Statistical Surveys Programme 2016

Obligatory survey.

Deadlines for answers in each method of data collection.

Article 28

1.The President of the Central Statistical Office shall appoint census enumerators, statistical interviewers, experts and voluntary statistical correspondents.

2.The responsibilities of census enumerators shall include collecting statistical data in population and housing censuses, whereas statistical interviewers shall collect statistical data in other surveys in the form of responses to questions contained in the statistical forms, questionnaires and interview documents.

3.The census enumerators and statistical interviewers during performing their tasks specified under paragraph 2 shall be legally protected as the public servants.

Organizational Instruction

Interviewers have to be  equipped by directors of regional offices with badges and identification cards.  

Interviewers must be trained, pass the exam successfully, and follow the methodological manual during the interview.

CSO - Central Statistical Office 

RSO – Regional Statistical Office

ARMA -  Agency for Restructuring and Modernisation of Agriculture

AFQI - Agricultural and Food Quality Inspection

HOGC - Head Office of Geodesy and Cartography

PESEL -  Personal Identification Number

REGON - National Official Business Register

TERYT - National Official Register of Territorial Division of the Country

CAPI - Computer Assisted Personal Interview

CATI  - Computer Assisted Telephone Interview

CAII  - Computer Assisted Internet

Agricultural holding is understood as a single unit, both technically and economically, which has a single management and which conducts agricultural activity. 

Agricultural activity (primary or secondary), according to the NACE. rev.2, includes activities listed in section A, division 01, groups:

- 01.1 - growing of non-perennial crops,
- 01.2 - growing of perennial crops,
- 01.3 - plant propagation,
- 01.4 - animal production (subgroup 01.49 is excluded, with the exception of the raising and breeding of ostriches, emu and rabbits as well as other fur animals),
- 01.5 - mixed farming,
- 01.6 - class 01.61 - support activities for crop production (maintaining good agricultural condition following environment protection standards).

A natural person’s agricultural holding (A_2$holdingtype ne 4) is covered in the survey if it has an agricultural land (A_3_1+B_5_1) of 1 ha or more or if it has an agricultural land less than 1 ha (even without agricultural land) conducting special branches of agricultural activity or complying with the following physical thresholds:
- 0.5 ha fruit trees plantations (B_4_1_1$ha), or
- 0.5 ha fruit bushes plantations (B_4_1_2$ha), or
- 0.3 ha ornamental plants and orchard nurseries (a part of B_4_5$ha), or
- 0.5 ha field vegetables and strawberries (B_1_7_1$ha), or
- 0.1 ha vegetables and strawberries under cover (B_1_7_2$ha), or
- 0.1 ha flowers and ornamental plants under cover (B_1_8_2$ha), or
- 0.5 ha hops (B_1_6_2$ha), or
- 0.1 ha tobacco (B_1_6_1$ha), or,
- 0.0025 ha mushrooms (B_6_1$ha), or 

- 10 cattle (C_2$heads), or
- 5 cows sum (C_2_6$heads, C_2_99$heads), or
- 50 pigs (C_4$heads), or
-10 sows (C_4_2$heads), or
- 20 sheep (C_3_1$heads), or
- 20 goats (C_3_2$heads), or
- 100 poultry (C_5$heads), or
- 5 horses (C_1$heads), or
- 50 rabbits (C_6$heads), or
- 10 wild animals kept for slaughter, (a part ofC_99$heads), or
- 20 beehives (C_7$heads), or

runs organic production.  (A_3_2_3$ha >0 or A_3_2_4_1$heads>0 or A_3_2_4_2$heads>0 or A_3_2_4_3$heads>0 or A_3_2_4_4$heads>0 or A_3_2_4_5=’y’)

A legal person’s agricultural holding (A_2$holdingtype = 4) - in case agricultural activity is not primary - is covered in the survey if it has an agricultural land (A_3_1+B_5_1) of 1 ha or more  or if it runs livestock production.

There are 1250 records with the total standard output equal to zero in the file sent to Eurostat. These are holdings with fallow land (B_1_12), kitchen gardens (B_2), permanent grassland and meadow no used for production, eligible for subsidies (B_3_3) and other livestock (C_99). These kind of farms were included in the survey because they meet the EU and national definitions of the holding and agricultural activity. The standard output coefficients for the characteristics mentioned above, according to the Community typology, is equal to zero.

