Abstract

The 1996 Papua New Guinea household survey is designed to measure the living standards of a random sample of PNG households. As well as looking at the purchases, own-production, gift giving/receiving and sales activities of households over a short period (usually 14 days), the survey also collects information on education, health, nutrition, housing conditions and agricultural activities. The survey also collects information on community level access to services for education, health, transport and communication, and on the price levels in each community so that the cost of living can be measured.

There are many uses of the data that the survey collects, but one main aim is for the results to help government, aid agencies and donors have a better picture of living conditions in all areas of PNG so that they can develop policies and projects that help to alleviate poverty. In addition, the survey will provide a socio-economic profile of Papua New Guinea, describing the access that the population has to agricultural, educational, health and transportation services, their participation in various economic activities, and household consumption patterns.

The survey is nationwide and the same questionnaire is being used in all parts of the country, including the urban areas. This fact can be pointed out if households find that some of the questions are irrelevant for their own living circumstances: there are at least some Papua New Guinean households for which the questions will be relevant and it is only by asking everyone the same questions that living standards can be compared.

Geographic coverage

The survey covers all provinces except Noth Solomons.

Analysis unit

• Household
• Individual
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Listing Form and Selection of the Sample Listing of households is the first job to be done after the team has settled in and completed the introductions to the community. Listing is best done by the whole team working together. This way they all get to know the community and its lay-out. However, if the census unit is too large this wastes too much time. So before beginning asks how many households there are, very roughly, in the census unit (noting that teams are supplied with the number of households that were there in the 1990 census). If the answer is 80 or more, divide the team into two and have each half-team work on one sector of the community/village. See the section below on what to do when the listing work is divided up.

If the census unit is a "line-up point" that does not correspond to any single village or community the number of households will often exceed 200 and frequently they are also quite dispersed. In this case it is not practical to attempt to list the whole census unit, so a decision is made in advance to split the census unit into smaller areas (perhaps groupings of clans). First, a local informant must communicate the boundaries of the census unit and for natural or administrative sub-units with the larger census unit (such as hamlets; or canyons/valleys). The sub-units should be big enough to allow for the selection of a set of households (about 30 or more), but should not be so large that excessive transport time will be needed each day just to find the household. Once the subunit is defined, its boundaries should be clearly described. Then one of the smaller units is randomly selected and the procedures outlined above are then followed to complete the listing. Note: only one of the sub-units are listed, sample chosen, and interviews undertaken.

The most important thing in the listing is to be sure that you list all the households and only the households belonging to the named village or census unit (or subset of the census unit if it is a line-up point). In rural areas, explain to village leaders at the beginning: "We have to write down all the households belonging to (Name) village." In case of doubt, always ask: "Does this household belong to (Name) village?" In the towns, the selected area is shown on a map. Check that the address where you are listing is within the same area shown.

Also explain: "We only write down the name of the head of household. When we have the list of all the households, we will select 12 by chance, for interview."

Procedure for Listing The listing team walks around in every part of the village, accompanied by a guide who is a member of the village. If possible, find a person who conducted the 1990 Census in this community or someone with similar knowledge of the community and ask them to be your guide. Make sure you go to all parts of the village, including outlying hamlets. In hamlets, on in any place far from the centre, always check: "Do these people belong to (Name) village?"

In every part of the village, ask the guide about every house: "Who lives in this house? What is the name of the household head?" Note that you do not have to visit every household. At best, you just need to see each house but you do not need to go inside it or talk to anyone who lives there. Even the rule of seeing each house may be relaxed if there are far away household for which good information can be provided by the guide.

Enter the names of household heads in the lines of the listing form. One line is used for each household. As the lines are numbered, the procedure gives a number to each household. When you come to the last house, check with the guide: "Are you sure we have seen all the houses in the village?"

NOTE: It does not matter in what order you list the households as long as they are all listed. After the listing is complete, check that all lines are numbered consecutively with no gaps, from start to finish. The number on the last line should be exactly the number of households listed.

Note: If the list is long (say more than 30 households) interviewer may encounter difficulties when looking for their selected household. One useful way to avoid this is to show the approximately the place in the list here certain landmarks come. This can be done by writing in the margin, CHURCH or STORE or whatever. You can also indicate where the lister started in a hamlet, for example.

Sample Selection The sampling work is done by the supervisor. The first steps are done at the foot of the first page of the listing form. The steps to be taken are as follows:

1. Fill in the numbers asked for at the foot of the last listing page, as follows:
2. M: enter the total number of households listed (same as last household number shown).
3. Interval L: calculate (M / 15) to the nearest whole number.
4. R: This is a random number with 3-digit decimals between 0.000 and 0.999.

5. MR: multiply M by R and round to the nearest whole number. (If decimal 0.5, round up).

6. MR gives the 1st selection. (Exception: If MR=0, L gives the first selection.) Enter S against this line in the selection column of the list.

