Crop production (apro_cp)

National Reference Metadata in ESS Standard for CROPS Reports Structure (ESQRSCP)

Compiling agency: National Institute of Statistics of Albania -INSTAT


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: Eurostat user support

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1. Contact Top
1.1. Contact organisation

National Institute of Statistics of Albania -INSTAT

1.2. Contact organisation unit

Land and Crops Statistics Sector

1.5. Contact mail address

St. Vllazën Huta, Building 35, Entrance 1, Tirana, ZIP Code 1017 Tirane


2. Statistical presentation Top
2.1. Data description

 

Annual Crop Statistics cover cereals, industrial plants, other crops on arable land, vegetables, fruits, citrus, olive, and vineyards. These statistics provide detailed information on the sown area, production area, harvested area, production of crops under arable land, as well as production of permanent crops and vegetables.

 

 

2.2. Classification system

The classification used in the Agriculture Statistics refers to the classifications and definitions according to the relevant EU regulations.

- EU (EC) No 543/2009 on Crops Statistics. (https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32009R0543&from=EN)

- NACE Rev.2 - Statistical classification of economic activities (https://ec.europa.eu/eurostat/en/web/products-manuals-and-guidelines/-/KS-RA-07-015)

2.3. Coverage - sector

Agriculture Statistics cover cereals, industrial crops, other field crops, vegetables, fruits, citrus fruits, olives, and vineyards.

2.4. Statistical concepts and definitions

Agricultural Economic Unit (AEU): The Agricultural Economic Unit is a single, technical-economic unit, designated in a unique direction, from the field and though in non-continuous parcels, in which agricultural and livestock production is conducted by a single person or group of persons, for the realization of agricultural - livestock activities.

Land use: The total area of the agricultural unit (farm) is the total area of the land consisting of the sum of the agricultural area used (UAA) and other lands.

The agricultural area used (UAA) consists of arable land, permanent crops, kitchen gardens used by the holding, and permanent grassland.

Arable land: Arable land (plowed or tilled) regularly, generally under a system of crop rotation. Crop rotation is the practice of alternating annual crops grown on a specific field in a planned pattern or sequence in successive crop years. Normally the crops are changed annually, but they can also be multi-annual. To distinguish arable land from permanent crops or permanent grassland, a threshold of five years is used. The area cultivated with field plants is the area planted with these kinds of plants in a given agricultural year. Here we speak of an area with main crops (primary). The main crops (primary) normally have a greater economical value than the other cultures and occupy the land in the most part of the year. The main crops are wheat, spring cultures like the grain maize, potatoes, the legume, industrial plants, the alfalfa, etc.

Permanent crops: Permanent crop area is an area of land with fruit trees, olives, citrus, and vineyards. Here are included the only areas with permanent crops in blocks.

Kitchen gardens: Areas devoted to the cultivation of agricultural products intended for self-consumption by the holder and his household, normally separated off from the rest of the arable land, and recognizable as kitchen gardens.

Permanent grassland: Land used permanently (for five years or more) to grow herbaceous forage crops, through cultivation (sown) or naturally (self-seeded), and that is not included in the crop rotation on the holding. The land can be used for grazing or mown for silage, hay, or used for renewable energy production.

Other land consists of forest-occupied land, unused agricultural land, and nonagricultural land.

The unutilized agricultural area: The unutilized agricultural area is the land area sufficiently able for agricultural production but for some reason, it hasn’t been used in the given agricultural year.

The forest area: The forest is a land area larger than 1 dynm, with pile-shaped forest trees covering over 30% of it and with the potential to reach over 3 m height, which represents a complex and multifunctional ecosystem with impacts on the surrounding environment.

Non-agriculture area: Other land is land occupied by buildings, farmyards, tracks, ponds, quarries, infertile land, rock, etc.

Harvest year: means the calendar year in which the harvest begins.

Area under cultivation: Area under cultivation means the area that corresponds to the total sown area, but after the harvest, it excludes ruined areas (e.g. due to natural disasters). The area under cultivation included main and secondary area of crops.

Production area of permanent crops: Production area’, in connection with permanent crops, means the area that can potentially be harvested in the reference harvest year. It excludes all non-producing areas, such as new plantations that have not yet started to produce, extensive production or abandoned.

2.5. Statistical unit

The observed statistical unit is the Agricultural Economic Unit (AEU).

