and advertising the statistical operation
Before the interviews, letters (circular letters) were sent to agricultural holders informing them on the statistical operation, its purposes, the importance of their cooperation, and the date of the interviews.

Priority of data collection
• Holdings with a location other than the address of the holder – prior to the interviews, interviewers identified the agricultural holdings that had been allocated to them and which were located in a commune other than that of the holder's address. Priority was given to these interviews, especially those located in different agricultural areas. It was thus ensured that the questionnaire would be transferred accordingly and the interview made in due time. In addition, this procedure also permitted to avoid the possibility of the holder returning to the agricultural holding, leading to a new transfer of the questionnaire. Priority contact with these holders could also in a first instance avoid the transfer of the respective questionnaires.
• Large holdings and/or holdings with significant activity in their location area – the evaluation of the holdings' size, as well as the importance of their activity in the respective geographical area, were two crucial factors for interview priority.

Prior scheduling of the interview
With a view to enhancing the success of the interview, in particular the required availability of the agricultural holder to respond to the interview on a single occasion, where possible, the interviewer made an appointment with the agricultural holder. It was thus possible to avoid, for instance, incomplete collection of data, additional visits, and unnecessary further availability for concluding the collection/interview.

“I have been here” message
Reminders were adopted insisting on the need for making the interview and obtaining the necessary information. Therefore, in those cases where interviewers visited the address of the holder or agricultural holding, but could not get in touch with the holder, they left the message “I have been here”, i.e. the indication that they had visited the holding/address of the holder, and informing of a date for a new contact. This was intended to speed up the process, permitting the interviewer to establish a future contact with the holder in order to obtain response.

Interview techniques
With a view to raising the awareness of interviewees, leading them to cooperate and supply the required information, during the interviews interviewees were always informed about the purpose of the survey. They were persuaded, motivated and clarified regarding the importance of their cooperation. Where necessary, interviewers always sought to provide the required explanations, showing dependability and availability. In order to ensure the confidentiality and reliability of data, no third persons were allowed during the interviews, except where that was required by the person responsible for the information supplied.

Reminder that a response must be given
Whenever an interview could not be made, irrespective of the reason (impossibility to locate the holding or to contact the holder, absence of the interviewee, refusal by the holder to answer the interview), every effort was made to reverse the situation. The interviewer could resort to the local technical staff member. The interview would be considered non-achieved only after such conclusion had been drawn by higher hierarchical members in the chain of collection, and the decision communicated to the local technical staff member.

Obtaining alternative contacts
In addition, obtaining alternative contacts whenever it was impossible to contact the holder proved to be quite an important asset in terms of recovering missing interviews.

Payment of non-achieved interviews
The actual payment of non-achieved interviews was a further incentive for the interviewer to take all necessary steps to obtain the interview.

Treatment of refusals – Reminders until interview was considered non-achieved
In those cases where the reason for not making the interview (non-achieved interviews) was refusal, the interviewer tried to reverse the situation, insisting, in person and accompanied by the local technical staff member, on the need for the agricultural holder, or the responsible person, to supply the information required.
When it was not possible to reverse the situation at this level, the section manager was informed and indicated the subsequent step. If the situation remained unchanged (non-achieved interview), the section manager would follow the procedures in force, and request guidance to the regional coordinating body. This body would be responsible for any decision on the impossibility of conducting the interview. This decision alone made it possible to record a questionnaire to an agricultural holding as a non-achieved interview.

Treatment of refusals – Circular letter
In the cases of refusal confirmed by the regional coordinating body, a circular letter was sent to the holder/person responsible for supplying the information, informing them of the mandatory nature of the response and the fines to which they were subject in case of non-compliance with the legal obligation (according to Article 4 (1) of the Law No 22/2008 and Article 4 of the Decree-Law 136/2012). This made it possible to reverse a number of refusals. The final number of non-achieved interviews due to refusal was rather low at national level (see item 6.3.3 Non response error - item 1).

In case of a census 1=3+4+5

Only for sample survey, in which case 2=3+4+5

This item is a subset of 3.

4>4.1+4.2

5=5.1+5.2

24528

5.1>=5.1.1+5.1.2

6=5.2+5.1.2+4.2

Data validation on the electronic questionnaire available on WebInq was primarily executed by the 659 on-line validation rules, the large majority (653) classified has fatal errors, which disable the conclusion and submission of the questionnaire. These errors were from different types, such as completeness checks (non-compliance with the compulsory filling-in of a certain field; e.g. total area of the holding not filled in), relational/consistency checks (if a certain field is/is not recorded, another field must be/does not have to be filled in; e.g. existence of irrigated area, where the field irrigated land had not been filled in) and range checks (data must be included within a certain range, or cannot attain a certain value; e.g. rice fields in Entre Douro e Minho). Correction of these errors was mandatory.

