Abstract

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

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

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

Geographic coverage

The survey covers all provinces except Noth Solomons.

Analysis unit

• Household
• Individual
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

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

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

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The HIECS 2008/2009 is the tenth Household Income, Expenditure and Consumption Survey that was carried out in 2008/2009, among a long series of similar surveys that started back in 1955.

The survey main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To measure mean household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To define mean household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependant on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income and expenditure for commodities and services. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its sources and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to sources, either from household production or not, in addition to household expenditure for non food commodities and services. - To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ...) in urban and rural areas. - To identify the percentage distribution of income recipients according to some background variables such as housing conditions, size of household and characteristics of head of household.

Compared to previous surveys, the current survey experienced certain peculiarities, among which: 1- Doubling the number of area segments from 1200 in the previous survey to 2526 segments with decreasing the number of households selected from each segment to be (20) households instead of (40) in the previous survey to ensure appropriate representatives in the society. 2- Changing the survey period to 15 days instead of one month in the previous one 200412005, to lighten the respondent burden and encourage more cooperation. 3- Adding some additional questions: a- Participation or the benefits gained from pension and social security system. b- Participation in health insurance system. 4- Increasing quality control Procedures especially for fieldwork to ensure data accuracy and avoid any errors in suitable time.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The sample of HIECS, 2008-2009 is a two-stage stratified cluster sample, approximately self-weighted, of nearly 48000 households. The main elements of the sampling design are described in the following.

1- Sample Size
It has been deemed important to retain the same sample size of the previous two HIECS rounds. Thus, a sample of about 48000 households has been considered. The justification of maintaining the sample size at this level is to have estimates with levels of precision similar to those of the previous two rounds: therefore trend analysis with the previous two surveys will not be distorted by substantial changes in sampling errors from round to another. In addition, this relatively large national sample implies proportional samples of reasonable sizes for smaller governorates. Nonetheless, over-sampling has been introduced to raise the sample size of small governorates to about 1000 households As a result, reasonably precise estimates could be extracted for those governorates. The over-sampling has resulted in a slight increase in the national sample to 48658 households.

2- Cluster size
An important lesson learned from the previous two HIECS rounds is that the cluster size applied in both surveys is found to be too large to yield an accepted design effect estimates. The cluster size was 40 households in the 2004-2005 round, descending from 80 households in the 1999-2000 round. The estimates of the design effect (deft) for most survey measures of the latest round were extraordinary large. As a result, it has been decided to decrease the cluster size to only 19 households (20 households in urban governorates to account for anticipated non-response in those governorates: in view of past experience non-response is almost nil in rural governorates).

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among the documentation materials published in both Arabic and English.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following: 1- Expenditure and consumption questionnaire. 2- Diary questionnaire for expenditure and consumption. 3- Income questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention of Labor Statisticians held in Geneva, 2003. - Using the recent Classification of Individual Consumption according to Purpose (COICOP). - Using more than one approach of expenditure measurement to serve many purposes of the survey.

A brief description of each questionnaire is given next:

1- Expenditure and Consumption Questionnaire

This questionnaire comprises 14 tables in addition to identification and geographic data of household on the cover page. The questionnaire is divided into two main sections.

Section one: Household schedule and other information. It includes: - Demographic characteristics and basic data for all household individuals consisting of 18 questions for every person. - Members of household who are currently working abroad. - The household ration card. - The main outlets that provide food and beverage. - Domestic and foreign tourism. - The housing conditions including 15 questions. - Means of transportation used to go to work or school. - The household possession of appliances and means of transportation. - This section includes some questions which help to define the social and economic level of households which in turn, help interviewers to check the plausibility of expenditure, consumption and income data.

Section two: Expenditure and consumption data It includes 14 tables as follows: - The quantity and value of food and beverages commodities actually consumed. - The quantity and value of the actual consumption of alcoholic beverages, tobacco and narcotics. - The quantity and value of the clothing and footwear. - The household expenditure for housing. - The household expenditure for furnishings, household equipment and routine maintenance of the house. - The household expenditure for health care services. - The household expenditure for transportation. - The household

Abstract Household surveys are one of the primary methodologies used in population-based studies. This narrative review of the literature aims to gather and describe the leading national and international household surveys of relevance. In Brazil, the historical role played by the Brazilian Institute of Geography and Statistics (IBGE) in conducting the most relevant research in the production of social data stands out. The Medical-Health Care Survey (AMS) and the National Household Sample Survey (PNAD), with the serial publication of Health Supplements, are the country’s primary sources of health information. In 2013, in partnership with the Ministry of Health, IBGE launched the National Health Survey (PNS), the most significant household health survey ever conducted in Brazil. The PNS-2019 received a major thematic and sampling expansion and, for the first time, applied the Primary Care Assessment Tool to assess PHC services in all 27 Brazilian states.

