Abstract

The 2001 Bulgaria Integrated Household Survey was conducted by BBSS Gallup International under the supervision of the World Bank. Because of the expected excessive level of attrition due to the large time lag from the last survey and the massive internal and external migration since 1997, for the purpose of this survey it was decided to draw a new cross-section of households. Using the same stratified two-stage cluster design adopted in 1995, a similar nationally-representative sample was drawn by the National Statistical Institute (NSI) from the pre-census listing of the 2001 Population Census.

The main objective of the survey was to provide comparable poverty figures with the previous studies, the questionnaire used is virtually identical to the one used in the previous surveys and when changes were introduced particular attention was paid to maintain consistency with the previous questionnaires.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size is 2,875 households

As in 1995, the original sampling plan called for the selection of five households in each of 500 randomly selected census clusters. In 2001, six households per cluster were provided by NSI to Gallup and the sixth household was used to replace households in the original sample in cases of refusal or absence. Each field substitution had to be verified by the team leader and approved by the field supervisor. A total of 2,500 households were finally interviewed. In addition, 133 Roma households were oversampled to allow more significant statistical comparisons of the group in some of the analyses. Detailed rules for the selection of the oversample were given to the enumerators and each selection was verified by the team leader.

Mode of data collection

Face-to-face [f2f]

Research instrument

Being a multi-purpose survey, the BIHS01 questionnaire follows the structure of a typical Living Standard Measurement Survey (LSMS). The survey collected exhaustive information for the estimation of a consumption aggregate. This includes food and non-food consumption expenditures as well as data for the imputation of housing rental value and the user value of durable goods. The questionnaire also contains comprehensive information for the estimation of income by source, as well as quite extensive information on health, education and the labor market.

The questionnaire has the following sections: Section 1: Household Roster Section 2: Migration Section 3: Education Section 4: Housing Section 5.1: Food Expenditure and Consumption Section 5.2: Purchase of Non-Food Commodities Section 6.1: Employment - status and history of employment Section 6.2: Main job - dependent activity (working for a salary or commission for somebody else) Section 6.3: Second - dependent activity (working for a salary or commission for somebody else) Section 6.4: Self employment - independent activity (working for yourself) Section 6.5: Agricultural land Section 6.6: Agriculture - crop production, yield Section 6.7: Agriculture assets Section 6.8: Agriculture - livestock: cattle, pigs, etc. Section 6.9: Other Farming Income and Costs Section 7.1: Remittances - Income Received from Absent Members of the Household or from Any Other Person. Section 7.2: Remittances - Absent Household Members and Other Persons Who Received Contributions from the Household Section 8.1: State old age pension Section 8.2: Private old age pension Section 8.3: Survivor's pension Section 8.4: Disability pension Section 8.5: Unemployment benefits - for all people above age 15 Section 8.6: Maternity and childcare benefits under the social assistance system
Section 8.7: In kind individual social benefits Section 8.8: Summary of child benefit allowance Section 8.9: Cash and in kind household social benefits Section 8.10: Other forms of revenue/debts Section 9.1: Household furniture and durable goods Section 9.2: Real estate assets Section 10: Health Status Section 11. Ethnicity of main respondent

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

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Households and persons

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: No

UNIT DESCRIPTIONS: - Households: A household is a group of people who normally live in the same household unit, who are or are not related to one another, and and who eat from the same pot.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Bureau of Statistics

SAMPLE DESIGN: The sample followed a two-stage design in which enumeration areas (EAs) served as the primary sampling units and households as the secondary sampling units. A total of 500 EAs were selected based on probability proportional to size (PPS) of the total EAs in each state and the total households listed in those EAs. In each EA, 10 households were selected randomly from a list of all households in the EA. In total, 4,851 households and 29,993 individuals were interviewed in 500 EAs.

SAMPLE UNIT: Enumeration area and household

SAMPLE FRACTION: 0.1%

SAMPLE SIZE (person records): 72,191

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires: household questionnaire, agricultural questionnaire, and community/prices questionnaire. The household questionnaire collected information on size and composition of the household, as well as demographic, migration, education, work, time use, household assets, income, savings, and food consumption and security. The agricultural questionnaire collected information on crop and livestock production, storage, and sales. The community/prices questionnaire collected information on community and prices components.

Abstract

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

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

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

Geographic coverage

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

Analysis unit

Household and Induvisual

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

Cleaning operations

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

Response rate

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

Abstract

The 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.

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.

Name of organization (Comment)

Abstract

The Pakistan Integrated Household Survey (PIHS) was conducted jointly by the Federal Bureau of Statistics (FBS), Government of Pakistan, and the World Bank. The survey was part of the Living Standards Measurement Study (LSMS) household surveys that have been conducted in a number of developing countries with the assistance of the World Bank. The purpose of these surveys is to provide policy makers and researchers with individual, household, and community level data needed to analyze the impact of policy initiatives on living standards of households.

