{"doc_desc":{"idno":"DDI_MWI_2024_IHPS-V_v01_M","producers":[{"name":"Development Data Group","abbr":"DECDG","affiliation":"World Bank Group","role":"Documentation of the survey"}],"version_statement":{"version":"Version 01 (July 2026)"}},"study_desc":{"title_statement":{"idno":"MWI_2024_IHPS-V_v01_M","title":"Integrated Household Panel Survey 2024 (Long-Term Panel and Sample Refresh, 51 EAs each)","alternate_title":"IHPS-V 2024"},"authoring_entity":[{"name":"National Statistical Office (NSO)","affiliation":"Ministry of Economic Planning and Development (MoEPD)"}],"production_statement":{"producers":[{"name":"The World Bank Living Standards Measurement Study","abbr":"LSMS","affiliation":"","role":"Technical assistance"}],"funding_agencies":[{"name":"World Bank Regional Statistical Capacity Building Project","abbr":"WB-Stat Cap","role":"Financial support"}]},"distribution_statement":{"contact":[{"name":"National Statistical Office","affiliation":"Ministry of Economic Planning and Development (MoEPD)","email":"commissioner@nso.gov.mw","uri":"https:\/\/www.nsomalawi.mw\/"}]},"series_statement":{"series_name":"Living Standards Measurement Study [hh\/lsms]","series_info":"The Integrated Household Panel Survey (IHPS) is a longitudinal survey embedded within the core Integrated Household Survey (IHS) program, designed to track trends in poverty, socioeconomic, and agricultural characteristics over time. The survey has been conducted five times: 2010, 2013, 2016, 2019, and 2024.\n\nThe 2010 baseline sample was drawn from the IHS3 cross-sectional sample to be representative at the national, regional, and urban\/rural levels across six strata: Northern, Central, and Southern regions, each split into rural and urban.\n\nIn 2013, the survey tracked all baseline households and individuals who had moved from their original dwellings, provided they were not servants or guests at baseline, were projected to be at least 12 years old, and resided in mainland Malawi (excluding Likoma Island and institutional settings). Split-off individuals' new households were also added to the sample, bringing the total to 4,000 households traceable to 3,104 baseline households.\n\nFrom 2016, due to budget constraints and the growing number of households to track, the sample was scaled back to households associated with 102 of the original 204 baseline enumeration areas (EAs). While regional-level tabulation is no longer possible from 2016 onwards, proportional allocation across regions was maintained. Accordingly, the domains of analysis from 2016 are limited to national, urban, and rural levels.\n\nThe 2024 round introduced an additional structural change: a partial refresh of the sample. Half of the 102 EAs, along with all associated households, were retired and replaced with freshly selected EAs and households. This was motivated by three considerations: reducing respondent burden for households that had participated across a decade; restoring cross-sectional representativeness, which tends to erode in ageing longitudinal samples as the underlying population changes over time; and controlling the expansion of the panel sample driven by individual-following rules. The remaining 51 EAs continued to be tracked as in previous rounds, with the 2024 round following all individuals from the 2019 households in those EAs.\n\nThroughout the design and implementation of the IHS6 and the IHPS, the NSO received technical assistance from the World Bank Living Standards Measurement Study (LSMS) team. Financial support for the IHPS was provided by Government of Malawi and the World Bank Statistical Capacity Building Project."},"version_statement":{"version_date":"2026-07-19","version_notes":"This is version 1 of the dataset and associated technical documents."},"study_info":{"abstract":"The fifth round of the Integrated Household Panel Survey (IHPS5) was launched in July 2024 as part of the Malawi Sixth Integrated Household Survey (IHS6) fieldwork operations. Its main objective is to provide updated and comparable information on household welfare and socioeconomic conditions, while preserving the longitudinal structure needed to analyse change across time.\n\nThe 2024 round comprised two sample components. The retained sample targeted 1,515 households interviewed in 2019, encompassing 7,099 individuals. Following the completion of tracking operations, the panel sample expanded to 1,948 households, reflecting household splits and relocations. The 1,515 tracking targets originate from 1,338 of the 2019 households, implying a household-level attrition rate of 11.6 percent. The refreshed sample component contributed an additional 815 households and 3,575 individuals, drawn from newly selected enumeration areas introduced in the 2024 round. These refreshed households will be incorporated into the panel component of the next IHS round.