7. Count down the list, beginning after the 1st selection, a distance of L lines to get the 2nd selection, then another L to get the 3rd, etc. When you come to the bottom of the list, jump back to the top as if the list were circular. Stop after the 15th selection. Mark the 13th, 14th, and 15th selections "RES" (for reserve). Mark the 1st - 12th selection "S" (for selection).

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1996 Papua New Guinea Household Survey questionnaire consists of three basic parts:

Household questionnaire first visit: asks a series of questions about the household, discovering who lives there, what they do, their characteristics, where they live, and a little about what kinds of things they consume. This questionnaire consists of the following sections. - Section 1. Household Roster - Section 2. Education - Section 3. Income Sources - Section 4. Health - Section 5. Foods in the Diet - Section 6. Housing Conditions - Section 7. Agricultural Assets, Inputs and Services - Section 8. Anthropometrics - Section 9. Household Stocks

Consumption recall (second visit questionnaire): is focused primarily on assessing the household's expenditure, gift giving and recieving, production, and level of wealth. The information in the first and second visits will provide information that can determine the household's level of consumption, nutrition, degree of food security, and ways in which it organizes its income earning activities. This questionnaire consists of the following sections. - Section 1. Purchases of Food - Section 2. Other Frequent Purchases - Section 3. Own-production of Food - Section 4. Gifts Received: Food and Frequent Purchases (START) - Section 5. Annual Expenses and Gifts - Section 6. Inventory of Durable Goods - Section 7. Inward Transfers of Money - Section 8. Outward Transfers of Money - Section 9. Prices - Section 10. Repeat of Anthropometric Measurements - Section 11. Quality of Life

Community Questionnaire: which is completed by the interview team in consultation with community leaders. This questionnaire also includes market price surveys that are carried out by the team when they are working in the community. Associated with this is a listing of all households in the community, which has to be done prior to the selection of the 12 households. This questionnaire consists of the following sections. - Section A. Listing of Community Assets - Section B. Education - Section C. Health - Section D. Town or Government Station - Section E: Transport and Communications - Section F. Prices - Section G. Changes in Economic Activity, Infrastructure, and Services

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 2019 IHPS was launched in April 2019 as part of the Malawi Fifth Integrated Household Survey fieldwork operations targeting the 2,508 households that were interviewed in 2016. 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 2019 data, 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.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Children under 5 years
• Consumption expenditure commodities/items
• Communities
• Agricultural household/ Holder/ Crop

Universe

The IHPS 2016 and 2019 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.

Kind of data

Sample survey data [ssd]

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. The IHPS 2019 tracked all individuals 12 years or older from the 2016 households.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

Data Entry Platform To ensure data quality and timely availability of data, the IHPS 2019 was implemented using the World Bank’s Survey Solutions CAPI software. To carry out IHPS 2019, 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 that the NSO provided. 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. 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 IHPS 2019 Survey Solutions CAPI based data entry application was designed to stream-line the data collection process from the field. IHPS 2019 Interviews were mainly collected in “sample” mode (assignments generated from headquarters) and a few in “census” mode (new interviews created by interviewers from a template) for the NSO to have more control over the sample. This hybrid approach was necessary to aid the tracking operations whereby an enumerator could quickly create a tracking assignment considering that they were mostly working in areas with poor network connection and hence could not quickly receive tracking cases from Headquarters.

The range and consistency checks built into the application was informed by the LSMS-ISA experience with the IHS3 2010/11, IHPS 2013 and IHPS 2016. 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 (the NSO management) assigned work to the supervisors based on their regions of coverage. The 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 IHPS 2019 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 fieldwork and through preliminary analysis. The first stage of data cleaning was conducted in the field by the field-based field teams utilizing error messages generated by the Survey Solutions application when a response did not fit the rules for a particular question. For questions that flagged an error, the 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. The 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, which were in turn sent to the field teams via email or DropBox. The 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 EA when required. Corrections to the data were entered in the rejected questionnaires and sent back to headquarters.

The data cleaning process was done in several stages over the course of the fieldwork and through preliminary analyses. The first stage was during the interview itself. Because CAPI software was used, as enumerators asked the questions and recorded information, error messages were provided immediately when the information recorded did not match previously defined rules for that variable. For example, if the education level for a 12 year old respondent was given as post graduate. The second stage occurred during the review of the questionnaire by the Field Supervisor. The Survey Solutions software allows errors to remain in the data if the enumerator does not make a correction. The enumerator can write a comment to explain why the data appears to be incorrect. For example, if the previously mentioned 12 year old was, in fact, a genius who had completed graduate studies. The next stage occurred when the data were transferred to headquarters where the NSO staff would again review the data for errors and verify the comments from the

Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

The General Household Survey has national coverage.

