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 copyright UK Data Service and data collection copyright owner.

The General Household Survey (GHS), ran from 1971-2011 (the UKDS holds data from 1972-2011). It was a continuous annual national survey of people living in private households, conducted by the Office for National Statistics (ONS). The main aim of the survey was to collect data on a range of core topics, covering household, family and individual information. This information was used by government departments and other organisations for planning, policy and monitoring purposes, and to present a picture of households, families and people in Great Britain. In 2008, the GHS became a module of the Integrated Household Survey (IHS). In recognition, the survey was renamed the General Lifestyle Survey (GLF). The GLF closed in January 2012. The 2011 GLF is therefore the last in the series. A limited number of questions previously run on the GLF were subsequently included in the Opinions and Lifestyle Survey (OPN).

Secure Access GHS/GLF
The UKDS holds standard access End User Licence (EUL) data for 1972-2006. A Secure Access version is available, covering the years 2000-2011 - see SN 6716 General Lifestyle Survey, 2000-2011: Secure Access.

History
The GHS was conducted annually until 2011, except for breaks in 1997-1998 when the survey was reviewed, and 1999-2000 when the survey was redeveloped. Further information may be found in the ONS document An overview of 40 years of data (General Lifestyle Survey Overview - a report on the 2011 General Lifestyle Survey) (PDF). Details of changes each year may be found in the individual study documentation.

EU-SILC
In 2005, the European Union (EU) made a legal obligation (EU-SILC) for member states to collect additional statistics on income and living conditions. In addition, the EU-SILC data cover poverty and social exclusion. These statistics are used to help plan and monitor European social policy by comparing poverty indicators and changes over time across the EU. The EU-SILC requirement was integrated into the GHS/GLF in 2005. After the closure of the GLF, EU-SILC was collected via the Family Resources Survey (FRS) until the UK left the EU in 2020.

Reformatted GHS data 1973-1982 - Surrey SPSS Files
SPSS files were created by the University of Surrey for all GHS years from 1973 to 1982 inclusive. The early files were restructured and the case changed from the household to the individual with all of the household information duplicated for each individual. The Surrey SPSS files contain all the original variables as well as some extra derived variables (a few variables were omitted from the data files for 1973-76). In 1973 only, the section on leisure was not included in the Surrey SPSS files. This has subsequently been made available, however, and is now held in a separate study, General Household Survey, 1973: Leisure Questions (SN 3982). Records for the original GHS 1973-1982 ASCII files have been removed from the UK Data Archive catalogue, but the data are still preserved and available upon request.

For the third edition of the study (July 2002), the depositor has supplied a retrospectively-calculated household weighting variable, WEIGHT96. This has been added to the household file, househld.por. The documentation is unchanged.


Main Topics:

The main GHS consisted of a household questionnaire, completed by the Household Reference Person (HRP), and an individual questionnaire, completed by all adults aged 16 and over resident in the household. A number of different trailers each year covering extra topics were included in later (post-review) surveys in the series from 2000.

• The household questionnaire covered the following topics: household information, accommodation type, housing tenure/costs, and consumer durables including vehicle ownership.
• The individual questionnaire included data from the household dataset, and additional sections on migration/citizenship/national identity/ethnicity, employment, pensions, education, health, child care, smoking, drinking, family information, financial situation, and income.
  

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

Within the frame of PCBS' efforts in providing official Palestinian statistics in the different life aspects of Palestinian society and because the wide spread of Computer, Internet and Mobile Phone among the Palestinian people, and the important role they may play in spreading knowledge and culture and contribution in formulating the public opinion, PCBS conducted the Household Survey on Information and Communications Technology, 2014.

The main objective of this survey is to provide statistical data on Information and Communication Technology in the Palestine in addition to providing data on the following: -

· Prevalence of computers and access to the Internet. · Study the penetration and purpose of Technology use.

Geographic coverage

Palestine (West Bank and Gaza Strip) , type of locality (Urban, Rural, Refugee Camps) and governorate

Analysis unit

Household. Person 10 years and over .

Universe

All Palestinian households and individuals whose usual place of residence in Palestine with focus on persons aged 10 years and over in year 2014.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame The sampling frame consists of a list of enumeration areas adopted in the Population, Housing and Establishments Census of 2007. Each enumeration area has an average size of about 124 households. These were used in the first phase as Preliminary Sampling Units in the process of selecting the survey sample.

Sample Size The total sample size of the survey was 7,268 households, of which 6,000 responded.

Sample Design The sample is a stratified clustered systematic random sample. The design comprised three phases:

Phase I: Random sample of 240 enumeration areas. Phase II: Selection of 25 households from each enumeration area selected in phase one using systematic random selection. Phase III: Selection of an individual (10 years or more) in the field from the selected households; KISH TABLES were used to ensure indiscriminate selection.

Sample Strata Distribution of the sample was stratified by: 1- Governorate (16 governorates, J1). 2- Type of locality (urban, rural and camps).

Sampling deviation

-

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire consists of identification data, quality controls and three main sections: Section I: Data on household members that include identification fields, the characteristics of household members (demographic and social) such as the relationship of individuals to the head of household, sex, date of birth and age.

Section II: Household data include information regarding computer processing, access to the Internet, and possession of various media and computer equipment. This section includes information on topics related to the use of computer and Internet, as well as supervision by households of their children (5-17 years old) while using the computer and Internet, and protective measures taken by the household in the home.

Section III: Data on persons (aged 10 years and over) about computer use, access to the Internet and possession of a mobile phone.

Cleaning operations

Preparation of Data Entry Program: This stage included preparation of the data entry programs using an ACCESS package and defining data entry control rules to avoid errors, plus validation inquiries to examine the data after it had been captured electronically.

Data Entry: The data entry process started on 8 May 2014 and ended on 23 June 2014. The data entry took place at the main PCBS office and in field offices using 28 data clerks.

Editing and Cleaning procedures: Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

Response rate

Response Rates= 79%

Sampling error estimates

There are many aspects of the concept of data quality; this includes the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are three components to the quality of statistics: accuracy, comparability, and quality control procedures.

Checks on data accuracy cover many aspects of the survey and include statistical errors due to the use of a sample, non-statistical errors resulting from field workers or survey tools, and response rates and their effect on estimations. This section includes:

Statistical Errors Data of this survey may be affected by statistical errors due to the use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators.

