Farm structure (ef)

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

Compiling agency: Statistical Service of Cyprus (CYSTAT) 

Time Dimension: 2016-A0

Data Provider: CY1

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
Statistical Service of Cyprus (CYSTAT) 
1.2. Contact organisation unit
Agriculture
1.5. Contact mail address

Statistical Service of Cyprus

CY-1444

Nicosia

Cyprus 


2. Statistical presentation Top
2.1. Data description
1. Brief history of the national survey 
The Statistical Service of Cyprus (CYSTAT) has been conducting a Census of Agriculture over the last 50 years or so, at approximately 10-year intervals. 
The main objective of these censuses was to enumerate the whole population of agricultural holdings in the country and to collect data on various basic characteristics of each holding. This population then, formed the agricultural register and was used for drawing samples of various sample surveys which were carried out on an annual basis during the periods between census years. 
In 2003, a farm structure census was carried out in the country, which was based, for the first time, on the guidelines and relevant regulations of the EU regarding farm structure surveys. In 2005 and 2007 Cyprus carried out farm structure surveys by drawing a sample from the register formed based on Census 2003. In 2010, the FSS was conducted as a census and in 2013 as a sample survey based on the relevant Regulation (No 1166/2008). 

 

2. Legal framework of the national survey 
- the national legal framework The legal basis for the conduct of the FSS, as indeed for the conduct of all Statistical Surveys carried out by CYSTAT, is the National Statistics Law of 2000.
The FSS 2016 was carried out in Cyprus based on the Regulation No 1166/2008 of the European Parliament and of the Council. 
- the obligations of the respondents with respect to the survey The law is very explicit in terms of the obligation of agricultural holders in providing the requested information. (Statistics Law No 15(I) 2000). The Law specifies the following:

Article 11.(2) The officers or the other persons referred to in subsection (1) have the obligation to inform the person from whom the provision of data is required about the conduct of a survey or work by virtue of Law, the purpose of the survey or work, statistical confidentiality and the penalties imposed in case of refusal of provision of data or of provision of false data, incomplete or inaccurate data.

Article 11.(3) Any person who refuses to provide data or who provides false, incomplete or inaccurate data is guilty of an offence and in case of conviction is liable to a fine not exceeding one thousand pounds or to imprisonment not exceeding six months or to both such fine and imprisonment.

- the identification, protection and obligations of survey enumerators Enumerators were given an official letter, dated and signed by the director of CYSTAT, stating the purpose of the survey, which was used during their visits to agricultural holders in order to prove that the survey was officially carried out by CYSTAT. 
2.2. Classification system

[Not requested]

2.3. Coverage - sector

[Not requested]

2.4. Statistical concepts and definitions
List of abbreviations
No abbreviations used
2.5. Statistical unit
The national definition of the agricultural holding
For the purpose of the FSS 2016 and for the previous farm structure survey (2013), exactly the same definition as in Regulation 1166/2008 was used:
“A holder is the natural person, group of natural persons or legal person on whose account and in whose name the holding is operated and who is legally and economically responsible for the holding, i.e. who takes the economic risks of the holding. The holder can own the holding outright or rent it or be a hereditary long-term leaseholder or a unsufructuary or a trustee. Data are collected for holders which are natural persons. If the holder is a legal person, data are collected for the manager of the holding. In group holdings where two or more natural persons carry out functions of the holder, only one of them is shown as such.” 

"Agricultural holding or holding means a single unit, both technically and economically, which has a single management and which undertakes agricultural activities listed in Annex I of the Regulation 1166/2008 within economic territory of the European Union, either as its primary or secondary activity"

The activities undertaken by an agricultural holding are:

  • Growing of non-perennial crops
  • Growing of perennial crops (Agricultural holdings which produce wine or olive oil from self-produced grapes or olives are also included)
  • Plant propagation
  • Animal production (All activities classified under 01.49 of NACE Rev. 2 (Raising of other animals) are excluded, except the raising and breeding of ostriches, emus and rabbits and bee-keeping and production of honey and beeswax)
  • Mixed farming
  • Holdings exclusively maintaining agricultural land in good agricultural and environmental condition are also included 
2.6. Statistical population
1. The number of holdings forming the entire universe of agricultural holdings in the country
The target population consisted of all agricultural holdings in the updated farm register, which was resulted from the Census of Agriculture 2010. The total number of these holdings of was 36410.

 

2. The national survey coverage: the thresholds applied in the national survey and the geographical coverage
Agricultural holdings and areas refer to Government controlled areas of the Republic of Cyprus.

