Agricultural Household Survey 2017
Rwanda, 2017
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Reference ID
RWA_2017_AHS_v01_EN_M_v01_A_OCS
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National Institute of Statistics of Rwanda
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Mar 02, 2021
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Mar 02, 2021
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Identification
Survey ID Number
RWA_2017_AHS_v01_EN_M_v01_A_OCS
Title
Agricultural Household Survey 2017
Country
| Name | Country code |
|---|---|
| Rwanda | RWA |
Study type
Agricultural Survey [ag/oth]
Abstract
Agriculture statistics are useful for monitoring progress on agriculture programs and policies in Rwanda. The government of Rwanda needs updated information on agricultural household in order to assist in addressing key agricultural issues and information needs that will inform policy makers and other stakeholders and allow more effective identification of priority intervention needs and to facilitate evidence-based decision making for the development of Agriculture sector.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
The scope of 2017 Agricultural Household Survey was related to socio-economic characteristics of agricultural households, crop production, use of agricultural production, awareness of agriculture technology, government policies and programs, access to inputs, access to finance, agricultural assets and livestock numbers.
Coverage
Geographic Coverage
National coverage
Universe
All household members
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Institute of Statistics of Rwanda | Ministry of Finance and Economic Planning |
Producers
| Name | Affiliation |
|---|---|
| Ministry of Agriculture and Animal Resources | Government of Rwanda |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Government of Rwanda | GoR | Funding |
Sampling
Sampling Procedure
In order to provide the basis for conducting sample surveys based on complete coverage of the household level in all 30 districts of Rwanda, and as a better way of collecting agricultural household data and finding better precise survey estimates, agricultural household survey(AHS) used a Multiple-Frame Sampling (MFS) methodology by which, area frame was constructed and survey sample was drawn from it.
In the sampling strategy of the SAS 2017, it was proposed that 960 PSUs be selected in the first instance by systematic sampling method with probability proportional to size. At the second stage the sampled PSUs were divided into SSUs among which only one SSUs was sampled at random for each PSU and used for the survey. 960 segments were drawn from three agricultural strata including intensive agriculture land on hillsides (stratum 1.1), intensive agriculture land in marshlands (stratum 2.0), rangelands (stratum 3.0). Using the open segment obliges to include urban strata in the sampling frame. Apart from stated strata, village stratum which combines two substrata; urban area (stratum 4.1) rural settlements (stratum 4.2) was added to the sample frame. This stratum was divided into segments and a sample of 600 segments was drawn by systematic sampling method.
It should be mentioned that the Stratum 4.1 and 4.2 were specially added to the purpose of having a complete sampling frame for estimation of livestock since a major portion of livestock are associated with households located in villages and rural urban area adjacent to grazing land that had previously been missing for all of the previous SAS area sampling frames. This survey was conducted among private agricultural households, in 4 strata used in Seasonal agricultural survey. Households were listed from the 1,560 sampled segments in the country. Among the listed households 16,057 households were found the ones applying agricultural activities. A single visit was done in every identified agricultural household and the information collected covered two agricultural seasons A and B of 2017 agricultural year.
In the sampling strategy of the SAS 2017, it was proposed that 960 PSUs be selected in the first instance by systematic sampling method with probability proportional to size. At the second stage the sampled PSUs were divided into SSUs among which only one SSUs was sampled at random for each PSU and used for the survey. 960 segments were drawn from three agricultural strata including intensive agriculture land on hillsides (stratum 1.1), intensive agriculture land in marshlands (stratum 2.0), rangelands (stratum 3.0). Using the open segment obliges to include urban strata in the sampling frame. Apart from stated strata, village stratum which combines two substrata; urban area (stratum 4.1) rural settlements (stratum 4.2) was added to the sample frame. This stratum was divided into segments and a sample of 600 segments was drawn by systematic sampling method.
It should be mentioned that the Stratum 4.1 and 4.2 were specially added to the purpose of having a complete sampling frame for estimation of livestock since a major portion of livestock are associated with households located in villages and rural urban area adjacent to grazing land that had previously been missing for all of the previous SAS area sampling frames. This survey was conducted among private agricultural households, in 4 strata used in Seasonal agricultural survey. Households were listed from the 1,560 sampled segments in the country. Among the listed households 16,057 households were found the ones applying agricultural activities. A single visit was done in every identified agricultural household and the information collected covered two agricultural seasons A and B of 2017 agricultural year.
Weighting
Taking into consideration of full completeness of the segment, sampling weights were calculated for each stratum in each district considering the total number of segments in the stratum and the sample size in the specific stratum. The weight was calculated as the inverse of the overall probability of selection, taking into account the probabilities from all sampling stages. For strata 1.1, 2.0 and 3.0, the sampling of segments was done through two stages and probabilities were calculated for each sampling stage. For strata 4.1 and 4.2 the sampling of segments was done through one stage and probabilities were calculated in order to determine the weight.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2017-07-18 | 2017-07-28 | Listing of households |
| 2017-07-30 | 2017-09-04 | Interview for agricultural households |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Data Collection Notes
Data collection consists of two distinct phases: The first Phase, known as Listing of households, consists of visiting all sampled segments and after identifying a dwelling (household) enumerators through reading the definition of household to the household head, identify the number of households in that dwelling record the information on household's main activity whereby each household was asked if there is at least one household member who was engaged in cropping or/ and livestock during the agricultural year 2016/2017.the second phase consists of visiting agricultural household from listing, all of them were interviewed and records were taken using survey instruments.In this phase each sampled agricultural household is requested to provide information related to socio-economic characteristics of agricultural households, crop production, use of agricultural production, awareness of agriculture technology, government policies and programs, access to inputs, access to finance, agricultural assets and livestock numbers.
