Farm structure (ef)

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

Compiling agency: Statistics Estonia

Time Dimension: 2016-A0

Data Provider: EE1

Data Flow: FSS_ESQRS_A


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



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

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1. Contact Top
1.1. Contact organisation
Statistics Estonia
1.2. Contact organisation unit
Enterprise and Agricultural Statistics Department
1.5. Contact mail address
Tatari 51, 10134 Tallinn, Estonia 


2. Statistical presentation Top
2.1. Data description
1. Brief history of the national survey 
The Agricultural Census (hereinafter AC) 2010 was the sixth AC in Estonia; the previous ones were conducted in 1919, 1925, 1929, 1939 and 2001. In AC 2001, the national threshold was used, but a new threshold was applied after that and the AC 2001 data were recalculated accordingly. On the basis of AC 2001 data, the Farm Register was composed – this is now regularly updated and used as a frame for all agricultural statistics surveys, including AC 2010.

Since 2001, Farm Structure Surveys have been conducted according to the EU legislation.

 

2. Legal framework of the national survey 
- the national legal framework

There is no special national legal act for FSS. The legal basis is the Official Statistics Act, just as in the case of other statistical surveys. 

- the obligations of the respondents with respect to the survey

The respondents are required to answer all questions and give true and complete answers. 

- the identification, protection and obligations of survey enumerators Field enumerators were not used. Confidentiality rules are imposed by the Official Statistics Act and are mandatory also for telephone interviewers. In the Official Statistics Act, it is said that persons who, in the course of performing their official duties or using data for scientific purposes, have access to data that allow direct or indirect identification of a statistical unit are required to ensure that such data are used only for statistical purposes and to prevent unlawful dissemination of such data. All other obligations for interviewers (introducing themselves, conducting surveys, special cases, etc.) are explained in the instruction manual for interviewers. All telephone interviews are recorded in order to enable the monitoring of the quality of the interviewers’ work.
2.2. Classification system

[Not requested]

2.3. Coverage - sector

[Not requested]

2.4. Statistical concepts and definitions
List of abbreviations
AC – Agricultural Census

ARIB – Agricultural Registers and Information Board

CATI – Computer Assisted Telephone Interview

IACS – Integrated Administration and Control System
2.5. Statistical unit
The national definition of the agricultural holding
The national definition is in accordance with the EU definition.

Agricultural holding – a unit with single technical and financial management which produces agricultural products or maintains its land in good agricultural and environmental condition and where:

- there is at least one hectare of utilised agricultural land or

- there is less than one hectare of utilised agricultural land and agricultural products are produced mainly for sale.

In the case of holdings with less than one hectare of utilised agricultural area, the physical threshold was used to determine potential holdings producing mainly for sale. The physical thresholds are in accordance with the thresholds specified in Annex II of Regulation (EC) No 1166/2008 but are lower.

Units where agricultural products are not produced but only land is maintained in good agricultural and environmental condition, even if they do not have other agricultural activity, are included from 2007.

2.6. Statistical population
1. The number of holdings forming the entire universe of agricultural holdings in the country
17,026

 

2. The national survey coverage: the thresholds applied in the national survey and the geographical coverage
The threshold is in accordance with EC 1166/2008. The survey is representative for NUTS2 (Estonia as a whole).

In the case of holdings with less than one hectare of utilised agricultural area, the physical threshold was used in order to determine potential holdings producing mainly for sale. The threshold was as follows: At least:
- 3 cattle (C2$heads);
- 10 pigs (C4$heads), sheep (C3_1$heads) or goats (C3_2$heads);
- 10 swarms of bees (C_7$hives);
- 100 heads of poultry (C_5$heads);
- 0.5 ha of fruit and berry plantations (B_4_1$ha);
- 0.3 ha of fresh vegetables (B_1_7_1$ha+B_1_7_2$ha);
- 0.2 ha of nursery (B_4_5$ha);
- 0.01 ha of outdoor flowers (B_1_8_1$ha), crops under glass (B_1_7_2$ha+B_1_8_2$ha) or arable land seeds (B_1_10$ha).
The physical threshold was used if there was no information about products produced for sale, i.e. only for targeting holdings that are producing mainly for sale.

 

3. The number of holdings in the national survey coverage 
The initial population was 17,026 and the final weighted population of the survey reference year, according to the national survey coverage, is 16,696 holdings.

 

4. The survey coverage of the records sent to Eurostat
There is no difference between the national and EU survey coverage. 