Agricultural holdings were considered and surveyed only:

- if they have utilised agricultural area equal or greater than one decare (1 decare = 0,1 ha) (A_3_1$ha) or

- if they have at least half decare (0.05 ha) in greenhouse (sum(B_1_7_2$ha, B_1_8_2$ha, B_4_7$ha)), or  

- if they own animals, and specifically:

     -  one and more cows (sum(C_2_6$heads, C_2_99$heads)) or

     - a total of two and more other large animals of any kind and age (such as horses, camels) (sum(C_2_1$heads, C_2_2$heads,  C_2_3$heads, C_2_4$heads,  C_2_5$heads, C_1$heads)) or

     - a total of five and more small animals of any age and gender (such as goats, sheep, pigs) (sum(C_3_1$heads, C_3_2$heads, C_4$heads)) or

     - fifty and more poultry (C_5$heads), or

     - twenty and more beehives (C_7$hive), or

     - five and more ostriches (C_5_3_4$heads), or

     - ten and more rabbit breeding females (C_6$heads). 

 

3. The number of holdings in the national survey coverage 
The initial list of population units in FSS was 36410 holdings and the sample taken was 17950 holdings, from which 15901 holdings were covered. The sample covered in 2016 was increased by 0.6% compared to the 15800 holdings covered in 2013 and the final weighted population was 34945 holdings.

 

4. The survey coverage of the records sent to Eurostat
No difference of survey coverage between holdings covered in the national survey and holdings for which records were sent to Eurostat. 

 

5. The number of holdings in the population covered by the records transferred to Eurostat
The same as in item 3. above. 

 

6. Holdings with standard output equal to zero included in the records sent to Eurostat
Data for 54 holdings were sent to Eurostat. These 54 sampled holdings (190 extrapolated holdings) have fallow land and/or permanent grassland no longer in production purposes and eligible for payment of subsidies, and the fact that they are kept in good agricultural and environmental conditions, makes the holdings eligible to be covered by the survey.

 

7. Proofs that the requirements stipulated in art. 3.2 the Regulation 1166/2008 are met in the data transmitted to Eurostat
The national survey does not have to comply with art 3.2. as it uses a threshold of utilised agricultural area below 1 hectare.

 

8. Proofs that the requirements stipulated in art. 3.3 the Regulation 1166/2008 are met in the data transmitted to Eurostat
For the purpose of Farm Structure Surveys, Cyprus uses the thresholds mentioned in item 2.6-2 above, and it ensures that all requirements are met as far as the coverage is concerned and all characteristics specified in Annex II of Regulation 1166/2008 are surveyed. 
2.7. Reference area
Location of the holding. The criteria used to determine the NUTS3 region of the holding
Cyprus is NUTS1 region and all data refer to Government controlled areas of the Republic of Cyprus.
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 period of the survey was September 1, 2015 until August 31, 2016; for the livestock characteristics was October 1, 2016. 

The reference period for the benefit of the holding for rural development measures was years 2014, 2015 and 2016. 

2.9. Base period

[Not requested]


3. Statistical processing Top
1.Survey process and timetable
Calendar (overview of work progress)

(I) November – December 2015

(a) Preparation of basic and supplementary questionnaires 
(b) Preparation for the conduct of a pilot survey in order to test the questionnaire and other parameters of the survey.
(c) Recruitment, training and carrying out of the pilot survey among 200 agricultural holdings.
(d) The pilot survey was analyzed and discussed by the staff of the Agricultural Section of CYSTAT.

(II) January – March 2016

(a) Corrections and preparation of basic and supplementary questionnaires of FSS.
(b) Preparation of the instructions, handbook and all relevant documents to be used in the survey.
(c) Preparation of the data entry software program by editing all validation rules.

(III) March – July 2016

(a) Updating and editing of the farm register formed from the Agricultural Census 2010.
(b) Sample selection on the basis of the typology prepared by EUROSTAT.
(c) Preparation of the data entry process continues by repeated tests of a software program designed by members of the project team.
(d) Printing and distributing all questionnaires, documents and other stationery materials to district offices. 
(e) District Officers were briefed on all administrative matters relating to the conduct of the survey. They were shown and explained all the documents that should be used.

(IV) August - September 2016

(a) Recruitment of area supervisors and enumerators. One week´s training of the district officers, the area supervisors and the enumerators. Three days were devoted entirely to the questionnaire, to coverage aspects of the survey and to administrative procedures that should be followed during the survey and two days for completing a real questionnaire and discussing it with the area supervisors. The training was provided by the project team in two groups of employees, the first group comprising enumerators of the districts of Nicosia and Larnaca and the second group comprising enumerators of Lemesos and Paphos. The first group was trained by the team at the central offices of CYSTAT in Nicosia and the second in Lemesos.
(b) The preparation of the data entry process continues by repeated tests of a software program designed by members of the project team. At this stage all the necessary hardware equipment was also set up in a special room at the central offices of CYSTAT. 

(V) September 2016 – December 2016

(a) Data collection.
(b) Data checking. This was done through a multi-stage process.
(c) Coverage checking
(d) Data entry
All of the above stages of work were carried out concurrently.

(VI) January 2017 – February 2017

(a) Data collection and data entry process continues.

(VII) February - March 2017

(a) Final checks of the FSS data entry process.
(b) Merging of all data and preparing for the data analysis for FSS.