The Pakistan Integrated Household Survey was carried out in 1991. This nationwide survey gathered individual and household level data using a multi-purpose household questionnaire. Topics covered included housing conditions, education, health, employment characteristics, selfemployment activities, consumption, migration, fertility, credit and savings, and household energy consumption. Community level and price data were also collected during the course of the survey.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the PIHS was drawn using a multi-stage stratified sampling procedure from the Master Sample Frame developed by FBS based on the 1981 Population Census.

SAMPLE FRAME:

This sample frame covers all four provinces (Punjab, Sindh, NWFP, and Balochistan) and both urban and rural areas. Excluded, however, are the Federally Administered Tribal Areas, military restricted areas, the districts of Kohistan, Chitral and Malakand and protected areas of NWFP. According to the FBS, the population of the excluded areas amounts to about 4 percent of the total population of Pakistan. Also excluded are households which depend entirely on charity for their living.

The sample frame consists of three main domains: (a) the self-representing cities; (b) other urban areas; and (c) rural areas. These domains are further split up into a number of smaller strata based on the system used by the Government to divide the country into administrative units. The four provinces of Pakistan mentioned above are divided into 20 divisions altogether; each of these divisions in turn is then further split into several districts. The system used to divide the sample frame into the three domains and the various strata is as follows: (a) Self-representing cities: All cities with a population of 500,000 or more are classified as self-representing cities. These include Karachi, Lahore, Gujranwala, Faisalabad, Rawalpindi, Multan, Hyderabad and Peshawar. In addition to these cities, Islamabad and Quetta are also included in this group as a result of being the national and provincial capitals respectively. Each self-representing city is considered as a separate stratum, and is further sub-stratified into low, medium, and high income groups on the basis of information collected at the time of demarcation or updating of the urban area sample frame. (b) Other urban areas: All settlements with a population of 5,000 or more at the time of the 1981 Population Census are included in this group (excluding the self-representing cities mentioned above). Urban areas in each division of the four provinces are considered to be separate strata. (c) Rural areas: Villages and communities with population less than 5,000 (at the time of the Census) are classified as rural areas. Settlements within each district of the country are considered to be separate strata with the exception of Balochistan province where, as a result of the relatively sparse population of the districts, each division instead is taken to be a stratum.

Main strata of the Master Sample frame

Domain / Punjab / Sindh / NWFP / Balochistan / PAKISTAN Self-representing cities / 6 / 2 / 1 / 1 / 10 Other urban areas / 8 / 3 / 5 / 4 / 20 Rural areas / 30 / 14 / 10 / 4 / 58 Total 44 / 19 / 16 / 9 / 88

As the above table shows, the sample frame consists of 88 strata altogether. Households in each stratum of the sample frame are exclusively and exhaustively divided into PSUs. In urban areas, each city or town is divided into a number of enumeration blocks with welldefined boundaries and maps. Each enumeration block consists of about 200-250 households, and is taken to be a separate PSU. The list of enumeration blocks is updated every five years or so, with the list used for the PIHS having been modified on the basis of the Census of Establishments conducted in 1988. In rural areas, demarcation of PSUs has been done on the basis of the list of villages/mouzas/dehs published by the Population Census Organization based on the 1981 Census. Each of these villages/mouzas/dehs is taken to be a separate PSU. Altogether, the sample frame consists of approximately 18,000 urban and 43,000 rural PSUs.

SAMPLE SELECTION:

The PIHS sample comprised 4,800 households drawn from 300 PSUs throughout the country. Sample PSUs were divided equally between urban and rural areas, with at least two PSUs selected from each of the strata. Selection of PSUs from within each stratum was carried out using the probability proportional to estimated size method. In urban areas, estimates of the size of PSUs were based on the household count as found during the 1988 Census of Establishments. In rural areas, these estimates were based on the population count during the 1981 Census.

Once sample PSUs had been identified, a listing of all households residing in the PSU was made in all those PSUs where such a listing exercise had not been undertaken recently. Using systematic sampling with a random start, a short-list of 24 households was prepared for each PSU. Sixteen households from this list were selected to be interviewed from the PSU; every third household on the list was designated as a replacement household to be interviewed only if it was not possible to interview either of the two households immediately preceding it on the list.

As a result of replacing households that could not be interviewed because of non-responses, temporary absence, and other such reasons, the actual number of households interviewed during the survey - 4,794 - was very close to the planned sample size of 4,800 households. Moreover, following a pre-determined procedure for replacing households had the added advantage of minimizing any biases that may otherwise have arisen had field teams been allowed more discretion in choosing substitute households.

