DDI_ETH_2001_AgSE-LU_v02_M
Central Statistical Agency
Accelerated Data Program
2006-08-14
NADA
Version 02 (October 2013). Edited version based on Version 1.1 (December 2010) DDI (DDI_ETH_2001_ASELU_v1.1_M) that was done by Central Statistical Agency, Ethiopia and reviewed by Accelerated Data Program, International Household Survey Network.
Agricultural Sample Enumeration, Land Use 2001-2002 (1994 E.C)
AgSE-LU 2001-02
ETH_2001_AgSE-LU_v01_M
Central Statistical Authority
NADA
Government of Ethiopia
Data Administrator
World Bank Microdata Library
Agricultural Census [ag/census]
Version 1.1: Edited and non anonymized dataset, for internal use only.
Agriculture
Land
Agriculture & Rural Development
Land (policy, resource management)
From agricultural point of view, land is an indispensable factor for production of crops, raising of livestock and other ancillary agricultural activities. The proper utilization of land holdings under different components will contribute to the development of the nation's agricultural products. In order to scrutinize this development as well as farmers' attitude towards land use practices, a timely and comprehensive land use data has paramount importance for governmental, non-governmental and private sector data users. According to the international recommendations for Agricultural Census, the total land use is categorized into five main land use types, which are land under temporary crops, land under permanent crops, grazing land, fallow land, woodland and land for other purposes. Based on these major land use categories, the 2001/02 (1994 E.C.) Ethiopian Agricultural Sample Enumeration (EASE) provides quantitative information on land utilization at Regional, Zonal and Wereda levels.
Ethiopia
The 2001-2002 (1994 E.C) Agricultural Sample Enumeration was designed to cover the rural and urban parts of all districts (weredas) in the country on a large-scale sample basis excluding the pastoralist areas of the Afar and Somali regional states.
Household, holder, type of land use
The 2001/02 (1994 E.C.) EASE covered all land holdings i.e., rural and urban holdings. In urban areas, size of land holdings was restricted to only cropland area and urban agricultural households were required to have a minimum size of 250 square meters in order to be covered in the census. On the other hand, in the rural areas land use data were collected without any size limitation of land holdings.
The coverage of land use data items in rural private holdings included all the categories of land used. However, in urban private holdings, the coverage of land use data item is limited to cropland area, which includes land under temporary and permanent crops.
Census/enumeration data [cen]
This survey covers data on farm holdings by type and size of land holdings; population in agricultural households, that is in rural and urban areas of private holding that are disaggregated by size of land holdings; land area and fragmentation by type of land use and size of holding; cropland area by crop categories and data on area under land tenure systems.
Central Statistical Authority of Ethiopia
Sampling Frame
The list of enumeration areas for each wereda was compiled from the 1994 Ethiopian Population and Housing Census cartographic work and was used a frame for the selection of the Primary Sampling Units (PSU). The 1994 Population and Housing Census enumeration area maps of the region for the selected sample EA's were updated, and the EA boundaries and descriptions were further clarified to reflect the current physical situation. The sampling frame used for the selection of ultimate sampling units (agricultural households) was a fresh list of households, which was prepared by the enumerator assigned in the sampled EA's using a prescribed listing instruction at the beginning of the launching of the census enumeration.
Sample Design
In order to meet the objectives and requirements of the EASE, a stratified two-stage cluster sample design was used for the selection of ultimate sampling units. Thus, in the regions each wereda was treated as stratum for which major findings of the sample census are reported. The primary sampling units are the enumeration areas and the agricultural households are secondary (ultimate) sampling units. Finally, after the selection of the sample agricultural households, the various census forms were administered to all agricultural holders within the sampled agricultural households.
For the private peasant holdings in the rural areas a fixed number (25) of sample EA's in each wereda and 30 agricultural households in each EA were randomly selected (determined). In urban areas, weredas with urban EA's of less than or equal to 25, all the EA's were covered. However, for weredas with greater than 25 urban EA's, sample size of 25 EA's was selected. In each sampled urban EA, 30 agricultural households were randomly selected for the census. The sampled size determination in each wereda and thereby in each EA was based upon the required precision level of the major estimates and the cost consideration. The pilot survey and the previous year annual agricultural sample survey results were used to determine the required sample sizes per wereda.
Sample Selection of Primary Sampling Units
Within each wereda (stratum) in the region, the selection of EAs was carried out using probability proportional to size systematic sampling. In this case, size being total number of agricultural households in each EA obtained from the listing exercise undertaken in the 1994 Ethiopian Population and Housing Census of the region.
Listing of Households and Selection of Agricultural Households
In each sampled enumeration area of the region, a complete and fresh listing of households was carried out by canvassing the households in the EA. After a complete listing of the households and screening of the agricultural households during the listing operation in the selected EA, the agricultural households were serially numbered. From this list, a total of 30 agricultural households were selected systematically using a random start from the pre-assigned column table of random numbers. The sampling interval for each EA was determined by dividing the total number of agricultural households by 30. For crop cutting exercise purposes (rural domain) a total of 20 agricultural households were randomly selected from the 30 sampled agricultural households. The systematical random sampling technique was employed in this case, because its application is simple and flexible, and it can easily yield a proportionate sample.
