MWI_2010_IHS-III_v01_M
Third Integrated Household Survey 2010-2011
Name | Country code |
---|---|
Malawi | MWI |
Living Standards Measurement Study [hh/lsms]
The First Integrated Household Survey (IHS1) was designed by the NSO with technical assistance from the International Food Policy Research Institute (IFPRI) and the World Bank (WB) to provide a complete and integrated data set to better understand target groups of households affected by poverty. 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. In 2003, the Government of Malawi decided to conduct the Second Integrated Household Survey (IHS2) in order to compare the current situation with the situation in 1997-98, and to collect more detailed information in specific areas. The IHS2 was implemented from March 2004 through March 2005. And, Third Integrated Household Survey (IHS3) was conducted by National Statistical Office (NSO) in March 2010-March 2011.
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) as well as the goals listed as part of the Malawi Growth and Development Strategy (MGDS).
Sample survey data [ssd]
The 2010-2011 Third Integrated Household Survey covered the following topics:
HOUSEHOLD
AGRICULTURE
FISHERY
COMMUNITY
National
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.
Name | Affiliation |
---|---|
National Statistical Office (NSO) | Ministry of Economic Planning and Development (MoEPD) |
Name | Role |
---|---|
The World Bank | Technical assistance |
Name | Role |
---|---|
Government of Malawi | Financial support |
World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture project | Financial support |
Norway | Financial support |
Irish Aid | Financial support |
Department for International Development | Financial support |
Millennium Challenge Corporation | Financial support |
German Development Corporation | Financial support |
The IHS3 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. It was decided to exclude the island district of Likoma from the IHS3 sampling frame, since it only represents about 0.1% of the population of Malawi, and the corresponding cost of enumeration would be relatively high. The sampling frame further excludes the population living in institutions, such as hospitals, prisons and military barracks. Hence, the IHS3 strata are composed of 31 districts in Malawi.
A stratified two-stage sample design was used for the IHS3.
Note: Detailed sample design information is presented in the "Third Integrated Household Survey 2010-2011, Basic Information Document" document.
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 hhwght. As noted above, the IHS3 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 33 each sample EA.
Note: Detailed weighting information is presented in the "Third Integrated Household Survey 2010-2011, Basic Information Document" document.
The survey was collectd using four questionnaires:
Start | End |
---|---|
2010-03 | 2011-03 |
Name | Affiliation |
---|---|
National Statistical Office | Ministry of Economic Planning and Development (MoEPD) |
IHS3 field based supervisors were responsible for managing the daily operations of their respective field based mobile team. Primary responsibilities included: (1) liaising with IHS3 management on schedules, field operation status, equipment status and needs, and special issues, (2) planning daily field operation schedules including coverage and transportation, (3) liaise with local authorities before commencing interview activities, (4) reviewing incoming questionnaires for completion and accuracy, (5) managing data entry schedule for completed questionnaires, (6) reviewing computer assisted field entry (CAFE) reports for field entered questionnaires, assigning physical questionnaire reviews, and authorizing review/call back completion, (7) administering community questionnaires within each enumeration area, (8) retrieving completed data files from data entry clerks and regularly transmitting data to the NSO central office in Zomba.
Training of Field Staff
Field staff for the IHS3 was selected through a series of exams held throughout the country. Advertisements were placed in the national newspapers advertising posts for enumerators and data entry clerks. Interested candidates took a test to determine their qualifications. Those who passed the test were invited to the training.
Training instruction was given to the field staff by the IHS3 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 16 best candidates were selected to be Field Supervisors, and 64 candidates were selected to be Field Enumerators. In addition, 16 Data Entry candidates were selected to join the field based mobile teams to process questionnaires on a rolling basis. In addition to the content training, data entry clerks received additional training in IHS3 data entry applications, protocols and data management and data back-ups.
Pre-enumeration Listing
Pre-enumeration listings were initiated before the start of each quarter of field work. Mobile listing teams equipped with printed maps of select EAs were used to record all dwellings and heads of households in select EAs. Household counts per each listed enumeration areas were relayed to NSO IHS3 Management and recorded. Where applicable, listing forms and maps were transferred directly to field teams after the completion of district quarterly listing activities.
Field Teams
Fieldwork for the IHS3 began in March 2010 and was administered simultaneously throughout the country until March 2011. 16 field-based mobile teams consisting of 1 supervisor, 4 enumerators, 1 data entry clerk 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) color coded, adequate set of questionnaire instruments to be administered in accordance with a given EA's cross-sectional vs. Panel A vs. Panel B status, and (4) the list of selected as well as replacement households to be interviewed in each EA.