Abstract

In the past decades, Nigeria has experienced substantial gaps in producing adequate and timely data to inform policy making. In particular, the country is lagging behind in producing sufficient and accurate agricultural production statistics. The current set of household and farm surveys conducted by the NBS covers a wide range of sectors. Except for the Harmonized National Living Standard Survey (HNLSS) which covers multiple topics, these different sectors are usually covered in separate surveys none of which is conducted as a panel. As part of the efforts to continue to improve data collection and usability, the NBS has revised the content of the annual General household survey (GHS) and added a panel component. The GHS-Panel is conducted every 2 years covering multiple sectors with a focus to improve data from the agriculture sector.

The Nigeria General Hosehold Survey-Panel, is the result of a partnership that NBS has established with the Federal Ministry of Agriculture and Rural Development (FMARD), the National Food Reserve Agency (NFRA), the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). Under this partnership, a method to collect agricultural and household data in such a way as to allow the study of agriculture's role in household welfare over time was developed. This GHS-Panel Survey responds to the needs of the country, given the dependence of a high percentage of households on agriculture activities in the country, for information on household agricultural activities along with other information on the households like human capital, other economic activities, access to services and resources. The ability to follow the same households over time, makes the GHS-Panel a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses to be made of how households add to their human and physical capital, how education affects earnings and the role of government policies and programs on poverty, inter alia.

The objectives of the survey are as follows 1. Allowing welfare levels to be produced at the state level using small area estimation techniques resulting in state-level poverty figures 2. With the integration of the longitudinal panel survey with GHS, it will be possible to conduct a more comprehensive analysis of poverty indicators and socio-economic characteristics 3. Support the development and implementation of a Computer Assisted Personal Interview (CAPI) application for the paperless collection of GHS 4. Developing an innovative model for collecting agricultural data 5. Capacity building and developing sustainable systems for the production of accurate and timely information on agricultural households in Nigeria. 6. Active dissemination of agriculture statistics

The second wave consists of two visits to the household: the post-planting visit occurred directly after the planting season to collect information on preparation of plots, inputs used, labour used for planting and other issues related to the planting season. The post-harvest visit occurred after the harvest season and collected information on crops harvested, labour used for cultivating and harvest activities, and other issues related to the harvest cycle.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

Agricultural farming household members.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample is designed to be representative at the national level as well as at the zonal (urban and rural) levels. The sample size of the GHS-Panel (unlike the full GHS) is not adequate for state-level estimates.

The sample is a two-stage probability sample:

First Stage: The Primary Sampling Units (PSUs) were the Enumeration Areas (EAs). These were selected based on probability proportional to size (PPS) of the total EAs in each state and FCT, Abuja and the total households listed in those EAs. A total of 500 EAs were selected using this method.

Second Stage: The second stage was the selection of households. Households were selected randomly using the systematic selection of ten (10) households per EA. This involved obtaining the total number of households listed in a particular EA, and then calculating a Sampling Interval (S.I) by dividing the total households listed by ten (10). The next step was to generate a random start 'r' from the table of random numbers which stands as the 1st selection. Consecutive selection of households was obtained by adding the sampling interval to the random start.

Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 households per EA are usually selected and give robust estimates.

In all, 500 clusters/EAs were canvassed and 5,000 households were interviewed. These samples were proportionally selected in the states such that different states had different samples sizes depending on the total number of EAs in each state.

Households were not selected using replacement. Thus the final number of household interviewed was slightly less than the 5,000 eligible for interviewing. The final number of households interviewed was 4,986 for a non-response rate of 0.3 percent. A total of 27,533 household members were interviewed. In the second, or Post-Harvest Visit, some household had moved as had individuals, thus the final number of households with data in both points of time (post planting and post harvest) is 4,851, with 27,993 household members.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Data Entry This survey used a concurrent data entry approach. In this method, the fieldwork and data entry were handled by each team assigned to the state. Each team consisted of a field supervisor, 2-4 interviewers and a data entry operator. Immediately after the data were collected in the field by the interviewers, the questionnaires were handed over to the supervisor to be checked and documented. At the end of each day of fieldwork, the questionnaires were then passed to the data entry operator for entry. After the questionnaires were entered, the data entry operator generated an error report which reported issues including out of range values and inconsistencies in the data. The supervisor then checked the report, determined what should be corrected, and decided if the field team needed to revisit the household to obtain additional information. The benefits of this method are that it allows one to: - Capture errors that might have been overlooked by a visual inspection only, - Identify errors early during the field work so that if any correction required a revisit to the household, it could be done while the team was still in the EA

The CSPro software was used to design the specialized data entry program that was used for the data entry of the questionnaires.