The farm was given the NUTS3 region ID of the LAU1 unit it is located within. Location of the farm within the LAU1 unit was verified and confirmed in the survey.

LAU1 unit was determined using the criterion of the location of the buildings (administrative, for livestock or other production), and if there were not buildings - the biggest parcel.

Data related to the land use, sown area, livestock and the number of agricultural tractors and telescopic loaders were collected as of 1 June 2016.

Information on the use of support from the Rural Development Programme - reference period 2014-2016.

The remaining data refers to the 12 months ending on the reference day (2 June 2015 – 1 June 2016).

The bodies involved in the survey were:

• Central Statistical Office,
• Statistical Computing Centre,
• Regional Statistical Offices,
• Centre for Research and Statistical Education,
• Institute of Agricultural and Food Economics - National Research Institute.

The share of responsibilities among bodies involved was as follows:

I. Within the CSO:

• Agriculture Department and Demography and Labour Department - all works related to methodology of the survey including the questionnaire content, trainings, elaboration of the algorithms for data control and corrections as well as data imputation, addition of administrative data, development of the assumptions for the Eurofarm, data analysis and publication.
• Methodology, Registers and Standards Department – sample design, sample selection, weight’s corrections, precision calculations.
• Surveys’ Programming and Coordination Department -  was responsible for organizational issues, such as engagement of interviewers and arrangement of equipment for data collection, checking at all stages of the survey progress. In addition specialists from this Department were responsible for preparation of the geographical coordinates.

II. Statistical Computing Centre, branch in Radom – prepared – based on the assumptions from the Agriculture Department – the electronic questionnaire, developed the managing application (CORstat), IT personnel was also involved in the process of purchasing tablets for interviewers as well as supervising the functioning of the CATI centre.

III. The RSOs

The RSO was responsible for conducting the survey in individual voivodship from the organizational and content point of view.

• Organizational  Coordinators - thanks to the CORstat application current observation of the course of survey was possible. Everyday pre-defined reports were prepared. In addition coordinators could prepare other necessary reports, using accessible filters. Coordinators could change channels for data collection.
• Content Coordinators – data control and analysis using the Content Module.
• External interviewers – data collection in CAPI (they were engaged from the resources of the Centre for Research and Statistical Education in Jachranka and were trained by the RSO staff both in the content of the survey and in the IT tools (tablet + electronic questionnaire)).
• Telephone interviewers – data collection  in CATI.
• Statistical interviewers (permanent and supplemental) - in case of lack of the telephone number of a farm or preferences of farmers for the face to face interview (CAPI), employees of the RSO played the role of statistical interviewers.

The RSO in Olsztyn – apart from the tasks enumerated above, the IT employees elaborated the Content Module to be used in the survey, they implemented the assumptions for data validation, imputation, typology of farms and supplemented individual records with data from administrative sources. They were also responsible for data processing and preparation of the file to be transmitted to Eurostat (Eurofarm).

IV. The Centre for Research and Statistical Education in Jachranka (the budget economy unit) was engaged as the subcontractor to organize recruitment of external interviewers.

V. Institute of Agricultural and Food Economics - National Research Institute -  in cooperation with the Agriculture Department was responsible for calculation of the Standard Output and preparation of the algorithms for typology calculation.

The source of the frame was the statistical register. The register was built on the base of the AC 2010 results and administrative sources.

The frame used to draw the sample for the survey is a list frame. The list frame included the following information:
- identification number of an agricultural holding,
- address of the holder,
- address of the seat of the holding,
- geographical coordinates of the address of a seat of the holder and of the seat of the holding,
- telephone number,
- e-mail address,
- information on the holder:
--- first name and surname/name,
--- PESEL number for a natural person,
--- identification number REGON for a legal person and an organisational unit,
- information necessary for stratification: running of organic production, special branches of agricultural activity, area of agricultural land, livestock, economic size.