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3 324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33 000 dwelling units (DUs). The number of PSUs in the current Master Sample (3 324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3 080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Computer Assisted Personal Interview

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Since 2019, the questionnaire for the GHS series changed and the variables were also renamed. For correspondence between old names (GHS pre-2019) and new name (GHS post-2019), see the document ghs-2019-variables-renamed.

Ridge to Reef data showing locations where household surveys took place, limited metadata, compiled in 2018

The Bangladesh Integrated Household Survey dataset is a thorough assessment of current standard of food security in Bangladesh taken from 2011-2012. The dataset includes all baseline household surveys made under the USAID-led Feed the Future initiative, a collaborative effort that supports country-owned processes and plans for improving food security and promoting transparency, and within the Zones of Influence as outlined by the Feed the Future Bangladesh plan. The survey was designed and supervised by the International Food Policy Research Institute (IFPRI). The survey was administered by Data Analysis and Technical Assistance, Dhaka, Bangladesh. Funding for the survey was provided by United States Agency for International Development (USAID). To protect the personal information of respondents, all personal identifiable information was removed, and the final dataset has been approved for publication by the Government of Bangladesh.

Graph and download economic data for Employment Level (CE16OV) from Jan 1948 to Jul 2025 about civilian, 16 years +, household survey, employment, and USA.

Urban Household Survey: Number of Household: Beijing data was reported at 2,800.000 Unit in 2012. This stayed constant from the previous number of 2,800.000 Unit for 2011. Urban Household Survey: Number of Household: Beijing data is updated yearly, averaging 1,500.000 Unit from Dec 1995 (Median) to 2012, with 18 observations. The data reached an all-time high of 3,165.000 Unit in 2010 and a record low of 500.000 Unit in 1998. Urban Household Survey: Number of Household: Beijing data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HC: No of Household Surveyed: City.

Abstract

The general aim of the Sierra Leone Integrated Household Survey (SLIHS) was to provide statistics on the living conditions of the people of Sierra Leone and to provide inputs to the government of Sierra Leone's policy making process. The study used consumption as the starting measure for household well-being and followed the standard in poverty analysis for developing countries. The SLIHS was prepared as joint work by Statistics Sierra Leone (SSL) and the World Bank Poverty Reduction and Economic Management Unit. SSL had the major responsibility of conducting the survey. The first chapter presents an overview of poverty, demographics, livelihoods, education, and health in Sierra Leone and measures progress in these indicators compared to the 2003 poverty assessment. The work was conducted as part of the poverty update and it included a series of policy notes with more detailed analysis. The objectives of the SLIHS include:

1. Provide benchmark poverty indicators against which the successes of the agenda for change (PRSP II) could be measured.
2. To measure the incidence of poverty alongside other indicators include providing information on patterns of household's consumption and expenditure at a greater level of disaggregation.
3. To provide data for the compilation of national accounts and computation of the Consumer Price Index (CPI)
4. In combination with earlier data this will give a data base for national and state planning and for the estimation of consumption as a proportion of household production.

The SLIHS was spread over a 12 month period in order to ensure a continuous recording of household consumption, expenditures and changes occurring thereof in 2011. A total of 9,671 Enumeration areas were selected and about 6,757 households were interviewed all over the country.

Geographic coverage

National

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The Integrated Household Survey (SLIHS) was administered to a representative sample of households. A total of about 6,832 households were selected of which 6,767 households were interviewed. The analytic work underlying this survey was produced in collaboration between Statistics Sierra Leone (SSL) and the World Bank. SSL adopted the local councils as the primary domain of study, this provided measures of levels of poverty and welfare at national and sub-national levels therefore addressing the recent strengths and weaknesses of government policies and programs. The census Enumeration area was used as a primary sampling unit (PSU) for the 2011 survey. The survey used a two-stage sampling design from the 2004 census frame. At the first stage 9,671 enumeration areas were selected. At the second stage, 85 Households per EA were selected the statistics obtained from the sampling frame have no difference compared to the census report. This means that the sampling frame covers the whole country.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SLIHS was comprised of a set of survey instruments. These were the following questionnaires: 1. Household Roster and Characteristics Questionnaire Part A 2. Household Consumption Expenditure and Income Questionnaire Part B

Response rate

95%

Geographic coverage

The survey covers all the Counties in Kenya based on the following levels National, Urban, Rural and County

Analysis unit

Households Indviduals within Households

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

These data reflect results of a household survey implemented in the summer of 2014. The survey randomly sampled households from 23 neighborhoods (census block groups) across 12 cities and 3 counties. Neighborhoods were purposively selected to represent different configurations of social, built, and natural environmental characteristics using the "iUTAH Urban Typology" (https://www.hydroshare.org/resource/84f00a1d8ae641a8af2d994a74f4ccfb/). Data were collected using a drop-off/pick-up methodology, and produced an overall response rate of over 62% (~2,400 respondents). The questionnaire included detailed questions related to household water use and landscaping behaviors, perceptions of water supply and quality, participation in water based recreation, concerns about water issues, and preferences for a range of local and state water policies.