\n\nTogether, the retained and refreshed components support both longitudinal analysis of welfare dynamics over time and the cross-sectional representativeness of the survey, ensuring that the IHPS remains a robust instrument for monitoring poverty and socioeconomic change in Malawi.","coll_dates":[{"start":"2024-07-23","end":"2025-01-30","cycle":""}],"nation":[{"name":"Malawi","abbreviation":"MWI"}],"geog_coverage":"National","analysis_unit":"\u2022 Households\n\u2022 Individuals\n\u2022 Children under 5 years\n\u2022 Consumption expenditure commodities\/items\n\u2022 Communities\n\u2022 Agricultural household\/ Holder\/ Crop","universe":"The 2024 round comprised two sample components. The retained component followed all individuals from the 2019 households associated with the 51 EAs that were carried forward from previous rounds, applying the same tracking rules as prior rounds, including following split-off individuals who formed or joined new households, as long as they were neither servants nor guests at the time of the IHPS 2019, were projected to be at least 12 years of age, and were known to be residing in mainland Malawi but excluding those in Likoma Island and in institutions, including prisons, police compounds, and army barracks. The refreshed component introduced households drawn from the 51 newly selected EAs that replaced the retired ones.","data_kind":"Sample survey data [ssd]","notes":"The Integrated Household Panel Survey series covers the following topics:\nHOUSEHOLD\n\u2022 Household and Geographic Area Identification and Survey Information (data of interview, enumerator's and supervisors codes, etc.)\n\u2022 Household Roster\n\u2022 Education\n\u2022 Health\n\u2022 Time Use and Labor\n\u2022 Housing\n\u2022 Food Consumption (over past one week)\n\u2022 Food Security\n\u2022 Non-food Expenditures - over past one week and one month\n\u2022 Non-food Expenditures - over past three months\n\u2022 Non-food Expenditures - over past 12 months\n\u2022 Durable Goods\n\u2022 Farm Implements, Machinery, and Structures\n\u2022 Household Enterprises\n\u2022 Children Living Elsewhere\n\u2022 Other Income\n\u2022 Gifts Given Out\n\u2022 Social Safety Nets\n\u2022 Credit\n\u2022 Subjective Assessment of Well-being\n\u2022 Shocks and Coping Strategies\n\u2022 Child Anthropometry\n\u2022 Deaths in Household\n\u2022 Savings\n\u2022 Child care\n\u2022 MAGNET \u2013 Goal setting\n\u2022 MAGNET \u2013 Generalized Livelihood Efficacy\n\nAGRICULTURE\n\u2022 Garden Roster (both for rainy season and dry (dimba) season)\n\u2022 Plot Roster (both for rainy season and dry (dimba) season)\n\u2022 Garden Details (both for rainy season and dry (dimba) season)\n\u2022 Plot Details (both for rainy season and dry (dimba) season)\n\u2022 Coupon Use (rainy season)\n\u2022 Other Inputs (both for rainy season and dry (dimba) season)\n\u2022 Crops (both for rainy season and dry (dimba) season)\n\u2022 Seeds (both for rainy season and dry (dimba) season)\n\u2022 Sales\/ Storage (both for rainy season and dry (dimba) season)\n\u2022 Tree\/ Permanent Crop Production (last 12 months)\n\u2022 Tree\/ Permanent Crop Sales\/ Storage (last 12 months)\n\u2022 Livestock\n\u2022 Livestock Products\n\u2022 Access to Extension Services\n\nFISHERY (Open catch and Aquaculture )\n\u2022 Species, Gear, Production and Labor\n\nCOMMUNITY\n\u2022 Roster of Informants\n\u2022 Basic Information\n\u2022 Economic Activities\n\u2022 Agriculture\n\u2022 Changes\n\u2022 Community Needs, Actions and Achievements\n\u2022 Communal Resource Management\n\u2022 Communal Organization"},"method":{"data_collection":{"sampling_procedure":"The IHPS sample underwent a structural change in 2024: a partial refresh, whereby 50 percent of the 102 EAs were retired (and all associated households emanating from those EAs) and replaced with an equivalent set of freshly selected EAs and households within them. There were several motivating factors behind this partial refresh. The first was the desire to alleviate the respondent burden of some households which had been participating in the IHPS across a decade. The second was the desire to boost cross-sectional representativeness of the IHPS with freshly identified and selected households. As longitudinal samples age, their cross-sectional representativeness tends to fade since the underlying population undergoes socio-demographic changes over time. While this deterioration in cross-sectional representativeness is partially offset through implementation practices (e.g., following of split-off households) and weight adjustments (e.g., calibration), incorporating a freshly selected set of households is the most effective strategy to improve cross-sectional representativeness. The third motivation was to carefully curb and regulate the expansion of the panel sample size induced by the individual following rules.