 

5. The number of holdings in the population covered by the records transferred to Eurostat
There is no difference between the national and EU survey coverage. The initial population was 17,026 and the final number of active holdings on the basis of survey results was 16,696. 

 

6. Holdings with standard output equal to zero included in the records sent to Eurostat
1,182 holdings, i.e. 7% of the total number of holdings have a standard output equal to zero. There were 253 of them in the sample, and these data are sent to Eurostat within the FSS 2016 dataset. These are holdings that have only permanent grassland which is not used for production purposes but only maintained in good agricultural and environmental condition or as fallow land, eligible for subsidies (i.e. the utilised agricultural area is at least 1 hectare). Some of them may also have kitchen gardens.

All holdings that have a utilised agricultural area above the threshold are eligible holdings, even if the entire utilised agricultural area is permanent grassland that is temporarily not used for production purposes but maintained in good agricultural and environmental condition (and is eligible for financial supports). Thus, they had to be included in the survey.

 

7. Proofs that the requirements stipulated in art. 3.2 the Regulation 1166/2008 are met in the data transmitted to Eurostat
A higher threshold than 1 hectare of utilised agricultural area is not used, thus art. 3.2 is not applicable. 

 

8. Proofs that the requirements stipulated in art. 3.3 the Regulation 1166/2008 are met in the data transmitted to Eurostat
The Farm Register is regularly updated on the basis of several sources, which guarantees that all agricultural holdings reaching one of the specified physical thresholds are covered.  
2.7. Reference area
Location of the holding. The criteria used to determine the NUTS3 region of the holding
The NUTS3 region of the holding is determined on the basis of the holding's main location received from the Farm Register, which is regularly updated on the basis of several registers and statistical sources.

The main location of the holding is the location of the holding’s centre (the location of the major part of the land, if there is no centre). The holding’s centre is the holder’s place of residence or the location of the holding’s buildings on the holding’s land. If the office or the holder’s residence lies more than 5 kilometres from the place of main activity, it cannot be considered as the reference place.

2.8. Coverage - Time
Reference periods/dates of all main groups of characteristics (both included in the EU Regulation 1166/2008 and surveyed only for national purposes)
The reference periods of all EU characteristics were in accordance with EC 1166/2008:
  • for land characteristics – 12 months ending on the reference day 01.09.2016;
  • for livestock characteristics – the reference day was 01.09.2016;
  • for labour force characteristics – 12 months ending on the reference day 01.09.2016;
  • for rural development measures – the reference period was 01.01.2014–31.12.2016.
2.9. Base period

[Not requested]


3. Statistical processing Top
1.Survey process and timetable

Calendar (overview of work progress)

Key activities of FSS 2016 Time/period
Preparatory works  
Preparing questionnaires, instructions and training materials; describing questionnaires with special software; creating and testing special software; composing survey list and pre-filled data; preparing data collection; hiring staff; promotion; etc. 1.07.2015–31.08.2016
Data collection and training interviewers  
Training courses for helpdesk and instructors 31.08, 12.09–13.09.2016
Data collection through the web 1.09–25.09.2016
Training courses for interviewers 21.09–23.09.2016
Data collection by interviewers 26.09–15.11.2016
Data collection from administrative registers 01.07.2016–31.01.2017
Data processing  
Data editing and output tables 01.09.2016–31.12.2017
Dissemination  
Preliminary results available on the website 14.03.2017
Final results available on the website 16.10.2017
Formatting, codification and validation of data and delivery to Eurostat 01.09.2016–31.12.2017

 

2. The bodies involved and the share of responsibilities among bodies
The body responsible for the FSS was Statistics Estonia and all related tasks were also performed by Statistics Estonia. 

 

3. Serious deviations from the established timetable (if any)
There were no serious deviations from the established calendar. 
3.1. Source data
1. Source of data
FSS 2016 was a sample survey which also included a 100% stratum. Part of the data were received from administrative sources. 

 

2. (Sampling) frame
The Statistical Register of Agricultural Holdings (Farm Register) was the frame.  It is a list frame.

The Statistical Farm Register is regularly updated on the basis of several administrative and statistical sources:

1) Register of Agricultural Support and Agricultural Parcels (together with annual land use data);
2) Register of Agricultural Animals;
3) Organic Farming Register;
4) Business Register for Statistical Purposes of Statistics Estonia (frame for business statistics; it is based on the Commercial Register, the Non-Profit Institutions and Foundations Register, the Register of Taxable Persons and the State Register of State and Local Government Agencies);
5) Population Register;
6) data received from official agricultural statistics surveys. 
On the basis of these sources, several data items are regularly updated in the statistical Farm Register. The registers are also used as sources for adding new holdings.