SAMPLE DESIGN EFFECTS:

The three-stage stratified sampling procedure outlined above has several advantages from the point of view of survey organization and implementation. Using this procedure ensures that all regions or strata deemed important are represented in the sample drawn for the survey. Picking clusters of households or PSUs in the various strata rather than directly drawing households randomly from throughout the country greatly reduces travel time and cost. Finally, selecting a fixed number of households in each PSU makes it easier to distribute the workload evenly amongst field teams. However, in using this procedure to select the sample for the survey, two important matters need to be given consideration: (a) sampling weights or raising factors have to be first calculated to get national estimates from the survey data; and (b) the standard errors for estimates obtained from the data need to be adjusted to take account for the use of this procedure.

Mode of data collection

Face-to-face [f2f]

Research instrument

The PIHS used three questionnaires: a household questionnaire, a community questionnaire, and a price questionnaire.

HOUSEHOLD QUESTIONNAIRE:

The PIHS questionnaire comprised 17 sections, each of which covered a separate aspect of household activity. The various sections of the household questionnaire were as follows: 1. HOUSEHOLD INFORMATION 2. HOUSING 3. EDUCATION 4. HEALTH 5. WAGE EMPLOYMENT 6. FAMILY LABOR 7. ENERGY 8. MIGRATION 9. FARMING AND LIVESTOCK 10. NON-FARM ENTERPRISE ACTIVITIES 11. NON-FOOD EXPENDITURES AND INVENTORY OF DURABLE GOODS 12. FOOD EXPENSES AND HOME PRODUCTION 13. MARRIAGE AND MATERNITY HISTORY 14. ANTHROPOMETRICS 15. CREDIT AND SAVINGS 16. TRANSFERS AND REMITTANCES 17. OTHER INCOME

The household questionnaire was designed to be administered in two visits to each sample household. Apart from avoiding the problem of interviewing household members in one long stretch, scheduling two visits also allowed the teams to improve the quality of the data collected.

During the first visit to the household (Round 1), the enumerators covered sections 1 to 8, and fixed a date with the designated respondents of the household for the second visit. During the second visit (Round 2), which was normally held two weeks after the first visit, the enumerators covered the remaining portion of the questionnaire and resolved any omissions or inconsistencies that were detected during data entry of information from the first part of the survey.

Since many of the sections of the questionnaire pertained specifically to female members of the household, female interviewers were included in conducting the survey. The household questionnaire was split into two parts (Male and Female). Sections such as SECTION 3: EDUCATION, which solicited information on all individual members of the household (male as well as female) were included in both parts of the questionnaire. Other sections such as SECTION 2: HOUSING and SECTION 12: FOOD EXPENSES AND HOME PRODUCTION , which collected data at the aggregate household level, were included in either the male questionnaire or the female questionnaire, depending upon which member of the household was more likely

Abstract

The Project for Statistics on Living standards and Development was a countrywide World Bank Living Standards Measurement Survey. It covered approximately 9000 households, drawn from a representative sample of South African households. The fieldwork was undertaken during the nine months leading up to the country's first democratic elections at the end of April 1994. The purpose of the survey was to collect statistical information about the conditions under which South Africans live in order to provide policymakers with the data necessary for planning strategies. This data would aid the implementation of goals such as those outlined in the Government of National Unity's Reconstruction and Development Programme.

Geographic coverage

National

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

(a) SAMPLE SIZE

Sample size is 9,000 households. The sample design adopted for the study was a two-stage self-weighting design in which the first stage units were Census Enumerator Subdistricts (ESDs, or their equivalent) and the second stage were households. The advantage of using such a design is that it provides a representative sample that need not be based on accurate census population distribution.in the case of South Africa, the sample will automatically include many poor people, without the need to go beyond this and oversample the poor. Proportionate sampling as in such a self-weighting sample design offers the simplest possible data files for further analysis, as weights do not have to be added. However, in the end this advantage could not be retained, and weights had to be added. The sampling frame was drawn up on the basis of small, clearly demarcated area units, each with a population estimate. The nature of the self-weighting procedure adopted ensured that this population estimate was not important for determining the final sample, however. For most of the country, census ESDs were used. Where some ESDs comprised relatively large populations as for instance in some black townships such as Soweto, aerial photographs were used to divide the areas into blocks of approximately equal population size. In other instances, particularly in some of the former homelands, the area units were not ESDs but villages or village groups. In the sample design chosen, the area stage units (generally ESDs) were selected with probability proportional to size, based on the census population.

