Building the Evidence Base on the Agricultural and Financial Lives of Smallholder Households
The objectives of the Smallholder Household Survey in Cote d'Ivoire were to:
- Generate a clear picture of the smallholder sector at the national level, including household demographics, agricultural profile, and poverty status and market relationships;
- Segment smallholder households in Cote d'Ivoire according to the most compelling variables that emerge;
- Characterize the demand for financial services in each segment, focusing on customer needs, attitudes and perceptions related to both agricultural and financial services; and,
- Detail how the financial needs of each segment are currently met, with both informal and formal services, and where there may be promising opportunities to add value.
Kind of data
Sample survey data [ssd]
Unit of analysis
Households and individual household members
The universe for the survey consists of smallholder households defined as households with the following criteria: 1) Household with up to 5 hectares OR farmers who have less than 50 heads of cattle, 100 goats/sheep/pigs, or 1,000 chickens; AND 2) Agriculture provides a meaningful contribution to the household livelihood, income, or consumption.
Producers and sponsors
The World Bank (GFMGP - CGAP)
InterMedia Survey Institute
LSMS team, The World Bank
Institut National de la Statistique, Cote d’Ivoire
Technical assistance in sample design
IPSOS Cote d’Ivoire
Technical assistance in data collection and data processing
The smallholder household survey in Cote d’Ivoire is a nationally-representative survey, with a target sample size of 3,000 smallholder households. The sample was designed to provide reliable survey estimates at the national level.
In preparation for the 2014 population census, the country was divided into 22,600 census enumeration areas (EAs). For the ongoing 2015 agricultural census, the National Statistical Office (INS) has identified 18,321 EAs that contain agricultural households. The sampling frame for the smallholder survey is the list of these enumeration areas (EAs) containing agricultural households.
Sample allocation and selection
In order to take nonresponse into account, the target sample size was increased to 3,333 households assuming a nonresponse rate of 10%. The total sample size was first allocated to the zones based on their population counts using the power allocation method. Within each zone, the resulting sample was then distributed to urban and rural areas in proportion to their population.
Given that EAs were the primary sampling units and 15 households were selected in each EA, a total of 223 EAs were selected.
The sample for the smallholder survey is a stratified multistage sample. Stratification was achieved by separating each zone into urban and rural areas. The urban/rural classification is based on the 2014 population census. Therefore, 6 strata were created, and the sample was selected independently in each stratum.
In the first stage, EAs were selected as primary sampling units with probability proportional to size, the size being the population count in the EAs. A household listing operation was conducted in all selected EAs to identify smallholder households and to provide a frame for selecting smallholder households to be included in the sample. In the second stage, 15 smallholders were sampled in each EA with equal probability.
In each sampled household, the household questionnaire was administered to the head of the household, the spouse, or any knowledgeable adult household member to collect information about household characteristics. The multiple respondent questionnaire was administered to all adult members in each sampled household to collect information on their agricultural activities, financial behaviors, and mobile money use. In addition, in each sampled household only one household member was selected using the Kish grid and was administered the single respondent questionnaire.
The full description of the sample design can be found in the user guide for this data set.
Deviations from sample design
After the selection of the EAs and the printing of the EA maps, it was necessary to reduce the number of EAs to be listed to 212 for budgetary reasons. Therefore, 212 EAs were randomly selected among the previously 223 sampled EAs and were finally included in the survey sample.
The smallholder survey in Cote d’Ivoire is the fifth survey in the series, following the surveys in Mozambique, Uganda, Tanzania and Bangladesh. Fieldwork in the first countries experienced a lot of failed call backs where identified eligible households and household members could not be interviewed during the time allocated to fieldwork in each country. As a result, the final sample size fell slightly short of the target. For this reason, in Cote d’Ivoire the number of households selected in each EA was increased from 15 to 17 following the household listing operation in all sampled EAs.
The user guide to the data set provides detailed tables on household and household member response rates for the Cote d’Ivoire smallholder household survey. A total of 3,415 households were selected for the survey, of which 3,109 were found to be occupied during data collection. Of these, 3,019 were successfully interviewed, yielding a household response rate of 97.1 percent.