Here we are making public an anonymized version of the large household survey dataset. To protect the identity of respondents, we have removed a few variables and truncated other variables.

Files included here: englishsurveys and spanishsurveys: These folders contain the survey questionnaires used specific to each neighborhood. Codebook in various formats: Tables (xls and csv files) with a list and definition of questions/variables, which correspond to the columns in the data files, and the encoding of the responses. Dataset in various formats: Tables (csv, xls, sas, sav, dta files) containing numeric responses to each question. Each participant's responses correspond to a row of data. Each question corresponds to a column of data. Interpretation of the coded responses is found in the data codebook. Maps: maps of the neighborhoods surveyed. SummaryReports: Summaries of the results that compare across three counties, summary reports for each county, highlight reports for each city.

Summary reports are also available at http://data.iutahepscor.org/mdf/Data/household_survey/ including an overall report that provides comparisons of how these vary across the three counties where we collected data (Cache, Salt Lake, and Wasatch) as well as summary reports for each county and highlights reports for each city.

This series measures the prevalence and correlates of drug use in the United States. The surveys are designed to provide quarterly, as well as annual, estimates. Information is provided on the use of illicit drugs, alcohol, and tobacco among members of United States households aged 12 and older. Questions include age at first use as well as lifetime, annual, and past-month usage for the following drug classes: marijuana, cocaine (and crack), hallucinogens, heroin, inhalants, alcohol, tobacco, anabolic steroids, nonmedical use of prescription drugs including psychotherapeutics, and polysubstance use. Respondents were also asked about substance abuse treatment history, illegal activities, problems resulting from use of drugs, perceptions of the risks involved, personal and family income sources and amounts, need for treatment for drug or alcohol use, criminal record, and needle-sharing. Questions on mental health and access to care, which were introduced in the 1994-B questionnaire (see NATIONAL HOUSEHOLD SURVEY ON DRUG ABUSE, 1994), were retained in this administration of the survey. Demographic data include sex, race, age, ethnicity, marital status, motor vehicle use, educational level, job status, income level, veteran status, and past and current household composition. This study has 1 Data Set.

Abstract

The objectives of the Smallholder Household Survey in Mozambique were to: • Generate a clear picture of the smallholder sector at the national level, including household demographics, agricultural profile, and poverty status and market relationships; • Segment smallholder households in Mozambique according to the most compelling variables that emerge; • Characterize the demand for financial services in each segment, focusing on customer needs, attitudes and perceptions related to both agricultural and financial services; and, • Detail how the financial needs of each segment are currently met, with both informal and formal services, and where there may be promising opportunities to add value.

Geographic coverage

National coverage

Analysis unit

Households and individual household members

Universe

The universe for the survey consists of smallholder households defined as households with the following criteria: 1) Household with up to 5 hectares OR farmers who have less than 50 heads of cattle, 100 goats/sheep/pigs, or 1,000 chickens; AND 2) Agriculture provides a meaningful contribution to the household livelihood, income, or consumption.

Kind of data

Sample survey data [ssd]

Sampling procedure

The CGAP smallholder household survey in Mozambique is a nationally-representative survey with a target sample size of 3,000 smallholder households. The sample was designed to provide reliable survey estimates at the national level and for the following regions: 1. North region, comprised of the provinces of Niassa, Cabo Delgado, and Nampula; 2. Centre region, comprised of Zambezia, Tete, Maica, and Sofala, Manica; and 3. South region, consisting of Inhambane, Maputo Province, Maputo City and Gaza.

Sampling Frame

The sampling frame for the smallholder household survey is the 2009-2010 Census of Agriculture and Livestock (Censo Agro-Pecuário, CAP II) conducted by the Mozambique National Statistical Office (INE) and based on the 2007 Census of Population and Housing (2007 RGPH). CAP II is a large sample that was designed to be representative at the district level and its sample of enumeration areas (EAs) is considered as the "master sample" for the national agricultural surveys. EAs with less than 15 agricultural households (mostly in urban areas) were excluded from the sampling frame for CAP II.

Sample Allocation and Selection

In order to take non-response into account, the target sample size was increased to 3,158 households assuming a household non-response rate of 5% observed in similar national households. The total sample size was first allocated to the three regions based on the number of agricultural households. Within each region, the resulting sample was further distributed proportionally to urban and rural areas.

The sample for the smallholder survey is a stratified multistage sample. Stratification was achieved by separating urban and rural areas within each region. Since the CAP II master sample that was used as the sampling frame for the survey is stratified by district, rural and urban areas, the rural strata of the individual districts for the CAP II master sample were collapsed up to the province level, and the same for the urban strata within each province. However, the district was still used as a sorting variable in order to provide implicit stratification by district.