Variance calculations revealed that there is no problem in disseminating results nationally or regionally (the West Bank, Gaza Strip), but some indicators show high variance by governorate, as noted in the tables of the main report.

Non-Statistical Errors Non-statistical errors are possible at all stages of the project, during data collection or processing. These are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous efforts were made to train the field workers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, and practical and theoretical training took place during the training course. Training manuals were provided for each section of the questionnaire, along with practical exercises in class and instructions on how to approach respondents to reduce refused cases. Data entry staff were trained on the data entry program, which was tested before starting the data entry process.

Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

The sources of non-statistical errors can be summarized as: 1. Some of the households were not at home and could not be interviewed, and some households refused to be interviewed. 2. In unique cases, errors occurred due to the way the questions were asked by interviewers and respondents misunderstood some of the questions.

Abstract

The objectives of the Smallholder Household Survey in Bangladesh 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 Bangladesh 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
• 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

Analysis unit

Households

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 2) Agriculture provides a meaningful contribution to the household livelihood, income, or consumption.

Kind of data

Sample survey data [ssd]

Sampling procedure

(a) SAMPLING FRAME

The smallholder household survey in Bangladesh 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. Bangladesh is divided into 7 administrative divisions. Each division is divided into districts, sub-districts, wards (for urban areas) or unions (for rural areas). Each ward is further divided into mahallas while each union consists of mauzas. For the 2008 agricultural census, mauzas and mahallas were further divided into 153,945 enumeration areas (EAs). The Bangladesh Bureau of Statistics maintains a list of 64,314 mauzas/mahallas. Among these, 750 mauzas/mahallas (i.e., 1.2% of the total number) have missing information on the number of agricultural households they contained in 2008. In addition, 18,377 mauzas/mahallas had less than 80 agricultural households. These mauzas/mahallas contain about 4.8% of the total number of agricultural households. The sampling frame for the smallholder survey consisted of the list of EAs for mauzas/mahallas containing at least 80 agricultural households in 2008. While at the mauza/mahalla level the number of agricultural households was available, at the EA level only the estimated number of (general) households was available along with the urban-rural classification.

(b) SAMPLE ALLOCATION AND SELECTION

To take nonresponse into account, the target sample size was increased to 3,158 households assuming a nonresponse rate of five percent observed in similar national household surveys. The total sample size was first allocated to the divisions based on the number of agricultural households in the sampling frame. Within each division, the resulting sample was then distributed to urban and rural areas in proportion to number of agricultural households. Given that EAs were the primary sampling units and 15 households were selected in each EA, a total of 211 EAs were selected. The sample for the smallholder survey is a stratified multistage sample. Stratification was achieved by separating each division into urban and rural areas. The urban/rural classification is based on the 2008 agricultural census. Therefore, 14 strata were created, and the sample was selected independently in each stratum.

In the first stage, EAs were selected as primary sampling units with probability proportional to size, the size being the number of households in the EAs. Prior to the selection, in each stratum, the list of EAs was sorted by district, sub-district, wards/unions, and mauzas/mahallas. A household listing operation was conducted in all selected EAs to identify smallholder households and to provide a frame for selecting smallholder households to be included in the sample. In the second stage, 15 smallholders were sampled in each EA with equal probability. In each sampled household, the household questionnaire was administered to the head of the household, the spouse, or any knowledgeable adult household member to collect information about household characteristics. The multiple respondent questionnaire was administered to all adult members in each sampled household to collect information on their agricultural activities, financial behaviours, and mobile money use. In addition, in each sampled 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.

Sampling deviation

The smallholder survey in Bangladesh is the fourth survey in the series, following the surveys in Mozambique, Uganda, and Tanzania. Fieldwork in those three countries has experienced a lot of failed call backs where identified eligible households and household members could not be interviewed during the time allocated to fieldwork in each country. As a result, the final sample size fell slightly short of the target. For this reason, in Bangladesh the number of households selected in each EA was increased from 15 to 17 following the household listing operation in all sampled EAs.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

The data files were checked for completeness, inconsistencies and errors by InterMedia and corrections were made as necessary and where possible. Following the finalization of questionnaires, a script was developed to support data collection on smart phones. The script was thoroughly tested and validated before its use in the field.

Response rate

100 percent for single respondent questionnare, 99.7 percent for household questionnaire and 96.4 percent for the Multiple Respondent questionnaire.

Sampling error estimates

The sample design for the smallholder household survey was a complex sample design featuring clustering, stratification and unequal probabilities of selection. For key survey estimates, sampling errors considering the design features were produced using either the SPSS Complex Sample module or STATA based on the Taylor series approximation method.

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.

Abstract

The objective of the Pakistan Integrated Household Survey (PIHS), a national sample survey, is to provide household and community level data which can be used to monitor, evaluate, and assess the impact of Social Action Program (SAP). Policymakers need to know; whether the poor have benefited from the program or whether increased government expenditure on the social sectors has been captured by the better off. In order to do this, a measure of living standards is needed so that benefits from public investment in social services can be compared across different income groups. For this purpose, PIHS includes a measure of household consumption (expenditure on goods and services) against which many of the outcome variables are tabulated. More generally, data collected in this survey also provides a valuable data base that can also be used to carry out research on a wide range of topics and issues.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Universe

The universe of PIH Survey consists of all urban and rural areas of all four provinces, Azad Jammu and Kashmir, FATA and Northern Areas as defined by the Provincial Governments. Military restricted areas have been excluded from the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame:

Separate sampling frames have been used in the survey for urban areas and rural areas as under.

Urban area:

FBS has developed its own urban area frame. This frame has been developed adopting Quick Count Record Survey techniques. According to this method, all urban areas know as cities/towns of the urban domain of the sampling frame have been divided into small compact areas known as enumeration blocks (E.Bs). Each enumeration block comprises about 200-250 households. Each Enumeration block has been divided into low, middle and high-income group, keeping in view the status of the majority of households. It will be used for drawing samples from the urban areas. There are 22800 enumeration blocks in all urban areas of the country.

