The Integrated Household Survey (IHS) is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office to monitor and evaluate the changing conditions of Malawian households. The Fourth Integrated Household Survey 2016-2017 (IHS4) which was implemented in the period of April 2016-April 2017 is the fourth of its kind. Previous rounds of the IHS program have been implemented every 6-7 years, but starting with the latest round of data collection, the upcoming IHS rounds will be fielded every 3 years as in line with the NSO vision of collecting poverty data on a more frequent basis.
The Integrated Household Survey is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO) roughly every 5 years to monitor and evaluate the changing conditions of Malawian households. The IHS data have, among other insights, provided benchmark poverty and vulnerability indicators to foster evidence-based policy formulation and monitor the progress of meeting the Millennium Development Goals (MDGs), the goals listed as part of the Malawi Growth and Development Strategy (MGDS) and now the Sustainable Development Goals (SDGs).
The IHS1 was conducted in Malawi from November 1997 through October 1998 and provided for a broad set of applications on policy issues regarding households' behaviour and welfare, distribution of income, employment, health and education. The Second Integrated Household Survey was implemented with technical assistance from the World Bank in order to compare the current situation with the situation in 1997-98, and to collect more detailed information in specific areas. The IHS2 fieldwork took placed from March 2004 through February 2005. The Third Integrated Household Survey (IHS3) expanded on the agricultural content of the IHS2 and was implemented from March 2010 to March 2011 under the umbrella of the World Bank Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) initiative, whose primary objective is to provide financial and technical support to governments in sub-Saharan Africa in the design and implementation of nationally-representative multi-topic panel household surveys with a strong focus on agriculture. The Fourth Integrated Household Survey 2016-2017 (IHS4) which was implemented in the period of April 2016-April 2017 covering 780 EAs throughout Malawi. As part of this project NSO also implemented the Integrated Household Panel Survey 2016 as a follow up to the IHPS 2013.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The 2016-2017 Fourth Integrated Household Survey covered the following topics:
- Household and Geographic Area Identification and Survey Information (data of interview, enumerator's and supervisors' codes, etc.)
- Household Roster
- Time Use and Labour
- Food Consumption (over past one week)
- Food Security
- Non-food Expenditures - over past one week and one month
- Non-food Expenditures - over past three months
- Non-food Expenditures - over past 12 months
- Durable Goods
- Farm Implements, Machinery, and Structures
- Household Enterprises
- Children Living Elsewhere
- Other Income
- Gifts Given Out
- Social Safety Nets
- Subjective Assessment of Well-being
- Shocks and Coping Strategies
- Child Anthropometry
- Deaths in Household
- Garden Roster (both for rainy season and dry (dimba) season)
- Plot Roster (both for rainy season and dry (dimba) season)
- Garden Details (both for rainy season and dry (dimba) season)
- Plot Details (both for rainy season and dry (dimba) season)
- Coupon Use (rainy season)
- Other Inputs (both for rainy season and dry (dimba) season)
- Crops (both for rainy season and dry (dimba) season)
- Seeds (both for rainy season and dry (dimba) season)
- Sales/ Storage (both for rainy season and dry (dimba) season)
- Tree/ Permanent Crop Production (last 12 months)
- Tree/ Permanent Crop Sales/ Storage (last 12 months)
- Livestock Products
- Access to Extension Services
- Network Roster
- Fisheries Calendar
- Fisheries Labour (last high season and last low season)
- Fisheries Inputs (last high season and last low season)
- Fisheries Output (last high season and last low season)
- Fish Trading (last high season and last low season)
- Roster of Informants
- Basic Information
- Economic Activities
- Community Needs, Actions and Achievements
- Communal Resource Management
- Communal Organization
Agriculture & Rural Development
Food (production, crisis)
Community Driven Development
Children & Youth
Members of the following households are not eligible for inclusion in the survey:
• All people who live outside the selected EAs, whether in urban or rural areas.
• All residents of dwellings other than private dwellings, such as prisons, hospitals and army barracks.
• Members of the Malawian armed forces who reside within a military base. (If such individuals reside in private dwellings off the base, however, they should be included among the households eligible for random selection for the survey.)
• Non-Malawian diplomats, diplomatic staff, and members of their households. (However, note that non-Malawian residents who are not diplomats or diplomatic staff and are resident in private dwellings are eligible for inclusion in the survey. The survey is not restricted to Malawian citizens alone.)
• Non-Malawian tourists and others on vacation in Malawi.
Producers and sponsors
National Statistical Office (NSO)
Ministry of Economic Planning and Development (MoEPD)
The World Bank
Government of Malawi
World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture project
WB LSMS-ISA project
Millennium Challenge Corporation
The IHS4 sampling frame is based on the listing information and cartography from the 2008 Malawi Population and Housing Census (PHC); includes the three major regions of Malawi, namely North, Center and South; and is stratified into rural and urban strata. The urban strata include the four major urban areas: Lilongwe City, Blantyre City, Mzuzu City, and the Municipality of Zomba. All other areas are considered as rural areas, and each of the 27 districts were considered as a separate sub-stratum as part of the main rural stratum. This is the first round of the survey to include the island district of Likoma in the sampling frame. The sampling frame further excludes the population living in institutions, such as hospitals, prisons and military barracks. Hence, the IHS4 strata are composed of 32 districts in Malawi.