The statistical register was updated every year with results of statistical surveys and administrative data: ARMA – Records of agricultural holdings, Records of producers; AFQI – Register of organic farms; Ministry of Finance -  Special branches of agricultural activity, CSO – REGON, TERYT.
Because of the organisation of statistical surveys and the schedule of the frame preparation as well as the dates of availability of statistical and administrative data  necessary for updating, data included in the frame was delayed in comparison with date of survey from 0,5 to 2 years.

The sampling design was based on a single-stage stratified random sampling of holdings with take-all strata.

The broad subject matter of this survey caused some special approach to sample drawing and first of all it caused necessity of usage of stratification.  Experience from previous farm structure surveys: 2005, 2007, 2010 and 2013 (experience of the European Union countries and Poland as well) was taken into account.

The method of a simple random sampling without replacement was used in every stratum independently.

Due to the fact that it was difficult to use the same variables for each type of holdings, therefore, before sampling, the population of holdings was divided into the following categories:
A. Farms with agricultural activity, not classified as organic farms, of which:
     I. farms, which in the sampling frame had: 20 head of sheep or 20  goats or 2000 heads of hens or 500 head of turkey or 500 head of goose or 500 head of duck or 80 beehives and farms conducting activity connected with special branches of agricultural production and with minimum 250 thousand euro economic size, as well
     II. basic category of farms with agricultural activity but not mentioned above.
B. Non-active farms.
C. New created farms and farms without established type of farming and economic size.
D. Organic farms.
E. Agricultural holdings of legal persons and organizational units without legal personality.

Each population category was divided by voivodships (NUTS 2) and strata were created using different criteria of stratification depending on the category of holdings.
There are 24 strata in total across all population categories:

Category A.I forms a single stratum - stratum h=01.
Category A.II comprises 10 strata i.e. h= 02, 03, ... 11
Category B comprises 5 strata i.e. h= 12, 13, ... 16
Category C comprises 6 strata i.e. h= 17, 18, ... 22
Category D forms a single stratum - stratum h=23.
Category E forms a single stratum - stratum h=24.

Samples were drawn only for:
- category A.II, strata h= 02, 03, ... 10
- category B, strata  h= 12, 13, ...15
- category C, strata h= 17, 18, ... 20

Category A.II -  as criteria of stratification, we took two variables: the area of agricultural land (A_3_1+B_5_1) and the economic size.  The economic size of holding was calculated in accordance with the Eurostat methodology.
Category B - as a criterion of stratification, the total area of holding (A_3_1+B_5_1+B_5_2+B_5_3) was used.
Category C - as a criterion of stratification, the area of agricultural land was used.  

Strata codes in database take into account intersection of original 24 sampling strata in each voivodship with NUTS2 codes, and additional strata with outliers (where weights are 1).

The size of the sample was decided in accordance with financial and organisational possibilities and the precision requirements provided in the Regulation 1166/2008. The number of agricultural holdings in the population and in the sample by category is provided in the following table:

           Number of holdings in the population and in the sample by categories

Stratification and sampling allocation were carried out by means of the numerical optimisation method. The description of the solution to this problem was published in the article written by B. Lednicki and R. Wieczorkowski (2003) (see section 9.6 Documentation on methodology - item 2).

Records of agricultural holdings benefitting from support in respect of the Rural Development Programme (used for replacing the values of characteristics)

Legal base:

EU - Regulation No 1305/2013 of the European Parliament and of the Council of 17 December 2013 on support for rural development by the European Agricultural Fund for Rural Development (EAFRD) and repealing Council Regulation (EC) No 1698/2005

PL -  Law of 20 February 2015 on support for rural areas development by the resources of the European Agricultural Fund for Rural Development within the Rural Development Programme  2014-2020

Responsibility: ARMA

Reference period: 2014-2016

Records of agricultural holdings (used for replacing the values of EFA characteristics, and validating and analysing the FSS data)

Responsibility: ARMA
Reference period: 2016 campaign

Register of Organic Farms (used for replacing the values of characteristics)

Legal base:

EU - Council Regulation (EC) No 834/2007 of June 2007 on organic production and the labelling of organic products and repealing Regulation (EEC) No 2029/91,

PL - Law of 25 June 2009 on organic farming. 

