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    Home / Food and Agriculture Microdata Catalogue / AGRICULTURAL-SURVEYS / SEN_2019_BRACED_V01_EN_M_V01_A_OCS
agricultural-surveys

Building Resilience and Adaptation to Climate Extremes and Disasters 2019

Senegal, 2019
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Reference ID
SEN_2019_BRACED_v01_EN_M_v01_A_OCS
Producer(s)
Initiative Prospective Agricole et Rurale (IPAR)
Collections
Agricultural Surveys
Metadata
Documentation in PDF DDI/XML JSON
Created on
Aug 09, 2021
Last modified
Aug 09, 2021
Page views
3128
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  • Study Description
  • Data Dictionary
  • Downloads
  • Get Microdata
  • Identification
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Survey instrument
  • Data collection
  • Data appraisal
  • Data Access
  • Disclaimer and copyrights
  • Metadata production
  • Identification

    Survey ID number

    SEN_2019_BRACED_v01_EN_M_v01_A_OCS

    Title

    Building Resilience and Adaptation to Climate Extremes and Disasters 2019

    Country
    Name Country code
    Senegal SEN
    Study type

    Agricultural Survey [ag/oth]

    Abstract

    This study is part of the policy dialogue on the issue of index-based livestock insurance for pastoral and agro-pastoral livestock in Senegal. Its objective was to provide a representative assessment of livestock farmers' perceptions of insurance in general and of potential index-based livestock insurance in particular.

    To this end, different potential insurance offers were proposed to herders to enable them to decide on the amounts they are willing to invest in them. The contingent valuation method was used for this purpose. The results showed that the risk of rainfall deficits (delayed rains and insufficient rains in general) is the main risk that farmers feel they face. This is also the risk they would like to have index insurance for. Knowing that this type of risk is insured by CNAAS in the framework of index insurance for farmers and that for nearly seven years indexes have been designed in the framework of the development of these types of products, this provides an interesting opportunity for pastoral livestock. Indeed, all the knowledge gained from the development of index-based crop insurance products could also be mobilised to develop an index-based livestock insurance product by making economies of scale. In addition, in our study, we used as an example of an index insurance product during the explanations provided to farmers, a product whose index is linked to the level of development of the grass cover and which would reimburse in the event of a rainfall deficit without being based on the verification of damage to the herds, but on the rainfall. Most farmers preferred such index insurance to conventional insurance, which would require verification per head of livestock.

    Finally, although theft of livestock was identified as an important risk, and often ranked second only to the risk of rainfall deficits, for the time being there is no consensus between CNAAS and the farmers on the possibility of covering it through a specific insurance product. Even if they need to be complemented with other qualitative studies, our results support the position of those stakeholders who believe that index-based livestock insurance is feasible and relevant for pastoral and agro-pastoral livestock. However, challenges remain and answers are still needed on major issues. Among these challenges, the question of how to design the indices in such a way as to embrace the mobility of livestock in the products that will be offered remains the most important.

    Kind of Data

    Sample survey data [ssd]

    Unit of Analysis

    Households

    Scope

    Notes

    The scope covers the following topics:

    • living conditions and assets owned by households
    • the demographic characteristics of the household
    • risks and coping strategies
    • investment and income from livestock
    • livestock numbers
    • income
    • knowledge and familiarity with insurance
    • perception of the usefulness of insurance
    • willingness to pay for index insurance.

    Coverage

    Geographic Coverage

    National coverage.

    The counties that were selected given the time and budget constraints of the study are:

    • Dagana and Podor in the Saint-Louis region,
    • Ranérou in the Matam region,
    • Linguère in the Louga region, and
    • Koumpentoum in the Tambacounda region.

    The survey is representative of the six zones identified as being the predominantly pastoral agro-pastoral zone, the predominantly agricultural agro-pastoral zone, the livestock fattening and trading zone, and the transit zone.

    Universe

    The survey covers livestock keepers identified within households and resource persons who are either representatives of livestock keepers' organisations, staff of technical livestock services, staff of projects and programmes working in the pastoral field, or large-scale livestock keepers in the target areas.

    Producers and sponsors

    Primary investigators
    Name
    Initiative Prospective Agricole et Rurale (IPAR)
    Funding Agency/Sponsor
    Name
    BRAIST

    Sampling

    Sampling Procedure

    All the pastoralist communes identified in the 5 counties are divided into 6 strata. Each stratum comprises a group of communes. The strata are defined according to the type of livestock farming (pastoral zone, predominantly pastoral agro-pastoral zone, predominantly agricultural agro-pastoral zone, fattening and livestock trade zone, transit zone). Thus, we chose a three-stage random sample in each of these six (6) defined strata.

    • First stage
      In the first stage, a sample of 15 communes corresponding to the primary units is drawn at random and distributed proportionally to the number of communes in each stratum.

    • Second stage
      In the second stage, a sample of 60 villages is drawn at random, with 4 villages in each commune. Let mih be a sample of villages drawn in commune i of stratum h (mih = 4 in the case of our study) is the probability of inclusion of the master villages. It should also be noted that if a selected village has fewer than 5 households, is difficult to access or is not found by the interviewers, then it had to be replaced. Thus, replacement villages were drawn and sequenced since they had to be selected progressively in case a village had to be replaced in a commune.

    • Third stage
      In the third stage, the list of households in each village drawn allows the agents to select a systematic sample of households. This consists of drawing 5 households in each sample village. Before proceeding with the draw, a list of households in the village is necessary to allow a random selection of sample households. The selected heads of households are then interviewed for the survey.

    Deviations from the Sample Design

    0%

    Response Rate

    100%

    Weighting

    Not available.

    Survey instrument

    Questionnaires

    Questionnaire Livestock index insurance in Senegal: perception and willingness to pay of livestock farmers.