2.6. Statistical population

Statistical populations are all Agricultural Economic Unit in Albania. Crop yield data is collected from the most representative farms at the municipal level.

2.7. Reference area

Agricultural Statistics cover the entire territory of the Republic of Albania.

2.8. Coverage - Time

Agriculture statistics date back to 1998.

2.9. Base period

Not applicable.


3. Statistical processing Top
3.1. Source data

  Source 1 Source 2 Source 3 Source 4
Have new data sources been introduced since the previous Quality Report?  NO      
If yes, which new data sources have been introduced since the previous quality report?
Type of source?
To which Table (Reg 543/2009) do they contribute?
Have some data sources been dropped since the previous Quality Report? NO      
Which data sources have been dropped since the previous quality report?
Type of source?
Why have they been dropped?
Additional comments


Data sources: Please indicate the data sources which were used for the reference year on which is reported

  Type Name(s) of the sources If other type, which kind of data source?
Table 1: crops from arable land      
Early estimates for areas
Final area under cultivation Administrative data
Expert estimate

Statistical Unit in the Ministry of Agriculture and Rural Development that colect data in regional level from extension services

Production Administrative data
Expert estimate

Statistical Unit in the Ministry of Agriculture and Rural Development that colect data in regional level from extension services

Yield Expert estimate

Ekspert in the MARD and Agriculture University

Non-existing and non-significant crops Expert estimate

INSTAT AND expert in the MARD

Table 2: Vegetables, melons and strawberries       
Early estimates for harvested areas Administrative data

 - Ministry of Agriculture and Rural Development 

 

Final harvested area Administrative data
Expert estimate

Statistical Unit in the Ministry of Agriculture and Rural Development that colect data in regional level from extension services

Production Administrative data
Expert estimate

Statistical Unit in the Ministry of Agriculture and Rural Development that colect data in regional level from extension services

Non-existing and non-significant crops Expert estimate

Expert of INSTAT and Ministry of Agriculture and Rural Development (MARD)

Table 3: Permanent crops      
Early estimates for production area

 

Final production area Administrative data
Expert estimate

Statistical Unit in the Ministry of Agriculture and Rural Development that colect data in regional level from extension services

Production Administrative data
Expert estimate

Statistical Unit in the Ministry of Agriculture and Rural Development that colect data in regional level from extension services expert

Non-existing and non-significant crops Expert estimate

Expert of INSTAT and Ministry of Agriculture and Rural Development (MARD)

Table 4: Agricultural land use      
Main area Administrative data
Expert estimate

Ministry of Agriculture and Rural development, and Minstry of Turism and Environment

Non-existing and non-significant crops Expert estimate
Total number of different data sources    
Additional comments    


Which method is used for calculating the yield for main arable crops? production divided by harvested area
If another method, describe it.
3.2. Frequency of data collection

  Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Source 7 Source 8 Source 9
Name of data source

Administrative data from the Ministry of Agriculture and Rural Development

Planning (month-month/year)
Preparation (month-month/year)
Data collection (month-month/year)

December 2019

Quality control (month-month/year)

February - April 2020

Data analysis (month-month/year)

April - June 2020

Dissemination (month-month/year)

June 2020

If there were delays, what were the reasons?
3.3. Data collection

Definitions Question In case yes, how do they differ?
Do national definitions differ from the definitions in Article 2 of Regulation (EC) No 543/2009? NO
Are there differences between the national methodology and the methodology described in the Handbook concerning e.g. the item and aggregate calculations? NO
Are special estimation/calculation methods used for main crops from arable land? NO
Are special estimation/calculation methods used for vegetables or strawberries? NO
Are special estimation/calculation methods used for permanent crops for human consumption? NO
Are special estimation/calculation methods used for main land use? NO
Do national crop item definitions differ from the definitions in the Handbook  (D-flagged data)? NO  
In case yes, how do they differ? ( list all items and explanations)
In case data are delivered for one of the items below, describe the crop species included in the item:


Population

Which measures were taken in order to make sure that the requirement stipulated in Art. 3.2 are met?
(Statistics shall be representative of at least 95 % of the areas of each table in the Regulation).
Is the data collection based on holdings?
If yes, how the holdings were identified?
If not, on which unit the data collection is based on?
When was last update of the holding register? (month/year)
Was a threshold applied?
If yes, size of the excluded area  Area excluded on the basis of the threshold in % of the total area for that crop
Cereals for the production of grain (in %)
Dried pulses and protein crops (in %)
Root crops (in %)
Oilseeds (in %)
Other industrial crops (included all industrial crops besides oilseeds)  (in %)
Plants harvested green from arable land (in %)
Total vegetables, melons and strawberries (in %)
Cultivated mushrooms (in %)
Total permanent crops (in %)
Fruit trees (in %)
Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)
Olive trees (in %)


Survey method (only for census and surveys)

  Survey 1  Survey 2 Survey 3  Survey 4 Survey 5  Survey 6 Survey 7
Name of the survey
Which survey method was used?
If 'other', please specify
Please provide a link to the questionnaire
Data entry method, if paper questionnaires?