Responsibility: AFQI
Reference day: 31 December 2016

Records of  the Land Communities (used for replacing the values of characteristics)
Responsibility: HOGC

Reference day: 1 January 2016

Law on official statistics:

Article 5

1.The official statistics have a mandate to collect from all available sources, specified in detail in the programme of statistical surveys of official statistics or in other laws and to gather statistical data from and about business entities, other legal entities and entities without legal status and their activities, further referred to as 'individual data' and statistical data on natural persons concerning their life and status, further referred to as 'personal data'.

Article 13

1.The data collected and stored by State administration bodies and units of local authorities, other governmental agencies, organs maintaining official registers and the National Bank of Poland, on the basis of Regulations other than this Law, are data of information systems of public administration, and are further referred to as the 'administrative records'.

3.State administration bodies and units of local authorities, other governmental agencies, organs maintaining official registers and the National Bank of Poland on a free-of-charge basis, shall submit to the official statistical services the administrative records stored by them in the scope, form and time specified each time in the programme of statistical surveys of official statistics, especially in the form of extracts from the registers, copies of data files, collected declarations, registration documents and other official forms, the results of measurements, and data on environment monitoring, and shall provide data from their computerised database systems.

The CSO representatives participate in meetings concerning the content of administrative registers and emphasize statistics’ needs, also in the context of reducing the burden on the respondent. This cooperation and the arguments presented by the statisticians bring moderate results, since changes to the administrative registers are laborious and costly. Actions at EU level aimed at coherence of the needs (statistical and administrative data) reported to Member States would be helpful.

Differences in definitions of some characteristics, for example:
Register of Organic Farms:

Organic farming - other animals covers: equidae, bees, rabbits, deers, and are different from the categories in Other livestock (C_99).

Records of agricultural holdings:

Total agricultural land as well as Permanent crops are different from characteristics (A_3_1+B_5_1) and B_4.

Different reference periods for statistical survey and administrative data.

For the FSS purposes (especially when the data is replaced) variables which have the same definition were used.

If possible, data was collected for individual characteristics so that allowed to aggregate data according to statistical requirements.

Differences in reference periods were taken into consideration when comparing and analyzing the data.

Register of Organic Farms:
There were 5 duplicated units with different agricultural production. The units were under the control of two certification bodies for different production. The one concerns crops production, the other – beekeeping.

Register of Organic Farms:

68 records with missing data were found.

The missing data were completed (AEQI).

Register of agricultural holdings (EFA):

800 records with missing data for EFA (needed data was not provided by farmers).

Register of Organic Farms:

Some data on organic crops area were given in square meters.

Register of agricultural holding benefitting from the Rural Development Programme:

Register of agricultural holdings (EFA):

Records of agricultural holdings: agricultural producers benefitting from direct payments in a given year (including EFA);
Register of Organic Farms: organic producers;
Records of agricultural holdings, Register of Organic Farms and Records of agricultural holdings benefitting from support in respect of the Rural Development Programme: the common identifier was the producer number in the ARMA which is linked to the PESEL or REGON of the holder.

Data were collected using the following methods:

• CAPI – conducted by external and statistical interviewers using tablets with questionnaire application.
• CATI – carried out by telephone interviewers with the use of specialist Call Centre software.
• CAII/CAWI – self-enumeration. On the CSO website, after entering a login and a password, respondents could access a questionnaire application.

In some cases mixed-mode was used (e.g. partly filled questionnaire in CAII was completed in CATI or CAPI).

The data entry modes were as follows:

• electronic data capture during CAPI and CATI,
• entering the data by the holder  - the  CAII /CAWI questionnaire application was downloaded from the CSO web site and installed on the respondent's computer. Once the form has been completed and the holder has saved the data, the data were automatically encrypted and sent to the central server.

A series of actions were introduced to reduce the non-response rate.

An important part of those actions was the dissemination among farmers of information regarding the survey, its objectives and significance, as well as the obligation to participate in the survey. To every respondent participating in the survey a letter from the CSO President was sent. In commune offices the posters informing about the survey have been placed. After sending the Presidents letter a hotline for respondents and interviewers started to work – from the beginning to the end of the survey.