Rural areas:

With regard to the rural areas, the lists of villages/mouzas/dehs according to population Census, 1998 have been used as sampling frame. In this frame, each village/mouza/deh is identifiable by its name, Had Bast number and Cadastral map etc. There are 50,588 mouzas/villages/dehs in the rural sub-universe of the survey

Sample size and its Allocation:

In view of the variability for the characteristics for which estimates are prepared, population distribution, field resources available and reliability constraints a sample size of 1,6400 households was considered appropriate to provide reliable estimates of key characteristics. The entire sample of households ((SSUs) has been drawn from 1150 Primary Sampling Units (SSUs) out of which 500 are urban and 650 are rural. This sample size has been considered sufficient to produce estimates of key variables at national and provincial level at 95% level of confidence with 5% to 7% margin of error. Due to security situation prevailing in FATA, 8 sample villages were not enumerated. Similarly, 90 sample households were not covered due to non-response/closed/non-contact and non-cooperation from the respondents in this Survey.The total number of sampling units covered is tabulated on page 21 of the HIES report

Stratification Plan:

Stratification scheme is adopted keeping in view the geographical level of estimates to be built-up and to control the variation in the under study characteristics of the survey population.The detail of the scheme is as under.

Urban Area:

With respect to the urban areas each of Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Sialkot, Sargodha, Bahawalpur, Hyderabad, Sukkur, Peshawar, Quetta and Islamabad being large size cities have been treated as independent stratum. Each of these cities has further been substratified according to low, middle, high-income groups based on the information collected in respect of each enumeration block. After excluding the population of large sized cities the remaining urban population in each defunct administrative division in all provinces has been grouped and treated as an independent stratum. Each of Azad Jammu & Kashmir, FATA and Northern Areas has been considered as independent strata separately.

Rural Area:

In the rural areas, the population of each district in Punjab, Sindh and N.W.F.P Provinces has been grouped together to constitute a stratum. For Balochistan province each of defunct administrative Division has been taken as a stratum. Azad Jammu & Kashmir FATA and Northern Areas have been considered as independent strata in rural areas separately.

Sample Design:

A two-stage stratified sample design has been adopted for this survey.

Selection of primary sampling Units (PSUs): Enumeration blocks in the urban domain and mouzas/dehs/villages in rural domain have been taken as primary sampling units (PSUs). Sample PSUs from each ultimate stratum/sub-stratum have been selected by probability proportional to size (PPS) method of sampling scheme. In this survey population of rural areas and households for urban areas have been adopted as measure of size for selecting Primary Sampling Units (PSUs) from the strata/ sub-strata formed in urban and rural subuniverses of the survey.

Selection of Secondary Sampling Units (SSUs): Households within each sample Primary Sampling Units (PSU) have been considered as secondary sampling units (SSUs). 16 and 12 households have been selected from each sample village and enumeration block respectively by random systematic sampling scheme with a random start.

Mode of data collection

Face-to-face [f2f]

Research instrument

The HIES questionnaire, revised to reflect integration with PIHS and improved data collection methods were used for the 2001-02 survey i.e. Income and Expenditure (Round- IV of PIHS). The questionnaire was split into two modules in order to obtain better quality of information separately from male and female respondents by the male and female enumerators respectively. Specifically, minor changes were made in the part containing the consumption expenditure items. To obtain the better quality of data from the well-informed female respondents, the relevant parts of consumption expenditure of food and non-food items have been included in the female part of the questionnaire. Information which is considered to be answered better by the male household respondents is included in the male part of the questionnaire. The structure of the new PIHS / HIES questionnaire used in 1998-99 and 2001-02 is shown in table 1.3 of the Survey Report

Response rate

90 sample households were not covered due to non-response/closed/non-contact and non-cooperation from the respondents in this Survey

Abstract

Panel data possess several advantages over conventional cross-sectional and time-series data, including their power to isolate the effects of specific actions, treatments, and general policies often at the core of large-scale econometric development studies. While the concept of panel data alone provides the capacity for modeling the complexities of human behavior, the notion of universal panel data – in which time- and situation-driven variances leading to variations in tools, and thus results, are mitigated – can further enhance exploitation of the richness of panel information.

The Basic Information Document (BID) provides a brief overview of the Nigerian General Household Survey (GHS) but focuses primarily on the theoretical development and application of panel data, as well as key elements of the universal panel survey instrument and datasets generated by the four rounds of the GHS. As the BID does not describe in detail the background, development, or use of the GHS itself, the wave-specific GHS BIDs should supplement the information provided here.

The Nigeria Universal Panel Data (NUPD) consists of both survey instruments and datasets from the two survey visits of the GHS - Post-Planting (PP) and Post-Harvest (PH) - meticulously aligned and engineered with the aim of facilitating the use of and improving access to the wealth of panel data offered by the GHS. The NUPD provides a consistent and straightforward means of conducting user-driven analyses using convenient, standardized tools.

The design of the NUPD combines the four completed Waves of the GHS Household Post-Planting and Post-Harvest Surveys – Wave 1 (2010/11), Wave 2 (2012/13), Wave 3 (2015/16), and Wave 4 (2018/19) – into pooled, module-specific survey instruments and datasets. The panel survey instruments offer the ease of comparability over time, with modifications and variances easily identifiable as well as those aspects of the questionnaire which have remained identical and offer consistent information. By providing all module-specific data over time within compact, pooled datasets, panel datasets eliminate the need for user-generated merges between rounds and present data in a clear, logical format, increasing both the usability and comprehension of complex data.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

Please see the GHS BIDs for each round for detailed descriptions of the sample design used in each round and their respective implementation efforts as this is a compilation of datasets from all previous waves.

Mode of data collection

Face-to-face [f2f]

Research instrument

The larger GHS-Panel project consists of three questionnaires (Household Questionnaire, Agriculture Questionnaire, Community Questionnaire) for each of the two visits (Post-Planting and Post-Harvest). The GHS-NUPD only consists of the Household Questionnaire.

GHS-Panel Household Questionnaire: The Household Questionnaire provides information on demographics; education; health (including anthropometric measurement for children); labor; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; and other sources of household income.

The Household Questionnaire is slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.

Cleaning operations

Please see the GHS BIDs for each round for detailed descriptions of data editing and additional data processing efforts as this is a compilation of datasets from all previous waves.

Abstract copyright UK Data Service and data collection copyright owner.

The English Housing Survey (EHS) is a continuous national survey commissioned by the Ministry of Housing, Community and Local Government (MHCLG) that collects information about people's housing circumstances and the condition and energy efficiency of housing in England. The EHS brings together two previous survey series into a single fieldwork operation: the English House Condition Survey (EHCS) (available from the UK Data Archive under GN 33158) and the Survey of English Housing (SEH) (available under GN 33277). The EHS covers all housing tenures. The information obtained through the survey provides an accurate picture of people living in the dwelling, and their views on housing and their neighbourhoods. The survey is also used to inform the development and monitoring of the Ministry's housing policies. Results from the survey are also used by a wide range of other users including other government departments, local authorities, housing associations, landlords, academics, construction industry professionals, consultants, and the general public.