Face-to-face [f2f]
Although the planning, organization and execution of the census were the responsibilities that rested within the CSA, development of the census forms was a tedious task that involved the formation of a working group composed of members of government and non-governmental organizations who are major users of agricultural data. Members of the working group were given the opportunity to identify their data requirements, define the needs of others and determine the specific questions that the forms should contain. The working group included the staff of the organizations that are involved in agricultural planning, collection of agricultural statistics and the use of data within the agricultural sector. The working group designed different forms for the various data items on crop area, production, and other variables of interest to meet the needs of current data users and also considered the future expectations. Attempt was made to make the content of the forms of acceptable length by distributing the variables to be collected in the different census forms.
The rural census questionnaires/forms included:
- Forms 94/0 and 94/1 that are used to record all households in the enumeration area, identify the agricultural households and select the units to be covered by the census.
- Form 94/2 is developed to list all the members of the sampled agricultural households and record the demographic and economic characteristics of each of the members.
- Forms 94/3A, 94/3B, 94/3C and 94/3D are prepared to enumerate crop data through interview and objective measurement.
- Form 94/5 is designed to record crop area data via the physical or objective measurement of crop fields.
- Form 94/6 is used to list all the fields under crop and select a crop field for each type of crop randomly for crop cutting exercise.
- Forms 94/7A, 94/7B, and 94/7C are developed for recording yield data on cereals, oil seeds, pulses, vegetables root crops and permanent crops by weighing their yields obtained from sub-plots and/or trees selected for crop-cuttings.
- Form 94/8 is prepared to enumerate livestock, poultry and beehives data by type, age, sex and purpose including products through interview (subjective approach).
- Forms 94/9, 94/10 and 94/11 are used to collect data on crop and livestock product usage; miscellaneous items and farm tools, implements, draught animals and storage facilities, in that order, by interviewing the sample holders.
"Belg" season questionnaires identified as:
- Form 94/12A and 94/12B that are used to record data on farm management practices of the "Belg" season.
- Form 94/4 was the questionnaire used for collecting data on crop production forecast for 2001-2002 and the data collected using this form was published in December 2001 subjectively, while 94/12C is for recording "Belg" season crop area through objective measurement and volume of production through interview approach.
On the other hand, the census questionnaires/forms used in the urban areas include:
- Form U-94/1 which used to record all households in the EA, identify the agricultural households and select the units to be covered by the census.
- Form U-94/2 is developed to list all the members of the sampled agricultural household and record the demographic and economic characteristics of each of the members.
- From U-94/3 is prepared to enumerate crop data through interview method.
- Form U-94/4 is prepared to enumerate livestock, poultry and beehives data by type, sex, age and purpose including products through interview (subjective approach).
- Form U-94/5 is used to collect data on crop and livestock usage.
Editing, Coding and Verification:
In the 2001-2002 Ethiopian Agricultural Sample Enumeration (EASE), the filled-in forms that were retrieved from 47 Branch Statistical Offices were primarily received and systematically registered at the documentation unit of the CSA head quarters in Addis Ababa. Before launching the actual editing and coding activities, the Natural Resources and Agricultural Statistics Department staff gave adequate training to the 157 editors and coders. These editors and coders carried out the manual editing, coding and verification of the filled-in EASE questionnaires in two shifts. At the outset, the editing and coding activities for the filled-in forms on area and agricultural practices took place; this was followed up by the editing and coding of the forms on the production of temporary crops (cereals, pulses, oil seeds, vegetables and root crops), livestock, farm implements, permanent crops, "Belg" and miscellaneous questionnaires region by region. For the filled-in forms on area and agricultural practices, verification was carried out on 100% basis for the first five weeks from the launching of the activity and then considering the quality performance of editor-coders the activity was dropped to 66% of the forms gradually. On the other hand, the verification activity has been carried out on 100% basis for the filled-in forms on production of the temporary and permanent crops, livestock, farm implements and all other completed forms. For the total country, the editing, coding and verification of the filled-in forms in general took about 330.6 working days. That is, the editing, coding and verification of the filled-in forms for area, agricultural practice, the production of the temporary and permanent crops, and livestock took about 198.5 working days, while that of the filled-in forms on farm implements, demographic characteristics, Belg season and the urban forms took around 132.1 working days.
Data Entry, Cleaning and Tabulation:
About 144 data encoders were assigned to undertake the data entry activity of 2001/02 EASE and it has been carried out on two-shift basis. Before the starting of the data entry operation data encoders were trained for about 5 days using computer programs developed by the Data Processing Department staff. The Programmers prepared the data entry programs using CENTRY, which is a data entry module of IMPS (Integrated Microcomputer Processing System). The data entry exercise has been carried out using 76 personal computers (PC's). Like that of the manual editing and coding activity, the filled-in forms on area and agricultural practices were entered first and this was followed by entry of the filled-in forms on the production of temporary crops, livestock, farm implements, permanent crops, "Belg" and miscellaneous questionnaires region by region till all the census data entry operations are completed. In order to ensure the quality of the data entry work, verification exercise was carried out. The entry of the filled-in forms on area and agricultural practices were verified on 100 % basis. Then the verification exercise was dropped to 66 % from the 6th week of the launching of the operation and was further reduced to 50% from the 10th week onwards by observing and assessing the magnitude of the percentage of errors. Later on verification process was carried out on 100% basis for the filled-in forms on the production of temporary and permanent crops, livestock, farm implements and all other completed forms. The verification activity was carried out through the process of re-entering the data. For the total country, the whole data entry process of the filled-in forms on area, agricultural practice, the production of the temporary and permanent crops, and livestock took around 253.1 working days, while that of the filled-in forms on farm implements, demographic characteristics, Belg season and the urban forms took about 257.9 working days. Data entered into the computer needs to be checked for completeness, consistency and validity. For this purpose computer edit programs were prepared by programmers using CONCOR, which is the editing module of IMPS. Using print-outs from these programs and referring to the filled-in census forms, corrections were made by nine trained manual data cleaning technicians. Moreover, nine other data-cleaning computer operators were involved in making the actual corrections of the data on the computer. Additionally, an intermediate set of instructions or programs were made available and applied on the data to prepare information suitable for tabulation. These programs were prepared using CSPro and IMPS software. Like IMPS Software, CSPro is used as a tool for entering, editing and tabulating data. CSA used the CSPro software for data editing and calculation of CVs. Data made ready for tabulation through the process of cleaning and intermediate programs was finally used to generate the required tables. This was done using tabulation programs developed by the senior programmers of the Data processing Department. The CENTS software, a tabulation component of IMPS, was used in producing the 2001-2002 EASE results.