In the interviewed households, 6,659 eligible household members were identified for the Multiple Respondent questionnaire. Interviews were completed with 5,706 eligible household members, yielding a response rate of 85.7 percent for the Multiple Respondent questionnaire.
Among the 3,019 eligible household members selected for the Single Respondent questionnaire, 2,949 were successfully interviewed yielding a response rate of 97.7 percent.
The sample for the smallholder household survey is not self-weighting; therefore, sampling weights were calculated. The first component of the weights is the design weight based on the probability of selection for each stage. The second component uses the response rate at both household and individual levels.
The design weights for households were adjusted for nonresponse at the household level to produce adjusted household weights. Sampling weights for the multiple respondent data file were derived from adjusted household weights by applying to them nonresponse rates at the individual level. For the single respondent data file, the same process was applied after taking into account the subsampling done within the household.
Finally, household and individual sampling weights were normalized separately at the national level so the weighted number of cases equals the total sample size. The normalized sampling weights were attached to the different data files and used during analysis.
Dates of collection
Mode of data collection
Computer Assisted Personal Interview [capi]
Data collection supervision
Three staff members from InterMedia’s local field partner coordinated and supervised fieldwork activities along with the independent QC team hired by InterMedia to oversee the overall quality function of data collection. The QC team stayed with the survey teams during fieldwork to closely supervise and monitor them.
To capture the complexity of smallholder households, the smallholder household survey was divided into three questionnaires: 1) The Household questionnaire; 2) the Multiple Respondent questionnaire; and 3) the Single respondent questionnaire. It was designed in this way to capture the complete portrait of the smallholder household, as some members of the household may work on other agricultural activities independently and without the knowledge of others.
The household questionnaire collected information on the following:
• Basic household members’ individual characteristics (age, gender, education attainment, schooling status, relationship with the household head).
• Whether each household member contributes to the household income or participates in the household’s agricultural activities. This information was later used to identify all household members eligible for the other two questionnaires.
• Household assets and dwelling characteristics.
Both the Multiple and Single Respondent questionnaires collected different information on the following:
• Agricultural practices—farm information such as size, crop types, livestock, decision-making, farming association, and markets.
• Household economics—employment, income, expenses, shocks, borrowing and saving habits, and investments.
The Single respondent questionnaire also collected the following information:
• Mobile phones—attitudes toward phones, use, access, ownership, desire, and importance.
• Financial services—attitudes toward financial products and services such as banking and mobile money, including ownership, usage, access and importance.
The questionnaires were translated into French and then pretested. After the pretest, debriefing sessions were held with the pretest field staff and the questionnaires were modified based on the observations from the pretest. After the questionnaires were finalized, a script was developed to support data collection on mobile phones. The script was tested and validated before it was use in the field.
Ipsos Cote d’Ivoire
The data files were checked for completeness, inconsistencies and errors by InterMedia and corrections were made as necessary and where possible.
Following the finalization of questionnaires, a script was developed using Dooblo to support data collection on smart phones. The script was thoroughly tested and validated before its use in the field.
The sample design for the smallholder household survey was a complex sample design featuring clustering, stratification and unequal probabilities of selection. For key survey estimates, sampling errors taking into account the design features were produced using either the SPSS Complex Sample module or STATA based on the Taylor series approximation method.
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor.
Anderson, Jamie. 2017. National Survey and Segmentation of Smallholder Households in Cote d'Ivoire: Household Level Data. Washington, D.C.: CGAP. Ref: CIV_2016_SHS_v01_M. Downloaded from [url]
Disclaimer and copyrights
Rights and Permissions: This work is available under the Creative Commons Attribution 3.0 Unported license (CC BY 3.0) http://creativecommons .org/licenses/by/3.0. Attribution: Cite the data as follows: Anderson, Jamie. 2017. National Survey and Segmentation of Smallholder Households in Cote d'Ivoire: Household Level Data. Washington, D.C.: CGAP. License: Creative Commons Attribution CC BY 3.0 All queries on rights and licenses should be addressed to CGAP Publications, 1818 H Street, NW, MSN IS7-700, Washington, DC 20433 USA; e-mail: firstname.lastname@example.org.
CGAP (Consultative Group to Assist the Poor), 2017.