There were also the so called warning errors, which basically warns the respondent that the situation he is describing is not usual. These errors are mostly relational/consistency checks (e.g. the holding has an irrigation system and does not record irrigated land, or the only labour force of the elder is the manager).

Face-to-face data collection mode:

Interviewer/staff member using a laptop to record data electronically
The interviewer's functions include data analysis, especially as regards consistency and alignment with local circumstances. Moreover, interviewers/staff using laptops also record, validate and review data in computer-readable format. In order to assist interviewers/staff in this function, 1 910 validation rules were created for recorded data, by resorting to the validation rules editor of SAGR. This editor makes it possible to centrally create strings of rules. A number of fine-tuning interventions and updates were made to the original rules in the course of the operation.
Validation rules triggered errors, which can be broken down into three large groups:

• Intrinsic errors (8) – those usually associated with the introduction of characters that are not accepted in specific recording fields, especially those related to the identification of the holder (e.g. characters not accepted in names, addresses, etc.). Any one of these errors prevents the questionnaire from being recorded;
• Fatal errors (1 298) – this type of error enables the questionnaire to be recorded; however, its validation will undoubtedly result in the questionnaire being labelled as incorrect, which prevents its conclusion. These errors can be completeness checks (non-compliance with the compulsory filling-in of a certain field; e.g. legal personality not filled in), relational/consistency checks (if a certain field is/is not recorded, another field must be/does not have to be filled in; e.g. existence of irrigated area, where the field irrigated land had not been filled in), arithmetic checks (wrong totals; e.g. wrong total cereal), range checks (data must be included within a certain range, or cannot attain a certain value; e.g. rice fields in Entre Douro e Minho), or sequential checks (non-sequential filling-in of certain fields; e.g. non-sequential filling-in of members of the holder's household). Correction of these errors is mandatory;
• Warning errors (604) – this type of error enables the questionnaire to be recorded and concluded. These errors may also be of the following types: range checks (e.g. rice field in the Algarve or rice exceeding 50 acres in Beira Litoral) and relational/consistency checks (e.g. the holding has an irrigation system and does not record irrigated land), completeness checks (e.g. the telephone was not filled in). These errors basically play a warning role, and the interviewer/staff member using a laptop will analyse the data triggering errors and confirm or correct them.

Validation may be broadly based, covering the whole national territory (443), or be restricted to the Mainland (413), Madeira (459), the Azores (144) or specific agricultural regions (451). For the Mainland questionnaire, specific validation rules were implemented for each region, so as to identify and validate certain characteristics.
Errors in SAGR were automatically triggered during the data recording procedure, enabling the staff member using a laptop to immediately correct/analyse data.
See 3.4 Example of the list of errors triggered during the data recording procedure (in annex, only available in Portuguese).
After the correction of fatal errors and the analysis of warning errors (reflected in confirmations and/or corrections of recorded data), interviewers, where they considered their work to have been concluded regarding the questionnaire/holding in question, would label it as “Concluded” in SAGR (afterwards, they would inform local technical staff members that the recorded information was ready to be analysed).

Local technical staff member
Local technical staff members analysed the information to detect possible inconsistencies in data collected and recorded, as well as incorrectly implemented concepts or misalignments with local/regional circumstances. An analysis was made of the information contained in the questionnaires concluded by the interviewers (those that they deemed ready to be analysed by the local technical staff member). For the purpose, the local technical staff member could/should resort to the Error Report, the Validate function, the Selection module and/or the Comparison with other Sources module. The local technical staff member could introduce corrections/changes, return it to the interviewer (Return to lower level). After a critical appraisal and analysis of the information, the local technical staff member would certify the questionnaire (thereby signalling the regional coordinating body that their work had been concluded and the questionnaire was ready to be analysed).

Regional coordinating body
After analysis, the regional coordinating body could return the questionnaire to the local technical staff member, who could resort to the interviewer, only if necessary for contacting the person responsible for the information supplied.

National coordinating body
In the course of the operation, the national coordinating body, similarly to the other elements in the data collection chain structure of the FSS, prepared regular analyses of data collected and, in order to complement and support regional analyses, submitted the output to be validated at the different levels in the chain of collection. As a result, the analyses implied the justification or correction of data collected. For different geographic levels, it usually covered information regarding:

• Comparison with other sources;
• Frequency of errors;
• Maximum permissible errors;
• Selections;
• Totalisers.

In addition to validating the information registered through warning and fatal errors, aggregate data and microdata in the FSS were also analysed. Information was analysed through the SAGR software application, by using features specifically developed for the purpose, in particular: totalisers, selections of holdings and comparison with external sources (microdata and aggregate data).