Estimated procedure of parameters of interest like total, yield and ratio and their sampling errors is presented in Appendix I of the reports which are attached with this metadata. Standard errors and coefficients of variations of estimates for selected variables are also given as an annex at the end of each report.
Central Statistical Agency of Ethiopia
"Central Statistical Agency of Ethiopia, Agricultural Sample Enumeration, Land Use 2001-2002 (AgSE-LU 2001), v1.1, provided by the National Data Archive. http://www.csa.gov.et"
The Central Statistical Agency (CSA) is committed to achieving excellence in the provision of timely, reliable and affordable official statistics for informed decision making in order to maximize the welfare of all Ethiopians. This is achieved through the collection and analysis of censuses, surveys and the use of administrative data as well as the dissemination a range of statistical products and providing assistance and services to users.
A microdata dissemination policy is established by CSA to address the conditions and the manner in which anonymized microdata files may be released to users for research purposes. It also strives to identify the different levels of anonymization for different categories of data use. This policy is available at CSA website (http://www.csa.gov.et).
CSA will release microdata files for use by researchers for scientific research purposes when:
The Director General is satisfied that all reasonable steps have been taken to prevent the identification of individual respondents.
The release of the data will substantially enhance the analytic value of the data that have been collected For all but purely public files, researchers disclose the nature and objectives of their intended research, It can be demonstrated that there are no credible alternative sources for these data, and
The researchers have signed an appropriate undertaking.
Terms and conditions of use of public data files are the following:
The data and other materials provided by CSA will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of CSA.
The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.
No attempt will be made to re-identify respondents, and no use will be made of the identity of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the CSA.
No attempt will be made to produce links among datasets provided by CSA, or among data from the CSA and other datasets that could identify individuals or organizations.
Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from CSA will cite the source of data in accordance with the Citation Requirement provided with each dataset.
An electronic copy of all reports and publications based on the requested data will be sent to CSA.
The original collector of the data, CSA, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Cost Recovery Policy:
It is the policy of CSA to encourage broad use of its products by making them affordable for users. Accordingly, CSA attempts to ensure that the costs of creating anonymized microdata files are built-in to the survey budget.
At the same time, CSA attempts to recover costs associated with the provisions of special services that benefit only a specific group. Information on the price of each dataset is available at CSA website (www.csa.gov.et )
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Landuse_National_Urban
Data about land use in urban areas
0
53
Landuse_National_Rural_Holder_Record
This dataset collected at holder level and contains basic social and economic characteristics of the household for rural area.
0
17
Landuse_National_Urban_Holder_Record
This dataset collected at holder level and contains basic social and economic characteristics of the household for urban area.
0
17
Landuse_National_Rural
Data about land use in rural areas
0
51
Household id
Household id
Household id
Household id
Household id
Household id
Region
Region
Region
Region
Region
Region
1
Tigray
2
Afar
3
Amhara
4
Oromiya
5
Somalie
6
Benshangul
7
SNNP
12
Gambela
13
Harari
14
Addis ababa
15
Dire dawa
Zone
Zone
Zone
Zone
Zone
Zone
District (wereda)
District (wereda)
District (wereda)
District (wereda)
District (wereda)
District (wereda)
Town
Town
Town
Town
Town
Town
1
Urban area
2
Urban area
3
Urban area
4
Urban area
5
Urban area
6
Urban area
7
Urban area
Keftegna
Keftegna
Keftegna
Keftegna
Keftegna
Kefetegna
Farmers associations/ Kebele
Farmers associations/ Kebele
Farmers associations/ Kebele
Farmers associations/ Kebele
Farmers associations/ Kebele
Kebele
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Household number
Household number
Household number
Household number
Household number
Household number
Holder number
Holder number
Holder number
Holder number
Holder number
Holder number
Parcel number
Parcel number
Parcel number
Parcel number
Parcel number
Parcel number
Field number
Field number
Field number
Field number
Field number
Field number