At the first sampling stage the CAP II sample EAs were selected systematically with PPS within each district, rural and urban stratum, where the measure of size was the number of agricultural households in the census frame. In general if the EAs are selected with PPS at the first sampling stage, a subsample of EAs would be selected with equal probability within each stratum. However, in the case of the smallholder survey, the district strata were collapsed to the province level (separately for the rural and urban strata). Within each province the weights in CAP II vary by district, rural/urban stratum, by a factor of Mdh/ndh, where Mdh is the total number of agricultural households in the CAP II sampling frame for stratum (rural/urban) h in district d (from the RGPH 2007), and ndh is the number of sample EAs selected for CAP II in stratum h of district d.

Therefore in order to stabilize the weights within the rural and urban stratum of each province for the smallholder survey, the subsample of EAs included in the smallholder sample were selected within each stratum with probability proportional to the measure Mdh/ndh.

A household listing operation was carried out in all selected EAs to identify smallholder households and to provide a frame for the selection of 15 households per selected EA at the third stage. Households were selected in each EA with equal probability. In each selected household, the household questionnaire was administered to the head of the household, the spouse or any knowledgeable adult household member. The multiple respondent questionnaire was administered to all adult members in each selected household. In addition, in each selected household only one household member was selected using the Kish grid and was administered the single respondent questionnaire.

The full description of the sample design can be found in the user guide for this data set.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Building on secondary research on the smallholder sector and discussions with stakeholders, the design process for the survey instrument began. This process involved defining the end goal of the research by: • Drawing from existing survey instruments; • Considering the objectives and needs of the project; • Accounting for stakeholder interests and feedback; • Learning from the ongoing financial diaries in country; and, • Building from a series of focus groups conducted early on in the study.

Using this foundation, a framework for the survey instrument was developed to share with stakeholders and capture all the necessary elements of a smallholder household. The framework consisted of five main subject areas: (i) demographics, (ii) household economics, (iii) agricultural practices, (iv) mobile phones, and (v) financial services.

In order to capture the complexity inside smallholder households, the smallholder household survey was divided into three questionnaires: the Household questionnaire, the Multiple Respondent questionnaire and the Single respondent questionnaire.

The household questionnaire collected information on: • Basic household members’ individual characteristics (age, gender, education attainment, schooling status, relationship with the household head) • Whether each household member contributes to the household income or participates in the household’s agricultural activities. This information was later used to identify all household members eligible for the other two questionnaires.
• Household assets and dwelling characteristics

Both the Multiple and Single Respondent questionnaires collected different information on: • Agricultural practices: farm information such as size, crop types, livestock, decision-making, farming associations and markets • Household economics: employment, income, expenses, shocks, borrowing and saving habits, and investments

In addition, the Single respondent questionnaire collected information on: • Mobile phones: attitudes toward phones, usage, access, ownership, desire and importance • Financial services: attitudes towards financial products and services such as banking and mobile money, including ownership, usage, access and importance.

Before the start of fieldwork, all three questionnaires were pretested in all languages to make sure that the questions were clear and could be understood by respondents. The pretest took place 19 - 24 June 2015 in Maputo, Mozambique and 17 - 20 July 2015 in Ihambane, Nampula and Tete, Mozambique. In total, the pretest covered 79 households. At the end of the pretest, debriefing sessions were held with the pretest field staff and the questionnaires were modified based on the observations from the pretest. Following the finalization of questionnaires, a script was developed to support data collection on smart phones. The script was tested and validated before its use in the field.

Cleaning operations

During data collection, InterMedia received a weekly partial SPSS data file from the field which was analyzed for quality control and used to provide timely feedback to field staff while they were still on the ground. The partial data files were also used to check and validate the structure of the data file. The full data file was also checked for completeness, inconsistencies and errors by InterMedia and corrections were made as necessary and where possible.

Response rate

The user guide includes household and individual response rates for the CGAP smallholder household survey in Mozambique. A total of 3,041 households were selected for the sample, of which 2,782 were found to be occupied during data collection. Of these, 2,574 were successfully interviewed, yielding a household response rate of 92.5 percent.

In the interviewed households 5,502 eligible household members were identified for individual interviews. Completed interviews were conducted for 4,456 yielding a response rate of 81.0 percent for the Multiple Respondent questionnaire.

Among the 2,574 selected for the Single Respondent questionnaire, 2,209 were successfully interviewed corresponding to a response rate of 85.8 percent.

Sampling error estimates

The sample design for the

Abstract

Annual Household Survey 2012-2013 is a nation- wide household survey, data collection operation of which was conducted from December 2012 to July 2013. The AHS consists of multiple topics related to household information including demography, education, housing facilities, consumption and labour force. However the survey is primarily focused on the annual household consumption and current labour force statistics. The food consumption and labour force related information was collected for past 7 days of the reference period whereas for other information related to non-food was past 12 months. Therefore, the result of the survey refers to the year 2012-201313. The results of AHS are presented in this statistical report covering five sections of the survey questionnaire. Structurally, the report contains six chapters including 42 tables, 21 figures and 5 appendices. Since the design of the survey questionnaire has followed the concepts and definitions adopted in Nepal Living Standards Surveys and Nepal Labour Force Surveys especially to capture household consumption aggregates and the current labour force related information respectively, the data analysis and tabulation is also done accordingly.

