The Integrated Household Survey (IHS) is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO; http://www.nsomalawi.mw/) 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), Sustainable Development Goals (SDGs) as well as the goals listed as part of the Malawi Growth and Development Strategy (MGDS). Previous rounds of the IHS program have been implemented every 6-7 years, but starting with the IHS4 2016/17 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 First Integrated Household Survey (IHS1) was implemented with technical assistance from the International Food Policy Research Institute (IFPRI) and the World Bank (WB). 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’ behavior and welfare, distribution of income, employment, health and education.
The Second Integrated Household Survey (IHS2; http://go.worldbank.org/JABABM36V0) 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. A sub-sample of IHS3 sample enumeration areas (EAs) (i.e. 204 EAs out of 768 EAs) was selected prior to the start of the IHS3 field work with the intention to (i) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection (ii) track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey 2013 (IHPS). The LSMS-ISA initiative also provided technical and financial assistance to the design and implementation of the IHPS, alongside DFID, Norway and Government of Malawi funding for the exercise. The IHPS 2013 main fieldwork took place during the period of April-October 2013, with residual tracking operations in November-December 2013.
The Fourth Integrated Household Survey 2016/17 (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. This panel subsample covered 102 of the 204 baseline IHS3 panel EAs and was conducted during the first half of IHS4 fieldwork. Throughout the design and implementation of the IHS4, the NSO received technical assistance as part LSMS-ISA. The financial support to the IHS4 was provided by Government of Malawi (GoM), WB LSMS-ISA project, and Millennium Challenge Corporation (MCC).
The Fifth Integrated Household Survey (IHS5) was implemented between April 2019 and April 2020 and followed the same set up as the IHS4, running concurrently with the Integrated Household Panel Survey 2019.
The Integrated Household Survey is one of the primary instruments implemented by the Government of Malawi through the National Statistical Office (NSO) roughly every 3-5 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).
Version 02: Edited, anonymized dataset for public distribution.
The following three modules has been updated; AG_MOD_J.dta, AG_MOD_K.dta and AG_MOD_M.dta.
The 2019-2020 Fifth 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 Labor
- 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 Labor (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
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
The IHS5 sampling frame is based on the listing information and cartography from the 2018 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. The sampling frame further excludes the population living in institutions, such as hospitals, prisons and military barracks. Hence, the IHS5 strata are composed of 32 districts in Malawi.
A stratified two-stage sample design was used for the IHS5.
Note: Detailed sample design information is presented in the "Fifth Integrated Household Survey 2019-2020, Basic Information Document" document.
12, 288 households from 768 Enumeration Areas were selected. Due to COVID-19, 51 Enumeration Areas were unable to be visited at the end of the 12-month fieldwork period. Due to this, the final response rate was 93 percent.
In order to analyze 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 noted above, the IHS5 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 IHS5 sample EAs were selected within each district with PPS from the 2018 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 "Fifth Integrated Household Survey 2019-2020, Basic Information Document" document.
Dates of Data Collection
Data Collection Mode
Computer Assisted Personal Interview [capi]
IHS5 field based supervisors were responsible for managing the daily operations of their respective field based mobile team. Primary responsibilities included: (1) liaising with IHS5 management on schedules, field operation status, equipment status and needs, and special issues, (2) planning daily field operation schedules including coverage and transportation, (3) liaising with local authorities before commencing interview activities, (3) making Survey Solutions questionnaire assignments on CAPI and syncing completed interviews with their Supervisor account (4) reviewing incoming questionnaires for completion and accuracy, (5) syncing reviewed questionnaires with the Headquarters account, (6) reviewing error reports from Headquarters generated through Stata checking system and assigning questionnaire reviews, and authorizing review/call back based on these reports, (7) administering community questionnaires within each enumeration area.
Data Collection Notes
Field staff for the IHS5 was selected after advertisements were placed in the national newspapers advertising posts for enumerators. Interviews were conducted to determine the most qualified candidates. Training instruction was given to the field staff by the IHS5 Management Team with help from World Bank LSMS-ISA team members. The training consisted of classroom instruction on the contents of the questionnaire, concepts and definitions, interview techniques and methods, and field practices in performing actual interviews to ensure that Enumerators fully understood the questionnaire. Training instructions are detailed in the Enumerator and Field Supervisor’s Manuals. At the end of the training session, trainees were assessed based on tests given during the training process and evaluations by the supervisory personnel. The best candidates were selected to be Field Supervisors, and 64 candidates were selected to be Field Enumerators.
Pre-enumeration listings were initiated before the start of each half of field work. Mobile listing teams equipped with printed maps of select EAs were used to record all dwellings and heads of households in selected cross-sectional EAs. Household counts per each listed enumeration areas were relayed to NSO IHS5 Management and recorded. Where applicable, listing forms and maps were transferred directly to field teams after the completion of district listing activities. Field Teams Fieldwork for the IHS5 began in April 2019 and was administered simultaneously throughout the country until April 2020. 18 field-based mobile teams consisting of 1 supervisor, 4 enumerators and 1 driver were assigned to cover specific districts. Each team supervisor received monthly enumeration assignment schedules on a quarterly basis throughout the field work. Monthly enumeration assignments were further accompanied by (1) enumeration area maps, (2) completed listing forms, (3) the list of selected as well as replacement households to be interviewed in each EA (4) the Survey Solutions assignments for the selected EA from headquarters.