Field weight
Field weight
Field weight
Field weight
Field weight
Field weight
Rate
Rate
Rate
Rate
Rate
Rate
Season
Season
Season
Season
Season
Season
1
Main ("Meher") season
2
"Belg" season
Field part
Field part
Field part
Field part
Field part
Field part
Type of land use
Type of land use
Type of land use
Type of land use
Type of land use
Name of crop or type of land use
1
Barley
2
Maize
3
Millet
4
Oats
5
Rice
6
Sorghum
7
"Teff"
8
Wheat
11
Chick peas
12
Haricot beans
13
Horse beans
14
Lentils
15
Field peas
16
Vetch
17
"Gibto"
18
Soya Bean
19
Cactus "Beles"
20
"Ensosela"
23
Linseed
24
Ground nuts
25
"Neug"
26
Rapeseed
27
Sesame
28
Sunflower
31
Black Cumin "Tikur Azmud"
32
"Kundo Berbera"
33
Cardamon "Korerima"
34
Chilies "Mitmita"
35
"Kerefa"
36
Fenugreek
37
Ginger
38
Red Peppers
39
Turmeric "Erd"
40
White Cumin
42
Banana
43
Grape
44
Lemond
45
"Mendarin"
46
Mangoes
47
Oranges
48
Papaya
49
Pineapples
50
"Tirengo"
51
Beet root
52
Cabbage
53
Carrot
54
"Abeba Gomen"
55
Garlic
56
Kale
57
Lettuce
58
Onion
59
Green Peppers
60
Potato
61
"Duba"
62
Sweet Potato
63
Tomatoes
64
"Godere"
65
Guava " Zeytun"
66
"Koke"
69
Spinach
70
"Fosoliya" (Fagoli)
71
Chat
72
Coffee
73
Cotton
74
"Enset"
75
Hops 'Gesho'
76
Sugar cane
77
Other stimulant crops
78
Tobacco
79
Coriander "Denbilal"
80
Sacred Basil "Beso bila"
81
"Tenadam"
83
"Kerbush"/ "Habhab"
84
Avocado
85
Grazing land
86
Fallow Land
89
Wood Land
98
Other root crops
99
Other land (water well,"awdema","gotera")
113
"Enjori"
114
Other permanents
115
Other fruit crops
116
"Timizmez kemem"
117
Other spices
118
Other pulses
119
Other oil seeds
120
Other cereals
121
Other cash crops
123
Other vegetables
999
Others not specified
Recode land use
Recode land use
Recode land use
Recode land use
Recode land use
Recode land use
1
Temporary crop
2
Permanent crop
3
Grazing land
4
Fallow land
5
Wood land
6
Other land
Type of holding
Type of holding
Type of holding
Type of holding
Type of holding
Type of holding
1
Private
2
Rented/contract
3
Other
9
Not stated
Field included in the extention package program
Field included in the extention package program
Field included in the extention package program
Field included in the extention package program
Field included in the extention package program
Has the field been included in the extention package program?
1
Yes
2
No
Number of trees
Number of trees
Number of trees
Number of trees
Number of trees
Total number of trees in the field (Excluding coffee,Chat, Pineapple, Sugar-cane)
Number of trees of bearing age
Number of trees of bearing age
Number of trees of bearing age
Number of trees of bearing age
Number of trees of bearing age
Total number of trees of fruit bearing age (Excluding coffee,Chat, Pineapple, Sugar-cane)
Irrigation used
Irrigation used
Irrigation used
Irrigation used
Irrigation used
Was the field irrigated?
1
Yes
2
No
9
Not stated
Seed type /variety of seeds used
Seed type /variety of seeds used
Seed type /variety of seeds used
Seed type /variety of seeds used
Seed type /variety of seeds used
Variety of seeds used
1
Improved
2
Non-improved
9
Not stated
Weight of non-improved seed
Weight of non-improved seed
Weight of non-improved seed
Weight of non-improved seed
Weight of non-improved seed
Weight of non-improved seed
Weight of improved seed
Weight of improved seed
Weight of improved seed
Weight of improved seed
Weight of improved seed
Weight of improved seed
Improved seed cost
Improved seed cost
Improved seed cost
Improved seed cost
Improved seed cost
Improved seed cost
Crop damaged
Crop damaged
Crop damaged
Crop damaged
Crop damaged
Was the crop damaged?
1
Yes
2
No
Damage reason
Damage reason
Damage reason
Damage reason
Damage reason
If "Yes" in "Was the crop damaged?"
What was the major cause of damage?
1
Too much rain
2
Too little rain
3
Insects
4
Crop disease
5
Weeds
6
Hail
7
Frost
8
Floods
9
Wild animals
10
Locust
11
Birds
12
Shortage of seeds
13
Depletion of soil fertility
14
Security problems
15
Other
Damage percent
Damage percent
Damage percent
Damage percent
Damage percent
If "Yes" in "Was the crop damaged?"
Percentage of damage
100
100
Any measure taken prevent damage
Any measure taken prevent damage
Any measure taken prevent damage
Any measure taken prevent damage
Any measure taken prevent damage
Any control/prevention measure takes for crop damage
1
Yes
2
No
Type of damage prevention
Type of damage prevention
Type of damage prevention
Type of damage prevention
Type of damage prevention
Type of damege prevantion
1
Chemical
2
Non chemical
3
Both
9
Not stated
Chemical used
Chemical used
Chemical used
Chemical used
Chemical used
If "Chemical" in "Type of damege prevantion"
Type of chemical damaged prevention used
1
Insecticide
2
Herbicide
3
Fungicide
4
Insectcide & herbicide
5
Insectcide & fungicide
6
Herbicide & fungicide
7
All
9
Not stated
Fertilizer used
Fertilizer used
Fertilizer used
Fertilizer used
Fertilizer used
Was the field fertilized?