 

3. Sampling design
3.1 The sampling design
One-stage stratified random sampling of agricultural holdings (a probability sampling design) was used.
3.2 The stratification variables
Economic size, type of farming and organic farming (yes/no) were the stratification variables. 
3.3 The full coverage strata
The full coverage stratum included holdings with a large economic size and holdings with rare types of farming. The full coverage stratum is compiled first and these holdings are excluded from the part that is further stratified for the sampling. 
3.4 The method for the determination of the overall sample size
The sample size was 6,750. It was determined based on the available financial resources combined with the expected rate of active holdings and the data collection method.
3.5 The method for the allocation of the overall sample size
The sample sizes in the strata were determined by proportional allocation regarding the population size. 
3.6 Sampling across time
A new sample is drawn for each survey. 
3.7 The software tool used in the sample selection
The SAS software was used for the sample selection. 
3.8 Other relevant information, if any
Not available.

 

4. Use of administrative data sources
4.1 Name, time reference and updating
1) Register of Agricultural Support and Agricultural Parcels (together with annual land use data) (IACS and Rural Development measures)
The main legal act is the European Union Common Agricultural Policy Implementation Act. The data are continuously updated. The received land use data refer to 2016 and the data on rural development measures refer to the period 2014–2016. Data about land use were used for prefilling and holders could correct their data if needed.

2) Register of Agricultural Animals (the Bovine Register)
The main legal act is the Infectious Animal Disease Control Act. The data are continuously updated. The data on livestock used in the survey refer to the survey reference date. Data about livestock were used for prefilling and holders could correct their data if needed. 

3) Organic Farming Register 
The main legal act is EC No 834/2007 on the EU level and the Organic Farming Act on the national level. The data are continuously updated. The data used refer to 2016. As the data on animals refer to the day of inspection, they are adapted to the survey reference date. The number of animals was updated for the reference date on the basis of survey data. A comparison was made between the number of all animals specified in the questionnaire and the number of animals according to the data received from the Organic Farming Register (the latter divides animals into the following categories: kept as “normal”, under conversion or fully organic). Due to the requirements for organic production, the animals of a particular species and age group can only be organic or non-organic, but not both at the same time.

4) Database of Certified Seed Producers

The main legal act is the Plant Propagation and Plant Variety Rights Act. The data are continuously updated. The data used refer to 2016. The initial data on seed production refer to the day of application and the final data refer to the inspection date. Data about seeds were used for prefilling and holders could correct their data if needed.

5) Land Cadastre of Land Board

The main legal act is Land Cadastre Act. The data are continuosly updated. The data used refer to 2016. Data about wooded area and other land were used for prefilling and holders could correct their data if needed.

6) Statistical Register of Agricultural Holdings (Farm Register)

The main legal Act is Official Statistics Act. The data are continuosly updated. The data refer to the survey reference date.

4.2 Organisational setting on the use of administrative sources
At the request of Statistics Estonia, chief processors of databases are required to submit data collected in the administrative records. 

Statistics Estonia has agreed the land use classification scheme with the IACS register but has not participated in other conceptual design (characteristics, definitions, classifications, formats, etc.) and has not done subsequent related revisions of the administrative sources.

4.3 The purpose of the use of administrative sources - link to the file
Please access the information in the file at the link: (link available as soon as possible)

 

4.4 Quality assessment of the administrative sources
  Method  Shortcoming detected Measure taken
- coherence of the reporting unit (holding)   The main drawback is that the units in the register are different from the unit used in agricultural statistics, i.e. agricultural holding. In the case of all registers, there may be problems with creating links between the units. It is easy to create a link with the holder, but this is difficult when several persons from one holding have registered their lands or animals separately in administrative registers.     Multiple listing errors were treated as explained under the item 6.3.1-2.1.
- coherence of definitions of characteristics   There is no information on coherence problems of definitions of characteristics. Still, in the case of most administrative data, prefilling has been used and holders can correct their data if needed. 
- coverage:      
  over-coverage There is no information on errors in the register. The registrar checks the register data regularly; therefore, we expect the data to be correct. This applies to all the administrative registers used.     
  under-coverage   Almost 0. This applies to all the administrative registers used.