The EHS has a complex multi-stage methodology consisting of two main elements; an initial interview survey of around 12,000 households and a follow-up physical inspection. Some further elements are also periodically included in or derived from the EHS: for 2008 and 2009, a desk-based market valuation was conducted of a sub-sample of 8,000 dwellings (including vacant ones), but this was not carried out from 2010 onwards. A periodic follow-up survey of private landlords and agents (the Private Landlords Survey (PLS)) is conducted using information from the EHS interview survey. Fuel Poverty datasets are also available from 2003, created by the Department for Energy and Climate Change (DECC).

The EHS interview survey sample formed part of the Integrated Household Survey (IHS) (available from the Archive under GN 33420) from April 2008 to April 2011. During this period the core questions from the IHS formed part of the EHS questionnaire.

End User Licence and Special Licence Versions:
From 2014 data onwards, the End User Licence (EUL) versions of the EHS will only include derived variables. In addition the number of variables on the new EUL datasets has been reduced and disclosure control increased on certain remaining variables. New Special Licence versions of the EHS will be deposited later in the year, which will be of a similar nature to previous EHS EUL datasets and will include derived and raw datasets.

Further information about the EHS and the latest news, reports and tables can be found on the GOV.UK English Housing Survey web pages.

The English Housing Survey, 2017-2018: Household Data comprises the derived interview data for all cases where an interview has been completed. Datasets are provided for single financial years together with annual weights. The survey consists of a detailed interview using a CAPI based program. An interview is first conducted with the householder. General topics and concepts covered include household characteristics, satisfaction with the home and the area, disability and adaptations to the home, ownership and rental details and income details.

The household data should be used for any analysis where only information from the household interview is required. Users who also require data from the physical survey should use the English Housing Survey, 2017: Housing Stock Data (SN 8494).

Main Topics:

The main topics covered include: general tenure and demographics; household income and housing costs; housing needs; housing aspirations and satisfaction; housing moves; and vulnerable and disadvantaged households.

Abstract

The primary objective of the Continuous Multi-Purpose Household Survey is to provide a permanent platform for the collection of data to compile socio-economic indicators to keep track of development in the country.

Geographic coverage

The survey had national coverage

Analysis unit

Households and individuals

Kind of data

Sample survey data

Mode of data collection

Face-to-face [f2f]

Research instrument

The Continuous Multi-Purpose Household Survey questionnaire included sections for collecting data on: 1) Household characteristics 2) Demographic and health characteristics of household members 3) Educational characteristics of household members 4) Labour force data of household members 5) Women 6) Elderly 7) Income and expenditure of the household

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.

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 main objectives of the Households Survey about Information and Communications Technology, 2006 is to provide statistical data on Information and Communication Technology for the Palestinian Households in the Palestinian Territory; in particular to provide statistical data on the possession telecommunication means, prevalence of computers and access to the Internet, possession and Use of Recreation Devices.

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and governorates

Analysis unit

Household, individual

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size is, 4609 households of which 3,109 households in the West Bank and 1,500 households in Gaza Strip.

The sampling frame is the list of enumeration areas peculiar to the 1997 Population, Housing and Establishment Census. Enumeration areas are residential areas containing about 150 housing units in average.

The sample strata have been designed on two levels: 1) First level: the governorate (16 governorates). 2) Second level: type of locality (urban, rural and camps).

The second stage was the selection of a systematic random sample of households within each selected area counted in the first phase, and 16 households on average were selected from the enumeration area. The third stage was the selection of an individual 10 years and over from the household, and Kish tables were used in the process of selecting the individual from the household to ensure randomness.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionnaire for the Information and Communications Households Survey, 2006, consists of three parts:

The First Part: It is composed of the following:- First Section: It is composed of identification data, quality control criteria, households members data that include data on demographic, social and economic characteristics such as: age, sex, refugee status, education and main profession.

Second Section: Data on characteristics of housing.

The Second Part: household Questionnaire: It is composed of questions about computer possessing, access to the Internet, having telecommunication means, households expenses on (ICT) available services, and use of recreation devices.

The Third Part: Questionnaire of Persons aged (10 years and over): Use of Computer, access to the Internet, having Mobil Phone, expenses on (ICT) Services available, Self-Propelled Automatic Messages (SPAM).

Cleaning operations

Data editing took place at a number of stages through the processing including:

1. office editing and coding
2. during data entry
3. structure checking and completeness
4. structural checking of SPSS data files

Response rate

The survey sample consists of about 4609 households of which 3,975 households completed the interview; whereas2,614households from the West Bank and1,361households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached84.1% while in the Gaza Strip it reached 90.7%. The response rate in the Palestinian Territory reached 86.2%.

Sampling error estimates

Detailed information on the sampling Error is available in the Survey Report.

Data appraisal

Detailed information on the data appraisal is available in the Survey Report.

Abstract

The General Household Survey is a brainchild of the National Bureau of Statistics (NBS) and is often referred to as Regular survey carried out on quarterly basis by the NBS over the years. In recent times, starting from 2004 to be precise, there is a collaborative effort between the NBS and the CBN in 2004 and 2005 and in 2006, 2007and 2008, the collaboration incorporated Nigerian Communications commission (NCC).

The main reason for conducting the survey was to enable the collaborating agencies fulfil their mandate in the production of current and credible statistics, to monitor and evaluate the status of the economy and the various government programmes such as the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals (MDGs).

The collaborative survey also assured the elimination of conflicts in data generated by the different agencies and ensured a reliable, authentic national statistics for the country.

Geographic coverage

National Coverage

Analysis unit

Household

Universe

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The GHS was implemented as a NISH module. Six replicates were studied per state including the FCT, Abuja. With a fixed-take of 10 HUs systematically selected per EA, 600 HUs thus were selected for interview per state including the FCT, Abuja. Hence, nationally, a total of 22,200 HUs were drawn from the 2,220 EAs selected for interview for the GHS. The selected EAs (and hence the HUs) cut across the rural and urban sectors.

The General Household Survey and the National Agricultural Sample Survey designs derived from NBS 2007/12 NISH sample design. The 2007/12 NISH sample design is a 2-stage, replicated and rotated cluster sample design with Enumeration Areas (EAs) as first stage sampling units or Primary Sampling Units (PSUs) while Housing Units constituted the second stage units (secondary sampling units). The housing units were the Ultimate Sampling Units for the multi-subject survey.