1
Yes
2
No
9
Not stated
Fertilizer type
Fertilizer type
Fertilizer type
Fertilizer type
Fertilizer type
If "Yes" in "Was the field fertilized?"
What type of fertilier used?
1
Natural
2
Chemical
3
Both
9
Not stated
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
1
Not aware
2
Too expensive
3
No money
4
Not available
5
No credit
6
Not good
7
Others
Chemical fertilizer type
Chemical fertilizer type
Chemical fertilizer type
Chemical fertilizer type
Chemical fertilizer type
If chemical (commercial) fertilizer used
1
Urea
2
Dap
3
Both
9
Not stated
Chemical fertilizer amount
Chemical fertilizer amount
Chemical fertilizer amount
Chemical fertilizer amount
Chemical fertilizer amount
Quantity of chemical fertilizer in kg
Natural fertilizer type
Natural fertilizer type
Natural fertilizer type
Natural fertilizer type
Natural fertilizer type
If natural fertilizer used mainly what type?
1
Manure
2
Compost
3
Both
4
Others
9
Not stated
Percent of field in use
Percent of field in use
Percent of field in use
Percent of field in use
Percent of field in use
Percent of field in use
Land use only
100
Single crop
Area measure - day
Area measure - day
Area measure - day
Area measure - day
Area measure - day
The field or other land use date of measurement - date
Area measure - month
Area measure - month
Area measure - month
Area measure - month
Area measure - month
The field or other land use date of measurement - month
1
Meskerem
2
Tikimt
3
Hidar
4
Tahsas
5
Tir
6
Yekatit
7
Megabit
8
Miazia
9
Ginbot
10
Sene
11
Hamle
12
Nehase
13
Pagume
99
Not stated
Local area measurement unit
Local area measurement unit
Local area measurement unit
Local area measurement unit
Local area measurement unit
Local area measurement unit
Local area amount
Local area amount
Local area amount
Local area amount
Local area amount
Local area amount
Reason for not measuring area
Reason for not measuring area
Reason for not measuring area
Reason for not measuring area
Reason for not measuring area
Reason if area measurment was not conducted
1
Not in farmers' association
2
Can't read bearing
3
Holder refused
4
Others
5
Measured
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Local production measurement unit
Local production measurement unit
Local production measurement unit
Local production measurement unit
Local production measurement unit
Local production measurement unit
Production in local unit
Production in local unit
Production in local unit
Production in local unit
Production in local unit
Production in local unit
Dry weight production (in KG)
Dry weight production (in KG)
Dry weight production (in KG)
Dry weight production (in KG)
Dry weight production (in KG)
Dry weight production (in KG)
Source of irrigation
Source of irrigation
Source of irrigation
Source of irrigation
Source of irrigation
Source of irrigation
1
River
2
Lake
3
Well
4
Tap water
5
Other
9
Not stated
"Belg" crop
"Belg" crop
"Belg" crop
"Belg" crop
"Belg" crop
"Belg" crop
1
Yes
2
No
Household id
Household id
Household id
Household id
Household id
Household id
Region
Region
Region
Region
Region
Region
1
Barley
2
Maize
3
Millet
4
Oats
5
Rice
6
Sorghum
7
"Teff"
8
Wheat
11
Chick peas
12
Haricot beans
13
Horse beans
14
Lentils
15
Field peas
16
Vetch
17
"Gibto"
18
Soya Bean
19
Cactus "Beles"
20
"Ensosela"
23
Linseed
24
Ground nuts
25
"Neug"
26
Rapeseed
27
Sesame
28
Sunflower
31
Black Cumin "Tikur Azmud"
32
"Kundo Berbera"
33
Cardamon "Korerima"
34
Chilies "Mitmita"
35
"Kerefa"
36
Fenugreek
37
Ginger
38
Red Peppers
39
Turmeric "Erd"
40
White Cumin
42
Banana
43
Grape
44
Lemond
45
"Mendarin"
46
Mangoes
47
Oranges
48
Papaya
49
Pineapples
50
"Tirengo"
51
Beet root
52
Cabbage
53
Carrot
54
"Abeba Gomen"
55
Garlic
56
Kale
57
Lettuce
58
Onion
59
Green Peppers
60
Potato
61
"Duba"
62
Sweet Potato
63
Tomatoes
64
"Godere"
65
Guava " Zeytun"
66
"Koke"
69
Spinach
70
"Fosoliya" (Fagoli)
71
Chat
72
Coffee
73
Cotton
74
"Enset"
75
Hops 'Gesho'
76
Sugar cane
77
Other stimulant crops
78
Tobacco
79
Coriander "Denbilal"
80
Sacred Basil "Beso bila"
81
"Tenadam"
83
"Kerbush"/ "Habhab"
84
Avocado
85
Grazing land
86
Fallow Land
89
Wood Land
98
Other root crops
99
Other land (water well,"awdema","gotera")
113
"Enjori"
114
Other permanents
115
Other fruit crops
116
"Timizmez kemem"
117
Other spices
118
Other pulses
119
Other oil seeds
120
Other cereals
121
Other cash crops
123
Other vegetables
999
Others not specified
Zone
Zone
Zone
Zone
Zone
Zone
District (wereda)
District (wereda)
District (wereda)
District (wereda)
District (wereda)
District (wereda)