(b) SAMPLE DESIGN

Systematic sampling was used throughout that is, sampling at fixed interval in a list of ESDs, starting at a randomly selected starting point. Given that sampling was self-weighting, the impact of stratification was expected to be modest. The main objective was to ensure that the racial and geographic breakdown approximated the national population distribution. This was done by listing the area stage units (ESDs) by statistical region and then within the statistical region by urban or rural. Within these sub-statistical regions, the ESDs were then listed in order of percentage African. The sampling interval for the selection of the ESDs was obtained by dividing the 1991 census population of 38,120,853 by the 300 clusters to be selected. This yielded 105,800. Starting at a randomly selected point, every 105,800th person down the cluster list was selected. This ensured both geographic and racial diversity (ESDs were ordered by statistical sub-region and proportion of the population African). In three or four instances, the ESD chosen was judged inaccessible and replaced with a similar one. In the second sampling stage the unit of analysis was the household. In each selected ESD a listing or enumeration of households was carried out by means of a field operation. From the households listed in an ESD a sample of households was selected by systematic sampling. Even though the ultimate enumeration unit was the household, in most cases "stands" were used as enumeration units. However, when a stand was chosen as the enumeration unit all households on that stand had to be interviewed. Census population data, however, was available only for 1991. An assumption on population growth was thus made to obtain an approximation of the population size for 1993, the year of the survey. The sampling interval at the level of the household was determined in the following way: Based on the decision to have a take of 125 individuals on average per cluster (i.e. assuming 5 members per household to give an average cluster size of 25 households), the interval of households to be selected was determined as the census population divided by 118.1, i.e. allowing for population growth since the census. It was subsequently discovered that population growth was slightly over-estimated, but this had little effect on the findings of the survey. Individuals in hospitals, old age homes, hotels and hostels of educational institutions were not included in the sample. Migrant labour hostels were included. In addition to those that turned up in the selected ESDs, a sample of three hostels was chosen from a national list provided by the Human Sciences Research Council and within each of these hostels a representative sample was drawn on a similar basis as described above for the households in ESDs.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

All the questionnaires were checked when received. Where information was incomplete or appeared contradictory, the questionnaire was sent back to the relevant survey organization. As soon as the data was available, it was captured using local development platform ADE. This was completed in February 1994. Following this, a series of exploratory programs were written to highlight inconsistencies and outlier. For example, all person level files were linked together to ensure that the same person code reported in different sections of the questionnaire corresponded to the same person. The error reports from these programs were compared to the questionnaires and the necessary alterations made. This was a lengthy process, as several files were checked more than once, and completed at the beginning of August 1994. In some cases, questionnaires would contain missing values, or comments that the respondent did not know, or refused to answer a question. These responses are coded in the data files with the following values:

VALUE MEANING -1 : The data was not available on the questionnaire or form -2 : The field is not applicable -3 : Respondent refused to answer -4 : Respondent did not know answer to question

Data appraisal

The data collected in clusters 217 and 218 should be viewed as highly unreliable and therefore removed from the data set. The data currently available on the web site has been revised to remove the data from these clusters. Researchers who have downloaded the data in the past should revise their data sets. For information on the data in those clusters, contact SALDRU http://www.saldru.uct.ac.za/.

Abstract

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

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

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

Geographic coverage

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

Analysis unit

Households

Individuals

Universe

All resident households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

The Sampling Frame

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

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

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

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

Stratification

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

Sampling

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

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

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

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

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

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

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

Sample sizes and allocation

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

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

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

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

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

where,

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

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

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

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

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

number of households in rural villages in the frame.

Monthly samples

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

Estimation

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

Mode of data collection

Face-to-face [f2f]

Research instrument

Four different questionnaires or forms were used in the survey:

1. Household listing form

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

1. Village questionnaire

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

    1. Demographic information

    2. Economy & Infrastructure

    3. Rainfall & Natural disasters

    4. Education

    5. Health

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

    7. Employment & Wages

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

    9. Sale prices of agricultural land in the village

    10. Recruitment of children for work outside the village 

1. Household questionnaire

The following modules were included in the Household questionnaire:

1. Initial visit

01A. List of household member

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

01C. Recall non-food expenditures

01D. Vulnerability

1. Education & Literacy

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

   1. Housing

3. Household economic activities

05A.Land ownership

05B.Production of

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 General Household Survey-Panel (GHS-Panel) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program. The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of approximately 5,000 households, which are also representative of the six geopolitical zones. The 2018/19 is the fourth round of the survey with prior rounds conducted in 2010/11, 2012/13, and 2015/16. GHS-Panel households were visited twice: first after the planting season (post-planting) between July and September 2018 and second after the harvest season (post-harvest) between January and February 2019.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Agricultural plots
• Communities

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

The original GHS-Panel sample of 5,000 households across 500 enumeration areas (EAs) and was designed to be representative at the national level as well as at the zonal level. The complete sampling information for the GHS-Panel is described in the Basic Information Document for GHS-Panel 2010/2011. However, after a nearly a decade of visiting the same households, a partial refresh of the GHS-Panel sample was implemented in Wave 4.

For the partial refresh of the sample, a new set of 360 EAs were randomly selected which consisted of 60 EAs per zone. The refresh EAs were selected from the same sampling frame as the original GHS-Panel sample in 2010 (the “master frame”). A listing of all households was conducted in the 360 EAs and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximated 3,600 households.