(VIII) March - April 2017

(a) Corrections and data analysis for EUROFARM purposes
(b) Commencement of data analysis for other purposes. Commencement of editing and updating of the farm register.

(IX) May 2017

(a) EUROFARM data sent to Eurostat

 

2. The bodies involved and the share of responsibilities among bodies
The organization of the FSS 2016 was undertaken entirely by the section of Agricultural Statistics of CYSTAT. A six-member team was formed in March 2016 comprising six permanent members of the staff of the Agricultural Section. Each member was given clear instructions relating to their duties and responsibilities together with a planned time-table which set out the target dates for completing the various tasks. Despite the fact that each member of the team was assigned specific tasks, the team met frequently in order to brief each other on work progress and to exchange views on problems arising during the work. This proved very useful in achieving homogeneity in respect of the way concepts were understood, in assuring that progress of the work was well-balanced and in continuity of the work as it had become possible for the work of each member to continue even in cases of absence, as supervision of this work could easily be undertaken by the other members of the team.

Specifically, the six members of the team were assigned the following general tasks:

(I) The first member who was also the person responsible for the survey, was assigned the task of preparing the basic and the supplementary questionnaire ensuring an exhaustive coverage of the list of characteristics, the task of drawing up the sample and was responsible for the general organization and coverage aspects of the survey and the data entry process.

(II) The first member together with the help of 1 permanent employee of the Data processing unit of CYSTAT, were assigned the task of preparing the data entry program and supervising the data entry process.

(III) Four members of the team were responsible for the collection of the data, each person for a different district of Cyprus. In this context they recruited and supervised all the necessary casual personnel.

The training of the enumerators and area supervisors was undertaken by all six members of the team but the main responsibility was shouldered by the member responsible for the questionnaires and data entry. It is noted that training took place in a multi-stage process. At the first stage, district officers were trained by the first member of the team. At the second stage, the district officers and area supervisors attended the training course of the team. Finally, at a third stage, area supervisors had the responsibility of training the enumerators in the presence and under the guidance of district officers and the team members. 


This ensured a more efficient implementation of the checking process (explained in detail in section 3.4 Data validation) since people were hierarchically in a better position to check, correct and direct the work of personnel under their responsibility.

In total 80 people worked in the FSS 2016. The status and responsibilities of these employees are shown below:

  • project leader : 1 employee, the person responsible for Agricultural Statistics
  • project team : 6 employees, permanent staff members of the Agricultural Statistics Section
  • district officers : 4 permanent employees, members of the project team
  • area supervisors : 10 casual employees
  • data collection : 60 casual employees
  • district checking units : 3 casual employees
  • central checking unit : 2 permanent employees and 2 casual employees
  • data entry : 6 casual employees
  • data analysis for Eurofarm purposes : 3 permanent employees (1 project leader and also member of the project team, 1 permanent employee of the Data processing unit of CYSTAT, 1 permanent employee of CYSTAT with previous experience on Eurofarm)
  • data analysis for other purposes : 1 project leader and also member of the project team

It is noted that the total number of employees above sums up to over 80 people due to the fact that the project team members and casual employees appear in more than one of the various categories of work responsibilities.

 

3. Serious deviations from the established timetable (if any)
Not existing.
3.1. Source data
1. Source of data
The Farm Structure Survey 2016 was conducted as a sample survey.

The coverage was based on the updated agricultural register (see further information in item 3.1-2. below). From this register, a catalogue of the holders, which included their name, address, telephone number and various characteristics of their holding, was formed and used for the purposes of the survey. 

 

2. (Sampling) frame
The register of agricultural holders was created based on the census 2010 and was updated based on surveys that occured between 2010 and 2016. 

A list frame is used, based on the holding`s identification number.

 

3. Sampling design
3.1 The sampling design
The FSS 2016 sample was selected with the method of one-stage stratified systematic random sampling.
3.2 The stratification variables
The stratification variables were the Standard Output and the farm type of the holding. All holdings were divided into 4 groups according to their Standard Output as follows:

1st group: SO is equal to 0

2nd group: SO is greater than 0 and smaller than 5000

3rd group: SO is greater than or equal to 5 000 and smaller than 15000

4th group: SO is greater than or equal to 15000

 

Then the holdings were divided according to their typology (two level farm type) and the resulting strata are presented in the table below:

 