Administrative data (This question block is only for administrative data)

  Admin source 1 Admin source 2 Admin source 3 Admin source 4 Admin source 5 Admin source 6
Name of the register
Description
Data owner (organisation)
Update frequency
Reference date (month/year)
Legal basis
Reporting unit
Identification variable (e.g. address, unique code, etc.)
Percentage of mismatches (%)
How were the mismatches handled?
Degree of coverage (holdings, e.g. 80%)
Degree of completeness (variables, e.g. 60%)
If not complete, which other sources were used ?
Were the data used for sample frame?
Data used for other purposes, which?
Which variables were taken from administrative sources?
Were there any differences in the definition of the variables between the administrative source and those described in the Regulation?
Please describe the differences
What measures were taken to eliminate the differences?
How was the reliability, accuracy and coherence (comparison to other available data) of the data originated from administrative data source (ante- and/or ex-post) checked?
What were the possible limitations, drawbacks of using the data from administrative source(s)?


Expert estimations (This question block is only for expert estimates)

  Expert estimate 1 Expert estimate 2 Expert estimate 3 Expert estimate 4 Expert estimate 5 Expert estimate 6
Name of the estimation
Data owner (organisation)
Update frequency (e.g. 1 year or 6 months)
Reference date (Month/Year  e.g. 1/16 - 8/16)
Legal basis
Use purpose of the estimates?
What kind of expertise the experts have?
What kind of estimation methods were used?
Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation?
If yes, please describe the differences
What measures were taken to eliminate the differences?
How were the reliability, accuracy and coherence (comparison to other available data) of the data originated from experts' estimates (ante- and/or ex-post)checked?
What were the possible limitations, drawbacks of using the data from expert estimate(s)?
Additional comments
3.4. Data validation

Which kind of data validation measures are in place? Automatic and Manual
What do they target? Completeness
Aggregate calculations
Is the data cross-validated against an other dataset? YES
If yes, which kind of dataset? Previous results
If other, please describe

The data were subjected to logical and mathematical checks. These checks are performed for all indicators that INSTAT publishes, throughout the data processing. Examples of administrative data verification methods include: Completeness check, consistency over time, arithmetic corrections (should not be too high), summary checks, time series check if there are large deviations, etc.

3.5. Data compilation

Not applicable.

Agriculture data is provided by the administrative source, at national level, and by municipality. Statistical information is available on time.

3.6. Adjustment

Not applicable.


4. Quality management Top
4.1. Quality assurance

  Completeness Punctuality Accuracy Reliability Overall quality
How would you describe the overall quality development since the previous quality report? Improvement Improvement Improvement Improvement Improvement
Is there a quality management process in place for crop statistics? YES        
If, yes, what are the components?

INSTAT is committed to providing information to the official statistics officer. Practicing in the Law "On Official Statistics", No.17 / 2018, Dated 17.04.2018, INSTAT Use statistical methods and processes in accordance with internationally accepted scientific principles and standards, and perform accessible analyzes with the power of Using and providing up-to-date statistics In fulfilling the task of filling in, INSTAT on the principles of service administration officers, for me with the European Statistics Code of Practice (European Statistics Code of Practice). the following principles: impartiality, process quality and statistical service, user orientation, employee orientation, statistical process effectiveness, and reduced service interference.The other casting process is programmed to minimize process errors. service meetings During the process of its collection, measures are taken to reduce non-response. All collected Write longer, administrative resources or surveys, and more families that INSTAT conducts by guaranteeing a quality final product.

       
Is there a Quality Report available? YES        
If yes, please provide a link(s)

http://instat.gov.al/media/7252/agriculture-statistics-esms_final.pdf

       
To which data source(s) is it linked?

Administrative

       
Has a peer-review been carried out for crop statistics? YES        
If, yes, which were the main conclusions?