In addition to these 3,600 refresh households, a subsample of the original 5,000 GHS-Panel households from 2010 were selected to be included in the new sample. This “long panel” sample was designed to be nationally representative to enable continued longitudinal analysis for the sample going back to 2010. The long panel sample consisted of 159 EAs systematically selected across the 6 geopolitical Zones. The systematic selection ensured that the distribution of EAs across the 6 Zones (and urban and rural areas within) is proportional to the original GHS-Panel sample. Interviewers attempted to interview all households that originally resided in the 159 EAs and were successfully interviewed in the previous visit in 2016. This includes households that had moved away from their original location in 2010. In all, interviewers attempted to interview 1,507 households from the original panel sample.

The combined sample of refresh and long panel EAs consisted of 519 EAs. The total number of households that were successfully interviewed in both visits was 4,976.

Sampling deviation

While the combined sample generally maintains both national and Zonal representativeness of the original GHS-Panel sample, the security situation in the North East of Nigeria prevented full coverage of the Zone. Due to security concerns, rural areas of Borno state were fully excluded from the refresh sample and some inaccessible urban areas were also excluded. Security concerns also prevented interviewers from visiting some communities in other parts of the country where conflict events were occurring. Refresh EAs that could not be accessed were replaced with another randomly selected EA in the Zone so as not to compromise the sample size. As a result, the combined sample is representative of areas of Nigeria that were accessible during 2018/19. The sample will not reflect conditions in areas that were undergoing conflict during that period. This compromise was necessary to ensure the safety of interviewers.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The GHS-Panel Wave 4 consists of three questionnaires for each of the two visits. The Household Questionnaire was administered to all households in the sample. The Agriculture Questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing and other agricultural and related activities. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

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. Household location is geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets.

GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicits information on land ownership and use; farm labor; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; and household fishing activities. Some information is collected at the crop level to allow for detailed analysis for individual crops.

GHS-Panel Community Questionnaire: The Community Questionnaire solicits information on access to infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

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.

The Agriculture Questionnaire collects different information during each visit, but for the same plots and crops.

Cleaning operations

CAPI: For the first time in GHS-Panel, the Wave four exercise was conducted using Computer Assisted Person Interview (CAPI) techniques. All the questionnaires, household, agriculture and community questionnaires were implemented in both the post-planting and post-harvest visits of Wave 4 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Survey Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given tablets which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CAPI was highly successful, as it allowed for timely availability of the data from completed interviews.

DATA COMMUNICATION SYSTEM: The data communication system used in Wave 4 was highly automated. Each field team was given a mobile modem allow for internet connectivity and daily synchronization of their tablet. This ensured that head office in Abuja has access to the data in real-time. Once the interview is completed and uploaded to the server, the data is first reviewed by the Data Editors. The data is also downloaded from the server, and Stata dofile was run on the downloaded data to check for additional errors that were not captured by the Survey Solutions application. An excel error file is generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files are communicated back to respective field interviewers for action by the interviewers. This action is done on a daily basis throughout the duration of the survey, both in the post-planting and post-harvest.

DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.

The second stage cleaning involved the use of Data Editors and Data Assistants (Headquarters in Survey Solutions). As indicated above, once the interview is completed and uploaded to the server, the Data Editors review completed interview for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences, these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. Additional errors observed were compiled into error reports that were regularly sent to the teams. These errors were then corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then approved by the Data Editor. After the Data Editor’s approval of the interview on Survey Solutions server, the Headquarters also reviews and depending on the outcome, can either reject or approve.

The third stage of cleaning involved a comprehensive review of the final raw data following

Abstract

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

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

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

Geographic coverage

National

Urban/Rural

Analysis unit

1. household

2. individual

Universe

All resident households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

The Cambodia Socio-Economic Survey 2003-04 (CSES) is conducted in a nationwide representative sample of 15,000 households within 900 sampling units (villages). It is divided into 15 monthly representative samples of 1000 households in 60 villages.

The sampling design and implementation was made in March 2003. A three-stage sample design was devised. Since NIS already had a master sample based on the Population Census 1998, consisting of 600 villages, it was used. But in order to reach the preferred number of 900 villages, the sample was extended to include an additional 300 villages.

In the first stage, a sample of villages was selected in the head office. The villages were initially stratified into 45 strata (province*urban/rural). The villages were selected using systematic sampling with probabilities proportionate to size (PPS). The size measures used for the selection were number of households in the village according the 1998 Census. The resulting sample thus consisted of 900 villages, of which 600 are in rural areas and 300 in urban areas.

In the second stage one Census Enumeration Area (EA or alternatively PSU) was selected randomly also in the head office. At the beginning of the fieldwork, all households in the selected EA were listed using a household listing form, and following internationally recommended procedures. A systematic sample of households was then drawn in a third stage. The third stage sample was 20 households in rural areas and 10 households in the urban areas.

Design work

The work on sample design was carried out in the following areas:

• Estimation of sampling errors and design effects in the CSES 1999

• Calculation of optimal sample size within primary sampling units

• Sample size and sample allocation for CSES 2003

The work was done in a group of NIS staff in the form of expert assisted hands-on training in sampling design and calculation of sampling errors.