Objectives The objectives of Annual Household Survey 2012-2013 are: • to estimate the label and structure of household consumption expenditure each year; • to measure unemployment and underemployment on yearly basis; • to collect information on the areas of demography, literacy, housing facilities etc; and • to create an annual database of household sector.

The survey is intended to support the National Accounts estimates, particularly of household sector. Moreover, the survey will explore the possibility of consumption based poverty measurement also.

Geographic coverage

The survey covers the whole country(National), Ecological belts( Mountain , Hill , Terai), rural and urban.

Analysis unit

Household and Induvisual

Universe

• All households in the country determined on the basis of the usual place of their residence (de jure househols). The households of diplomatic missions, the institutional households (like people living in schools hostels, prisons, army camps and hospitals) were excluded from the survey.
• All persons aged 5 years and above household members.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample frame from the National Population and Housing Census 2011 is being used for sampling of AHS 2012-2013. The Annual Household Survey 2012-2013 is the multi-stage random sampling design with equal PSUs or households distributed between urban and rural areas considering the heterogeneous labour force activities to provide a detailed picture of employment situation in the urban areas. So the prescribed 200 PSUs are divided equally in two parts, i.e., 100 PSUs each for urban and rural. The design has applied the concept of master sample frame. The sample size for the survey has been estimated at 3000 households in 200 Primary Sampling Units (PSUs). These 200 PSU shave been equally distributed between two study domains, viz. Urban Nepal and Rural Nepal. The PSUs were selected with Probability Proportional to Size, the measure of size being the square root of the number of households in each ward. Fifteen households were selected for the interview from each of the selected PSU using Systematic Sampling. The technical note of the sampling procedure is given at Appendix I of report AHS 2012-2013 .

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire of AHS 2012/13 survey contains five sections. The first section contains individual or demographic information. Section two, three and four includes on household consumption including housing and housing expenses, food expenses and home production, and non-food expenses, consumption of durables and own account production respectively. The last section deals with current economic activity or labour force. The food consumption part of the questionnaire has covered broad food categories only. The household consumption part of the questionnaire has been designed in line with that of Nepal Living Standards Survey. Likewise, for the labour force part, it has followed the structure of Nepal Labour Force Survey 2008, but in current basis only. A 16-paged household questionnaire with 5 sections and 4 appendices in Nepali language was administered in the AHS. The English translation of the questionnaire has been presented at Appendix II of AHS 2012/13 report.

Cleaning operations

Data entry and data verification of Annual Household Survey 2012-2013was conductaed at field. For this task, a simple and clear data entry programme was developed in CSPro software, and each team was given a personal computer having the entry program so that every team could be able to enter the interviewed household data in the respective field area. In other words, data entry and data verification work was done in the field residing in the corresponding PSU. Therefor both mannual and batch editing was carried out and CSPro programme wsa used for consistancy checking.

Response rate

The survey enumerated 1485 (99%) sample households from 99 PSUs out of 100 PSUs of rural area. As regards to urban sample, all 1500 (100%) sample household from 100 PSUs are interviewed. Thus, in total 2985 (99.5%) households were enumerated in the survey.

Abstract

The CSES is a household survey with questions to households and the household members. In the household questionnaire there are a number of modules with questions relating to the living conditions, e.g. housing conditions, education, health, expenditure/income and labour force. It is designed to provide information on social and economic conditions of households for policy studies on poverty, household production and final consumption for the National Accounts and weights for the CPI.

The main objective of the survey is to collect statistical information about living standards of the population and the extent of poverty. Essential areas as household production and cash income, household level and structure of consumption including poverty and nutrition, education and access to schooling, health and access to medical care, transport and communication, housing and amenities and family and social relations. For recording expenditure, consumption and income the Diary Method was applied for the first time. The survey also included a Time Use Form detailing activities of household members during a 24-hour period.

Another main objective of the survey is also to collect accurate statistical information about living standards of the population and the extent of poverty as an essential instrument to assist the government in diagnosing the problems and designing effective policies for reducing poverty, and in evaluating the progress of poverty reduction which are the main priorities in the "Rectangular Strategy" of the Royal Government of Cambodia.

Geographic coverage

National Phnom Penh/Other Urban/Other Rural Provinces/Groups of provinces

Analysis unit

Households

Individuals

Universe

All resident households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

In this section the sampling design and the sample selection for CSES 2009, is described. The sampling design for the 2009 survey is the same as that used for the CSES 2004. The sampling design for the 2004 CSES is described in for instance National Institute of Statistics (2005a).