Crop statistics data time series (at least for the years 2013-2017) need to be finalised and assessed based on supply balance sheets and/or EAA data, and/or with related data from input-output tables. The published data need to be accompanied with a description of the method of recalculations (metadata).

 

It is recommended to introduce early estimates on crop areas and production by the implementation of the June survey (already piloted in 2018 using tablets for data collection).

 

INSTAT has to carefully follow the progress in preparation of the vineyard register and assess the possibility of its use for a future vineyard survey (in the EU foreseen in 2026). Special attention has to be paid to the matching method, since data are required to deliver to the EUROFARM database together with the core FSS data.

       
What quality improvement measures are planned for the next 3 years? Increase of resources        
If, other, please specify        
Additional comments        


Annexes:
Sector Review of Agriculture Statistics of the Republic of Albania
4.2. Quality management - assessment

Data on agriculture yields are collected from the most representative farms at the municipal level. The data collected is sent to the Ministry of Agriculture and Rural Development, where vegetable production specialists make estimates comparing field data collected with farm data over the years.


5. Relevance Top
5.1. Relevance - User Needs

Are there known unmet user needs? YES
Describe the unmet needs

Users of Agriculture Statistics are divided into internal and external users.

External users:

• Public Administration Institutions

• Universities

• Non-profit national and international organizations

• Businesses

• Researchers, students, and other similar groups.

 

Internal users:

• National Accounts Directorate

• Directorate of Economic Statistic

• Directorate of Social Statistics

• Directory of Real Sector Who use Agriculture Statistics as input to their work.

Does the Regulation 543/2009 meet the national data needs? YES
Does the ESS agreement meet the national needs? YES
If not, which additional data are collected?
Additional comments
5.2. Relevance - User Satisfaction

Have any user satisfaction surveys been done? YES
If yes, how satisfied the users were? Satisfied
Additional comments

Page Views (Hits) on “Agriculture Statistics” in 2019 are around 15.160 clicks. 8 During 2019, INSTAT conducted User Satisfaction Survey from INSTAT publications. The survey results show that the overall quality of Agriculture Statistics is rated 3.47 (69.4%) on a scale of 1 (very poor) to 5 (very good).

5.3. Completeness

The completeness of Agricultural Statistics for 2019 is judged by comparing the quality and quantity of the indicators covered by INSTAT with those required by the regulations followed. The level of completeness of the indicators at the aggregated level is in full compliance with the regulation: "REGULATION (EC) No. 543/2009 on crop statistics" and as such all indicators required by EUROSTAT are reported. The detailed level of these indicators produced by INSTAT is realized through expert evaluation methods in the field. The completeness level of the indicators produced by INSTAT considering also the detailed level required under the regulations is approximately 80%.


6. Accuracy and reliability Top
6.1. Accuracy - overall

Information on Agriculture Statistics is collected from administrative sources, subject to enforcement of the legal basis and applicable Memorandums of Understanding. Overall, data have been checked with those of previous years to identify any significant changes in data performance. In case of changes, INSTAT notifies the MARD to inform about the findings in order to correct this data if necessary or to be officially confirmed.

6.2. Sampling error

Sampling method and sampling error

  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name
Sampling basis?
If 'other', please specify
Sampling method?
If stratified, number of strata?
If stratified, stratification basis?
If 'other', please specify
Size of total population
Size of sample
Which methods were used to assess the sampling error? 
If other, which?
Which methods were used to derive the extrapolation factor? 
If other, which?
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas
If the results were compared with other sources, please describe the results
Which were the main sources of errors?


Sampling error - indicators

utilised agriculture area, area under protected area (greenhouses), area of plantation of citrus, wheat area, plant harvest green area, industrial crops, root cropsa and dry pulses and protein crops


Coefficient of variation (CV) for the area (on the MS level)

  Survey 1  Survey 2 Survey 3  Survey 4 Survey 5  Survey 6 Survey 7
Name of the survey
Cereals for the production of grain (in %)
Dried pulses and protein crops (in %)
Root crops (in %)
Oilseeds (in %)
Other industrial crops (included all industrial crops besides oilseeds)  (in %)
Plants harvested green from arable land (in %)
Total vegetables, melons and strawberries (in %)
Cultivated mushrooms (in %)
Total permanent crops (in %)
Fruit trees (in %)
Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)
Olive trees (in %)
Additional comments            
6.3. Non-sampling error
6.3.1. Coverage error