The proper training of interviewers also contributed to the reduction of the number of refusals. They were able to inspire a positive response to the survey and handle difficult respondents. If a holder was absent, the interviewers were able to conduct interviews with adult members of the holder's household.

The work of interviewers was monitored by regional Organizational Coordinator using the management application (CORstat).

If, during the online self-enumeration, a respondent completed only a part of the questionnaire, a interviewer called or visited that respondent to complete the form.

In cases of legal persons’ holdings, the reminders were sent by e-mail.

Number of holdings in the survey frame plus possible (new) holdings added afterwards

In case of a census 1=3+4+5

Number of holdings in the gross sample plus possible (new) holdings added to the sample

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

Number of ineligible holdings with ceased activities

This item is a subset of 3.

Number of holdings with unknown eligibility status

4>4.1+4.2

Number of eligible holdings

5=5.1+5.2

Number of eligible non-responding holdings

5.1>=5.1.1+5.1.2

Number of the records in the dataset 

6=5.2+5.1.2+4.2

In the FSS, one electronic form was used being adjusted to the specific methods of data collection. The questionnaire included the agricultural farm identification number, legal status, name of the holder/holding, the address of the headquarter of the holding and of the holder and contact data. Further part of the form included questions grouped into ten major sections:

1. 1.      Land use;
2. 2.      Sown area and other;
3. 3.      Methods of agricultural production
4. 4.      Irrigation
5. 5.      Use of fertilisers;
6. 6.      Livestock;
7. 7.      Tractors and telescopic loaders;
8. 8.      Economic activity conducted on the holding;
9. 9.      Income structure of the holder’s household;
10. 10.  Labour force.

The list of questions in the electronic questionnaire is provided in the annex.

Data validation took place at the data collection level (interviewers), regional (voivodship) level (Content Coordinators) and central level (CSO experts).

Questionnaire application contained the algorithms of accounting and logical control. At the same time, the applications did not allow the omission of the questions which were required to be completed on certain “paths” of the interview. The data was subject to control and approval by Content Coordinators in the Content Module. If any data was found to be potentially incorrect, a Content Coordinator could make the necessary adjustments (if on the basis of the available data such an adjustment was possible) or request that the interview be repeated.

After loading the data obtained from the approved CAPI, CATI, CAII forms and administrative sources, as well as imputed data for units non-response, the central set was subject to automatic logical, accounting and range control. The algorithms of control were prepared by the CSO experts and also contained the rules for validation required by Eurostat (Manual for data suppliers, survey 2016, rev. 7).

For each module (section) of the questionnaire, the rules for inter-section control were prepared. The control also covered the inspection of section interrelations and coherence. The modules were controlled in a particular order. After checking and making any potential adjustments to a given module, the next module was checked. The rules of control in individual modules also had a pre-determined order. If an error was identified, the application performed automatic adjustment.

After the control was completed, a report was generated containing information on the used validation rules, occurring errors and applied adjustments. The records which contained errors and could not be automatically corrected were analysed by experts who decided on recognising the error or choosing the adjustment method on the basis of specialist knowledge and available data.

Tools for data validation were:

- at the stage of data collection  -  the questionnaire application, the Content Module (the Module received the data collected by interviewers/telephone interviewers, when a given farm was closed by the voivodship Organizational Coordinator. The Content Module, after supplementary validation, was used by Content Coordinators to analyse the collected data in detail. The analysis could use pre-defined inquiries (filters) and individually constructed queries (on the basis of SQL tools)).

- at the stage of data processing (central dataset) - a dedicated application using SQL and SAS tools.

4. Any other applied adjustment of weights.

The list of characteristics for the FSS 2016 is in accordance with the EU requirements and the subject scope of the survey, and also accounted for the requirements of the statistics and the needs of the domestic users. Apart from the characteristics required by Eurostat and fulfilling the national needs at the same time, in the FSS characteristics exclusively for the domestic needs were collected in addition. These needs were submitted primarily, by the Ministry of Agriculture and Rural Development (own analyses, shaping the agricultural policy), scientific institutes, producer’s organizations as well as for the needs of statistics: ensuring the data time series, livestock production forecasts, crops and harvest estimates, estimates of the number of workforce engaged in agriculture - ALI, analyses on population connected with agriculture and rural  areas, calculation of the registered unemployment rate.