For AHS 2017, NISR employed 200 field workers 168 enumerators, 23 team leaders at district level, 7 regional supervisors and 3 data editors. Training was provided to all fieldwork personnel on the data collection methodologies associated with the use of GPS household location and computer tablet questionnaires used for data collection. The computer assisted personal interviewing data collection method allowed for very fast and efficient uploading and transfer of the enumerated data from the field to NISR headquarters for processing. The tablet software instruments (electronic version of the paper questionnaires) allowed for instantaneous checking of the respondent data and automatically directed the enumerator questioning to reduce non-sampling errors within the data collection.
For AHS 2017, NISR employed 200 field workers 168 enumerators, 23 team leaders at district level, 7 regional supervisors and 3 data editors. Training was provided to all fieldwork personnel on the data collection methodologies associated with the use of GPS household location and computer tablet questionnaires used for data collection. The computer assisted personal interviewing data collection method allowed for very fast and efficient uploading and transfer of the enumerated data from the field to NISR headquarters for processing. The tablet software instruments (electronic version of the paper questionnaires) allowed for instantaneous checking of the respondent data and automatically directed the enumerator questioning to reduce non-sampling errors within the data collection.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| National Institute of Statistics of Rwanda | NISR | Ministry of Finance and Economic Planning |
Questionnaires
Questionnaires
Listing questionnaire was used to list all households inside the segment.
Agricultural household questionnaire was used to collect data in agricultural households and contained twelve sections:
Section 0. General information
Section I: Household member's characteristics
Section II: land tenure and crops planted during agricultural year 2016-2017 agricultural year
Section III: extension services and agricultural programs in 2016-2017 agricultural year
Section IV: funding during 2016-2017 agricultural year
Section V: agricultural inputs during 2016-2017 agricultural year
Section VI: agricultural practices during 2016-2017 agricultural year
Section VII: agricultural tools during 2016-2017 agricultural year
Section VIII: Use of production, storage facilities and expenses on harvesting and storage during 2016-2017 agricultural year
Section IX: number of animals
Section X: animal's products and use
Section XI: animal inputs and services
Questionnaire design took into account the requests raised by major data users and stakeholders, it was developed in English then translated into Kinyarwanda for data collection, All the sections of the questionnaire were published in English.
Agricultural household questionnaire was used to collect data in agricultural households and contained twelve sections:
Section 0. General information
Section I: Household member's characteristics
Section II: land tenure and crops planted during agricultural year 2016-2017 agricultural year
Section III: extension services and agricultural programs in 2016-2017 agricultural year
Section IV: funding during 2016-2017 agricultural year
Section V: agricultural inputs during 2016-2017 agricultural year
Section VI: agricultural practices during 2016-2017 agricultural year
Section VII: agricultural tools during 2016-2017 agricultural year
Section VIII: Use of production, storage facilities and expenses on harvesting and storage during 2016-2017 agricultural year
Section IX: number of animals
Section X: animal's products and use
Section XI: animal inputs and services
Questionnaire design took into account the requests raised by major data users and stakeholders, it was developed in English then translated into Kinyarwanda for data collection, All the sections of the questionnaire were published in English.
Data Processing
Data Editing
The questionnaire was designed in CSPro software to facilitate electronic data collection. Tablets were used to collect data
Data editing took place at a number of stages throught the processing, including:
a) During data entry
b) Office editing and coding
c) Structure checking and completeness.
Data editing took place at a number of stages throught the processing, including:
a) During data entry
b) Office editing and coding
c) Structure checking and completeness.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| National Institute of Statistics of Rwanda | NISR | [email protected] | www.statistics.gov.rw |
Confidentiality
1. The data and other materials provided by the National Institute of Statistics of Rwanda will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the Nationall Institute of Statistics of Rwanda .
2. 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.
3. 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 National l Institute of Statistics of Rwanda .
4. No attempt will be made to produce links among datasets provided by the National l Institute of Statistics of Rwanda.
Access conditions
1. The data and other materials provided by the National Institute of Statistics of Rwanda will not be redistributed or sold to other individuals, institutions, or organizations without the written agreement of the Nationall Institute of Statistics of Rwanda .
2. 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.
3. 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 National l Institute of Statistics of Rwanda .
4. No attempt will be made to produce links among datasets provided by the National l Institute of Statistics of Rwanda.
2. 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.
3. 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 National l Institute of Statistics of Rwanda .
4. No attempt will be made to produce links among datasets provided by the National l Institute of Statistics of Rwanda.
Citation requirements
National Institute of Statistics of Rwanda (NISR), Agricultural Household Survey 2017 report, December 2018
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| National Institute of Statistics of Rwanda | NISR | [email protected] | www.statistics.gov.rw |
Disclaimer and copyrights
Copyright
(c) 2018, National Institute of Statistics of Rwanda
Metadata production
DDI Document ID
DDI_RWA_2017_AHS_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Metadata adapted for FAM |
| National Institute of Statistics of Rwanda | NISR | Ministry of Finance and Economic Planning | Documentation of the study |
DDI Document version
RWA_2017_AHS_v01_EN_M_v01_A_OCS_v01