\n\nNote: Detailed sample design information is presented in the \"Integrated Household Panel Survey 2024, Basic Information Document\" document.","coll_mode":["Computer Assisted Personal Interview [capi]"],"coll_situation":"Field staff for the IHPS were recruited following advertisements placed in national newspapers calling for enumerator positions. Shortlisted candidates were interviewed to select the most qualified individuals. The IHS Management Team, supported by World Bank LSMS-ISA team members, provided training to the field staff. The training included classroom sessions covering the questionnaire content, key concepts and definitions, interviewing techniques, and practical field exercises to ensure enumerators fully understood the survey tools. Detailed training instructions are provided in the Enumerator and Field Supervisor\u2019s Manuals.\nAt the end of the training, participants were evaluated through tests and assessments by supervisory staff. The top-performing candidates were selected as Field Supervisors, while 72 candidates were chosen as Field Enumerators.\n\nPre-enumeration listing exercises were conducted before the start of each phase of fieldwork. Mobile listing teams, equipped with printed maps of selected Enumeration Areas (EAs), recorded all dwellings and heads of households in the chosen cross-sectional EAs. Household counts for each listed enumeration area were submitted to the NSO IHS6 Management Team and properly documented. Where applicable, listing forms and maps were handed over directly to the field teams upon completion of district-level listing activities.\nFieldwork for the IHS6 commenced in July 2024 and was conducted simultaneously across the country until July 2025. Note that the panel operations were meant to end in January 2025, but there were some residual tracking cases that extended up to May 2025. Eighteen field-based mobile teams, each consisting of one supervisor, four enumerators, and one driver, were deployed to cover specific districts. Team supervisors received monthly enumeration assignment schedules on a quarterly basis. These assignments were accompanied by (1) enumeration area maps, (2) completed listing forms, (3) lists of selected and replacement households to be interviewed in each EA, and (4) Survey Solutions assignments for the selected EAs from headquarters.\n\nEach mobile field team included four enumerators responsible for conducting household interviews throughout the scheduled fieldwork period. The main duties of enumerators included accurately and completely administering the household, agriculture, and fishery questionnaires. Their responsibilities encompassed: (1) locating assigned households, (2) explaining the purpose of the survey and obtaining informed consent from respondents, (3) implementing all relevant questionnaire modules, (4) taking anthropometric measurements for eligible household members, (5) using GPS technology to record household locations and measure agricultural fields, and (6) participating in the review and correction of completed questionnaires.","weight":"Sampling weights are an essential component of any probability-based household survey, ensuring that the estimates produced are representative of the population within each survey domain. For the IHPS 2024, weights were constructed to reflect each household's probability of being selected into the sample, with further adjustments made to account for nonresponse and attrition, and to align the estimates with external population data through calibration.\n\nNote: Detailed weight calculation information is presented in the \"Integrated Household Panel Survey 2024, Basic Information Document\" document.","cleaning_operations":"DATA ENTRY PLATFORM\nTo ensure high data quality and timely data availability, the IHS6 used the World Bank\u2019s Survey Solutions CAPI software. Each team supervisor was provided with a laptop computer and a wireless internet router, while each enumerator received a 10-inch GPS-enabled Samsung tablet. The use of Survey Solutions enabled real-time data availability, as completed questionnaires were approved by supervisors and synced to the headquarters server as frequently as possible. While administering the first module of the questionnaire, enumerators also recorded the GPS coordinates of dwelling units using their tablets. This allowed headquarters to view the location of dwellings plotted on a map of Malawi, facilitating remote supervision by verifying both the number of interviews completed and whether sampled households fell within the correct Enumeration Area (EA) boundaries.\n\nGeo-referenced household locations captured on the tablets complemented GPS measurements taken with Garmin eTrex 30 handheld devices. These locations were linked with publicly available geospatial databases, enabling the inclusion of various geospatial variables such as distance to the nearest market, climatology, soil and terrain characteristics, and other environmental factors \u2014 in the analysis.\n\nDATA MANAGEMENT\nThe IHS6 Survey Solutions CAPI application was designed to streamline the data collection process. Interviews were collected in \u201csample\u201d mode (with assignments generated from headquarters), rather than \u201ccensus\u201d mode, giving the NSO greater control over the sample.