The list of characteristics surveyed exclusively for the national needs:

• income structure of holder’s household,
• sales of the final production,
• area of successive secondary crops (winter, spring),
• area of nurseries of fruit trees and bushes,
• number of head of heifers and bullock below 1 year,
• specific weight and use groups of pigs,
• number of head of lambs and ewes used for dairy production,
• number of head of laying hens producing eggs for consumption and hatching,
• number of head of female fur animals (other than rabbits),
• number of tractors per the power of engine,
• use of mineral, lime and organic fertilisers,
• use of plant protection products,
• did the person live and form a household with the holder on 1 June,
• work on own holding in the current week (exclusively; mainly; additionally; worked only outside the holding),
• level of general education of the manager,
• person’s working time scope on the farm related to agricultural production during the last 12 months less than 0.05 of a full-time job (0-112 hours, i.e. 0-14 days),
• number of working days worked on the holding connected with agricultural production in the period of the last 12 months by contractual employees, neighbour assistance, other persons working on the legal persons’ farms.

All RSEs are compliant (with one exception – slight excess for rare variable „Fruit and berry plantations” in one of the NUTS 2 region with smallest area of UAA - PL33).

Before the survey, 8,5% of potential duplicates were identified in the frame. They were eliminated during the data collection. The survey showed that approximately 1% of the real duplicates were in the frame.

Duplicates were treated as liquidated units therefore the weights were adjusted.

6,2%

Over-coverage rate was computed as the proportion of units from the sample which do not belong to the target population to the overall sample size.

The main source of measurement errors were respondents and interviewers/ telephone interviewers.

There were cases when respondents reported the area of agricultural land according to geodetic definition rather than statistical. Detailed calculation of the holding’s area in the later part of the form application corrected the majority of this errors. There were cases when respondents discontinued the interview (CAII) or answered less accurately at the end of the interview.

Wide range of surveyed characteristics, difficult questions, as well as unclear definitions also caused measurement errors.

Characteristics that caused most measurement errors are listed below:

• respondents and interviewers found the Labour force section as the most complicated. There was a tendency to deliberately shorten the list of members of the family labour particularly with regard to the questions concerning OGA (E_2_2_1 – E_2_2_4). There was also a problem with collecting information on the working time of hired workers involved in OGA (E_2_4_1, E_2_4_2),
• more than 50% of production self-consumed by the holder (A_3_3_1) – this question was difficult because of the definition of final production (this definition should be simplify and added to the Handbook),
• problem with separation of the area of fresh vegetables growing in the crop rotation with agricultural crops (B_1_7_1_1) from growing in rotation with horticultural crops (B_1_7_1_2),
• settlement of arable land in the area of applied tillage methods: conventional (M_1_1), conservation (M_1_2) and direct seeding (M_1_3),
• question concerning soil cover: normal winter crop ((M_2_1_1), cover or intermediate crop (M_2_1_2), plant residues (M_2_1_3), bare soil (M_2_1_4),
• manure exported from the holding (M_6_3) and manure imported to the holding (M_6_4).,

The main external source which was used for the data comparisons was data from the ARMA. The outliners and inliners in the livestock data were compared with the data of the animal production survey. This check allowed to catch respondents’ and interviewers’ errors concerning area of agricultural land and number of animals.

All detected errors were corrected automatically or by expert method at the data collection stage or during the dataset validation. For characteristics for which errors most often appear, the Manual for interviewers is supplemented with comments and additional explanations. The control algorithms in the form application and the validation rules are also improved.

The main reasons for unit non-response were the lack of contact and the refusals.

Re-weighting was performed to eliminate this error.  Legal persons’ holdings and organic farms were exceptions (all organic holdings as well as legal persons’ holdings included in the frame were covered by the survey and additional information about them was available), as imputation was used in their case.

In accordance with Regulation 1166/2008, for all organic farms covered by the survey (including non-response organic units) data on organic land use, sown area and livestock were transferred from the Register of Organic Farms. The remaining data were imputed from the most similar organic farms whose data were obtained during the survey (the “nearest neighbour” method).

