Integrated Household Panel Survey 2010-2013-2016 (Long-Term Panel, 102 EAs)
Malawi, 2010 - 2016
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Reference ID
MWI_2010-2016_IHPS_v03_M
Producer(s)
National Statistical Office
Collection(s)
Metadata
Created on
Dec 05, 2017
Last modified
Jan 30, 2020
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Identification
Survey ID Number
MWI_2010-2016_IHPS_v03_M
Title
Integrated Household Panel Survey 2010-2013-2016 (Long-Term Panel, 102 EAs)
Country/Economy
| Name | Country code |
|---|---|
| Malawi | MWI |
Study type
Living Standards Measurement Study
Series Information
The Integrated Household Panel Survey (IHPS) was integrated into the core Integrated Household Survey (IHS) program to study trends in poverty, socioeconomic and agricultural characteristics over time through a longitudinal survey.
At the time of the Third Integrated Household Survey (IHS3) 2010 (i.e. baseline), the IHPS sample (known as the IHPS 2010) had been selected, out of the overall IHS3 cross-sectional sample, to be representative at the national-, regional-, urban/rural levels, and for each of the following 6 strata: (i) Northern Region – Rural, (ii) Northern Region – Urban, (iii) Central Region – Rural, (iv) Central Region – Urban, (v) Southern Region – Rural, and (vi) Southern Region – Urban.
The IHPS 2013 attempted to track all baseline households as well as individuals that moved away from the baseline dwellings between 2010 and 2013 as long as they were neither servants nor guests at the time of the IHS3; 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. Once a split-off individual was located, the new household that he/she formed/joined since 2010 was also brought into the IHPS sample. In view of the tracking rules, the final IHPS 2013 sample, therefore, included a total of 4,000 households that could be traced back to 3,104 baseline households.
Given the increasing numbers of households to be tracked, as well as budget/resource constraints, starting in 2016, the IHPS target household sample was adjusted as the households that have been associated with 102 out of 204 baseline EAs. Although the IHPS 2016 cannot be tabulated by region, the stratification of the IHPS 2010 sample by region, urban and rural strata was still maintained with a proportional allocation of the sample across the regions, based on the distribution of the sampling frame from the 2008 Malawi Census. The selection ensured that the IHPS 2016 had a sufficient sample size in the urban stratum to obtain reliable national estimates for the urban and rural domains. Thus, starting in 2016, the IHPS domains of analysis will be limited to the national, urban and rural areas.
At the time of the Third Integrated Household Survey (IHS3) 2010 (i.e. baseline), the IHPS sample (known as the IHPS 2010) had been selected, out of the overall IHS3 cross-sectional sample, to be representative at the national-, regional-, urban/rural levels, and for each of the following 6 strata: (i) Northern Region – Rural, (ii) Northern Region – Urban, (iii) Central Region – Rural, (iv) Central Region – Urban, (v) Southern Region – Rural, and (vi) Southern Region – Urban.
The IHPS 2013 attempted to track all baseline households as well as individuals that moved away from the baseline dwellings between 2010 and 2013 as long as they were neither servants nor guests at the time of the IHS3; 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. Once a split-off individual was located, the new household that he/she formed/joined since 2010 was also brought into the IHPS sample. In view of the tracking rules, the final IHPS 2013 sample, therefore, included a total of 4,000 households that could be traced back to 3,104 baseline households.
Given the increasing numbers of households to be tracked, as well as budget/resource constraints, starting in 2016, the IHPS target household sample was adjusted as the households that have been associated with 102 out of 204 baseline EAs. Although the IHPS 2016 cannot be tabulated by region, the stratification of the IHPS 2010 sample by region, urban and rural strata was still maintained with a proportional allocation of the sample across the regions, based on the distribution of the sampling frame from the 2008 Malawi Census. The selection ensured that the IHPS 2016 had a sufficient sample size in the urban stratum to obtain reliable national estimates for the urban and rural domains. Thus, starting in 2016, the IHPS domains of analysis will be limited to the national, urban and rural areas.