Town
Town
Town
Town
Town
Town
8
Rural
Keftegna
Keftegna
Keftegna
Keftegna
Keftegna
Kefetegna
Farmers associations
Farmers associations
Farmers associations
Farmers associations
Farmers associations
Kebele
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Household number
Household number
Household number
Household number
Household number
Household number
Holder number
Holder number
Holder number
Holder number
Holder number
Holder number
Holder weight
Holder weight
Holder weight
Holder weight
Holder weight
Holder weight
Holder ratio
Holder ratio
Holder ratio
Holder ratio
Holder ratio
Holder ratio
Type of holding
Type of holding
Type of holding
Type of holding
Type of holding
Type of holding
1
Crop only
2
Livestock only
3
Crop & livestock
9
Not stated
Holder age
Holder age
Holder age
Holder age
Holder age
Holder age
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30
31
31
32
32
33
33
34
34
35
35
36
36
37
37
38
38
39
39
40
40
41
41
42
42
43
43
44
44
45
45
46
46
47
47
48
48
49
49
50
50
51
51
52
52
53
53
54
54
55
55
56
56
57
57
58
58
59
59
60
60
61
61
62
62
63
63
64
64
65
65
66
66
67
67
68
68
69
69
70
70
71
71
72
72
73
73
74
74
75
75
76
76
77
77
78
78
79
79
80
80
81
81
82
82
83
83
84
84
85
85
86
86
87
87
88
88
89
89
90
90
91
91
92
92
93
93
94
94
95
95
96
96
97
97
98
98
99
99
Holder sex
Holder sex
Holder sex
Holder sex
Holder sex
Holder sex
1
Male
2
Female
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
1
Illiterate
2
No formal education
3
Grade 1
4
Grade 2
5
Grade 3
6
Grade 4
7
Grade 5
8
Grade 6
9
Grade 7
10
Grade 8
11
Grade 9
12
Grade 10
13
Grade 11
14
Grade 12
15
More than grade 12
99
Not stated
Household size
Household size
Household size
Household size
Household size
Household size
1
1
2
2
Household id
Household id
Household id
Household id
Household id
Household id
Region
Region
Region
Region
Region
Region
1
Tigray
2
Afar
3
Amhara
4
Oromiya
5
Somalie
6
Benshangul
7
SNNP
12
Gambela
13
Harari
14
Addis ababa
15
Dire dawa
Zone
Zone
Zone
Zone
Zone
Zone
District (wereda)
District (wereda)
District (wereda)
District (wereda)
District (wereda)
District (wereda)
Town
Town
Town
Town
Town
Town
1
Urban
2
Urban
3
Urban
4
Urban
5
Urban
6
Urban
7
Urban
Keftegna
Keftegna
Keftegna
Keftegna
Keftegna
Kefetegna
Farmers associations/ Kebele
Farmers associations/ Kebele
Farmers associations/ Kebele
Farmers associations/ Kebele
Farmers associations/ Kebele
Kebele
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Household number
Household number
Household number
Household number
Household number
Household number
Holder number
Holder number
Holder number
Holder number
Holder number
Holder number
Holder weight
Holder weight
Holder weight
Holder weight
Holder weight
Holder weight
Holder ratio
Holder ratio
Holder ratio
Holder ratio
Holder ratio
Holder ratio
Type of holding
Type of holding
Type of holding
Type of holding
Type of holding
Type of holding
1
Crop only
2
Livestock only
3
Crop & livestock
9
Not stated
Holder age
Holder age
Holder age
Holder age
Holder age
Holder age
1
1
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30
31
31
32
32
33
33
34
34
35
35
36
36
37
37
38
38
39
39
40
40
41
41
42
42
43
43
44
44
45
45
46
46
47
47
48
48
49
49
50
50
51
51
52
52
53
53
54
54
55
55
56
56
57
57
58
58
59
59
60
60
61
61
62
62
63
63
64
64
65
65
66
66
67
67
68
68
69
69
70
70
71
71
72
72
73
73
74
74
75
75
76
76
77
77
78
78
79
79
80
80
81
81
82
82
83
83
84
84
85
85
86
86
87
87
88
88
89
89
90
90
91
91
92
92
93
93
94
94
95
95
96
96
97
97
99
99
Holder sex
Holder sex
Holder sex
Holder sex
Holder sex
Holder sex
1
Male
2
Female
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
Educational attainment (highest grade completed)
1
Illiterate
2
No formal education
3
Grade 1
4
Grade 2
5
Grade 3
6
Grade 4
7
Grade 5
8
Grade 6
9
Grade 7
10
Grade 8
11
Grade 9
12
Grade 10
13
Grade 11
14
Grade 12
15
More than grade 12
99
Not stated
Household size
Household size
Household size
Household size
Household size
Household size
Household id
Household id
Household id
Household id
Household id
Household id
Region
Region
Region
Region
Region
Region
1
Tigray
2
Afar
3
Amhara
4
Oromiya
5
Somalie
6
Benshangul
7
SNNP
12
Gambela
13
Harari
14
Addis ababa
15
Dire dawa
Zone
Zone
Zone
Zone
Zone
Zone
District (wereda)
District (wereda)
District (wereda)
District (wereda)
District (wereda)
District (wereda)
Town
Town
Town
Town
Town
Town
8
Rural
Keftegna
Keftegna
Keftegna
Keftegna
Keftegna
Kefetegna
Farmers associations/ kebele
Farmers associations/ kebele
Farmers associations/ kebele
Farmers associations/ kebele