However, in the case of the Register of Agricultural Animals, there are problems with coverage, as all animals do not have to be registered in this register. 
So, in the case of these data, prefilling has been used and holders can correct their data if needed. 
  misclassification There is no information on errors in the register. The registrar checks the register data regularly; therefore, we expect the data to be correct. This applies to all the administrative registers used.     
  multiple listings There is no information on errors in the register. The registrar checks the register data regularly; therefore, we expect the data to be correct. This applies to all the administrative registers used.     
- missing data There is no information on errors in the register. The registrar checks the register data regularly; therefore, we expect the data to be correct. This applies to all the administrative registers used.     
- errors in data There is no information on errors in the register. The registrar checks the register data regularly; therefore, we expect the data to be correct. This applies to all the administrative registers used.     
- processing errors There is no information on errors in the register. The registrar checks the register data regularly; therefore, we expect the data to be correct. This applies to all the administrative registers used.     
- comparability There is no information on errors in the register. The registrar checks the register data regularly; therefore, we expect the data to be correct. This applies to all the administrative registers used.     
- other (if any)      

 

4.5 Management of metadata
The metadata for all administrative sources are described in the SA metadata system iMETA (dedicated database) and are updated systematically each year.
4.6 Reporting units and matching procedures
Register of Agricultural Support and Agricultural Parcels - natural and legal persons who have agricultural area or benefit from rural development measures.

Register of Agricultural Animals - natural and legal persons who own agricultural animals.

Organic Farming Register - natural and legal persons engaged in organic production.

Database of Certified Seed Producers - natural and legal persons who grow seeds and want the relevant fields to be certified.

Land Cadastre of Land Board - natural and legal persons whose lands are registered in the Land Cadastre. 

Statistical Register of Agricultural Holdings (Farm Register) - agricultural holdings.

Data are matched through ID code in IACS and Register of Agricultural Animals, ID code in Organic Farming Register, business register code and personal identification code.

4.7 Difficulties using additional administrative sources not currently used
There are no other relevant administrative sources available.
3.2. Frequency of data collection
Frequency of data collection
Every three or four years. 
3.3. Data collection
1. Data collection modes
A mixed data collection mode was used: Internet and telephone interviews supported by CATI technology.

 

2. Data entry modes
A mixed data entry mode was used: mainly online data entry by the holder and electronic data capture during telephone interviews.

 

3. Measures taken to increase response rates
Several measures were taken to increase response rates: written and telephone reminders; follow-up contacts with respondents who had only partly completed their questionnaires, with the data of larger holdings treated especially carefully; the mailing list is kept continuously up-to-date; the telephone interviewers have received special training, etc. 

 

4. Monitoring of response and non-response
1 Number of holdings in the survey frame plus possible (new) holdings added afterwards

In case of a census 1=3+4+5

17,026 
2 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

6,750
3 Number of ineligible holdings 330 
3.1 Number of ineligible holdings with ceased activities

This item is a subset of 3.

not available 
4 Number of holdings with unknown eligibility status

4>4.1+4.2

97 
4.1 Number of holdings with unknown eligibility status – re-weighted 97 
4.2 Number of holdings with unknown eligibility status – imputed
5 Number of eligible holdings

5=5.1+5.2

6,323
5.1 Number of eligible non-responding holdings

5.1>=5.1.1+5.1.2

5.1.1 Number of eligible non-responding holdings – re-weighted
5.1.2 Number of eligible non-responding holdings – imputed
5.2 Number of eligible responding holdings 6,323
6 Number of the records in the dataset 

6=5.2+5.1.2+4.2

6,323 

 

5. Questionnaire(s) - in annex
Questionnaire is provided in annex.


Annexes:
3.3-5 Questionnaire of FSS 2016
3.4. Data validation
Data validation
Several types of checks were used – data format checks, completeness checks, range checks, relational checks, etc. Inconsistencies compared to administrative data and/or other surveys were identified (see section 8.3 Coherence – cross domain).

The tools used for data validation were the electronic questionnaire which included arithmetical and logical controls (Internet and CATI versions) and a special data processing program.

Data validation was done on several levels – holders filling in online questionnaires, telephone interviewers, instructors and finally data processors.

3.5. Data compilation
Methodology for determination of weights (extrapolation factors)
1. Design weights
Design weights are the inverse of the units' selection probabilities. 
2. Adjustment of weights for non-response
The Horvitz-Thompson estimator was used in reweighting. 
3. Adjustment of weights to external data sources
Adjustment of weights to external data sources was not used. 
4. Any other applied adjustment of weights
Not applied.
3.6. Adjustment

[Not requested]


4. Quality management Top

To assure the quality of processes and products, Statistics Estonia applies the EFQM Excellence Model, EU Statistics Code of Practice and the ESS Quality Assurance Framework (QAF). Statistics Estonia is also guided by the requirements provided for in § 7. „Principles and quality criteria of producing official statistics” of the Official Statistics Act.