For the farms of legal persons, some data for land use, sown area and animal stock were transferred from the reporting forms and the remaining data were imputed from the most similar holdings of legal persons which took part in the survey (the “nearest neighbour” method). All legal persons' holdings are covered by the reporting system of the CSO. In case of imputation of non-response legal persons' units, we used the following reporting forms: “The report on the sown area, yield and harvest”( R-05sz), “The report on the area of horticultural crops under protective cover”( R-08), “The report on the cattle, sheep and poultry population and livestock production”( R-ZW-B), “The report on the pig population and the production of pork”(R-ZW-S).

The bias risk associated with non-response was limited thanks to the fact that weights correction was made separately in particular sampling stratum. The strata, in turn, were created separately in several of the most important holdings’ categories. 

Incomplete questionnaires occurred in the case of online self-interviews (CAII). They were forwarded for completion to the CATI or CAPI methods.

In the CAPI and CATI methods, apart from infrequent cases, fully completed forms were obtained. The questionnaire application did not allow to skip questions.

If after finishing the stage of the data collection, incomplete questionnaires occurred, they were supplemented on the basis of filled questions by the Content Coordinators using the Content Module (expert's method).

The Content Coordinators, based on their agricultural knowledge and the specificity of agriculture in their voivodship, supplemented missing data. The method was used only if the level of completion of the questionnaire allowed to determine the kind of holding and the type of production. In case of questionnaires filled slightly, data were removed from the database and the farm was marked as unit non-response.

There were no significant non-responses for any of the surveyed characteristics.

The main sources of processing errors were: mistakes in algorithms for validation programme made by the CSO experts, as well as wrong implementation of the algorithms by IT. 

Wrong algorithms and errors in implementation were verified and corrected.

The CSO has revision policy in line with the European Statistics Code of Practice,  legal acts of the European Union concerning Community statistics as well as guidelines on ESS revision policy for the Principal European Economic Indicators (PEEIs).

In case of planned revision, the CSO elaborates annual schedule for the revisions of statistical data, which is published on the Information Portal of the CSO. This schedule contains all revisions planned for particular year, including dates of data availability after completion of the revision, of which final data.

In addition, information on important planned revisions, resulting from changes in classifications, standards, methodology or definitions is provided in an especially prepared information notes on the Information Portal of the CSO in advance relevant to the publication of data.

In case of unplanned revisions and corrections of editorial errors, results are published immediately after their completion together with explanation of the reasons.

In case of farm structure surveys (including FSS 2016) there is a practice of publishing preliminary data and final data. Since 2002 to date there was no need to conduct unplanned revisions in case of the FSS.

The definitions of characteristics for the FSS 2016 were in accordance with the EU requirements and in compliance with the Handbook FSS 2016.

The number of hours per year for a full-time employee used to calculate the Annual Work Unit is 2120.

Data on common land were collected from administrative source.

There have been no changes in comparison to the FSS 2013.

The FSS 2016 data are not fully comparable with the AC 2002, FSS 2005 and 2007 data, but are comparable with AC 2010 data. The differences concern only the smallest units, i.e. under 1 ha of agricultural area.

The previous method did not continue and in the FSS 2016, for the first time, separate data on common land were collected. To avoid overlapping of the area of common land, during training of interviewers, as well as in the methodological manual it was underlined that the area of the agricultural land does not contain common land.

The FSS validated, aggregated data were analyzed with comparison with other sources of data: crop and animal production surveys (eg animal slaughter, poultry hatching), other statistical surveys (eg external trade balance), external sources (eg ARMA,  data from rape and sugar beet contracting),  The analysis of the FSS data showed that results and trends were coherent.

The FSS data are used in agricultural analysis, estimation of crop and animal production, EAA, national accounts, labour force and agro-environmental studies, as well as FADN.