Farmers associations/ kebele
Kebele
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Enumeration area
Household number
Household number
Household number
Household number
Household number
Household number
Holder number
Holder number
Holder number
Holder number
Holder number
Holder number
Parcel number
Parcel number
Parcel number
Parcel number
Parcel number
Parcel number
Field number
Field number
Field number
Field number
Field number
Field number
Field weight
Field weight
Field weight
Field weight
Field weight
Field weight
Rate
Rate
Rate
Rate
Rate
Rate
Season
Season
Season
Season
Season
Season
1
Main ("Meher") season
2
"Belg" season
Field part
Field part
Field part
Field part
Field part
Field part
1
1
2
2
3
3
Type of land use
Type of land use
Type of land use
Type of land use
Type of land use
Name of crop or type of land use
1
Barley
2
Maize
3
Millet
4
Oats
5
Rice
6
Sorghum
7
"Teff"
8
Wheat
11
Chick peas
12
Haricot beans
13
Horse beans
14
Lentils
15
Field peas
16
Vetch
17
"Gibto"
18
Soya Bean
19
Cactus "Beles"
20
"Ensosela"
23
Linseed
24
Ground nuts
25
"Neug"
26
Rapeseed
27
Sesame
28
Sunflower
31
Black Cumin "Tikur Azmud"
32
"Kundo Berbera"
33
Cardamon "Korerima"
34
Chilies "Mitmita"
35
"Kerefa"
36
Fenugreek
37
Ginger
38
Red Peppers
39
Turmeric "Erd"
40
White Cumin
42
Banana
43
Grape
44
Lemond
45
"Mendarin"
46
Mangoes
47
Oranges
48
Papaya
49
Pineapples
50
"Tirengo"
51
Beet root
52
Cabbage
53
Carrot
54
"Abeba Gomen"
55
Garlic
56
Kale
57
Lettuce
58
Onion
59
Green Peppers
60
Potato
61
"Duba"
62
Sweet Potato
63
Tomatoes
64
"Godere"
65
Guava " Zeytun"
66
"Koke"
69
Spinach
70
"Fosoliya" (Fagoli)
71
Chat
72
Coffee
73
Cotton
74
"Enset"
75
Hops 'Gesho'
76
Sugar cane
77
Other stimulant crops
78
Tobacco
79
Coriander "Denbilal"
80
Sacred Basil "Beso bila"
81
"Tenadam"
83
"Kerbush"/ "Habhab"
84
Avocado
85
Grazing land
86
Fallow Land
89
Wood Land
98
Other root crops
99
Other land (water well,"awdema","gotera")
113
"Enjori"
114
Other permanents
115
Other fruit crops
116
"Timizmez kemem"
117
Other spices
118
Other pulses
119
Other oil seeds
120
Other cereals
121
Other cash crops
123
Other vegetables
999
Others not specified
Recode land use
Recode land use
Recode land use
Recode land use
Recode land use
Recode land use
1
Temporary crop
2
Permanent crop
3
Grazing land
4
Fallow land
5
Wood land
6
Other land
Type of holding
Type of holding
Type of holding
Type of holding
Type of holding
Type of holding
1
Private
2
Rented/contract
3
Other
Field included in the extention package program
Field included in the extention package program
Field included in the extention package program
Field included in the extention package program
Field included in the extention package program
Has the field been included in the extention package program?
1
Yes
2
No
Number of trees
Number of trees
Number of trees
Number of trees
Number of trees
Total number of trees in the field (Excluding coffee,Chat, Pineapple, Sugar-cane)
Number of trees of bearing age
Number of trees of bearing age
Number of trees of bearing age
Number of trees of bearing age
Number of trees of bearing age
Total number of trees of fruit bearing age (Excluding coffee,Chat, Pineapple, Sugar-cane)
Irrigation used
Irrigation used
Irrigation used
Irrigation used
Irrigation used
Was the field irrigated?
1
Yes
2
No
Seed type /variety of seeds used
Seed type /variety of seeds used
Seed type /variety of seeds used
Seed type /variety of seeds used
Seed type /variety of seeds used
Variety of seeds used
1
Improved
2
Non-improved
9
Not stated
Weight of non-improved seed
Weight of non-improved seed
Weight of non-improved seed
Weight of non-improved seed
Weight of non-improved seed
Weight of non-improved seed
Weight of improved seed
Weight of improved seed
Weight of improved seed
Weight of improved seed
Weight of improved seed
Weight of improved seed
Improved seed cost
Improved seed cost
Improved seed cost
Improved seed cost
Improved seed cost
Improved seed cost
Crop damaged
Crop damaged
Crop damaged
Crop damaged
Crop damaged
Was the crop damaged?
1
Yes
2
No
Cause of damage
Cause of damage
Cause of damage
Cause of damage
Cause of damage
If "Yes" in "Was the crop damaged?"
What was the major cause of damage?
1
Too much rain
2
Too little rain
3
Insects
4
Crop disease
5
Weeds
6
Hail
7
Frost
8
Floods
9
Wild animals
10
Locust
11
Birds
12
Shortage of seeds
13
Depletion of soil fertility
14
Security problems
15
Other
Damage percent
Damage percent
Damage percent
Damage percent
Damage percent
If "Yes" in "Was the crop damaged?"