\n\nThe range and consistency checks built into the application drew on lessons from the LSMS experience in previous IHS rounds. These pre-programmed checks allowed for the detection and reporting of potential issues, which could be investigated and corrected before an enumeration area was closed. Headquarters (NSO management) assigned work to supervisors based on their regions of coverage. Supervisors then assigned specific tasks to enumerators linked to their accounts. Work assignments and the syncing of completed interviews were carried out via Wi-Fi connection to the IHS6 server. Because the data was available in real time, it was closely monitored throughout the data collection period. Upon receipt at headquarters, the data was exported to STATA for additional consistency checks, cleaning, and analysis.\n\nDATA CLEANING\nData cleaning was carried out in several stages during fieldwork and preliminary analysis. The first stage occurred in the field, where teams used the error reports generated by the Survey Solutions application. For any flagged errors, enumerators were required to add comments explaining the issue and confirming that they had verified the response with the respondent. Supervisors were expected to sync enumerator tablets frequently to minimize the number of pending questionnaires and enable daily reviews. Some supervisors reviewed interviews on the tablets before syncing, recorded notes in the supervisor account, and rejected questionnaires when necessary.\n\nThe second stage involved additional error reports generated in Stata and shared with field teams via email. Field supervisors collected these reports for their assigned areas and worked with enumerators to review, investigate, and correct errors. The rapid error-reporting process allowed for call-backs to respondents while teams were still in the enumeration area when needed. Corrections were made to rejected questionnaires and sent back to headquarters.\n\nFurther cleaning was performed after interviews were approved, to resolve systematic errors and ensure consistency across data modules. Case-by-case cleaning was also conducted during preliminary analysis, particularly for out-of-range values and outliers.\n\nAll cleaning activities were undertaken in close collaboration with World Bank staff who provided technical assistance to the NSO throughout the design and implementation of the IHS6."},"analysis_info":{"response_rate":"Since the first round in 2010, every effort has been made to track and interview households and individuals that had moved away from their original EA and keep attrition to a minimum. These efforts continued in 2024, particularly for the long panel retained sample. During IHPS5 (2024), a total of 1,515 households from IHPS4 (2019) served as tracking targets for the retained sample, comprising 7,099 individuals. By the conclusion of the 2024 tracking operation, the panel sample had expanded to 1,948 households. This increase is attributable to households relocating or an individual within a household splitting off to establish a new household. These 1,515 households originate from 1,338 of the 2019 households, indicating a household-level attrition rate of 11.6 percent."}},"data_access":{"dataset_use":{"contact":[{"name":"Kanyanda Shelton, Commissioner of Statistics","affiliation":"National Statistical Office - Malawi","email":"commissioner@nso.gov.mw","uri":""},{"name":"LSMS Data Manager","affiliation":"The World Bank","email":"lsms@worldbank.org","uri":""}],"cit_req":"Citation requirements\nUse of the dataset must be acknowledged using a citation which would include:\n\u2022 the Identification of the Primary Investigator\n\u2022 the title of the survey (including country, acronym and year of implementation)\n\u2022 the survey reference number\n\u2022 the source and date of download.","conditions":"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:\n1. 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.\n2. Three copies of all publications, conference papers, or other research reports based entirely or in part upon the requested data will be supplied to:\nCommissioner Shelton Kanyanda\nNational Statistical Office\nChimbiya Road\nP.O. Box 333\nZomba, Malawi\nTel: +265 (0) 1 524 377\/111\nFax: +265 (0) 1 525 130\ne-mail: commissioner@nso.gov.mw\nweb site: http:\/\/www.nsomalawi.mw\n3. The researcher will refer to the Malawi 2024 IHPS 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).\n4. Users will not use the location information to reveal the identity of survey respondents.\n5. Users will not publish results (map or other form) that would allow communities or individuals to be identified.\n6. Users who download the data may not pass the data to third parties.\n7. The database cannot be used for commercial ends, nor can it be sold.","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."}}},"schematype":"survey","tags":[{"tag":"NODOI"}]}