4.1. Quality assurance

[Not requested]

4.2. Quality management - assessment

[Not requested]


5. Relevance Top
5.1. Relevance - User Needs
Main groups of characteristics surveyed only for national purposes 
The national characteristics are not used in this survey. Still, land use data are collected in more detail than required by the FSS legislation in order to fulfill the requirements of crop statistics legislation. The sown areas of the following crops were surveyed: separately winter wheat and spring wheat (instead of 2.01.01.01), winter barley and spring barley (instead of 2.01.01.04), triticale, buckwheat and mixed grain (instead of 2.01.01.99), field peas and field beans (instead of 2.01.02.01), winter rape and turnip rape and spring rape and turnip rape (instead of 2.01.06.04), fresh vegetables outdoor or under low protective cover and strawberries outdoor or under low protective cover (instead of 2.01.07.01), cereals and pulses harvested green and other plants harvested green (instead of 2.01.09.02.99), black fallow and green fallow (instead of 2.01.12). These characteristics were added as they are required by EC 543/2009. The reason is that it is not possible to request the data twice – separately for the FSS and then in more detail for the Crop Production Survey.
5.2. Relevance - User Satisfaction

[Not requested]

5.3. Completeness
Non-existent (NE) and non-significant (NS) characteristics - link to the file. Characteristics possibly not collected for other reasons
Please access the information in the file at the link: (link available as soon as possible)
5.3.1. Data completeness - rate

[Not requested]


6. Accuracy and reliability Top
6.1. Accuracy - overall
Main sources of error
The methodology of the survey, thorough review of the data and comparison with administrative data, previous surveys and other sources guarantee sufficient precision of key indicators as well as compliance with the EC 1166/2008 requirements. 

However, measurement errors may occur in the case of some indicators that are not verifiable by administrative and other sources (see 6.3.2 Measurement error manure export).

6.2. Sampling error
Method used for estimation of relative standard errors (RSEs)
Information about the method used for the estimation of relative errors is presented in the annex. 


Annexes:
6.2. Method for estimation RSE
6.2.1. Sampling error - indicators

1. Relative standard errors (RSEs) - in annex

  

2. Reasons for possible cases where precision requirements are applicable and estimated RSEs are above the thresholds
RSEs are below thresholds. 


Annexes:
6.2.1-1 Relative standard errors
6.3. Non-sampling error

See below

6.3.1. Coverage error
1. Under-coverage errors
Frame under-coverage could be considered as non-existent as the frame has been updated on the basis of all available sources. 

  

2. Over-coverage errors
These units were included in the frame but did not belong to the target population. Mostly these units had finished their agricultural activity or their agricultural activity had decreased below the threshold. This was detected during data collection and therefore does not cause errors in the survey results.

To correct over-coverage and prevent over-estimation of the number of holdings and other characteristics, recomputing of the design weights for the sampled units (by considering a corrected population) is undertaken.

2.1 Multiple listings 
Multiple listings may occur when several persons from one holding exist in the frame (have registered themselves in administrative registers). They are discovered during the survey and the questionnaire is completed only once for the whole holding. They are treated as errors in the population and sample; thus, when the information is received, the design weights are changed accordingly. 

 

3. Misclassification errors
All units have been classified on the basis of the newest available information. 

 

4. Contact errors
Contact data have been updated on the basis of all available sources. 

 

5. Other relevant information, if any
Not available.
6.3.1.1. Over-coverage - rate
Over-coverage - rate
The frame over-coverage was 330 units (1.9% of the frame). 330 is the estimated over-coverage in the population, taking into account that the population was 17,026 units and the total number of holdings according to the final results was 16,696. Therefore, 17,026 – 16,696 = 330 units. 
6.3.1.2. Common units - proportion

[Not requested]

6.3.2. Measurement error
Characteristics that caused high measurement errors
The most difficult question was M_6_3$T Total produced manure exported from the holding. The reason is that holders do not have information about these quantities, and if they try to give an estimate, these estimations may not be accurate. The data were checked using the livestock coefficients of produced manure per livestock head (developed by the Estonian University of Life Sciences). It was assumed that it is not possible to export more manure than is produced. In total, data of 15% of holdings who have exported manure were corrected.

Information about other major measurement errors is not known. The questionnaires were carefully designed, they were in electronic format and included several arithmetical and logical checks. A part of the information was collected by trained interviewers.  