    The information collected concerned the socio-demographic characteristics, agricultural and socio-economic activities of livestock farmers.

    Data collection

    Dates of Data Collection
    Start End
    2019-08-01 2019-08-12
    Data Collection Notes

    Our data collection was carried out by first recruiting and training the interviewers, and then mobilising them in the field for a period of 6 days. We then carried out a remote control based on the data collected daily and the GPS coordinates collected automatically.

    Training and deployment of interviewers

    Firstly, for the recruitment of interviewers, we identified a group of 12 interviewers with the following characteristics:

    • Each of them had at least 7 years of survey experience;
    • Each spoke the most common Fulani dialect in the area correctly;
    • Each was almost 100% ethnic Fulani, so they were able to establish a relationship of trust with the respondent;
    • Each had already carried out at least one survey in a pastoral environment, during which questions on the size of the herd were asked.

    After recruiting the interviewers, we trained them over a two-day period. During these two days, we shared with them the objective of the study, the principle of index-based agricultural insurance, its methodology in terms of contingent valuation of willingness to pay and the identification of the person to be surveyed in the household after having identified the household to be surveyed. The questionnaire was converted into a data collection application or electronic questionnaire. This application was tested on the last day of training through simulated survey exercises that also allowed for the oral translation of all questions into Fulani. This exercise enabled the understanding of the questions to be harmonised between the interviewers to reduce the risk of discrepancies in the explanations given to the farmers.

    The stages of the training were as follows:

    • Detailed explanation of the methodological aspects;
    • Presentation of the objectives of the survey;
    • Silent reading of the paper questionnaire "Survey Yourself": in this exercise the agents, while reading the questionnaire, play the role of both the interviewer and the respondent. This pedagogical exercise allows the interviewers to ask themselves different questions even before reading the questionnaire in plenary;
    • Reading the questionnaire, question by question;
    • Training of interviewers on smartphones and the collection application;
    • Translation of the questionnaire into the local language (Pulaar);
    • Paired survey: during this exercise, the interviewers will be paired up; one agent plays the role of the interviewer and the other plays the role of the respondent. Then the roles are reversed.

    Coordination of surveys and data control

    After the training, the teams were divided into groups of four people. In each team, there were three interviewers and a supervisor responsible for coordinating the team's actions and reporting regularly on the field situation to the study coordinator and statistician who are based in Dakar. As 15 communes were chosen for the surveys, they were divided into three, with five communes to be surveyed per team. To give each team freedom of movement, a vehicle with a driver was provided for each team. Mission orders and letters of introduction to be presented to the local authorities were also made available to them to facilitate their first contact with the local population and to have elements of proof of their good faith.
    The team supervisor was responsible for reporting to the statistician in charge of the survey and the survey coordinator any difficulties or issues identified in the execution of the survey by their team. The team's statistician ensured that the data were reported daily and, on the basis of this, debriefed the supervisors on the quality of the data collected. The data collected through the tablets was uploaded via the Internet to a web platform set up for this purpose. The technology we used for mobile data collection is called ODK Collect. It is a suite of tools that allows data to be collected using mobile devices such as smartphones and/or tablets (running Android) and to submit the same data to an online server.

    Data appraisal

    Data Appraisal

    Checks on the application allowed the identification of implausible information.

    The control of the data was done at several levels:

    • firstly, at the level of the collection application, a number of checks were integrated on the limit of the range of quantitative variables, on the filters, etc.
    • then, before sending the data, the supervisors went through all the questionnaires with the interviewers to ensure the quality of the responses (completeness, consistency)
    • Finally, quality control also consisted of structural and consistency checks and then the reconciliation and correction of the data files using STATA. It should also be noted that the GPS coordinates made it possible to verify that the villages and communes chosen were really those covered in the field.

    Data Access

    Confidentiality
    Is signing of a confidentiality declaration required? Confidentiality declaration text
    yes See http://anads.ansd.sn/index.php/catalog
    Access conditions

    Microdata are only accessible to services and organizations under the national statistical system, NGOs, UN agencies and other organizations with the following reservations:

    • Any use of data produced or managed by IPAR must be subject to '' a request for authorization addressed to IPAR. It will clearly mention the use that will be made of the data and a copy in French or English of the study project will be attached to the request.

    • The requesting service or organization must undertake to respect the following conditions:

    1. The user must comply with the provisions of Articles 6 and 7, Chapter 2, Section 2 of Senegalese Law No. 2004.21 on the organization of statistical activities, which requires any person handling individual data, collected by the services and organizations under the authority of the national statistical system, to guarantee the anonymity of the natural or legal persons concerned by the survey, and to use this data only for the purpose of disseminating or publishing aggregated statistical results.

    2. The user is entirely responsible for his conclusions or studies drawn from these data and in this, the responsibility of IPAR can not be engaged in any way whatsoever.

    3. The data must not be copied or transmitted to other persons or organizations, directly or indirectly, without the prior written consent of IPAR.

    4. Any publication drafted using data from IPAR must include the following statement "Source: Survey - X , Year N , Initiative Prospective Agricole et Rurale (IPAR), www.ipar.sn"

    Disclaimer and copyrights

    Disclaimer

    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

    Metadata production

    DDI Document ID

    DDI_SEN_2019_BRACED_v01_EN_M_v01_A_OCS_FAO

    Producers
    Name Affiliation Role
    National Agency for Statistics and Demography Ministry of Economy, Planning and Cooperation Metadata producer
    Office of Chief Statistician Food and Agriculture Organization Metadata adapted for FAM

    Metadata version

    DDI Document version

    SEN_2019_BRACED_v01_EN_M_v01_A_OCS

    Back to Catalog
    Food and Agriculture Organization of the United Nations

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