Last update: August 15, 2024
This page contains information about some of the data available in the FEWS NET Data Explorer (FDE) for Burkina Faso. This is not a comprehensive guide.
For information about using the filters and fields for specific domains in the FDE, see Choose a Data Domain.
Summary table
ISO 3166-1 codes | Alpha 2: BF, Alpha 3: BFA, Numeric: 854 |
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Administrative units | Regions, provinces, communes |
Agricultural seasons | Rainy (starts as early as April) and dry seasons |
Major crops | Maize, millet, sorghum |
Country food security context
Statistical reporting units
Burkina Faso usually uses administrative units as their statistical reporting units.
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Administrative (admin) units are the geographical areas into which a country is divided. FEWS NET uses the following terminology: National boundary = admin 0, First sub-national division = admin 1 (e.g., states in the United States), Second sub-national division = admin 2 (e.g., counties in the United States), and so on. |
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Since 2001, there have been only small local issue-related changes in the boundaries of a few of the 45 provinces. In 2020, FEWS NET added Admin 3 boundaries (communes), though they were present in the country before then.
Crop data
Explore our crop data.
View our documentation on using the Crop Domain.
Crop estimate data sources
A key source of Burkina Faso crop data is the Conseil national de la statistique (CNS), source of most of the crop data found in the FEWS NET Data Warehouse. See also the l’Institut national de la statistique et de la démographie (INSD) website for other agricultural data and information. Regional statistical yearbooks available from the CNS provide additional important crop information and data at regional and provincial levels.
Crop reporting units
The boundaries used for crop reporting nominally align with the Admin 2 level provinces.
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Plaine/Bas-fond irrigated (PS): In Burkina Faso there has been extensive development of “plaines” (irrigated fields with bunding) and “bas-fonds amenagés” (irrigated bas-fonds, or low-lying areas that may fill during the rains, and which are irrigated using that rainwater, or other drawn from a near-by source, and not necessarily just rain-fed). Cooperative Cooperative groupings manage some of these areas, and others may be small-scale commercial in nature. Some of these may be growing vegetables and other crops outside of the rainy season, although not reported as such.
Bas-fonds rainfed (PS): Another more common bas-fonds farming system is only fed by rainfall and is not irrigated or managed (amenagé) in the same way.
Rainfed (PS): This category covers everything else grown in fields, often dispersed and planted with multiple crops, during the rainy season without irrigation and with few resources.
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Crop estimation methodology
The following description of the crop estimation methodology employed in Burkina Faso was extracted from a report entitled “Resultats Définitifs de la Campagne Agricole 2014/2015 et Perspectives de la Situation Alimentaire et Nutritionnelle” (page 60), published by the General Secretariat, Direction Générale des Etudes et des Statistiques Sectorielles (DGESS). Given its age, it may not exactly represent current practice, but rather a view of how earlier estimations were undertaken.
Crop area definitions
Area planted (Superficie superficie de la parcelle): This is the physical area of the planted crops, with no reference to the proportions of each crop planted. Superfice
Monoculture (superfice en pure (monoculture): This is the physical area of the planted crop when there is only one crop. Superficie en principale (area
Area of a dominant crop (superficie en principale): This is the physical area of one crop which that constitutes the majority of the crops planted (2 or more). Superficie en secondaire (area
Area of a secondary crop (superficie en secondaire): This is the physical area of one specific crop which that does not constitute the majority of the crops planted (2 or more).
Survey objectives
The first objective is to assess the areas, yields, and production of important crops in the rainy season. This assessment is done in two stages: - August/September for initial seasonal forecasts, and - at the end of the harvests for the final results.
The specific objective of the survey is to produce objective cereal harvest forecasts early in the year (September), in order to inform the government and its development partners of the country’s food supply. These forecasts help to establish a provisional national cereal balance sheet, estimate on-farm stocks for own consumption, and assess results by province and for each crop. Additionally, the survey collects information on credit, the use of inputs, marketing intentions, agricultural employment opportunities, farming income, livestock attached to agricultural households, the demography of agricultural households, etc.
The sample survey data are supplemented by data from administrative sources relating to harvests on developed plains and in lowland areas, particularly for rice and corn crops which are grown in both the rainy season and dry season (by irrigation) in these production systems.