The sampling frame for the 2009 survey is based on preliminary data from the General Population Census conducted in 2008. The sample is selected as a three stage cluster sample with villages in the first stage, enumeration areas in the second stage and households in the third.

The Sampling Frame

Preliminary data from the General Population Census 2008 was used to construct the sampling frame for the first stage sampling, i.e. sampling of villages. All villages except 'special settlements' were included in the frame. In all, the first stage sampling frame of villages consisted of 14,073 villages, see Appendix 1. Compared to previous years the frame used for the 2009 survey based on the census 2008 was more up to date than in previous surveys which were based on the population census 1998.

The following variables were used from the census; Province code, province name, district code, district name, commune code, commune name, village code, village name, urban-rural classification of villages, the number of households per village and, the number of enumeration areas in the village.

In the second-stage Enumeration Areas (EA) are selected in each selected village. In most villages only one EA was selected but in some large villages more than one was selected.

For the third stage, the sampling of households, a frame was constructed in field. For selected EAs the census map of the village, including EAs and residences, was given to enumerator who updated the map and listed the households in the selected EA. A sample of households was then selected from the list.

Stratification

The sampling frame of villages was stratified by province and urban and rural. There are 24 provinces and each village is classified as either urban or rural which means that in total we have 48 strata, see Appendix 1. Each stratum of villages was sorted by district, commune and village code.

Sampling

The sampling design in the CSES 2009 survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two. The sampling designs used in the three stages were:

Stage 1. A systematic pps sample of villages, Primary Sampling Units (PSUs) was selected from each stratum,

i.e. without replacement systematic sampling with probabilities proportional to size. The size measure used was the number of households in the village according to the sampling frame.

Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1.

As mentioned above, in a few large villages more than one EA was selected.

Stage 3. In each selected EA a sample of households was selected by systematic sampling.

The selection of villages and EAs were done at NIS while the selection of households in stage three was done in field. As mentioned in section 1.1 all households in selected EAs were listed by the enumerator. The sample of households was then selected from the list.

Sample sizes and allocation

The sample size of PSUs, were, as in the 2004 survey, 720 villages (or EAs). In urban villages 10 households were selected and in rural 20 households. In all 12,000 households were selected.

Urban and rural villages were treated separately in the allocation. The allocation was done in two steps. First the sample sizes for urban and rural villages in the frame were determined and then sample sizes for the provinces within urban and rural areas were determined, i.e. the strata sample sizes.

The total sample size was divided into to two, one sample size for urban villages and the other for rural villages. The calculation of the sample sizes for urban and rural areas were done using the proportion of consumption in the two parts of the population. Data on consumption from the CSES 2007 survey was used. The resulting sample sizes for urban villages was 240 and for rural 480. (Some adjustments of the calculated sample sizes were done, resulting in the numbers 240 and 480).

Allocation of the total sample size on the strata within urban and rural areas respectively, was done in the following way. The sample size, i.e. the number of PSUs, villages, selected from stratum h, is proportional to the number of households in stratum h, i.e.

n(Ih)=n1(Mh/Sum of Mh) (1.1)

where,

is the sample size in stratum h, i.e. the number villages selected in stratum h,

is the total sample size of villages for urban or rural villages,

H is the number of strata in urban or rural areas,

is the number of households in stratum h according to the frame.

As mentioned above, the sample size calculations are done separately for urban and rural villages, i.e. for strata with urban villages (1.1) is used with nI = 240 and is the number of households in urban villages in the frame and for rural villages (1.1) is used with nI = 480 and is the

number of households in rural villages in the frame.

Monthly samples

In section 1.3 the selection of the annual sample was described. The annual sample was divided into 12 monthly samples of equal sizes. The monthly samples consisted of 20 urban and 40 rural villages. The division of the annual sample into monthly samples was done so that as far as possible each province would be represented in each monthly sample. Since the sample size of villages in some provinces is smaller than 12, all provinces were not included in all monthly samples. Also, the outline of the fieldwork with teams of 4 enumerators and one supervisor puts constraints on how to divide the annual sample into monthly samples. The supervisors must travel between the villages in a team and therefore the geographical distance between the villages surveyed by a team cannot be too large.

Estimation

Totals, ratios such as means or proportions were estimated for the population or for subgroups of population, i.e. domains of study. The domains were defined by e.g. region or sex. Means and proportions were estimated by first estimating totals and then calculating the ratio of two estimated totals. To estimate totals from a sample survey weights are needed.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four different questionnaires or forms were used in the survey:

1. Household listing form

The Household listing and mapping were done prior to the sampling. During the household listing the enumerator recorded household information on e.g. location, number of members and principal economic activity.