Over-coverage - rate


Common units - proportion

not aplicate


  Data source 1 Data source 2 Data source 3 Data source 4 Data source 5 Data source 6 Data source 7 Data source 8 Data source 9
Name of the data source
Error type
Degree of bias caused by coverage errors
What were the reasons for coverage errors?
Which actions were taken for reducing the error or to correct the statistics?
Additional comments
6.3.2. Measurement error

  Data source 1 Data source 2 Data source 3 Data source 4 Data source 5 Data source 6 Data source 7 Data source 8 Data source 9
Name of the data source
Was the questionnaire based on usual concepts for respondents?
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?
Preparatory (field) testing of the questionnaire?
Number of units participating in the tests? 
Explanatory notes/handbook for surveyors/respondents? 
On-line FAQ or Hot-line support for surveyors/respondents?
Were pre-filled questionnaires used?
Percentage of pre-filled questions out of total number of questions
Were some actions taken for reducing the measurement error or to correct the statistics?
If yes, describe the actions and their impact
6.3.3. Non response error

Unit non-response - rate


Item non-response - rate


  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name
Unit level non-response rate (in %)
Item level non-response rate (in %)              
               - Min% / item
               - Max% / item
               - Overall%
Was the non-response been treated ?
Which actions were taken to reduce the impact of non-response?
Which items had a high item-level non-response rate? 
Which methods were used for handling missing data?
(several answers allowed)
In case of imputation which was the basis?
In case of imputation, which was the imputation rate (%)?
Estimated degree of bias caused by non-response?
Which tools were used for correcting the data?
Which organisation did the corrections?
Additional comments
6.3.4. Processing error

Not applicable.

6.3.4.1. Imputation - rate

Not applicable.

6.3.5. Model assumption error

Not applicable

6.4. Seasonal adjustment

Not applicable.

6.5. Data revision - policy

Revision policies of the Agriculture Statistics are made in accordance with the revision policy as well as the error handling policy set by INSTAT.

 

For more refer to:

- Revision policy

- The errors treatment policy



Annexes:
STATISTICAL REVISION POLICY
THE ERRORS TREATMENT POLICY
6.6. Data revision - practice

If the authorities that send information on Agriculture Statistics to INSTAT will report changes in the information provided through tables, this data will be updated and published in the forthcoming publication accompanied by an explanatory note to the user.


7. Timeliness and punctuality Top
7.1. Timeliness

Time lag - first result


Time lag - final result

Results of Agriculture Statistics are published on INSTAT website (T + 171 days) and (T + 263 days) after the reference period. The following are considered two different reference periods for the relevant areas on which these results are based.

 

Timeliness

Agricultural production 12/31/2019 6/19/2020 (171 days)

Planted Area 9/30/2019 6/19/2020 (263 days)


  Cereals Dried pulses and protein crops Root crops Oilseeds Other industrial crops Plants harvested green Vegetables and melons Strawberries Cultivated mushrooms Fruit trees Berries Nut trees Citrus fruit trees Vineyards Olive trees
How many main data releases there are yearly in the national crop statistics for the following types of crops?

1

1

1

1

1

1

1

1

0

1

1

1

1

1

1

How many of them are forecasts (releases before the harvest)?

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

When was the first  forecasting published for the crop year on which is reported? (day/month/year)
When were the final results published for the crop year on which is reported? (day/month/year) 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020 19/06/2020
Additional comments
7.2. Punctuality

The data of Agriculture Statistics are disseminated according to the publication calendar. The publication of Agriculture Statistics has been punctual in time to 100% of publications carried out over the time. 

 
 
7.2.1. Punctuality - delivery and publication
Statistical domain                                Reference period                  Date of announcement       Date of publication            Time lag  

Agricultural production                         12/31/2019                         6/19/2020                         6/19/2020                        0

Planted Area                                        9/30/2019                           6/19/2020                        6/19/2020                        0


8. Coherence and comparability Top
8.1. Comparability - geographical

Data on Agriculture Statistics are all inclusive; they are produced at national level and by municipality level. Statistics are compared by geographical distribution and regionalization of agricultural products.

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable.

8.2. Comparability - over time

Length of comparable time series

Statistical information on Agriculture Statistics is collected in the same way dating back to 2012, providing comparability of 8 years. Data are constantly monitored to ensure their comparability over time.