In previous surveys PSUs have been villages. It was decided to use village as PSU also for the CSES 2004 mainly because the communes were considered too large (and too few) to serve efficiently as PSUs. Another factor weighing in favor of villages was the fact that there already exists a master sample of villages at NIS.

The master sample consists of 600 villages (88 urban and 512 rural villages). The selection of villages was made with PPS sampling, hence facilitating an approximately self-weighing design with equal workloads in the villages. It was discussed whether a further stratification on 3-4 crude income-level strata should be done in urban Phnom Penh in order to secure a good spread of the sample over different income levels. It was decided not to do such stratification. Phnom Penh has a large sample (90 villages) selected with systematic sampling over a geographically ordered sample frame; this will in itself secure a reasonably good spread of PSUs.

The master sample is allocated over the strata proportionally to the total number of households in the strata. A problem with the master sample is that due to the proportional allocation the urban sample is too small to provide for good estimates in the urban domain. It was therefore decided to expand the sample to include 600 rural villages and 300 urban villages.

Secondary Sampling Units (SSU)

The 600 villages in the master sample are divided in small segments containing approximately ten households each by using census enumeration area maps. As a consequence the boundaries of the segments would be difficult to identify in the field. There would be a risk that housing units constructed after the census will be missed when households are listed within segments during the fieldwork. It was therefore decided not to use the segments in the second stage sampling. The available options are in this situation either (a) to select households directly on stage in the village or (b) to use the enumeration areas as secondary sampling units. Selecting households directly would require a listing of all households in the village prior to the fieldwork. Such a listing would become time-consuming in large villages. It was therefore decided that enumeration areas would be used as SSUs, and that one enumeration area is selected within each sampled village.

Implementation

Villages were selected with a systematic PPS procedure within each stratum. For each sampled village one census enumeration area (EA) was selected. As the enumeration areas are roughly of the same size, the selection was done with equal probability sampling.

Ten (10) households were selected in each sampled village in the CSES 99. Calculations indicated that this sample size was close to optimum. Since the optimum is rather flat, the loss in efficiency from sample sizes of 12-15 is fairly small.

From a purely sampling efficiency point of view, a larger sample than 15 households per village should not be taken. However, factors relating to interviewers' security and well-being weighed in favor of having two interviewers per village in the rural areas. A workload of 10 households between the two interviewers in the village was considered too small. A workload of 15-20 households would be reasonable. All things taken together resulted in a sample of 10 households in urban areas (with one interviewer per village) and 20 households in rural areas.

The resulting sample consisted of 300 urban PSUs and 600 rural PSUs. From the urban PSUs 10 households were selected while 20 households were selected from rural PSUs. The sample thus contained 15000 households to be interviewed during 15 fieldwork months with 1000 different households each month.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five different questionnaires or forms were used in the survey:

Form 1: Household listing sheets to be used in the sampling procedure in the enumeration areas.

Form 2: Village questionnaire answered by the village leader about economy and infrastructure, crop production, health, education, retail prices and sales prices of agriculture, employment and wages, and recruitment of children for work outside the village.

Form 3: Household questionnaire with questions for each household member, including modules on migration, education and literacy, housing conditions, crop production, household liabilities, durable goods, construction activities, nutrition, fertility and child care, child feeding and vaccination, health of children, mortality, current economic activity, health and illness, smoking, HIV/AIDS awareness, and victimization.

Form 4: Diary form on daily household expenditure and income

Form 5: Time use form detailing activities of household members during one 24-hour period.

Questionnaire design

The questionnaire is one of the first items in a strategy for quality control in data collection through surveys. Any piece of information to be collected must be formulated as a question so that all interviewers can be trained to read the questions in the same way. The questions must be formulated in such a way that all interviewers feel comfortable reading the questions aloud and that all respondents understand the questions in the same way. The layout of the questionnaire must be done so that the interviewer immediately understands how the respondent's answer should be recorded. A lot of work is normally needed to meet these requirements that are built into the process of communication in the interview situation. This is the kind of work in which final perfection is elusive and further improvements can always be made.

The initial work on questionnaire design resulted in a first draft prepared by NIS in early 2003. With expert assistance from Statistics Sweden in March the same year, a systematic walk-through question by question was done. A number of essential problems to be solved were then identified while errors or minor problems

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.

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

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.

Sampling deviation

The total sample size for the IHS3 was 12,288 households sampled from a total of 768 EAs. At the end of the survey, a total of 12,271 households were interviewed. Of the 12,271 interviewed households, 688 were replacements (6 percent)

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Data Entry:

Data Entry Clerks Each IHS3 field team was assigned 1 data entry clerk to process completed questionnaires at the team's 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 (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 catalogued by the Data Manager and electronic data loaded onto a central server to enable data entry verification on networked computers.