6.3.3. Non response error
1. Unit non-response: reasons, analysis and treatment
There were a few holdings (with unknown eligibility status) that did not complete the questionnaires. Reweighting was used to compensate for non-response.

Unit non-response was small and there were no strata with much larger non-response than the average. Therefore, the results of FSS 2016 can be regarded as good.

 

2. Item non-response: characteristics, reasons and treatment
In general, the design of the questionnaire did not enable item non-responses. Still, in the case of cattle, sheep and goats, the questionnaires were prefilled with data of 1 July and respondents were informed that there is no need to correct them if the data in the register is correct and they accept that we take the data of 1 September (reference date) directly from the register. 

43 holdings had in their questionnaires only prefilled administrative data and their all other data can be regarded as item non-responses. In case of item non-responses, the data of the Farm Structure Survey 2013 or Agricultural Census 2010 were used for imputation. If these data were missing, the hot-deck imputation (nearest neighbour) method was used for imputation.

6.3.3.1. Unit non-response - rate
Unit non-response - rate
During data collection, no information was received for 97 units (1.5%) with unknown eligibility status. Reweighting was used to compensate for that, as, according to the IACS register, these units were active.

There were no holdings within the totally surveyed stratum for which data were missing (including utilised agricultural area and livestock data from administrative sources). There were cases when the holding accepted the administrative data but did not give further information, but this is not unit non-response and has been treated as item non-response. Therefore, unit non-response within the eligible units is 0.

6.3.3.2. Item non-response - rate
Item non-response - rate
In general, the design of the questionnaire did not enable item non-responses. Still, in the case of cattle, sheep and goats, the questionnaires were prefilled with data of 1 July and respondents were informed that there was no need to correct them if the data in the register is correct and they accept that we take the data of 1 September (reference date) directly from the register. The rates of respondents who chose this possibility were the following: 93% of respondents with cattle, 94% of respondents with sheep and 90% of respondents with goats. 

43 holdings had in their questionnaires only prefilled administrative data and their all other data can be regarded as item non-responses. So, the highest item non-response rates were 0.7% (for the data of manager, for example). Some other examples: 0.3% for full time regular male and female employees, 0.6% for crop rotation and up to 0.5% for soil cover.

6.3.4. Processing error
1. Imputation methods
If possible, data from the Farm Structure Survey 2013 or Agricultural Census 2010 were used. If these data were missing, the hot-deck imputation (nearest neighbour) method was used for imputation.

Administrative data were also used, if available – these were mostly used to prefill the questionnaires, but there were cases when the relevant administrative data for some units were received later. 

 

2. Other sources of processing errors
The data were checked and edited with the help of special data editing software. In case of errors, imputation was used. Due to several arithmetical and logical checks, it is practically impossible for processing errors to exist in the data.

 

3. Tools used and people/organisations authorised to make corrections
During data processing, the new editing software was used. The people authorised to make corrections included permanent data collection and processing staff. Two persons were also hired temporarily, one of them has worked on the previous Farm Structure Surveys and therefore has great experience.
6.3.4.1. Imputation - rate
Imputation - rate
There were cases when the holding accepted the administrative data but did not give further information, but this is not unit non-response and has been treated as item non-response.

Therefore, the imputation rates are the same as the item non-response rates presented in item 6.3.3.2 Item non-response error.

6.3.5. Model assumption error

[Not requested]

6.4. Seasonal adjustment

[Not requested]

6.5. Data revision - policy
Data revision - policy
There are no planned revisions of published data. 
6.6. Data revision - practice
Data revision - practice
There are no planned revisions of published data.  
6.6.1. Data revision - average size

[Not requested]


7. Timeliness and punctuality Top
7.1. Timeliness

See below

7.1.1. Time lag - first result
Time lag - first result
Preliminary results were released on 14 March 2017, i.e 2.5 months from the last day of the reference year. 
7.1.2. Time lag - final result
Time lag - final result
Final results were released 9.5 months from the last day of the reference year. 
7.2. Punctuality

See below

7.2.1. Punctuality - delivery and publication
Punctuality - delivery and publication
The data have been published at the time announced in the release calendar. 


8. Coherence and comparability Top
8.1. Comparability - geographical
1. National vs. EU definition of the agricultural holding
There are no differences between the national and EU definition of the holding. 

 

2.National survey coverage vs. coverage of the records sent to Eurostat
There are no differences between national survey coverage and the records sent to Eurostat. Still, the initial survey list normally includes some over-coverage, which is removed during data processing. 