First Stage Selection: Generally, the NISH Master Sample in each state is made up of 200 EAs drawn in 20 replicates. A replicate consists of 10 EAs. Replicates 4 - 9, subsets of the Master Sample were studied for modules of the NISH. Sixty EAs were selected with equal probability from the list of EAs in each state of the federation and FCT, Abuja.

Second Stage Selection: In each selected EA, a listing of housing units was carried out. The result provided the frame for the second stage selection. Ten housing units were selected systematically in each EA after the completion of the listing exercise. Thereafter, all the households within the selected HUs were interviewed using GHS questionnaire.

At EAs level, out of the expected 2,220 EAs, 2,204 were covered. (by the table on page 177 of the report) and TABLE 1.6 RETRIEVAL STATUS OF GHS RECORDS

At housing unit level, out of the 22,200 expected to be covered, 21,796 were canvassed. (same as above)

AS PER DATA SET At EAs level, out of the expected 2,220 EAs 2,204 were covered. At housing unit level, out of the 22,200 expected to be covered, 18,355 were canvassed.

Sampling deviation

Variance Estimate (Jackknife Method) Estimating variances using the Jackknife method will require forming replicate from the full sample by randomly eliminating one sample cluster [Enumeration Area (EA) at a time from a state containing k EAs, k replicated estimates are formed by eliminating one of these, at a time, and increasing the weight of the remaining (k-1) EAs by a factor of k/(k-1). This process is repeated for each EA.

For a given state or reporting domain, the estimate of the variance of a rate, r, is given by k Var(r ) = (Se)2 = 1 S (ri - r)2 k(k-1) i=1

where (Se) is the standard error, k is the number of EAs in the state or reporting domain.

r is the weighted estimate calculated from the entire sample of EAs in the state or reporting domain.
ri = kr - (k - 1)r(i), where

r(i) is the re-weighted estimate calculated from the reduced sample of k-1 EAs.

To obtain an estimate of the variance at a higher level, say, at the national level, the process is repeated over all states, with k redefined to refer to the total number of EAs (as opposed to the number in the states).

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the GHS is a structured questionnaire based on household characteristics with some modifications and additions. The House project module is a new addition and some new questions on ICT.

The questionnaires were scanned.

This section were divided into eleven parts.

Part A: Identification code, Response status, Housing characteristics/amenities and Information communication Technology (ICT). Part B: Socio-demographic characteristics and Labour force characteristics Part C: Information about the people in the household who were absent during the period of the survey. Part D: Female contraceptive only, and children ever born by mothers aged 15 years and above Part E: Births of children in the last 12 months, and trained birth attendant used during child delivery. Part F: Immunization of children aged 1 year or less and records of their vaccination Part G: Child nutrition, exclusive breast feeding and length of breast feeding. Part H: Deaths in the last 12 months, and causes of such deaths. Part I: Health of all members, of the household and health care providers. Part J: Household enterprises, income and profit made from such activities. Part K: Household expenditure, such as school fees, medical expenses, housing expenses, remittance, cloth expenses, transport expenses and food expenses.

Cleaning operations

The data editing is in 2 phases namely manual editing before the questionnaires were scanned. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire.

The second editing is the computer editing, this is the cleaning of the already scanned data by the subject matter group. The questionnaires were processed at the zones. On completion, computer editing was also carried out to ensure the integrity of the data. .

Response rate

At National basis, 99.3 percent response rate was acheived at EA level .

While 82.7 percent was acheived at housing units level.

Sampling error estimates

No sampling error estimate

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were three levels of supervision involving the supervisors at the first level, CBN staff, NBS State Officers and Zonal Controllers at second level and finally the NBS/NCC Headquarters staff constituting the third level supervision.

Abstract

The Bosnia and Herzegovina Multiple Indicator Cluster Survey 2000 (B&H MICS 2000) is a nationally representative survey of households, women and children (aged 0 – 18 years). The main objectives of the survey were to provide up-to-date information for assessing the situation of children and women in Bosnia and Herzegovina at the end of the decade, and to furnish the data needed for monitoring progress toward the goals established at the World Summit for Children and as a basis for future action. Data on breast-feeding and salt iodination are available from previous UNICEF supported surveys. 1-4 Data on the remaining End of Decade Goals are available from other sources and are presented in the Bosnia and Herzegovina End of Decade Report. The B&H MICS 2000 survey covered the territory of Bosnia and Herzegovina minus the district of Brèko. This was omitted for sampling and organisational reasons. The survey was carried out in mid 2000 in a joint process with input from two entity field teams, from the Federation of Bosnia and Herzegovina and Republika Srpska. State level and entity level data are presented in this report. The survey sampled 10 772 households across the territory with a very high response rate of 98 percent. A total of 35 571 people lived in the households that responded, making this the largest such survey conducted in Bosnia and Herzegovina in the past ten years. The level of completion of the questionnaires was very high, and the data was subjected to multiple quality checks at all stages of the survey.

Geographic coverage

The B&H MICS 2000 survey covered the territory of Bosnia and Herzegovina minus the district of Brèko. This was omitted for sampling and organisational reasons.

Analysis unit

Household, Women, Children

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the survey was designed to provide estimates of the indicators at the national level, for urban and rural areas, and for the two entities - the Federation ofBosnia and Herzegovina and Republika Srpska. The district of Brèko in the North East corner of the State was not included in the survey, due to organisational and statistical sampling difficulties. Developing a sampling frame was perhaps the single biggest challenge in this survey. The most recent complete census data were from 1991. Subsequently, there had been widespread conflict and massive population movements both within and from the state. A two stage sampling method was used and this is explained in detail in Appendix C of the final report.

Stage 1

The geographical area of Bosnia and Herzegovina (with the exception of Brèko district) was selected. The enumeration areas from the 1991 census were taken as the basis for developing the sampling frame. This was updated in the Federation using three additional sources of information, the OSCE voter lists, population estimates from UNHCR and municipality registration data. Additionally, the sampling frame was adjusted in RS using the results of a 1997 census of refugees and displaced people. The entire geographical area of the survey was then divided into segments using probability proportional to size at the municipality level. Each segment covered approximately 110 households. The segments were then randomly selected and an additional number of alternate segments were identified so that in the case of a segment being unusable (empty, mined etc.) an alternate segment could be assigned.