Farmtype GROUPS TOTAL
SO=0 0<SO<5000 5000≤SO<15000 15000≤SO
15 0 481 186 220 887
16 0 547 261 736 1,544
21 0 8 31 163 202
22 0 174 154 423 751
23 0 1 12 154 167
35 0 1,334 560 471 2,365
36 0 3,134 2,414 3,075 8,623
37 0 5,991 938 433 7,362
38 0 3,567 1,679 1,612 6,858
45 0 1 0 175 176
46 0 6 4 5 15
47 0 0 0 3 3
48 0 232 369 1,092 1,693
51 0 6 6 42 54
52 0 107 28 48 183
53 0 227 155 140 522
61 0 864 576 1,046 2,486
73 0 39 43 64 146
74 0 17 9 25 51
83 0 6 8 35 49
84 0 953 475 552 1,980
90 293 0 0 0 293
Total 293 17,695 7,908 10,514 36,410
3.3 The full coverage strata
Full coverage for holdings with 15000≤SO. 
3.4 The method for the determination of the overall sample size
According to the budget available to the Agricultural Sector of the Statistical Service of Cyprus, it was decided that the total sample size should be about 18000 holdings from the total of 36410 farms.
3.5 The method for the allocation of the overall sample size
Based on the percentage of the total SO of the holdings in each of the 4 groups to the total SO of the population, it was decided to cover the 28.6% of standard output from the second group, 71.4% from the third group and all the holdings from the fourth group. From the first group it was decided to cover the 1/3 of the holdings. Then the sample was drawn from each strata formed from the farmtype of the holding, taking into account the percentage total SO of the strata on the total SO of each group. At the end of the process, a sample was drawn comprising 17950 holdings. 
3.6 Sampling across time
No new sample was necessary. 
3.7 The software tool used in the sample selection
The sample selection was implemented in Excel spreadsheets. 
3.8 Other relevant information, if any
Not available

 

4. Use of administrative data sources
4.1 Name, time reference and updating
No use of administrative data sources was made in the FSS 2016. 
4.2 Organisational setting on the use of administrative sources
Not applicable 
4.3 The purpose of the use of administrative sources - link to the file
Not applicable 

 

4.4 Quality assessment of the administrative sources
  Method  Shortcoming detected Measure taken
- coherence of the reporting unit (holding) Not available Not available  Not available 
- coherence of definitions of characteristics Not available Not available  Not available 
- coverage: Not available  Not available Not available
  over-coverage Not available Not available Not available
  under-coverage Not available Not available Not available
  misclassification Not available Not available Not available
  multiple listings Not available Not available Not available
- missing data Not available Not available Not available
- errors in data Not available Not available Not available
- processing errors Not available Not available Not available
- comparability Not available Not available Not available
- other (if any) Not available Not available Not available

 

4.5 Management of metadata
Not applicable 
4.6 Reporting units and matching procedures
Not applicable 
4.7 Difficulties using additional administrative sources not currently used
 Not applicable 
3.2. Frequency of data collection
Frequency of data collection
FSS surveys are carried out in Cyprus every 3 years and every 10 years as a census. 
3.3. Data collection
1. Data collection modes
Data collection was carried out through paper questionnaires, which were filled out by interviewers during personal visits to the respondents. 

 

2. Data entry modes
Data entry was carried out in the central office of CYSTAT, where computers were loaded with the specific software program. The data entry software was designed by the responsible personnel of the Agricultural Statistics Section and the Data Processing Unit of the Statistical Service of Cyprus. 

 

3. Measures taken to increase response rates
After the data collection had started, supervisors were instructed to contact the chairman of each local community council a few days prior to visiting any specific community and to explain the purpose of the survey and ask for their assistance in order to ensure smooth cooperation of the community’s residents during data collection. This action also ensured that respondents were reminded for the carrying out of the FSS 2016 and this proved useful, especially in those cases where visits to a community were carried out well after the announcements in the press and the commencement of data collection.

 

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

36493 
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

17588 
3 Number of ineligible holdings 1193 
3.1 Number of ineligible holdings with ceased activities

This item is a subset of 3.

917 
4 Number of holdings with unknown eligibility status

4>4.1+4.2

150
4.1 Number of holdings with unknown eligibility status – re-weighted 0
4.2 Number of holdings with unknown eligibility status – imputed 0
5 Number of eligible holdings

5=5.1+5.2

16245 
5.1 Number of eligible non-responding holdings

5.1>=5.1.1+5.1.2

344 
5.1.1 Number of eligible non-responding holdings – re-weighted 0
5.1.2 Number of eligible non-responding holdings – imputed 0
5.2 Number of eligible responding holdings 15901 
6 Number of the records in the dataset 

6=5.2+5.1.2+4.2

15901 

 

5. Questionnaire(s) - in annex
See annex.


Annexes:
3.3-5. QUESTIONNAIRE_FSS_2016
3.4. Data validation
Data validation
Edit rules/checks

Accurate and good quality data were set from the start as a primary objective of the survey. This goal could only be achieved if the collected data could efficiently and effectively be checked. For this purpose, a multilevel checking system of questionnaires was set up immediately after data collection commenced.

1. During the first week of data collection, area supervisors were instructed to collect and check all the questionnaires completed by every interviewer on a daily basis. This action was considered particularly important in the sense that any errors made would be identified at the earliest stage and brought to the attention of the interviewers so that the degree of repetition of such errors would be minimised considerably during the rest of data collection period.

The checks made by area supervisors were of twofold nature:

- First, they were obligated to check the information contained in each questionnaire for errors or inaccuracies. These checks included completeness, validations in relation to information available in the register and between related variables, acceptable ranges, summations, ratios and rational checks. 