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 selected 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 CAFE review and correction of field entered questionnaires.
Data Entry Clerks
Each IHS3 field team was assigned 1 data entry clerk to process completed questionnaires at the teams field based residence. Each data entry clerk was issued a laptop with the CSPro based data entry application, a printer to produce error reports on entered questionnaire, and flash disks for transferring files. The field based data entry clerk's primary responsibilities included: (1) receiving the completed questionnaires following the field supervisor's initial screening, (2) organizing and entering completed questionnaire in a timely manner, (3) generating and printing error reports for supervisor review, (4) modifying data after errors were resolved and authorized by the field supervisor, and (5) managing data files and local data back-ups. The data entry clerk was responsible for beginning initial data entry upon receipt of questionnaires from the field and generating error reports as quickly as possible after interviews were complete in the EA. When long distance travel to an enumeration area by the field team was required and the field team was required to spend multiple days away from their field residence the data entry clerk was required to travel with the team in order to maintain data processing schedules.
Field Based Data Entry and CAFE
To better facilitate higher quality data and increase timely availability of data during the data capture process IHS3 utilized computer assisted field entry (CAFE). First data entry was conducted by field based data entry clerks immediately following completion of the team's daily field activities. Each team was equipped with 1 laptop computer for field based data entry using a CSPro-based application. The range and consistency checks built into the CSPro application was informed by the LSMS-ISA experience in Tanzania and Uganda, and the review of the IHS2 data. 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. Completed data was frequently relayed to the NSO central office in Zomba via email and tracked and processed upon receipt.
Double Data Entry
Double data entry was implemented by a team of data entry clerks based at the NSO central office. Electronic data and questionnaires received from the field were cataloged by the Data Manager and electronic data loaded onto a central server to enable data entry verification on networked computers. To increase quality, the Data Entry Manager monitored the data verification staff and conducted quality assessments by randomly selecting processed questionnaires and comparing physical questionnaires to the result of double data entry. Data verification clerks were coached on inconsistencies when required.
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 error reports produced by the data entry applications. Field supervisors collected reports for each enumeration area and household 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 by the field based data entry clerk before transmitting data to the NSO central office.
Upon receipt of the data from the field, module and cross module checks were performed using Stata to identify systematic issues and, where applicable, field teams were asked to investigate, revise and resend data for questionnaires still in their possession. Revised data files were cataloged and then replaced previous version of the data.
After data verification by the headquarters' double data entry team, data from the first data entry and second data entry were compared. Cases that revealed large inconsistencies between the first and second data entry, specifically large amounts of missing case level data in the second data entry relative to the first data entry were completely reentered. Further, variable specific inconsistency reports were generated and investigated and corrected by the double data entry team.
Additional cleaning was performed after the double data entry team cleaning activities 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 IHS3.
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:
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.
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 Charles Machinjili
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
The researcher will refer to the Malawi 2010-2011 IHS3 Survey as the source of the information in all publications, conference papers, and manuscripts. At the same time, the World Bank is not responsable for the estimations reported by the analyst(s).
Users will not use the location information to reveal the identity of survey respondents
Users will not publish results (map or other form) that would allow communities or individuals to be identified
Users who download the data may not pass the data to third parties.
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:
Citation requirement is the way that the dataset should be referenced when cited in any publication. Every dataset should have a citation requirement. This will guarantee that the data producer gets proper credit, and that analytical results can be linked to the proper version of the dataset. The Access Policy should explicitly mention the obligation to comply with the citation requirement. The citation should include at least the primary investigator, the name and abbreviation of the dataset, the reference year, and the version number. Include also a website where the data or information on the data is made available by the official data depositor.
Example:
Use of the dataset must be acknowledged using a citation which would include:
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.
Name | Affiliation | URL | |
---|---|---|---|
National Statistical Office | Ministry of Economic Planning and Development (MoEPD) | enquiries@statistics.gov.mw | http://www.nso.malawi.net |
LSMS Data Manager | The World Bank | lsms@worldbank.org | http://go.worldbank.org/QJVDZDKJ60 |
DDI_MWI_2010_IHS-III_v01_M
Name | Affiliation | Role |
---|---|---|
Development Economics Data Group | The World Bank | Ducumentation of the DDI |
2012-04-30
Version 01 (April 30)