Stage 2

The fieldwork teams then went to their allocated segments and made a listing of all households in each segment. From these, the fieldwork supervisors with assistance from the entity statistical institutes updated the old maps if necessary, and in some cases made new maps. Where segments were empty of households, had fewer than 80 households or were heavily mined, they were excluded and an alternate segment selected from the reserve list. Adjustments to the sampling plan are described in detail in Appendix C of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The three questionnaires (household, women aged 15 - 49 and children under the age of five) for the B&H MICS 2000 were based on the MICS Model questionnaires with minor modifications and additions. A household questionnaire was administered in each household, which collected information on household members including sex, age, literacy, marital status and orphanhood status. The household questionnaire also included education, child labour and water and sanitation modules. The questionnaire for women contained the following modules: · Child mortality · Maternal and new-born health · Contraceptive use · HIV/AIDS.

The questionnaire for children under the age of five was administered to the mother or carer of the child and included modules on: · Birth registration and early learning · Care during illness · Immunisation · Anthropometry

The MICS Model Questionnaires were translated from English into Bosnian/Croatian (Roman script) and Serbian (Cyrillic script). The questionnaires were then pre-tested in 100 households in each entity during June 2000. Based on the results of these pre-tests, modifications were made to the wording and translation of the questionnaires. For the full questionnaires, see Appendix D of the report which is provided as External Resources.

Response rate

The survey sampled 10 772 households across the territory with a very high response rate of 98 percent. A total of 35 571 people lived in the households that responded, making this the largest such survey conducted in Bosnia and Herzegovina in the past ten years. The level of completion of the questionnaires was very high, and the data was subjected to multiple quality checks at all stages of the survey.

Data appraisal

Of the 10 772 households selected for the survey sample, 10 742 were found to be occupied (Table 1). Of these, 10 546 were successfully interviewed to give a household response rate of 98 percent. The response rate was slightly higher in rural areas (99 %) than in urban areas (97%). In the interviewed households, 8 912 eligible women aged 15-49 years were identified. Of these, 8 726 were successfully interviewed, yielding a response rate of 98 percent. In addition, 2 642 children under the age of five years were listed in the household questionnaire.

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

The Global Comparative Study on REDD+ (GCS REDD+) was launched in 2009 by the Center for International Forestry Research (CIFOR) to ensure that policy-makers and practitioner communities have access to – and use – the information, analyses and tools they need to: design and implement REDD+ and other forest-based mitigation strategies in effective, efficient and equitable ways that also promote social and environmental co-benefits; and rigorously assess to what degree REDD+ has delivered. Module 2 (Subnational REDD+ and low emissions development initiatives) focuses on assessing the performance of subnational REDD+ and other low-emission development initiatives, including subnational jurisdictional programmes and local-level projects. Module 2 evaluated the impacts of 23 REDD+ project and program sites in six countries: Brazil, Cameroon, Indonesia, Peru, Tanzania and Vietnam. The research uses a before–after/control–intervention (BACI) approach. In this approach, identical data are collected both before and after the initiative starts, and in an ‘intervention’ area (that is, the location that is impacted by the REDD+ initiative) and a ‘control’ area (that is, a location that has similar characteristics to the intervention area, but is not impacted by the REDD+ initiative). Data collection for the ‘before’ period was carried out in 2010/11 (hereafter referred as ‘Phase 1’), and for the ‘after’ period in 2013/14 (hereafter referred as ‘Phase 2’). At each site, four intervention villages and four control villages were surveyed. In each village, three types of data collection instruments were implemented in Phase 1 and Phase 2: a Household Questionnaire; a Village Questionnaire; and a Women’s Questionnaire. The Household dataset corresponds to the Household Questionnaire, which is used to: 1.Measure the potential effect of REDD+ on household well-being on the basis of objective metrics (livelihood, assets and income in the course of 12 months) and subjective metrics (perceived well-being status and the reasons for change for those who experience change); 2.Measure the potential effect of REDD+ on land and resource use at the level of the household; 3.Measure household knowledge of and involvement in the process of establishing and implementing REDD+. The Household Questionnaire is divided into 5 main sections: 1. Basic information on household members; 2. household assets; 3. household income; 4. perceptions of wellbeing and wellbeing change in last two years; and, 5. involvement in and assessment of forest conservation interventions. The Household Questionnaire was carried out in 18 of the 23 subnational initiatives. The Household dataset includes 4524 households in phase 1 and 3988 in phase 2, of which 3529 were interviewed twice (not all the phase 1 households could be interviewed again in phase 2 due to attrition). Variables from Phase 1 start with P1H_section&question number, and variables from Phase 2 start with P2H_section&question number. The research design and methods are further described in Sunderlin et al. (2016) as well as in several GCS REDD+ publications (see ‘Related publications’).