- Second, they were instructed to make coverage checks. They were asked to come in contact with all of the respondents for whom a questionnaire was completed (either through telephone or personal visit) and to ensure that the questionnaire was filled out according to instructions, that is, during the personal visit of the interviewer to the respondent and that all questions were asked. This checking method was implemented from the very first week of data collection and this proved useful because enumerators knew that all their work was thoroughly checked and that there was no room for shallow approaches.

From the second week onwards, area supervisors were obligated to collect the completed questionnaires from every interviewer and were instructed to carry out numerical completeness and validation checks to all questionnaires, whereas they were instructed to carry out analytical, weekly coverage checks on a sample of at least 10% of the collected questionnaires. They should also ensure that this sample contained at least one questionnaire for each interviewer so that the work of everyone was checked on a weekly basis. Taking into account that every area supervisor was responsible for about 7 interviewers, each of whom completed 20 questionnaires per week, this checking process implied that area supervisors had to check analytically at least 20 questionnaires per week. In cases where mistakes were found repeatedly on the questionnaires of any specific enumerator, the checking unit was asked to raise the percentage of questionnaires checked with respect to the work of that enumerator. Similarly, the percentage of questionnaires checked was raised in the case that mistakes were frequently found in the questionnaires of any particular area supervisor.

2. District officers were requested to set up checking units comprising one or two casual employees working under their guidance and supervision. These units had the obligation to come in contact with those people who reported not having an agricultural holding in order to ensure that the interviewer had actually visited these people and the declaration of not having an agricultural holding is correct. It is noted that interviewers were instructed to report those cases where they visited people who reported that they were not holders of any agricultural holding, providing the name and address of these people.

3. The central office of CYSTAT gave clear instructions to permanent employees to check at least 5% of the questionnaires submitted by each area supervisor. They were also instructed to ensure that the sample of questionnaires chosen for checking purposes should include at least some cases of those questionnaires that were analytically checked at an earlier stage. This process ensured that not only the work of interviewers was being checked but also the work of area supervisors. This level of checking was also done on a weekly basis in order to identify errors and weaknesses as early as possible and to take immediate action for correction purposes and for avoiding repetition and accumulation of mistakes.

4. Finally, checks were carried out during data entry by the software program itself. The program carried out several checks such as consistency checks, valid value and range checks, arithmetic checks etc.


Checks on the accuracy of the data and on coverage were concurrently done.

 

Tools used for data validation

The software program used during data entry (see point 4 above)

 

Level of data validation

The first step of this checking process was in the hands of area supervisors (see point 1 above).

The second step of the checking process was carried out by district officers (see point 2 above).

A third level of checking was carried out at the central office of CYSTAT (see point 3 above).

3.5. Data compilation
Methodology for determination of weights (extrapolation factors)
1. Design weights
For FSS 2016, the weight of each holding is estimated by:

Whi = Nhi / nhi

where:

  • Nhi is the total number of holdings in stratum i and
  • nhi is the number of holdings in the sample selected from stratum i

The weight of each holding is proportional to the sample size of the stratum in which the holding belongs.

2. Adjustment of weights for non-response
As non-response was small, no adjustments were deemed necessary in order to account for such cases. 
3. Adjustment of weights to external data sources
Not applied
4. Any other applied adjustment of weights
Not applied
3.6. Adjustment

[Not requested]


4. Quality management Top
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 
In FSS 2016, the questionnaire included all the characteristics set out by the Regulation No. 1166/2008.

Some characteristics were added to the questionnaire which are not mentioned in EC 1166/2008 but are necessary for national purposes. These were the following:

1) first name and surname, personal identification code and contact details of the holders;
2) detailed data on agricultural crops were recorded with respect to the different municipalities where the actual area was located;
3) areas were recorded on lentils, chick peas, cowpeas, haricot beans, louvana, beetroot, dasheen (kolocasi), groundnuts, sesame, different kinds or fruit trees, nuts and citrus fruits, carob trees;
4) number of livestock on horses and donkeys.

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 following link: (link to be 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
In FSS 2016 there were coverage and measurement errors but all were considered minimal since considerable emphasis was given to coverage aspects of the survey and to the quality of the collected data. This was achieved through the implementation of a multi-stage checking process both for purposes of coverage and for purposes of minimizing errors on the questionnaires. The timing of the checking process, the corrections and data entry were also carefully planned in order to minimize the time lag between the visit to the respondent and the re-visits for corrections where such re-visits were deemed necessary.
6.2. Sampling error
Method used for estimation of relative standard errors (RSEs)
In FSS 2016, the standard error for each variable is estimated by:

 Se = √ΣHi=1 Nhi (Whi - 1) S2i

where:

  • Nhi is the total number of holdings in stratum i
  • Whi is the weight of each holding in stratum i and
  • S2i is the variance within stratum i
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
Due to Cyprus size and specifically the agricultural field, the changes that might have occurred in the 3-year period (2013-2016) might lead to high variation within some strata from which the sample was drawn from the updated register 2010. 