Survey design
Sample frame (Base base de sondage): The “Village” sample of the Population and Housing Census-2006 (7,871 villages and sectors), with 1,219,241 agricultural households.
Type of survey (Type type de sondage: ): Two-stage survey with stratification at the first stage (village) and at the second stage (agricultural household). The stratification at the second stage is induced by that of the first stage.
Sample selection (Tirage tirage de l’échantillon): - First stage: The primary units (PU) are the administrative villages. They are selected according to the unequal probability drawing method and without replacement. The probability of a PU appearing is proportional to its size in number of households. - Second stage: The secondary units are the agricultural households. They are selected by simple random drawing and without replacement. Each household of the same primary unit has the same probability of appearing in the sample.
The sample (Échantillonéchantillon): 887 villages and 5,322 households distributed by stratum. The number of sample households per stratum was determined according to the available budget and desired reliability, using Neymann’s optimal allocation method. The panel from the last General Agricultural Census (RGA 2006-2008) was renewed to take into account the aging and sample fatigue of households comprising it.
Description
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The survey used the following questionnaires: -
Book 1:Census of members, census of plots, census of abandoned plots and use of inputs, household livestock
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Book 2: Measurement of areas, selecting and weighing of yield squares
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Book 3:Evaluation of areas for August forecasts
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Book 4: Estimation of cereal stocks and harvest forecasts and estimation of production of abandoned plots
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Book 5: Use of household agro-sylvo-pastoral production
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Book 6: Food security (
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two rounds: in September and December)
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Book 8: Household equipment and acquisition of inputs.
Pilot survey procedure (Déroulement enquête pilote)
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Training of field staff
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At the beginning of the agricultural campaign, two 2 training sessions are organized for all staff involved in the data collection system:
At the central level: Training of trainers (ministry executives, central directorates involved and regional supervisors).
At the regional level: Training of investigators and controllers in each of the 13 regions. The training is provided jointly by a central team and regional supervisors. During this session, 154 controllers and 796 investigators are trained
Data collection (Collecte)
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Data collection is carried out from June to December. Two types of collection are used: mobile collection using tablets (CAPI) in ten 10 regions and paper collection using paper questionnaires (PAPI) in three 3 regions: East, Boucle du Mouhoun and Sahel.
For PAPI collection, the Ministry is responsible for designing data entry programs, training agents and data entry controllers. The control of the data entry of each region's files is ensured by the regional supervisor, supported by the central team. Ministry technical experts edit the inconsistencies noted in the files. Each regional supervisor of the regions with paper collection, supported by the central team, is responsible for checking and possibly correcting inconsistencies on in the files already entered.
For CAPI collection, data is downloaded directly from the server and subjected to prescribed cleaning procedures in order to identify inconsistencies. The correction of inconsistencies noted at this level is done by consulting the various supervision reports and/or by directly contacting the field system for verification with households.
Calculation of aggregates (Calcul des agrégats)
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The weighting parameters are calculated in order to allow extrapolation of data at the provincial, regional, and national levels.
Editing of results (Edition des résultats)
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By applying the weightings to the collected data, the preliminary tables are edited. They are submitted for plausibility review to each region, supported by the central team. The correction of improbabilities allows the editing of the final tables which are then validated at several levels.
Internal technical validation (Validation technique interne)
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During the internal validation working sessions, the results are presented by the processing team. At this stage, discussions always focus on the plausibility, and the results of the work are shared during the session with the central departments of the ministry.
Official validation (Validation officielle)
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The internally validated production data are used with other types of data to develop food security aggregates (cereal and food balance sheets, provincial cereal needs coverage rate, provincial caloric proxies) and food security indicators at the micro level (level of household cereal autonomy, household cereal insecurity, etc.). All of these results are presented to the Food Situation Forecasting Committee (CPSA), which officially validates them before introducing them to the Council of Ministers for adoption.This description of the crop estimation methodology employed in Burkina was extracted from a report entitled “Resultats Définitifs de la Campagne Agricole 2014/2015 et Perspectives de la Situation Alimentaire et Nutritionnelle” (page 60), published by Secretary General, Direction Générale des Etudes et des Statistiques Sectorielles. Given its age, it may not exactly represent current practice, but rather a view of how earlier estimations were undertaken.