Abstract copyright UK Data Service and data collection copyright owner.The Integrated Household Survey (IHS), which ran from 2009-2014, was a composite survey combining questions asked on a number of social surveys conducted by the Office for National Statistics (ONS) to produce a dataset of 'core' variables. The ONS stopped producing IHS datasets from 2015 onwards; variables covering health, smoking prevalence, forces veterans, sexual identity and well-being will be incorporated into the Annual Population Survey - see the Which surveys (or modules) are included in the IHS? and What is the IHS? FAQ pages for further details. Background and history of the IHS The aim of the IHS was to produce high-level estimates for particular themes to a higher precision and lower geographic level than current ONS social surveys. The 'core' set contained around 100 questions, but a respondent was only asked a proportion of those depending on routing from answers to questions. The core questions were asked, where possible, at the beginning of the component surveys. In January 2008, a set of core questions was introduced within three ONS surveys in the General Lifestyle Survey, Living Costs and Food Survey, and the Opinions and Lifestyle Survey. In April 2008 the IHS core questions were also introduced on the English Housing Survey, bringing the family of modules on the IHS up to four. The IHS dataset for 2008-2009 was used as a pilot for the concept, developing the systems and designing the weighting methodology. The IHS data for that period have not been published as they do not provide better quality information than that within existing surveys. Hence, the earliest IHS data currently available cover 2009-2010. In April 2009 the IHS core questions were introduced on the Labour Force Survey (LFS) and Annual Population Survey (APS) questionnaires and from June 2009 the Life Opportunities Survey (LOS, which also ran from 2009-2014) was included in the IHS family of modules. With the inclusion of these new surveys the IHS became complete, with an achieved annual sample size of approximately 450,000 individuals from interviews undertaken in Great Britain and Northern Ireland. Therefore, the first IHS dataset released covers the period April 2009-March 2010, starting the IHS data series from the point that all surveys were included. The large sample size and UK-wide coverage meant that various geographical breakdowns were possible in the IHS, and it is possible to use a geographical hierarchy to drill down to lower level detail within an area. The IHS also contained data collected from the following surveys: General Lifestyle Survey; Living Costs and Food Survey; Opinions and Lifestyle Survey; English Housing Survey; Labour Force Survey; Annual Population Survey; and Life Opportunities Survey. All questions had been removed from the component surveys by 2014 and the IHS closed that year. Further information is available from the ONS Integrated Household Survey (Experimental statistics): January to December 2014 webpage. Available IHS data: End User Licence and Secure Access Users should note that there are two versions of the IHS. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version (SN 8075). The Secure Access version contains more detailed variables relating to age, age of youngest dependent child, country of birth, family unit type, household and household reference person, industry class, sub-class and division, month left last job, cohabitation, country of residence history, multiple households at address, nationality, New Deal training types, National Statistics Socio-Economic Classification (NS-SEC) long version, qualifications, household relationships, minor Standard Occupational Classification (SOC) groups, sexual identity, training and working age. The more detailed geographic variables present include county, unitary/local authority, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions and Training and Enterprise Councils (TECs). Users should note that the user guide also mentions variables that are not included in either the EUL or Secure Access datasets held at the Archive. The EUL version contains less detailed variables. For example, the lowest geography available is Government Office Region, only major (3-digit) SOC groups are included for main, second and last job, and only industry sector for main, second and last job. Users are advised to first obtain the standard EUL version of the data before making an application for the Secure Access version to see if they are sufficient for their research requirements. The Special Licence version of the IHS January - December, 2011 is available under SN 7062. Main Topics:The IHS core questions cover several themes. These include:economic activityeducationhealth and disabilityidentityincomeIncome variables: Users should note that while income data are collected within the IHS and questions are included in the questionnaire, ONS have so far not been able to harmonise the income variables across the different surveys that comprise the IHS. Therefore, there are currently no income variables included in datasets deposited at the Archive; the variables are only included in the Government Statistical Services (GSS) client and ONS internal research datasets. For further details, see the IHS user guide. Each of the surveys comprising the IHS have their own sampling design, meaning that the IHS includes clustered and non-clustered, multistage and single stage component samples and also cross-sectional and longitudinal data.

Abstract

The Armenian Household Budget Survey (HBS) 1996 was designed to be a nationally representative survey capable of measuring the standard of living in the Republic of Armenia (ROA) through the collection of data on the family, demographic, socio-economic and financial status of households. The survey was conducted in November - December 1996, on the whole territory of the republic by the State Department of Statistics (SDS) of ROA with technical and financial assistance from the World Bank.

The data collected included information on household composition, housing conditions, education level of household members, employment and income, savings, borrowing, as well as details on levels of expenditure including those on food, non-food, health, tourism and business. The survey covered about 100 villages and 28 towns. The size of the sample was 5,040 households of which 4,920 responded which makes the survey the largest carried out in Armenia to date and one with a very high response rate for a transition economy. The expenditure part of the data was collected using two different methods administered for different households. The methods are: recall method in which households were asked, during the interview, about their expenditures made during the last 30 days preceding the date of the interview; and a diary method where households were given a diary they used to record details about their income and expenditure on a daily basis for 30 days during the interview period. About 25% of the total sample of interviewed households used diaries and 75% used the recall method. The unit of study in the survey was the household, defined as a group of co-resident individuals with a common living budget. As will be explained in detail, the AHBS 96 was generally designed as a two stage stratified sampling, but for large urban areas with an almost definite probability of being selected, a one stage sampling was adopted.

The Armenian HBS 1996 is not a standard Living Standards Measurement Study (LSMS) survey - the questionnaire used is more limited in scope and much different in format from a typical LSMS. This survey used no community or price questionnaires; it did not use most of LSMS’ prototypical fieldwork and data quality procedures, and the technical assistance did not come from the LSMS group in the World Bank. Nonetheless, the goals are some what LSMS-like and the data is certainly worth archiving. They are therefore being entered into the LSMS archives to guarantee their future accessibility to World Bank and other users.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The State Department of Statistics specified 3 domains of interest for this study. These are Yerevan (the capital of ROA), Other Urban areas and Rural areas. Recent estimates of earthquake zones assigned almost equal populations to these domain zones of interest, and as a result there was no need for special targeting and no particular reason was implied for departing from a proportionate (or self-weighting) design.

A self-weighting sample was derived by selecting Primary Sampling Units (PSUs) with probability proportional to their size (where size is defined as the number of households) and then taking a constant number of households from each selected. The sample, therefore, was designed to be self-weighted and representative at the administrative regions (Marzes) level, for urban and rural areas, and within urban areas by the size of cities, and in rural areas by elevation. The number of households to be selected in each PSU was 20, so 250 PSUs were required to make up 5000 households.

Note: See detailed sample design and sample implementation information in the technical document, which is provided in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Armenia HBS 96 questionnaire was designed to collect information on several aspects of household behavior -- demographic composition, housing, health, consumption expenditures as well as income by source and employment. Information was collected about all the household members, not just about the head of the household alone.

Household Questionnaire

The main household questionnaire used in Armenia HBS 96 contained 13 sections, each of which covered a separate aspect of household activity. The various sections of the household questionnaire are described below followed by a brief description of the diary used to record the daily income and expenditure activities of participating households. All households completed sections A through J, L, and M. Households selected to receive the recall method for expenditures completed section K as well; the remainder filled out the diary instead of being interviewed for section K.

A . FAMILY CHARACTERISTICS AND HOUSING: This section collected basic demographic data such as name, age, sex, education, health, marital status and economic status of everyone living in the household, number of people in the household, etc. In addition, information collected included data on the type of educational institutions attended (private/public), special groups (disabled, single parents, orphan...), dwelling amenities and conditions of the household such as type of dwelling (apartment, house, hostel...) and available facilities (electricity, hot water, telephone...)

B. INCOME FROM EMPLOYMENT: This section collected information on income from employment, type of industry each household member is engaged in, type of ownership of the organization where each person works, salary and other cash payments received, employment subsidies in terms of services (e.g. transport and health ). The recall period covers the 30 days prior to the interview date.