  Crops from arable land
(Table 1)
Vegetables, melons and strawberries (Table 2) Permanent crops
(Table 3)
Agricultural land use
(Table 4)
Have there been major breaks in the time series in the previous 5 years? NO NO NO NO
If yes, to which were they related?
If other, which?
Which items were affected?
Year of break (number)
Impact on comparability
Additional comments
8.3. Coherence - cross domain

With which other data sources the crop statistics data have been compared?  None
If others, which?
If no comparisons have been made, why not?


Differences between ACS and other data sources (%)

Results of comparisons FSS 2016 Orchard survey 2017 IACS Other source(s)  In case of other sources, which?
Cereals    
Dried pulses and protein crops    
Root crops    
Oilseeds    
Other industrial crops (than oilseeds)    
Plants harvested green    
Total vegetables, melons and strawberries    
Vegetables and melons    
Strawberries    
Cultivated mushrooms  
Total permanent crops  
Fruit trees
Berries  
Nut trees  
Citrus fruit trees
Vineyards
Olive trees
If there were considerable differences, which factors explain them?  
8.4. Coherence - sub annual and annual statistics

Not applicable.

8.5. Coherence - National Accounts

Not applicable.

8.6. Coherence - internal

The internal consistency of the data is checked before being finalized. The relationships between variables and coherence across different series are also checked.


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

9.2. Dissemination format - Publications

  Availability Links
Publications Electronic
Paper

All publications are in bilingual Albanian and English

Publications in English Electronic
Paper

http://www.instat.gov.al/media/7171/statistical-yearbook-2019___.pdf

http://www.instat.gov.al/media/7170/rsy-2.pdf

http://www.instat.gov.al/media/7176/albania-in-figures.pdf

9.3. Dissemination format - online database

Data tables - consultations


  Availability Links
On-line database accessible to users YES

http://databaza.instat.gov.al/pxweb/en/DST/?rxid=cb86cb64-f7ee-441a-9067-e04c03c2f93e

Website National language
English

http://www.instat.gov.al/

 

http://www.instat.gov.al/en/

9.4. Dissemination format - microdata access

Availability Links
NO

Data on Agriculture Statistics are administrative data and as such the most detailed level of data obtained is at municipality level. Therefore, INSTAT does not have available data on Agriculture Statistics at micro level.

9.5. Dissemination format - other

Users can submit other specific Agriculture Statistics requests through a dedicated Data Requests session.

9.6. Documentation on methodology

  Availability Links
Methodological report National language
English

http://www.instat.gov.al/en/themes/agriculture-and-fishery/agriculture/#tab4

Quality Report National language
English

http://www.instat.gov.al/media/7251/statistikat-e-bujq%C3%ABsis%C3%AB_esms_final.pdf - QR in Albanian

 

http://instat.gov.al/media/7252/agriculture-statistics-esms_final.pdf - QR in English

Metadata National language

For internal use.

Additional comments  
9.7. Quality management - documentation

Not applicable.

9.7.1. Metadata completeness - rate

Not applicable.

9.7.2. Metadata - consultations

INSTAT is committed to providing information to the official statistics officer. Practicing in the Law "On Official Statistics", No.17 / 2018, Dated 17.04.2018, INSTAT Use statistical methods and processes in accordance with internationally accepted scientific principles and standards, and perform accessible analyzes with the power of Using and providing up-to-date statistics In fulfilling the task of filling in, INSTAT on the principles of service administration officers, for me with the European Statistics Code of Practice (European Statistics Code of Practice). the following principles: impartiality, process quality and statistical service, user orientation, employee orientation, statistical process effectiveness, and reduced service interference. The other casting process is programmed to minimize process errors. service meetings During the process of its collection, measures are taken to reduce non-response. All collected Write longer, administrative resources or surveys, and more families that INSTAT conducts by guaranteeing a quality final product.

 Data on agriculture yields are collected from the most representative farms at the municipal level. The data collected is sent to the Ministry of Agriculture and Rural Development, where vegetable production specialists make estimates comparing field data collected with farm data over the years.


10. Cost and Burden Top

Efficiency gains if compared to the previous quality report? Increased use of administrative data
Staff further training
If other, which?
Burden reduction measures since the previous reference year 
If other, which?


11. Confidentiality Top
Restricted from publication
11.1. Confidentiality - policy
Restricted from publication
11.2. Confidentiality - data treatment
Restricted from publication


12. Comment Top


Related metadata Top


Annexes Top