A stratified two-stage sample design was used for the IHS4. Note: Detailed sample design information is presented in the "Fourth Integrated Household Survey 2016-2017, Basic Information Document" document.
Deviations from the Sample Design
The total sample size for the IHS4 was 12,480 households sampled from a total of 779 EAs5. At the end of the survey, a total of 12,447 households were interviewed. The survey allowed replacement of households. Of the 12,447 interviewed households, 557 were replacements (4.5 percent).
In order to analyse the data and produce accurate representativeness of the population, the sample variables must be weighted using the household sampling weights provided in each file as hh_wgt. As noted above, the IHS4 data are representative at the national, urban/rural, regional and district-level.
The basic weight for each sample household is equal to the inverse of its probability of selection (calculated by multiplying the probabilities at each sampling stage). As indicated in the previous section, the IHS3 sample EAs were selected within each district with PPS from the 2008 PHC frame. At the second stage, 16 sample households were selected with equal probability from the listing for each sample EA. Note: Detailed weighting information is presented in the "Fourth Integrated Household Survey 2016-2017, Basic Information Document" document.
Dates of Data Collection
Data Collection Mode
Computer Assisted Personal Interview [capi]
DATA ENTRY PLATFORM
To ensure data quality and timely availability of data, the IHS4 was implemented using the World Bank's Survey Solutions CAPI software. To carry out IHS4, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8-inch GPS-enabled Samsung Galaxy Tab S2 tablet computer. The use of Survey Solutions allowed for the real-time availability of data as the completed data was completed, approved by the Supervisor and synced to the Headquarters server as frequently as possible. While administering the first module of the questionnaire the enumerator(s) also used their tablets to record the GPS coordinates of the dwelling units. In Survey Solutions, Headquarters can then see the location of the dwellings plotted on a map of Malawi to better enable supervision from afar - checking both the number of interviews performed and the fact that the sample households lie within EA boundaries. Geo-referenced household locations from that tablet complemented the GPS measurements taken by the Garmin eTrex 30 handheld devices and these were linked with publically available geospatial databases to enable the inclusion of a number of geospatial variables - extensive measures of distance (i.e. distance to the nearest market), climatology, soil and terrain, and other environmental factors - in the analysis.
The IHS4 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHS4 Interviews were collected in “sample” mode (assignments generated from headquarters) as opposed to “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample.
The range and consistency checks built into the application was informed by the LSMS-ISA experience in IHS3 and IHPS. Prior programming of the data entry application allowed for a wide variety of range and consistency checks to be conducted and reported and potential issues investigated and corrected before closing the assigned enumeration area. Headquarters (NSO management) assigned work to supervisors based on their regions of coverage. Supervisors then made assignments to the enumerators linked to their Supervisor account. The work assignments and syncing of completed interviews took place through a Wi-Fi connection to the IHS4 server. Because the data was available in real time it was monitored closely throughout the entire data collection period and upon receipt of the data at headquarters, data was exported to STATA for other consistency checks, data cleaning, and analysis.
The data cleaning process was done in several stages over the course of field work and through preliminary analysis. The first stage of data cleaning was conducted in the field by the field based field teams utilizing errors generated with the Survey Solutions application. For questions that flagged an error, enumerators were expected to record a comment within the questionnaire to explain to their Supervisor the reason for the error and confirming that they double checked the response with the respondent. Supervisors were expected to sync the enumerator tablets as frequently as possible to avoid having many questionnaires on the tablet, and to enable daily checks of questionnaires. Some Supervisors preferred to review completed interviews on the tablets so they would review prior to syncing but still record the notes in the Supervisor account and reject questionnaires accordingly. The second stage of data cleaning was also done in the field and this resulted from the additional error reports generated in STATA and sent to teams via email. Field supervisors collected reports for their assignments and in coordination with the enumerators reviewed, investigated, and collected errors. Due to the quick turn-around in error reporting, it was possible to conduct call backs while the team was still operating in the enumeration area when required. Corrections to the data were entered in the rejected questionnaires and sent back to headquarters.
Additional cleaning was performed after interviews were “Approved” where appropriate to resolve systematic errors and organize data modules for consistency and efficient use. Case by case cleaning was also performed during the preliminary analysis specifically pertaining to out of range and outlier variables. All cleaning activities were conducted in collaboration with the WB staff providing technical assistance to the NSO in the design and implementation of the IHS4.
National Statistical Office
Ministry of Economic Planning and Development (MoEPD)
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