 

3. National vs. EU characteristics
The handbook vers 11 rev 1 was used. There were no differences between the national and EU concepts. One Annual Work Unit is considered to include 1,800 hours.

 

4. Common land
4.1 Current methodology for collecting information on the common land
There is no common land in Estonia. 
4.2 Possible problems encountered in relation to the collection of information on common land and possible solutions for future FSS surveys
Not applicable.
4.3 Total area of common land in the reference year
Not applicable. 
4.4 Number of agricultural holdings making use of the common land or Number of (especially created) common land holdings in the reference year
Not applicable.

 

5. Differences across regions within the country
 Survey is representative for NUTS 2, which is Estonia as a whole.

 

6. Organic farming. Possible differences between national standards and rules for certification of organic products and the ones set out in Council Regulation No.834/2007
There are no differences. 
8.1.1. Asymmetry for mirror flow statistics - coefficient

[Not requested]

8.2. Comparability - over time
1. Possible changes of the definition of the agricultural holding
There have been no changes. 

 

2. Possible changes in the coverage of holdings for which records are sent to Eurostat
There have been no changes. 

 

3. Changes of definitions and/or reference time and/or measurements of characteristics
There have been no changes.

 

4. Changes over time in the results as compared to previous FSS, which may be attributed to sampling variability
There have been no changes. 

 

5. Common land
5.1 Possible changes in the decision or in the methodology to collect common land
There have been no changes. 
5.2 Change of the total area of common land and of the number of agricultural holdings making use of the common land / number of common land holdings
Not applicable.

 

6. Major trends on the main characteristics compared with the previous FSS survey
Main characteristic Current FSS survey Previous FSS survey Difference in % Comments
Number of holdings 16,696  19,186  -13%  Decrease in the number of holdings is mainly related to restrictions for permanent grassland not used for production purposes. Therefore, many holdings which did not produce agricultural products but only maintained their land in good agricultural and environmental conditions, have finished their activity. Their percentage in the total number of holdings has decreased from 24% to 7%.
Utilised agricultural area (ha) 995,103  957,506  4%   
Arable land (ha) 686,556  628,312  9%   
Cereals (ha) 351,354  311,032  13%  Area of cereals has increased on account of rape and turnip rape.
Industrial plants (ha) 75,261  87,243  -14%  Decrease in the area of rape and turnip rape is related to the increase in the area of cereals.
Plants harvested green (ha) 178,635  166,811  7%   
Fallow land (ha) 16,692  40,964  -59%  Percentage of fallow in the arable land is quite small and therefore the percentage of the change is so large. From 2001, the area of fallow land has been 16,700–42,200 hectares.
Permanent grassland (ha) 304,283  324,556  -6%   
Permanent crops (ha) 3,471  3,464  0%   
Livestock units (LSU) 279,325  310,108 -10%  The number of livestock units has decreased due to the African swine fever (which has caused the decrease in the number of pigs) and crises (extremely low prices) in the milk sector (which has caused the decrease in the number of dairy cows).
Cattle (heads) 258,109  261,900  -1%   
Sheep (heads) 90,831  87,044  4%   
Goats (heads) 4,473  3,868  16%  The number of goats is quite small and therefore the percentage of change is so large. From 2001, the number of goats has been 3,700–5,100 heads.
Pigs (heads) 279,870  378,852  -26%  African swine fever
Poultry (heads) 1,903,300  2,166,435  -12%  As poultry breeding is very concentrated and most poultry is kept in very large holdings and as lots, the number of poultry is very much related to the reference date of the survey.
Family labour force (persons) 24,933  30,898 -19%  The number of holdings has decreased by 13% and many small holdings of natural persons have disappeared, so the family labour force has decreased accordingly. Additionally, there is a trend that more successful holdings of natural persons register their holdings as legal persons and therefore their labour force previously registered as family labor force is now registered as regular employees.
Family labour force (AWU) 8,311  10,236 -19%  The number of holdings has decreased by 13% and many small holdings of natural persons have disappeared, so the family labour force has decreased accordingly. Additionally there is a trend that more successful holdings of natural persons register their holdings as legal persons and therefore their labour force previously registered as family labor force is now registered as regular employees.
Non family labour force regularly employed (persons) 13,450  13,323 1%   
Non family labour force regularly employed (AWU) 11,146 11,315 -1%   
8.2.1. Length of comparable time series

[Not requested]

8.3. Coherence - cross domain
1. Coherence at micro level with other data collections
Comparisons of microdata were made with the Register of Agricultural Animals, the Register of Agricultural Support and Parcels (including land use data for 2016), the Organic Farming Register and the Database of Certified Seed Producers, the crop production survey and animal surveys.