Abstract
The 2016 Integrated Household Panel Survey (IHPS) was launched in April 2016 as part of the Malawi Fourth Integrated Household Survey fieldwork operation. The IHPS 2016 targeted 1,989 households that were interviewed in the IHPS 2013 and that could be traced back to half of the 204 enumeration areas that were originally sampled as part of the Third Integrated Household Survey (IHS3) 2010/11. The panel sample expanded each wave through the tracking of split-off individuals and the new households that they formed. Available as part of this project is the IHPS 2016 data as well as the rereleased IHPS 2010 & 2013 data including only the subsample of 102 EAs with updated panel weights. Additionally, the IHPS 2016 was the first survey that received complementary financial and technical support from the Living Standards Measurement Study – Plus (LSMS+) initiative, which has been established with grants from the Umbrella Facility for Gender Equality Trust Fund, the World Bank Trust Fund for Statistical Capacity Building, and the International Fund for Agricultural Development, and is implemented by the World Bank Living Standards Measurement Study (LSMS) team, in collaboration with the World Bank Gender Group and partner national statistical offices. The LSMS+ aims to improve the availability and quality of individual-disaggregated household survey data, and is, at start, a direct response to the World Bank IDA18 commitment to support 6 IDA countries in collecting intra-household, sex-disaggregated household survey data on 1) ownership of and rights to selected physical and financial assets, 2) work and employment, and 3) entrepreneurship – following international best practices in questionnaire design and minimizing the use of proxy respondents while collecting personal information. This dataset is included here.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Households
- Individuals
- Children under 5 years
- Consumption expenditure commodities/items
- Communities
- Agricultural household/ Holder/ Crop
- Individuals
- Children under 5 years
- Consumption expenditure commodities/items
- Communities
- Agricultural household/ Holder/ Crop
Version
Version Description
v3: Edited data. Individual modules added, household and community modules updated.
Version Notes
The following files were replaced:
- Dataset HH_MOD_B_16.dta
- COM_MOD_CG_16.dta
- The Basic Information Document
The following files were added
- IND_MOD_A.dta
- IND_MOD_B.dta
- IND_MOD_F.dta
- IND_MOD_H.dta
- IND_MOD_I.dta
- IND_MOD_J.dta
- IND_MOD_K.dta
- IND_MOD_L.dta
- IND_MOD_NR.dta
- Dataset HH_MOD_B_16.dta
- COM_MOD_CG_16.dta
- The Basic Information Document
The following files were added
- IND_MOD_A.dta
- IND_MOD_B.dta
- IND_MOD_F.dta
- IND_MOD_H.dta
- IND_MOD_I.dta
- IND_MOD_J.dta
- IND_MOD_K.dta
- IND_MOD_L.dta
- IND_MOD_NR.dta
Scope
Notes
The Integrated Household Panel Survey series covers the following topics:
HOUSEHOLD
- Household and Geographic Area Identification and Survey Information (data of interview, enumerator's and supervisors codes, etc.)
- Household Roster
- Education
- Health
- Time Use and Labor
- Housing
- 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
- Credit
- Subjective Assessment of Well-being
- Shocks and Coping Strategies
- Child Anthropometry
- Deaths in Household
AGRICULTURE
- 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
- Livestock Products
- Access to Extension Services
- Network Roster
FISHERY
- 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)
COMMUNITY
- Roster of Informants
- Basic Information
- Economic Activities
- Agriculture
- Changes
- Community Needs, Actions and Achievements
- Communal Resource Management
- Communal Organization
HOUSEHOLD
- Household and Geographic Area Identification and Survey Information (data of interview, enumerator's and supervisors codes, etc.)
- Household Roster
- Education
- Health
- Time Use and Labor
- Housing
- 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
- Credit
- Subjective Assessment of Well-being
- Shocks and Coping Strategies
- Child Anthropometry
- Deaths in Household
AGRICULTURE
- 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
- Livestock Products
- Access to Extension Services
- Network Roster
FISHERY
- 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)
COMMUNITY
- Roster of Informants
- Basic Information
- Economic Activities
- Agriculture
- Changes
- Community Needs, Actions and Achievements
- Communal Resource Management
- Communal Organization
Coverage
Geographic Coverage
National
Universe
The IHPS 2016 attempted to track all IHPS 2013 households stemming from 102 of the original 204 baseline panel enumeration areas as well as individuals that moved away from the 2013 dwellings between 2013 and 2016 as long as they were neither servants nor guests at the time of the IHPS 2013; 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.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Statistical Office | Government of Malawi |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Living Standards Measurement Study - Integrated Surveys on Agriculture | The World Bank | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Government of Malawi | GoM | Financial support |
| The World Bank Living Standards Measurement Study - Integrated Surveys on Agriculture | WB LSMS-ISA | Financial support |
| Millennium Challenge Corporation | MCC | Financial support |
Sampling
Sampling Procedure
A sub-sample of IHS3 2010 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) to track and resurvey these households in 2013 in accordance with the IHS3 fieldwork timeline and as part of the Integrated Household Panel Survey (IHPS 2013) and (ii) visit a total of 3,246 households in these EAs twice to reduce recall associated with different aspects of agricultural data collection. At baseline, the IHPS sample was selected to be representative at the national, regional, urban/rural levels and for each of the following 6 strata: (i) Northern Region - Rural, (ii) Northern Region - Urban, (iii) Central Region - Rural, (iv) Central Region - Urban, (v) Southern Region - Rural, and (vi) Southern Region - Urban. The IHPS 2013 main fieldwork took place during the period of April-October 2013, with residual tracking operations in November-December 2013.
Given budget and resource constraints, for the IHPS 2016 the number of sample EAs in the panel was reduced to 102 out of the 204 EAs. As a result, the domains of analysis are limited to the national, urban and rural areas. Although the results of the IHPS 2016 cannot be tabulated by region, the stratification of the IHPS by region, urban and rural strata was maintained.