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

See below

6.3.1. Coverage error
1. Under-coverage errors
The large volume of information that was provided from the farm register assisted in minimizing the number of cases lost. From the initial sample taken from the register, 83 cases were not possible to be covered because they were new units that were not included in the frame, because of real birth or demergers. This leads to a statistically insignificant under-coverage rate of 0,5%. 

  

2. Over-coverage errors
Coverage was limited to visits to holders who appeared in the sample satisfying the relevant threshold. This implies that there could be no over-coverage. However, 917 cases no longer belonged to the target population leading to an over-coverage rate of 5,2%. These 917 units were holdings with ceased activities because of three main reasons. First reason is that they changed the use of the holding in the sense that the land was no longer agricultural but became land plots for building, second the size of the holding was under the threshold required from the survey, and last the agricultural activities were abandoned. These cases accounted for 0,8% of the total UAA, which was considered insignificant. However, the cases were subtracted from the frame and the weights were recalculated.
2.1 Multiple listings 
The farm register played a major role in avoiding duplicate recordings of holdings. This was achieved by checking key variables on the questionnaires against the information on the register. However, duplicate recordings emerged in those cases where the holding belonged to two or more persons who lived in different areas and resulted to 47 cases (0,3%). These cases were subtracted from the frame and the weights were recalculated. 

 

3. Misclassification errors
No cases observed. 

 

4. Contact errors
Contact errors occured in 150 cases where the holders where unable to be located. These cases led to 0,9% error and these holdings were not surveyed. 

 

5. Other relevant information, if any
Coverage errors are taken into account for purposes of up-dating the farm register in those cases that the cause of the errors is fully clarified. 
Coverage and other non-sampling errors were minimized during the multi-stage checking process that took place concurrently with data collection and data entry. These errors accounted for 0,3% of the total UAA and therefore the number of holdings and their characteristics were not affected significantly. Anyhow, all errors were taken into consideration and the weights were recalculated.
6.3.1.1. Over-coverage - rate
Over-coverage - rate
The over-coverage rate is calculated by dividing the number of ineligible units in the sample to the gross sample (1193/17588) = 6,78% 
6.3.1.2. Common units - proportion

[Not requested]

6.3.2. Measurement error
Characteristics that caused high measurement errors
When cases of measurement errors were found, they were corrected at the very moment they were found, therefore by the end of the survey the measurement errors in the data were minimised.

Errors were checked by checking the data against the prior information available in the existing register and in many cases by contacting the holder again through the telephone. The need for such corrections was minimal. Follow-up interviews were carried out during the data collection process in those cases where the checking process suggested that these should be done. These checks were based on relevant information about each holding which was already available from previous surveys of the Statistical Services. After the completion of data collection, however, neither follow-up interviews took place nor imputations were made.

The analytical checking process in conjunction with the intensive call-back strategy minimised almost entirely missing and inaccurate data as well as the number of lost cases. This led to the elimination of any measurement errors and therefore no correction of statistics was necessary.

6.3.3. Non response error
1. Unit non-response: reasons, analysis and treatment
Non-response in the sense of cases of agricultural holdings for which no a priori information was available and which refused to provide information is estimated to be minimal. Specifically:

Holder was too busy to give information = 54 cases

Holder refused to give any information = 184 cases

Holder was unable to give information because of illness = 66 cases

Holder was abroad during the survey period = 40 cases

The area covered by the above holdings represents 2% of the total UAA and the rate of non-response is also 2%, which is considered insignificant and the impact is minimal. Therefore there was no need to recalculate the weights due to the above non-response.

 

2. Item non-response: characteristics, reasons and treatment
Non-response in the sense of only partly completed questionnaires was non-existent. 
6.3.3.1. Unit non-response - rate
Unit non-response - rate
The non-response rate for the FSS 2016 is estimated to be 2%. 
6.3.3.2. Item non-response - rate
Item non-response - rate
Not applicable 
6.3.4. Processing error
1. Imputation methods
No imputations were applied.

 

2. Other sources of processing errors
Data collection and data entry were organised in such way so as to take place almost simultaneously.
Processing errors were not an issue because of two main reasons: first, checks were made by area supervisors on the paper questionnaires before starting the data entry process and second, the data entry program was built in such a way so to identify any possible errors (consistency, value, range, arithmetic, etc.) that the questionnaires might have. The errors which were made during the data entry process (typing errors) were easily corrected through the re-typing of the correct data.

By the end of the survey and the finalisation of the data, all errors were eliminated. 