The differences between microdata were clarified and also corrected, if needed. The differences occurred due to differences in definitions, units and methodology.  

 

2. Coherence at macro level with other data collections
Comparisons of aggregated data were made with the Register of Agricultural Animals, the Register of Agricultural Support and Parcels (including land use data for 2016) of the Agricultural Registers and Information Board (ARIB), the Organic Farming Register and the Database of Certified Seed Producers, the crop production survey and animal surveys. 
The differences with registers on the macrodata level were caused by differences in definitions and methodology (not all holdings are applying for subsidies; there is a threshold in the FSS; not all animals have to be registered in the Register of Agricultural Animals, or they have to be registered within a certain time period, etc.).
The data of different surveys are in line with each other. For example, ARIB’s land use data for all subsidy applicants showed 983,622 hectares (1.2% less than the total utilised agricultural area in FSS 2016). The number of cattle in the Register of Agricultural Animals was 0.2% smaller than the number of cattle in FSS 2016.
In the case of organic farming data, the total sum of organic farming area and area under conversion to organic farming in the Organic Farming Register was 0.2% smaller than in FSS 2016.
8.4. Coherence - sub annual and annual statistics

[Not requested]

8.5. Coherence - National Accounts

[Not requested]

8.6. Coherence - internal

[Not requested]


9. Accessibility and clarity Top
9.1. Dissemination format - News release

[Not requested]

9.2. Dissemination format - Publications
1. The nature of publications
The preliminary data of FSS 2016 were published in the form of main tables in the statistical database, news release and article in the quarterly bulletin of Statistics Estonia. The final results of all data together with metadata were published in the statistical database of Statistics Estonia. 

 

2. Date of issuing (actual or planned)
The preliminary data were published on 14 March 2017.

The final results were published on 16 October 2017. 

 

3. References for on-line publications
www.stat.ee/valjaanne-2017_eesti-statistika-kvartalikiri-1-17
9.3. Dissemination format - online database
Dissemination format - online database
The statistical database of Statistics Estonia is available at www.stat.ee
9.3.1. Data tables - consultations
Data tables - consultations
The online data tables of the Farm Structure Survey were used 10,574 times in 2016; 12,979 times in 2015; 14,768 times in 2014 and 13,430 times in 2013. 
9.4. Dissemination format - microdata access
Dissemination format - microdata access
The dissemination of data collected for the purpose of producing official statistics is guided by the requirements provided for in sections 34 and 35 of the Official Statistics Act.

Scientists can, under special contracts, use confidential microdata for research purposes at the safe centre on Statistics Estonia's premises or through remote access. They can make the analysis but only an employee of Statistics Estonia can send the research results to the user's e-mail address after the disclosure control has been performed. 

9.5. Dissemination format - other

[Not requested]

9.6. Documentation on methodology
1. Available documentation on methodology
The national methodological report is delivered to Eurostat. The publications include a short methodological overview. 

 

2. Main scientific references
Not available.
9.7. Quality management - documentation
Quality management - documentation
The national methodological report is delivered to Eurostat. 
9.7.1. Metadata completeness - rate

[Not requested]

9.7.2. Metadata - consultations

[Not requested]


10. Cost and Burden Top
Co-ordination with other surveys: burden on respondents
Detailed data about crops were collected in order to avoid duplicate data collection in the Crop Production Survey.

In order to reduce costs, all holdings could provide their data electronically. In order to reduce the burden, administrative data were used as much as possible. 


11. Confidentiality Top
11.1. Confidentiality - policy
Confidentiality - policy
Data that permit direct or indirect identification of a statistical unit, thereby disclosing individual information, are confidential data. 

The treatment of confidential data is regulated by the Procedure for Protection of Data Collected and Processed by Statistics Estonia: http://www.stat.ee/dokumendid/19410.

The producer of official statistics disseminates data collected for the production of official statistics for public use only in a form that precludes the possibility of direct or indirect identification of a statistical unit.

11.2. Confidentiality - data treatment
Confidentiality - data treatment
The data are published and transmitted without characteristics that permit identification of respondents, and are classified into groups of at least three holdings. Also, the data are not published if the share of data relating to a particular holding in the aggregate data is too high. 


12. Comment Top
1. Possible improvements in the future
There are no suggestions for improvements. 

 

2. Other annexes
There are no other annexes. 


Related metadata Top


Annexes Top