Field based mobile teams consisted of 4 enumerators to field household interviews over the course of the scheduled field work. An Enumerator’s major areas of responsibility were to accurately and completely administer the household, agriculture, and fishery questionnaires. Enumerators were responsible for: (1) locating assigned households, (2) relaying the source and purpose of the survey and obtaining respondent permission to implement the interview, (3) implementing all pertinent questionnaire modules, (4) systematically obtaining anthropometric measures for qualified household members, (5) using GPS technology to mark and record household locations and take agricultural field measurements, and (6) participating in the review and correction of questionnaires.
National Statistical Office
Ministry of Economic Planning and Development (MoEPD)
The Household Questionnaire is a multi-topic survey instrument and is near-identical to the content and organization of the IHS3 and IHS4 questionnaires. It encompasses economic activities, demographics, welfare and other sectoral information of households. It covers a wide range of topics, dealing with the dynamics of poverty (consumption, cash and non-cash income, savings, assets, food security, health and education, vulnerability and social protection). Although the IHS5 household questionnaire covers a wide variety of topics in detail it intentionally excludes in-depth information on topics covered in other surveys that are part of the NSO’s statistical plan (such as maternal and child health issues covered at length in the Malawi Demographic and Health Survey).
All IHS5 households that are identified as being involved in agricultural or livestock activities were administered the agriculture questionnaire, which is primarily modelled after the IHS3 counterpart. The modules are expanding on the agricultural content of the IHS4, IHS3, IHS2, AISS, and other regional agricultural surveys, while remaining consistent with the NACAL topical coverage and methodology. The development of the agriculture questionnaire was done with input from the aforementioned stakeholders who provided input on the household questionnaire as well as outside researchers involved in research and policy discussions pertaining to the Malawian agriculture. The agriculture questionnaire allows, among other things, for extensive agricultural productivity analysis through the diligent estimation of land areas, both owned and cultivated, labor and non-labor input use and expenditures, and production figures for main crops, and livestock. Although one of the major foci of the agriculture data collection effort was to produce smallholder production estimates for major crops, it is also possible to disaggregate the data by gender and main geographical regions. The IHS5 cross-sectional households supply information on the last completed rainy season (2017/2018 or 2018/2019) and the last completed dry season (2018 or 2019) depending on the timing of their interview.
The design of the IHS5 fishery questionnaire is identical to the questionnaire designed for IHS3. The IHS3 fisheries questionnaire was informed by the design and piloting of a fishery questionnaire by the World Fish Center (WFC), which was supported by the LSMS-ISA project for the purpose of assembling a fishery questionnaire that could be integrated into multi-topic household-surveys. The WFC piloted the draft instrument in November 2009 in the Lower Shire region, and the NSO team considered the revised draft in designing the IHS5 fishery questionnaire.
The content of the IHS5 Community Questionnaire follows the content of the IHS3 & IHS4 Community Questionnaires. A “community” is defined as the village or urban location surrounding the enumeration area selected for inclusion in the sample and which most residents recognize as being their community. The IHS5 community questionnaire was administered to each community associated with the cross-sectional EAs interviewed. Identical to the IHS3 and IHS4 approach, to a group of several knowledgeable residents such as the village headman, the headmaster of the local school, the agricultural field assistant, religious leaders, local merchants, health workers and long-term knowledgeable residents. The instrument gathers information on a range of community characteristics, including religious and ethnic background, physical infrastructure, access to public services, economic activities, communal resource management, organization and governance, investment projects, and local retail price information for essential goods and services.
DATA ENTRY PLATFORM
To ensure data quality and timely availability of data, the IHS5 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHS5, 1 laptop computer and a wireless internet router were assigned to each team supervisor, and each enumerator had an 8–inch GPS-enabled Lenovo 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 range and consistency checks built into the application was informed by the LSMS-ISA experience in previous IHS waves. 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 IHS5 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 IHS5 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHS5 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 previous IHS waves. 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 IHS5.
National Statistical Office
Ministry of Economic Planning and Development (MoEPD)
LSMS Data Manager
The World Bank
In receiving these data it is recognized that the data are supplied for use within my organization, and I agree to the following stipulations as conditions for the use of the data:
1. The data are supplied solely for the use described in this form and will not be made available to other organizations or individuals. Other organizations or individuals may request the data directly.
2. Three copies of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to:
The World Bank
Development Economics Data Group
LSMS Database Administrator
1818 H Street, NW
Washington, DC 20433, USA
tel: (202) 473-9041
fax: (202) 522-1153
3. The researcher will refer to the Malawi 2019-2020 IHS5 Survey as the source of the information in all publications, conference papers, and manuscripts. At the same time, the World Bank is not responsible for the estimations reported by the analyst(s).
4. Users will not use the location information to reveal the identity of survey respondents.
5. Users will not publish results (map or other form) that would allow communities or individuals to be identified.
6. Users who download the data may not pass the data to third parties.
7. The database cannot be used for commercial ends, nor can it be sold.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download.
Disclaimer and copyrights
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.