Quality Checks:

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 catalogued 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 re-entered. 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.

Response rate

99.9 percent

Abstract

The Second Malawi Integrated Household Survey is a nationally representative sample survey designed to provide information on the various aspects of household welfare in Malawi. The survey was conducted by the National Statistical Office from March 2004- April 2005. The survey collected information from a nationally representative sample of 11,280 households. The sampling design is representative at both national and district level hence the survey provides reliable estimates for those areas.

This is the third survey conducted under the Integrated Household Surveys Programme. The other surveys conducted under this Programme were; the Household Expenditure and Small Scale Economic Activities (HESSEA) conducted in 1990 and the first Integrated Household Survey (IHS1) conducted in 1997/98. The National Statistical Office also conducted the Core Welfare Indicators Questionnaire (CWIQ) in 2002 and the Welfare Monitoring Survey (WMS 2005). The WMS has been designed to provide quick results of welfare levels of the country and is less comprehensive relative to the IHS.

The survey is designed to cover a wide array of subject matter, whose primary objective of is to provide a complete and integrated data set to better understand the target population of households affected by poverty. Some specific objectives of the survey are as follows; · Provide timely and reliable information on key welfare and socio-economic indicators and meet special data needs for the review of the Malawi Poverty Reduction Strategy, which have been implemented in Malawi for the last five years since year 2002. · Provide data to come up with an update of the poverty profile for Malawi (poverty incidence, poverty gap, severity of poverty) · Derive indicators for monitoring of Malawi’s progress towards achievement of the Millennium Development Goals (MDGS) and the MPRS targets. · Provide an understanding of the people of Malawi’s living conditions. · Derive an independent estimate of total household expenditure. · Provide information on household consumption on selected items with the aim of revising the weights in the Malawi Consumer Price Index (CPI).

Geographic coverage

The sample frame includes all three regions of Malawi: north, centre and south and it is representative at both national and district level

Analysis unit

Households Individuals Communities

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHS2 had a total sample size of 11,280 households. The sample for IHS-2 was drawn using a two-stage stratified sampling procedure from a sample frame using the 1998 Population and Housing Census enumeration areas (EAs). Each of the twenty-seven districts was considered as a separate sub-stratum of the main rural stratum (except for Likoma district). The urban stratum includes the four major urban areas: Lilongwe, Blantyre, Mzuzu, and the Municipality of Zomba.

The IHS-2 used a two-stage stratified sample selection process. The primary sampling units (PSU) were the Enumeration areas. These were selected for each strata on the basis of probability proportional to size (PPS). The second stage involved randomly selecting 20 households in each EA. Every listed household in an EA had an equal chance of being selected to be enumerated.

The sample frame includes all three regions of Malawi: north, centre and south. The IHS-2 stratified the country into rural and urban strata. The total sample was 11,280 households (564 EAs x 20 households)

The listing of all households in the enumeration area was conducted by NSO staff in three phases in January, May and October 2004.

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Mode of data collection

Face-to-face [f2f]

Research instrument

The IHS-2 household questionnaire maintained comparisons with the earlier IHS-1 household questionnaire wherever possible. However, the IHS-2 questionnaire is more detailed and new modules were added. The questionnaire covered the socio economic characteristics of the household in the following modular aspects; · Demographic, · Education, · Health · Agriculture · Labour-force · Anthropometric information

There were five modules included in the 2004 questionnaire that did not appear in the 1997-98 questionnaire. These included; · Security and Safety, · Social Safety Nets, · Credit, · Subjective Assessment of Well-being, and · Recent Shocks to the Household.

In addition there were seven agricultural modules that collected more detailed information on the agricultural situation in households than was collected in IHS-1.

The IHS-2 Community Questionnaire was designed to collect information that is common to all households in a given area. During the survey a “community” was defined as the village or urban location surrounding the selected enumeration area, which most residents recognise as being their community. The questionnaire was administered to a group of several knowledgeable residents such as the village headman, headmaster of the local school, agricultural field assistant, religious leaders, local merchants, health workers and long-term knowledgeable residents. Information collected included basic physical and demographic characteristics of the community; access to basic services; economic activities; agriculture; how conditions have changed over the last five years; and prices for 47 common food items, non-food items, and ganyu labor.

Cleaning operations

(a) Data Entry Data capturing for the IHS-2 started as soon as the first months of fieldwork was completed in April 2005. Data entry was done concurrently with data collection. The IHS-2 data entry centre was centralised at the National Statistical Office headquarters and was organized as follows; Once the questionnaires arrived the data editor checked the questionnaires and assigned questionnaire numbers. The CSPRO software was used to capturer the data. This software provides automatic data checks for acceptable values for the variables, and checks between different modules of the questionnaire.

(b) Data Cleaning The data cleaning process was done in several stages. The first stage was to make sure that the data as captured reflected the information that the informants provided. The data processing manager did the error checks for each enumeration area. These were cross-examined physically with the questionnaires, and the errors were documented.