Percentage of damage
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30
31
31
32
32
33
33
34
34
35
35
36
36
37
37
38
38
39
39
40
40
41
41
42
42
43
43
44
44
45
45
46
46
47
47
48
48
49
49
50
50
51
51
52
52
53
53
54
54
55
55
56
56
57
57
58
58
59
59
60
60
61
61
62
62
63
63
64
64
65
65
66
66
67
67
68
68
69
69
70
70
71
71
72
72
73
73
74
74
75
75
76
76
77
77
78
78
79
79
80
80
82
82
83
83
84
84
85
85
86
86
87
87
88
88
89
89
90
90
91
91
92
92
93
93
94
94
95
95
96
96
97
97
98
98
99
99
100
100
999
999
Any measure taken prevent damage
Any measure taken prevent damage
Any measure taken prevent damage
Any measure taken prevent damage
Any measure taken prevent damage
Any control/prevention measure takes for crop damage
1
Yes
2
No
Type of damage prevention
Type of damage prevention
Type of damage prevention
Type of damage prevention
Type of damage prevention
Type of damege prevantion
1
Chemical
2
Non-chemical
3
Both
Type of chemical damaged prevention used
Type of chemical damaged prevention used
Type of chemical damaged prevention used
Type of chemical damaged prevention used
Type of chemical damaged prevention used
If "Chemical" in "Type of damege prevantion"
Type of chemical damaged prevention used
1
Insecticide
2
Herbicide
3
Fungicide
4
Insectcide & herbicide
5
Insectcide & fungicide
6
Herbicide & fungicide
7
All
9
Not stated
Fertilizer used
Fertilizer used
Fertilizer used
Fertilizer used
Fertilizer used
Was the field fertilized?
1
Yes
2
No
Fertilizer type
Fertilizer type
Fertilizer type
Fertilizer type
Fertilizer type
If "Yes" in "Was the field fertilized?"
What type of fertilier used?
1
Natural
2
Chemical
3
Both
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
Reason for not using chemical fertilizer
1
Not aware
2
Too expensive
3
No money
4
Not available
5
No credit
6
Not good
7
Others
Chemical fertilizer type
Chemical fertilizer type
Chemical fertilizer type
Chemical fertilizer type
Chemical fertilizer type
If chemical (commercial) fertilizer used
1
Urea
2
Dap
3
Both
9
Not stated
Chemical fertilizer amount
Chemical fertilizer amount
Chemical fertilizer amount
Chemical fertilizer amount
Chemical fertilizer amount
Quantity of chemical fertilizer in kg
Natural fertilizer type
Natural fertilizer type
Natural fertilizer type
Natural fertilizer type
Natural fertilizer type
If natural fertilizer used mainly what type?
1
Manure
2
Compost
3
Both
4
Others
9
Not stated
Percent of field in use
Percent of field in use
Percent of field in use
Percent of field in use
Percent of field in use
Percent of field in use
Land use only
1
1
2
2
3
3
4
4
5
5
6
6
7
7
8
8
9
9
10
10
11
11
12
12
13
13
14
14
15
15
16
16
17
17
18
18
19
19
20
20
21
21
22
22
23
23
24
24
25
25
26
26
27
27
28
28
29
29
30
30
31
31
32
32
33
33
34
34
35
35
36
36
37
37
38
38
39
39
40
40
41
41
42
42
43
43
44
44
45
45
46
46
47
47
48
48
49
49
50
50
51
51
52
52
53
53
54
54
55
55
56
56
57
57
58
58
59
59
60
60
61
61
62
62
63
63
64
64
65
65
66
66
67
67
68
68
69
69
70
70
71
71
72
72
73
73
74
74
75
75
76
76
77
77
78
78
79
79
80
80
81
81
82
82
83
83
84
84
85
85
86
86
87
87
88
88
89
89
90
90
91
91
92
92
93
93
94
94
95
95
96
96
97
97
98
98
99
99
100
Single crop
Area measure - day
Area measure - day
Area measure - day
Area measure - day
Area measure - day
The field or other land use date of measurement - date
Area measure - month
Area measure - month
Area measure - month
Area measure - month
Area measure - month
The field or other land use date of measurement - month
1
Meskerem
2
Tikimt
3
Hidar
4
Tahsas
5
Tir
6
Yekatit
7
Megabit
8
Miazia
9
Ginbot
10
Sene
11
Hamle
12
Nehase
13
Pagume
99
Not stated
Local area measurement unit
Local area measurement unit
Local area measurement unit
Local area measurement unit
Local area measurement unit
Local area measurement unit
Local area amount
Local area amount
Local area amount
Local area amount
Local area amount
Local area amount
Reason for not measuring area
Reason for not measuring area
Reason for not measuring area
Reason for not measuring area
Reason for not measuring area
Reason if area measurment was not conducted
1
Not in farmers' association
2
Can't read bearing
3
Holder refused
4
Others
5
Measured
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Enumerator area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Computer computed area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Area (in SQ M)
Local production measurement unit
Local production measurement unit
Local production measurement unit
Local production measurement unit
Local production measurement unit
Local production measurement unit
Production in local unit
Production in local unit
Production in local unit
Production in local unit
Production in local unit
Production in local unit
Dry weight production (in KG)
Dry weight production (in KG)
Dry weight production (in KG)
Dry weight production (in KG)
Dry weight production (in KG)
Dry weight production (in KG)