RWA_2021_SAS_v01_M
Season Agriculture Survey 2021
Name | Country code |
---|---|
Rwanda | RWA |
Agricultural Census [ag/census]
The main objective of the Seasonal Agricultural Survey is to provide timely, accurate, reliable, and comprehensive agricultural statistics that describe the structure of agriculture in Rwanda mainly in terms of land use, crop area, yield, and crop production to monitor current agricultural and food supply conditions and to facilitate evidence-based decision making for the development of the agricultural sector.
The National Institute of Statistics of Rwanda (NISR) has been conducting seasonal agricultural surveys since 2012 for the estimation of the national agricultural crop area and production estimates. In the 2020/2021 agricultural year, the NISR conducted Seasonal Agricultural Survey (SAS) covering the three agricultural seasons. The SAS provides information used as a tool to assist in addressing key agricultural issues and information needs that will inform policymakers and other stakeholders and allow more effective identification of priority intervention needs.
Sample survey data [ssd]
This seasonal agriculture survey focused on the following units of analysis: Small scale agricultural farms and large scale farms.
Version 01. Edited, anonymous dataset for public use.
National coverage allowing district-level estimation of key indicators.
The SAS 2021 targeted potential agricultural land and large scale farmers.
Name | Affiliation |
---|---|
National Institute of Statistics of Rwanda | Ministry of Finance and Economic Planning |
Name | Affiliation | Role |
---|---|---|
National Institute of Statistics of Rwanda | Ministry of Finance and Economic Planning | Producer of the Survey |
Name | Role |
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Government of Rwanda | Funder of the Survey |
Out of 5 defined agricultural strata, only dominant hill crop land stratum, dominant wetland crops stratum, dominant rangeland stratum and mixed stratum were considered as land potential for agriculture. The remaining stratum is the non-agricultural land. Note that clusters covered by tea plantations were not considered in the area sample frame due to reasons stated above. Thus, SAS is conducted on 4 above mentioned strata to cover other major crops.
In 2021 agricultural year, the total sample used was 1200 segments. At first stage,1200 segments were selected and allocated at district level based on the power allocation approach (Bankier, 1988). Sampled segments inside each district were distributed among strata with a proportional-to-area criterion.
At second stage, 25 sample points were systematically selected, following a special distance of 60 meters between points. Sample points are reporting units within each segment, where enumerators go to every point, locate and delineate plots in which the sample points fall, and collect records of land use and related information. The recorded information represents the characteristics of the whole segment which are extrapolated to the stratum level and hence the combination of strata within each district provides district area related statistics.
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.
Start | End |
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2021 | 2021 |
During the SAS 2021 exercise, data collection covered three main agricultural seasons A, B and C and was conducted into two separate phases in each season: the first phase, known as screening activity (post-planting phase), consists of visiting all sampled segments and demarcating all plots with sampled points with the aim of covering the information related to land area, planted crops and land use. While the second phase involves capturing of production data by visiting sampled agricultural plots identified from screening activity as well as all large scale farmers
To ensure the smooth completion of the SAS workload, NISR employed 128 Enumerators, 29 Team Leaders and 3 Editors. All fieldwork staff hold a degree in agriculture sciences and were consistently trained by NISR headquarter staff before starting data collection in each season. Moreover, a higher-level supervision was organised and done by staff from NISR who frequently visited the field teams during each phase of data collection in order to ensure the quality of collected data.
It was conducted from September to August of the following year to gather up-to-date information for monitoring progress on agriculture programs and policies in Rwanda.
The SAS 2021 covered three agricultural seasons:
During the supervision of SAS 2021, NISR staff was deployed in different districts to keep a permanent supervision aspect and assistance to field staff, and see how they are conducting the data collection activities as well as monitoring if all techniques learnt in training are being put into practice in data collection
Specifically, the role of supervisors was:
· To assist and provide technical guidance to the field workers during screening exercise.
· To provide technical support to the fieldworkers so that any issues which have not been dealt with in training are resolved during data collection and guiding fieldworkers to respond to new challenges.
· Supporting Fieldworkers in their work plan of day-to day activities in order to respect the survey timeline.
· To review current crop production status by noting explanations on increase or decrease of production in visited districts.
Organization name | Affiliation | URL |
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National Institute of Statistics of Rwanda | Ministry of Finance and Economic Planning | https://statistics.gov.rw/ |
DDI_RWA_2021_SAS_v01_M
Name | Affiliation | Role |
---|---|---|
National Institute of Statistics of Rwanda | Ministry of Finance and Economic Planning | Producer of the survey |
Development Data Group | The World Bank | Metadata adapted for World Bank Microdata Library |
2023-08-02
Version 01 (August 2023): This metadata was downloaded from the Rwanda NISR catalog (https://microdata.statistics.gov.rw/index.php/catalog) and it is identical to Rwanda NISR version(RWA-NISR-SAS-2021-v0.1). The following two metadata fields were edited - Document ID and Survey ID.