Response rate

total of 11,280 were selected for the sample of which 10,777 households were occupied and successfully interviewed, yielding a response rate of 96 percent. Of the selected households 507 replacements were made. The primary reason for replacement was that the dwelling could be found but no household member could be found after repeated attempts or the dwelling was unoccupied.

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.

Abstract

Institute for Strategic Studies and Prognoses (ISSP) in Montenegro has undertaken several household surveys in an effort to provide timely and relevant data that is useful for policy makers and analysts. While data constraints have limited the ability to evaluate poverty and living standards in recent years, new household surveys collected by ISSP in 2002, 2003 and 2004 allow baselines to be established in regards to the living standards of the Montenegrin population and against which we can monitor changes in the future. Furthermore, with these data on household living standards, analysis can evaluate the role of social policies in supporting the poor as well as the potential impact of major policy reforms.

The ISSP surveys drew attention, once again, to the need for accurately measuring household living conditions according to well accepted standards, and for monitoring these trends on a regular basis. These surveys have provided the country with an invaluable training ground towards the development of a permanent household survey system to support the government strategic planning in its fight against poverty.

Geographic coverage

National

Analysis unit

• Households
• Individuals
• Persons aged 15 and above
• Consumption Expenditure Commodities / Items

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2004 Household Survey consists of a sample of about 1,000 households interviewed in all municipalities. Of these, 600 households are considered to be the Core Sample. In addition there are two booster samples (200 households each).

The Republic of Montenegro is divided geographically into 3 regions and into 21 municipalities which are, in turn, divided into settlements. Since the last census in Montenegro was undertaken in November 2003, the data were not fully available to be utilized for all stages of sample design. The preliminary results from the Census were used to compute the population share of each of the 21 municipalities in the total population. In turn, these population shares were used identify the target number of households for the Core sample.

In order to create a sample listing of households for each municipality and given the limited availability of the current Census data, the ISSP team had to look beyond the Census data. The research team identified two possible sources for developing the sample frame. The first is the Voting Registration list. The second source is the Mass Voucher Privatization (MVP) listing of all people compiled in order to distribute vouchers among the population of citizens over 18 years in the summer of 2001. Both lists exclude IDPs (which includes the Roma population in its definition). At the time when sampling was done, the MVP list was newer than the voting registration list. ISSP concluded that these two lists were fairly comparable. In addition, list of the households paying the bill to the Electricity Company was available as well, but with double entries included due to the almost 60,000 of weekend houses registered in Montenegro.

The MVP list was used to randomly list Core sample households such that the sample proportion in each municipality was equal to the overall population proportions. Households were interviewed based on this random sampling list for the municipality, with no clustering design in the sample within municipality, thereby reducing survey design effects which increase standard errors. The exception for this procedure was for Roma and displaced persons. The sample of Roma and displaced households in the Core sample were listed based on additional data sources (Roma NGOs and UNHCR list of displaced persons) since they are missing from the MVP. Roma and displaced persons in the Core sample listing are from Podgorica only since the largest share of these populations live in the central part of Montenegro (68% of Roma and 36% of displaced persons).

Of the Core sample of 600 households, 93% (559) are resident households, 3% (18) are Roma and 4% (23) are displaced households.

In addition to the Core sample, the 2004 Household Survey sample included two booster samples. A booster sample of 200 households was created in 3 municipalities defined as areas with certain ecological problems: Pljevlja (70), Mojkovac (60), and Zeta Valley (70). In order to have enough vulnerable and poor families for analytical purposes, the second booster sample of another 200 households was created from the listing of Family Material Support (FMS) program.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2004 Household Survey by ISSP consists of a detailed household questionnaire. The questionnaire is divided into several modules. These modules were aimed at matching as much as possible the specificity of Montenegro in terms of data needs, as driven by pressing policy questions. Their design (e.g. questions asked, their sequence, units and time-frames used) was adapted to fit the Montenegro reality. The questions covered in the 2004 survey were revised from the previous rounds with considerable input from policy-makers and analysts concerned with living standards measurement in Montenegro.

The questionnaire was divided in eight sections based on the topics covered, and was administered to households in one visit.

Cleaning operations

Data entry (DE) program was developed to facilitate the data entry process. The data entry program was developed using Microsoft Access software. Technical support of the World Bank was provided in order to develop ISSP capacities in this area. Among the useful features of the DE program which allowed for prompt and accurate entry were: a) The data entry form page was identical with the questionnaire page, which facilities data entry. b) Range checks for most variables where appropriate. c) Skip rules. The cursor of data entry jumps to the necessary box depending on the entered value of the previous variable.

Training for the data entry operators ran from May 25 to May 30, 2004.

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

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

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

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

The View Table only contains 200 records for preview purposes. Find the Questionaire Codebook and supporting documentation HERE.Find the full Household Survey Dataset HERE.