1. Village questionnaire

The Village questionnaire was used to gather basic common information on:

    1. Demographic information

    2. Economy & Infrastructure

    3. Rainfall & Natural disasters

    4. Education

    5. Health

    6. Retail prices (food and non-food items)

    7. Employment & Wages

    8. Access to common property resources during the last 5 years

    9. Sale prices of agricultural land in the village

    10. Recruitment of children for work outside the village 

1. Household questionnaire

The following modules were included in the Household questionnaire:

1. Initial visit

01A. List of household member

01B. Food, beverages and tobacco consumption during the last 7 days

01C. Recall non-food expenditures

01D. Vulnerability

1. Education & Literacy

2. Information on migration (includes past and current migration)

   1. Housing

3. Household economic activities

05A.Land ownership

05B.Production of

Graph and download economic data for Employed Persons in Washington County, WI (LAUCN551310000000005) from Jan 1990 to Jun 2025 about Washington County, WI; Milwaukee; WI; persons; household survey; employment; and USA.

Survey on the use of water to mitigate heat in households in Jakarta

Abstract

Agriculture statistics are useful for monitoring progress on agriculture programs and policies in Rwanda. The government of Rwanda needs updated information on agricultural household in order to assist in addressing key agricultural issues and information needs that will inform policy makers and other stakeholders and allow more effective identification of priority intervention needs and to facilitate evidence-based decision making for the development of Agriculture sector.

Geographic coverage

National coverage

Analysis unit

Households

Universe

All household members

Kind of data

Sample survey data [ssd]

Sampling procedure

In order to provide the basis for conducting sample surveys based on complete coverage of the household level in all 30 districts of Rwanda, and as a better way of collecting agricultural household data and finding better precise survey estimates, agricultural household survey(AHS) used a Multiple-Frame Sampling (MFS) methodology by which, area frame was constructed and survey sample was drawn from it.

In the sampling strategy of the SAS 2017, it was proposed that 960 PSUs be selected in the first instance by systematic sampling method with probability proportional to size. At the second stage the sampled PSUs were divided into SSUs among which only one SSUs was sampled at random for each PSU and used for the survey. 960 segments were drawn from three agricultural strata including intensive agriculture land on hillsides (stratum 1.1), intensive agriculture land in marshlands (stratum 2.0), rangelands (stratum 3.0). Using the open segment obliges to include urban strata in the sampling frame. Apart from stated strata, village stratum which combines two substrata; urban area (stratum 4.1) rural settlements (stratum 4.2) was added to the sample frame. This stratum was divided into segments and a sample of 600 segments was drawn by systematic sampling method.

It should be mentioned that the Stratum 4.1 and 4.2 were specially added to the purpose of having a complete sampling frame for estimation of livestock since a major portion of livestock are associated with households located in villages and rural urban area adjacent to grazing land that had previously been missing for all of the previous SAS area sampling frames. This survey was conducted among private agricultural households, in 4 strata used in Seasonal agricultural survey. Households were listed from the 1,560 sampled segments in the country. Among the listed households 16,057 households were found the ones applying agricultural activities. A single visit was done in every identified agricultural household and the information collected covered two agricultural seasons A and B of 2017 agricultural year.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Listing questionnaire was used to list all households inside the segment.

Agricultural household questionnaire was used to collect data in agricultural households and contained twelve sections: Section 0. General information Section I: Household member's characteristics Section II: land tenure and crops planted during agricultural year 2016-2017 agricultural year Section III: extension services and agricultural programs in 2016-2017 agricultural year Section IV: funding during 2016-2017 agricultural year Section V: agricultural inputs during 2016-2017 agricultural year Section VI: agricultural practices during 2016-2017 agricultural year Section VII: agricultural tools during 2016-2017 agricultural year Section VIII: Use of production, storage facilities and expenses on harvesting and storage during 2016-2017 agricultural year Section IX: number of animals Section X: animal's products and use Section XI: animal inputs and services

Questionnaire design took into account the requests raised by major data users and stakeholders, it was developed in English then translated into Kinyarwanda for data collection, All the sections of the questionnaire were published in English.

Cleaning operations

The questionnaire was designed in CSPro software to facilitate electronic data collection. Tablets were used to collect data

Data editing took place at a number of stages throught the processing, including: a) During data entry b) Office editing and coding c) Structure checking and completeness.

Abstract

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).

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Children under 5 years
• Consumption expenditure commodities/items
• Communities
• Agricultural household/ Holder/ Crop

Universe

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.

Kind of data

Sample survey data [ssd]

Sampling procedure

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.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey was collectd using four questionnaires: 1) Household Questionnaire 2) Agriculture Questionnaire 3) Fishery Questionnaire 4) Community Questionnaire

Cleaning operations

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.

The Nepal Population-Based Survey (PBS) provides a comprehensive assessment of the current status of agriculture and food security in 20 districts across the western, mid-western and far-western development regions of the country. This file reports data reported by women survey participants.

The Bangladesh Integrated Household Survey dataset is the baseline for the USAID-led Feed the Future program in Bangladesh. Access the data by downloading the zip file in the Source Link field.