The following publications have been issued or are planned to be issued:

1.      Land use and sown area

2.      Characteristics of agricultural holdings

Publications 1 contains preliminary results, publications 2 - final results (data collected in all sections of questionnaire). The publications contain methodological information, together with basic definitions, analysis of results, as well as tables presenting numerical data (publication 2 presents data from all sections of the FSS questionnaire). The FSS 2016 data will be also available in comprehensive CSO publications, e.g. in the Statistical Yearbook of Poland and the Statistical Yearbook of Agriculture. All publications are released in paper form, and are available on-line.

1. May 2017
2. September 2017

Researchers can use anonymised micro-data at a specially prepared computer station in the CSO. Reports with aggregated data generated by user are checked by experts (statistical staff), responsible for enforcing statistical confidentiality according to the rules mentioned in section 11. Confidentiality.

1. CODY  R. (2008), Cody’s Data Cleaning Techniques using SAS, Second edition, SAS Institute Inc., Carry, North Carolina, USA,
2. LAVALLEE P., HIDIROGLOU M. (1988),  On the Stratification of Skewed Populations, Survey Methodology, 14, pp. 3 – 43,
3. LEDNICKI B., WIECZORKOWSKI R. (2003), Optimal stratification and sample allocation between subpopulation and strata, Statistics in Transition, Vol. 6 No. 2, pp. 287 – 303,
4. KOZAK M., (2004),  Optimal stratification using random search method in agricultural surveys,  Statistics in Transition, Vol. 6 No. 5, pp. 797-806.

Pursuant to the provisions of the Law on official statistics, all individual information and personal data collected and stored are covered by statistical confidentiality. The data obtained in the farm structure survey can only be used exclusively for statistical studies, compilations and analyses and for creation by the public statistical services the frames for statistical surveys conducted by those services. Sharing or use of data collected for other purposes is prohibited under the sanction of criminal liability.

According to the above-mentioned Laws, all persons performing work related to the FSS 2016 were obliged to comply with the statistical confidentiality and were allowed to perform the work after training and instruction about the nature of the statistical confidentiality, as well as, signing the written oath with the content specified in the Law on official statistics.

Similar as in the case of all statistical surveys conducted by the CSO, also in the course of collecting, storing, processing and disseminating data from the FSS 2016, the provisions of the Law on official statistics were strictly complied.

The Law on official statistics provides for the confidentiality and safety of statistical data in the articles cited below:

Article 10.

The collected and gathered in the statistical surveys of official statistics individual and personal data shall be confidential and subject to particular protection; the data shall be used exclusively for statistical calculations, compilations and analyses and for the creation by the statistical services of official statistics sampling frames for statistical surveys conducted by those services; providing or use of individual and personal data for other than specified above purposes shall be prohibited (statistical confidentiality).

Article 12.

The staff of the official statistical services, the census enumerators, statistical interviewers and other persons performing activities in the name and on the behalf of official statistics, having direct access to individual and personal data shall be obliged to observe without exceptions the statistical confidentiality and shall be allowed to perform those activities only after delivering an oath in a written form, at a statistical office or other units of official statistical services, of the following contents:
“I hereby take summons that I shall perform my tasks on the behalf of the official statistics dutifully, in accordance with the professional ethics of a statistician and that I shall keep secret from the third parties the individual data known to me during performing those tasks.”
Article 39.

The President of the Central Statistical Office shall ensure that the storing of collected statistical data guarantees observing the principles of statistical confidentiality.

Article 38.

1. It shall not be allowed to publish or disseminate individual data obtained in the statistical services of official statistics.

2. It shall not be allowed to publish or disseminate obtained in statistical surveys of official statistics statistical information which can be linked or can identify natural persons or individual data characterising business entities, especially if the aggregated data consist of less than three entities or the share of one entity in the compilation is higher than the three-fourths of the total.

• shortening the period between updating of the frame and drawing the sample,
• cooperation with the owners of administrative sources on further improvement of data quality and accelerating the date of data delivery to the CSO,
• in order to diminuish the respondents' burden and strengthen data control – prefilling the questionnaire with administrative data before the survey,
• change of the survey date from June/July to October/November – lower respondents engagement with field work, possibility to obtain updated administrative data,
• in order to encourage farmers to use CAII method - allow the respondents contact on the chat or telephone with a content expert during completing the questionnaire,  adding the possibility of providing data by respondent calling for the hotline.