 

3. Tools used and people/organisations authorised to make corrections
Processing errors were corrected by two members of the project team.
The central checking unit remained active until the end of the data completion process.
Its role was to check and correct any errors that arose during data entry and to obtain answers relating to the missing items.  
6.3.4.1. Imputation - rate
Imputation - rate
No imputations were applied. 
6.3.5. Model assumption error

[Not requested]

6.4. Seasonal adjustment

[Not requested]

6.5. Data revision - policy
Data revision - policy
A data revision policy is in place at CYSTAT. It is published on CYSTAT’s website, at the following link: http://www.mof.gov.cy/mof/cystat/statistics.nsf/dissemination_en/dissemination_en?OpenDocument

CYSTAT also publishes a list of scheduled revisions (regular or major revisions), also published on its website, at the following link: http://www.mof.gov.cy/mof/cystat/statistics.nsf/releasecalendar_en/releasecalendar_en?OpenDocument

In the case of FSS 2016, no revisions are made.
6.6. Data revision - practice
Data revision - practice
No revisions were made.  
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
Not applicable 
7.1.2. Time lag - final result
Time lag - final result
The final results have been sent to Eurostat in May 2017 and they will be published in summary tables, ensuring confidentiality, in the official website of CYSTAT by the end of February 2018, 14 months after the end of the survey reference year (December 2016 - February 2018).  
7.2. Punctuality

See below

7.2.1. Punctuality - delivery and publication
Punctuality - delivery and publication
Eurofarm was delivered 6 months before the transmission deadline and summary tables will be uploaded on the website by the end of February 2018


8. Coherence and comparability Top
8.1. Comparability - geographical
1. National vs. EU definition of the agricultural holding
No difference between the national definition and the EU definition of the holding. 

 

2.National survey coverage vs. coverage of the records sent to Eurostat
The population covered is fully aligned with the records sent to Eurostat. 

 

3. National vs. EU characteristics
The FSS 2016 questionnaire was drawn up based on the characteristics as these are set by the Commission Regulation (EC) No. 1166/2008. The Handbook on implementing FSS definitions for FSS 2016 was also used in order to define the characteristics included in the questionnaire.

The Annual Working Unit is calculated using 8 hours per day, 260 days a year as a full-time equivalent number.

 

4. Common land
4.1 Current methodology for collecting information on the common land
Common land was collected as a separate category under the types of tenure as it is defined in the handbook and was added to the normal land of the holding (total UAA).
4.2 Possible problems encountered in relation to the collection of information on common land and possible solutions for future FSS surveys
Not identified.
4.3 Total area of common land in the reference year
The total area recorded in FSS 2016 as common land was 23 hectares. 
4.4 Number of agricultural holdings making use of the common land or Number of (especially created) common land holdings in the reference year
It was estimated that 11 agricultural holdings are making use of the common land. 

 

5. Differences across regions within the country
During the reference period, no extreme weather conditions occurred. 

 

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 between national standards and rules for certification of organic products and the ones set out in Council Regulation No 834/2007.  
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
The definition of a holder and of an agriculture holding remained the same as in 2013. 

 

2. Possible changes in the coverage of holdings for which records are sent to Eurostat
No, there have been no changes for FSS 2016.

 

3. Changes of definitions and/or reference time and/or measurements of characteristics
The questionnaire remained basically the same as of previous FSS surveys, with the addition of some characteristics that had to be collected in the FSS 2016 and the deletion of unnecessary ones based on previous FSS results. 

The reference period (mentioned in concept 2.8 Time coverage) remained the same as in FSS 2013. 

 

4. Changes over time in the results as compared to previous FSS, which may be attributed to sampling variability
No significant changes. 

 

5. Common land
5.1 Possible changes in the decision or in the methodology to collect common land
Common land in previous FSS was collected under the category of other types of tenure as agricultural land with different exploitation status and was added to the normal land of the holding. However, in FSS 2016 common land is recorded as a separate characteristic as defined in the handbook of definitions. First, in chapter 3 of the questionnaire (LEGAL PERSONALITY AND MANAGEMENT OF THE HOLDING) the holder is asked whether the holding is a common land unit and second, the common land is recorded in chapter 6 (TYPE OF TENURE OF UTILIZED AGRICULTURAL AREA OF THE HOLDING) in which common rights with other holding apply. 
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
The total number of holdings making use of common land decreased from 226 holdings in 2013 to 11 holdings in 2016 and the corresponding common land decreased from 292 ha to 23 ha. The decrease is attributed to the different methodology used which was better defined in the handbook of definitions and therefore better explained and clarified to the enumerators and hence to the holders giving the information. Also note that holders seem to prefer using their own land for cultivating crops or for animal grazing even though that land could be rented from someone else.   