Given budget and resource constraints, for the IHPS 2016 the number of sample EAs in the panel was reduced to 102 out of the 204 EAs. As a result, the domains of analysis are limited to the national, urban and rural areas. Although the results of the IHPS 2016 cannot be tabulated by region, the stratification of the IHPS by region, urban and rural strata was maintained.
Weighting
The methodology used to calculate the IHPS panel weights (provided in the data as panelweight) is discussed in detail in “Weight calculations for panel surveys with sub-sampling and split-off tracking” (Himelein, 2013). In order to analyze the IHPS 2013 data and produce accurate representativeness of the population, the sample variables must be weighted using the variable panelweight and taking into account the complex survey design.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2010 | 2016 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Supervision
IHS4/IHPS 2016 field based supervisors were responsible for managing the daily operations of their respective field based mobile team. Primary responsibilities included: (1) liaising with IHS4 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
Training of Field Staff
Field staff for the IHS4 and IHPS 2016 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 IHS4 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. For each team one of the top enumerators was tagged as the “Assistant Supervisor” so that at least two people on the team were trained to use the Survey Solutions Supervisor account if need be.
Field Teams
Fieldwork for the IHS4 and IHPS 2016 began in April 2016 and was administered simultaneously throughout the country until 30 April 2017. 17 field-based mobile teams consisting of 1 supervisor, 4 enumerators and 1 driver were assigned to cover specific districts. An 18th team served as the tracking team for the panel subcomponent during the first half of fieldwork (further details in IHPS 2016 BID), and then also focused on cross-section during quarters 3 and 4.
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.
Enumerators
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.
Field staff for the IHS4 and IHPS 2016 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 IHS4 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. For each team one of the top enumerators was tagged as the “Assistant Supervisor” so that at least two people on the team were trained to use the Survey Solutions Supervisor account if need be.
Field Teams
Fieldwork for the IHS4 and IHPS 2016 began in April 2016 and was administered simultaneously throughout the country until 30 April 2017. 17 field-based mobile teams consisting of 1 supervisor, 4 enumerators and 1 driver were assigned to cover specific districts. An 18th team served as the tracking team for the panel subcomponent during the first half of fieldwork (further details in IHPS 2016 BID), and then also focused on cross-section during quarters 3 and 4.
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.
Enumerators
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.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| National Statistical Office | NSO | Ministry of Economic Planning and Development (MoEPD) |
Data Processing
Data Editing
DATA ENTRY PLATFORM
To ensure data quality and timely availability of data, the IHPS 2016 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out full IHS4 and IHPS 2016, 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.
DATA MANAGEMENT
The IHS4 and IHPS 2016 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.
DATA CLEANING
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 and IHPS 2016.
To ensure data quality and timely availability of data, the IHPS 2016 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out full IHS4 and IHPS 2016, 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.
DATA MANAGEMENT
The IHS4 and IHPS 2016 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.
DATA CLEANING
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 and IHPS 2016.
Access policy
Contacts
Access 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:
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:
Commissioner Mercy Kanyuka
National Statistical Office
Chimbiya Road
P.O. Box 333
Zomba, Malawi
Tel: +265 (0) 1 524 377/111
Fax: +265 (0) 1 525 130
e-mail: ihs@statistics.gov.mw
web site: www.nso.malawi.net
AND
The World Bank
Development Economics Research Group
LSMS Database Administrator
MSN MC3-306
1818 H Street, NW
Washington, DC 20433, USA
tel: (202) 473-9041
fax: (202) 522-1153
e-mail: lsms@worldbank.org
3. The researcher will refer to the Malawi 2016-2017 IHS4 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.
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:
Commissioner Mercy Kanyuka
National Statistical Office
Chimbiya Road
P.O. Box 333
Zomba, Malawi
Tel: +265 (0) 1 524 377/111
Fax: +265 (0) 1 525 130
e-mail: ihs@statistics.gov.mw
web site: www.nso.malawi.net
AND
The World Bank
Development Economics Research Group
LSMS Database Administrator
MSN MC3-306
1818 H Street, NW
Washington, DC 20433, USA
tel: (202) 473-9041
fax: (202) 522-1153
e-mail: lsms@worldbank.org
3. The researcher will refer to the Malawi 2016-2017 IHS4 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.
Citation requirements
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
- 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
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_MWI_2010-2016_IHPS_v03_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank Group | Documentation of the DDI |
DDI Document version
Version 03 (October 2019)
Identical to version 02, with updates to the following
- Abstract
- Basic Information Document
Replaced datasets: Dataset HH_MOD_B_16.dta & COM_MOD_CG_16.dta
Added dataset: Individual dataset
Identical to version 02, with updates to the following
- Abstract
- Basic Information Document
Replaced datasets: Dataset HH_MOD_B_16.dta & COM_MOD_CG_16.dta
Added dataset: Individual dataset