C. INCOME FROM SELF EMPLOYMENT: This section collected information about self-employed persons, their income from selfemployment, costs of equipment and raw materials owned by their business, sector in which the individual is self-employed, etc. The recall period covers 30 days prior to the interview.

D. STATE BENEFITS: This section included information on entitlements and receipt of state benefits such as pension, disability, child benefit, unemployment benefit, single-mother benefit, etc. during the last 30 days preceding the date of the interview.

E. OTHER CASH INCOMES: Included in this section are approximate values of the various types of cash incomes such as those from sale of property, valuables, alimony, rent from properties, dividends and interest, help from relatives, etc. the household received during the last 30 days preceding the date of the interview.

F. AID (ASSISTANCE): This section included information on whether food and non-food (e.g. medical help) assistance were received by the household in forms other than cash from friends, relatives, humanitarian organizations, etc. and the values of such assistance received during the last 30 days preceding the date of the interview.

G. SAVINGS, ASSETS AND LOANS: This section collected information on savings, assets and loans made by the household to others, amount of borrowing from others, and the associated interest rates during the past 30 days.

H. GENERAL ECONOMIC SITUATION: This section collected information about the current economic situation as perceived by the household, how it changed over the past 90 days and the household’s future expectations over the next 90 days.

I. LAND OWNERSHIP AND AGRICULTURAL PRODUCE: This section collected information on the amount of land owned by the household in hectares, each crop type harvested and consumed, crop in storage for own household use, home produced food such as diary products, milk, eggs, etc. and animal stock. The recall period for this section generally is the current year, but for the value of household consumption, and crops sold in the market, it uses a recall period of the past 30 days.

J. FOOD IN STOCK (RESERVES): This section collected data on the amount of food in stock the household currently has such as bread, meat, cereals vegetables, etc.

K. EXPENDITURE FOR 30 DAYS (RECALL METHOD): This section collected expenditure information for the last 30 days on food purchases by item; clothing and foot wear for adults; children’s clothes; fabrics; household furniture, cars, carpets, and electrical appliances; household consumables such as soap and stationary; building materials, bathroom appliances and household tools; household utensils; household services; utilities; leisure activities; health; transport; education; domestic animals; land; tourism; and business activities.

L. EMIGRATION: This section collected information on whether anybody in the household worked outside Armenia for more than three months over the past five years; if the emigrating household member is still abroad and his/her final destination country.

M. "PAROS" social program:2 This section collected information on whether the household is in the PAROS program and points the family has in the PAROS system in their social passport.

Z. GUESTS AND EATING OUT This section collected information on how many people ate in the household during the 30 days prior to the interview, how many times the household invited guests for dinner; and was invited; amount of food given to friends and relatives by the household. The codes for these variables are available in the data dictionary.

Diary Questionnaire

The diary questionnaire was used to collect daily income and expenditure activities of the participating households for 30 consecutive days during the interview period. It was administered to 25% of the households in the sample who also completed sections A through J, L and M from the

Abstract

The Integrated Household Survey (IHS) 2015 provided data for the measurement of the economic well-being of the population. The data has a valuable input in the CPI and national accounts and remains valuable in the proper construct CPI. Data from the survey constituted one of the two basic types of data needed to update the weighting pattern of the Consumer Price Index (CPI) to ensure it adequately reflected the spending habits of the Gambian population which is reflective of the seasonal nature of household expenditure. The IHS is the ideal large-sample Household Expenditure survey, which is more appropriate to provide regional breakdown compared to the weaker outlet-type breakdowns

This survey was important because it provided The Gambia Government with comprehensive information on the socioeconomic status of the population and to enable government to monitor the determinants of poverty and its dynamics. Information from the IHS can be used to assess the current levels of differences among population and to evaluate basic household needs in key sectors such as drinking water, energy, schooling, health facilities, sanitation, employment and other sectors. The specific objectives of the survey are:

1. To provide a database that allows for end time analysis of national level government policies embedded within the PAGE.
2. To understand the poverty dynamics across the country and factors influencing them.
3. To obtain in depth understanding on the living standards of households to livelihood strategies and measures of income diversification.
4. To get information on household expenditure patterns to update the National Accounts.
5. To obtain a new set of weights for the basket of goods and services that allow for upgrading the Consumer Price Index (CPI).
6. To build capacity and development of sustainable systems to produce accurate and timely information on households in The Gambia.
7. Some training activities are envisaged under this project such as a STATA workshop, household survey design and management, and study tours for poverty analysis.

Geographic coverage

National

Analysis unit

Households, Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The Integrated Household Survey 2015 was divided into four sub-samples representing seasonal/ quarterly variation.

A two-stage probability proportional to size (PPS) stratified random sampling (size being number of households per EA) without replacement was adopted. At each stage, sub-samples of equal size were independently drawn without replacement. Sampling units were selected for each subsample with simple random sampling without replacement. Each survey period (a quarter - 3 months) was allocated one sub-sample. Local Government Area (LGA) and District corresponds to the survey Stratum. Enumeration Areas (EAs) were taken as the first stage units whilst 20 households within EAs were selected as the second stage units.

First Stage Stratification: Except for Kanifing LGA which does not have district connotation per se, EAs were stratified per districts for the other seven LGAs. The actual sample size was 600 EAs (12,000 households) but due to rounding up the sample increase to 605 EAs.10 districts have less than 4 EAs and to be able to capture the sessional variation in them they are adjusted to 4 EAs. A total of 22 EAs were added to the sample. The final sample is about 622 EAS (12,440 households). A total of 44 (district) first stage strata including Kanifing were determined.

First Stage Sample: Taking into consideration the available resources and manpower, 622 EAs consisting of four subsamples of 155.5 EAs each was covered during the entire survey period of twelve months. Thus, each phase (a quarter - 3 months) of the survey was allocated 155.5 EAs.

Second Stage Sample: Again, the available resources dictated a sample size of 12,440 households. It required twelve teams constituting twelve (12) supervisors and seventy (70) enumerators each were assigned to different geographical locations, taking into account social and cultural considerations amongst others. Each enumerator covered a total of 259. Seventeen (17) households in each phase of a three-month period corresponding to 12.96EAs. Each team will be allocated about 4.32 EAs or 86.38 households per month. Twenty (20) households per EA were selected with simple random sampling without replacement - all of which part one and part two questionnaires were administered.

Mode of data collection

Face-to-face [f2f]