 

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 34945 35385  -1   
Utilised agricultural area (ha) 111930  109332  2  
Arable land (ha) 84248  80118   
Cereals (ha) 25193  31263  -19  This decrease is slightly offset by an increase in plants harvested green. Year 2016 was not a very good year for cereals in general and production levels were low. 
Industrial plants (ha) 128  61  110  Very small areas, not significant. However it seems that the increase is attributed to the increase in the cultivation of Aromatic, medicinal and culinary plants which rose from 40 hectares in 2013 to 86 hectares in 2016 (115%).
Plants harvested green (ha) 40611  29856  36  This increase is slightly offset by a decrease in cereals harvested for grain. Also, unfavorable weather conditions resulted in the delayed vegetation on permanent grassland in 2016, and therefore, the growth of fodder crops on arable land. 
Fallow land (ha) 11289  10253  10  The small increase of fallow land is due to the fact that a lot of farmers during 2016 preferred to leave their land to recover and was maintained in good agricultural and environmental conditions in order to be eligible for subsidies.
Permanent grassland (ha) 1376  1848  -26  This decrease is mainly a results of the unfavorable weather conditions, which resulted in the delayed vegetation on permanent grassland in 2016.
Permanent crops (ha) 26259  27319  -4   
Livestock units (LSU) 172084  174518  -1   
Cattle (heads) 53710  53274   
Sheep (heads) 264803  257169   
Goats (heads) 169980  171406  -1   
Pigs (heads) 265042  290928  -9   
Poultry (heads) 2603567  1851659  41  The number of poultry can differ considerably between the years. The increase is mainly due to the fact that people tend to prefer white meat in their daily diet and therefore, farmers are producing more poultry because of the high demand. Moreover, in 2013 non-response may had an effect about this difference.
Family labour force (persons) 68369  73087  -7   
Family labour force (AWU) 11196  11513  -3   
Non family labour force regularly employed (persons) 4536  4298   
Non family labour force regularly employed (AWU) 3950  3726   
8.2.1. Length of comparable time series

[Not requested]

8.3. Coherence - cross domain
1. Coherence at micro level with other data collections
The results of the survey were compared against those of FSS 2013 and the census of 2010 as well as against those of several annual surveys. Where the comparisons showed significant deviations in the results, the differences were investigated and either corrected or explained or, in the majority of cases, both.

 

2. Coherence at macro level with other data collections
Results were evaluated after the analysis of the FSS 2016 data was finalized and were compared against those of FSS 2013 and annual surveys. Basic results of the comparisons are shown in item 8.2-6 above.
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
No publication is planned to be produced, however summary tables are planned to be published in the official website of CYSTAT. 

 

2. Date of issuing (actual or planned)
The summary tables are planned to be uploaded on the website by the end of 2017. 

 

3. References for on-line publications
Not applicable. 
9.3. Dissemination format - online database
Dissemination format - online database
Summary tables are planned to be uploaded on the website by the end of 2017. 
9.3.1. Data tables - consultations
Data tables - consultations
Not applicable 
9.4. Dissemination format - microdata access
Dissemination format - microdata access
Statistical micro-data from CYSTAT’s surveys are accessible for research purposes only and under strict provisions as described below:

Under the provisions of the Statistics Law, CYSTAT may release microdata for the sole use of scientific research. Applicants have to submit the request form "APPLICATION FOR DATA FOR RESEARCH PURPOSES" giving thorough information on the project for which micro-data are needed.

The application is evaluated by CYSTAT’s Confidentiality Committee and if the application is approved, a charge is fixed according to the volume and time consumed for preparation of the data. Micro-data may then be released after an anonymisation process which ensures no direct identification of the statistical units but, at the same time, ensures usability of the data. The link for the application is attached below.



Annexes:
9.4. Link to the application for access to microdata on CYSTAT's website
9.5. Dissemination format - other

[Not requested]

9.6. Documentation on methodology
1. Available documentation on methodology
Methodology is planned to be published in the website of CYSTAT along with the summary tables.  

 

2. Main scientific references
Not applicable. 
9.7. Quality management - documentation
Quality management - documentation
Not available. 
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
During the data collection of FSS 2016 no other annual surveys were conducted.


11. Confidentiality Top
11.1. Confidentiality - policy
Confidentiality - policy
Official statistics are released in accordance to all confidentiality provisions of the following:
  • National Statistics Law No. 15(I) of 2000 (especially Article 13 on statistical confidentiality).
  • Regulation (EC) No 223/2009 of the European Parliament and of the Council of 11 March 2009 on European statistics and its later amendments (especially Chapter 5 on statistical confidentiality).
  • European Statistics Code of Practice (especially Principle 5 on statistical confidentiality).
  • CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data.


Annexes:
11.1. Statistics Law No. 15(I) of 2000
11.1. Regulation (EC) No 223/2009 on European statistics (consolidated text)
11.1. European Statistics Code of Practice
11.1. Code of Practice for the Collection, Publication and Storage of Statistical Data
11.2. Confidentiality - data treatment
Confidentiality - data treatment
The treatment of confidential data is regulated by CYSTAT's Code of Practice for the Collection, Publication and Storage of Statistical Data.

Eurofarm data are send through Edamis encrypted and the summary tables will show total values for all Cyprus and will not include row data in order to ensure confidentiality.



Annexes:
11.2. Code of Practice for the Collection, Publication and Storage of Statistical Data


12. Comment Top
1. Possible improvements in the future
Not available 

 

2. Other annexes
Not available 


Related metadata Top


Annexes Top