Both data collection modes:

The analysis of totalisers, i.e. aggregate information per geographic level, is essential to evaluate the consistency of collected data vis-à-vis local circumstances. Totalisers of the different geographic levels were analysed according to profiles in the chain of collection, thereby ensuring that an analysis would be carried out for all geographic levels.

Selections refer to the search for holdings according to selected conditions, with a view to detecting incorrections in data collection. The critical appraisal of aggregate data made it possible to obtain elements for the analysis of microdata, particularly in the identification of overvalued variables and high variable values – maximum permissible errors. Selections were frequently based on the existence of a given warning error (so as to identify potential systematic errors made by interviewers) and were especially adjusted to local agricultural specificities, i.e. a dynamic process.

The comparison of recorded data with other sources was instrumental for validating the information. For further information, see item 8.3 Coherence - cross domain.

For budgetary reasons, the FSS did not include the planned quality survey, therefore it was not possible to estimate coverage errors and content/measurement errors.

The non-response units and the unknown eligibility status units were eliminated from the sample, which was re-weighted.

There were also 316 units not found by the interviewer, which were considered with unknown eligibility status.

There is no pattern for the non-respondent holdings. This occurred throughout all the holdings' categories (whether we consider the size or the type of holding), which means that the non-response bias risks are not significant.

Questionnaire returned by the chain of collection
In addition to the interviewer, the questionnaire was analysed by different profiles in the FSS chain of collection (see section 3.4 Data validation), implying its return in case of error and/or information misaligned with local circumstances. This led to a more thorough analysis/validation. Returning the questionnaire to the interviewer and identifying the reasons avoided the perpetuation of possible errors and erroneous interpretations of the concepts.

Regular meetings involving the collection structure
Meetings carried out at the different levels of the FSS chain of collection facilitated information flows among them. Discussing the main issues/problems arising from the work developed made it easier to standardise the criteria to solve similar situations.

Procedures to confirm/correct microdata
The illustration in annex outlines the procedures to be followed when incorrections are detected or when questions raise doubts. The solution may involve confirming the situation after analysis of the “Observations” field, in a simpler case, or a new contact with the holder, in the most complex case. See annex.

Punctuality of the publication of the results

The number of hours per year for a full-time employee, used to calculate the Annual Work Unit, was 1 800h.

Finally, it is important to stress that the entire UAA of common land holdings is common land.

• All variables concerning organic farming;
• A_3_1_4 - Area of common land;
• A_2 - Legal personality of the holding, namely those identified as common land;
• B_1_8 - Flowers and ornamental plants (excluding nurseries);
• C_6 - Rabbits, breeding females

These changes may be chiefly accounted for by two reasons:
• The type of survey held in 2013 and 2016 (sample surveys). The common land (as the other legal person) wasn´t considered in the sampling design (in Annex IV of Regulation (EC) No 1166/2008 there is no precision requests concerning the legal personality of the holding);
• The difficulty in quantifying precisely the areas of these holdings. Common land extends throughout large open hilly mountainous areas, with poor soils and pastures or forest land, and it is often very difficult for the common land governing board itself to indicate the area in a precise manner.

The random differences in animal categories between this administrative source and the Farm structure survey results can mainly be justified by the basic methodological differences of these two operations (sample survey versus administrative exhaustive source).

FSS statistics are, obviously, crossable with other statistics/domains, namely crop, animal and national account statistics.

Statistics Canada, Survey methods and practices.

The analysis made to the variables collected in FSS and their mostly physical nature prevents the respective agricultural holders from being in any way identified. Moreover, there are variables such as crop area (in the case of temporary crops, as the name indicates, they vary every year depending on market and weather conditions during the crop year, and, in the case of permanent crops, they vary depending on the options taken by farmers at a given moment, with new planting or grubbing-up, etc.), which, due to its variability, do not allow for the identification of any holder. Information on livestock is under the same conditions: due to seasonality throughout the crop year, arising either from the productive cycle or from demand peaks on feast days (Christmas, Easter, etc.), it reveals significant changes in total livestock over the year. Also, agricultural labour is not subject to secrecy, given that it is collected and made available in groups, according to the legislation in force (Article 6 (4) (b) of the NSS Law).
Therefore, and also given the vast geographical area covered, no situations are envisaged in which the information released leads to direct or indirect identification of a certain agricultural holder, therefore there will be no statistical confidentiality treatment.

Dissemination of economic data, by type
Any issues related to the typology of holdings and economic data associated with physical data that are measurable in euro may be released, provided that they are based on aggregates. This information is currently already released as such, therefore this situation is also covered by the legislation in force.