The data cleaning process was done in a number of stages. The first step was to ensure proper quality control during the fieldwork. This was achieved in part by using the concurrent data entry system which was, as explained above, designed to highlight many of the errors that occurred during the fieldwork. Errors that are caught at the fieldwork stage are 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 sent from the state to the head office of NBS where a second stage of data cleaning was undertaken.

During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information for required variables, sections, questionnaires and EAs. Any problems found were then reported back to the state where the correction was then made. This was an ongoing process until all data were delivered to the head office.

After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete set of data. Where problems were identified, this was reported to the state. There the questionnaires were checked and where necessary the relevant households were revisited and a report sent back to the head office with the corrections.

The final stage of the cleaning process was to ensure that the household- and individual-level data sets were correctly merged across all sections of the household questionnaire. 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. This was also done for crop- by-plot information as well.

Response rate

The response rate was very high. Response rate after field work was calculated to be 93.9% while attrition rate was 6.1% for households. During the tracking period, 52.4% of the attrition was tracked while at the end of the whole exercise, the response rate was: Post Harvest: 97.1%

Sampling error estimates

No sampling error

Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely-designed Household Survey includes modules that measure the cognitive skills (reading, writing and numeracy), socio-emotional skills (personality, behavior and preferences) and job-specific skills (subset of transversal skills with direct job relevance) of a representative sample of adults aged 15 to 64 living in urban areas, whether they work or not. The cognitive skills module also incorporates a direct assessment of reading literacy based on the Survey of Adults Skills instruments. Modules also gather information about family, health and language. The STEP Skills Measurement Survey for Ukraine is integrated into the Ukrainian Longitudinal Monitoring Survey (ULMS) 2012.

Geographic coverage

The STEP survey was limited to the urban area of Ukraine.

Analysis unit

The units of analysis are the individual respondents and households. A household roster is undertaken at the start of the survey and the individual respondent is randomly selected among all household members aged 15 to 64 included. The random selection process was designed by the STEP team and compliance with the procedure is carefully monitored during fieldwork.

Universe

The target population for the Ukraine STEP survey comprises all non-institutionalized persons 15 to 64 years of age (inclusive) living in private dwellings in urban areas of the country at the time of data collection. This includes all residents except foreign diplomats and non-nationals working for international organizations.

The sample excluded individuals permanently institutionalized in medical facilities, military quarters, and prisons; these exclusions totalled about 725,000 persons or about 2% of the population. Also excluded from STEP was a 30-km zone around the Chernobyl Nuclear Power Plant, an area with a high level of radiation contamination where public access is restricted and all population was evacuated.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Ukraine used a stratified sample design comprised of three components: 1) ULMS Panel Sample; 2) New ULMS-2012 subsample; 3) Step Urban Subsample.

In the ULMS Panel Sample and the Step Urban Subsample, the urban sample was selected within 26 strata consisting of the Autonomous Republic of Crimea, the city of Kiev, and 24 Oblasts, i.e., geographic administrative units. In the New ULMS-2012 subsample, there was no explicit stratification. The Survey Weighting Summary (see related materials) provides more information on the sampling procedure.

Sampling deviation

Some of the sampled households were ineligible for STEP for reasons such as vacant, not habitable, no eligible household member, etc.

Mode of data collection

Face-to-face [f2f]

Research instrument

The merged ULMS-STEP survey instrument consists of three questionnaires : (i) the merged household questionnaire\roster, including the first block of STEP; (ii) the standard individual questionnaire, including the fifth block of STEP and some parts of the second, third and fourth blocks of STEP; (iii) and the extended individual questionnaire, with an additional module on employment skills and a Reading Literacy Assessment developed by Educational Testing Services (ETS).

All countries adapted and translated both instruments from English, following the STEP Technical Standards: 2 independent translators adapted and translated the Background Questionnaire and Reading Literacy Assessment, while reconciliation was carried out by a third translator. In the Ukraine STEP survey, household and individual questionnaires were prepared in both Ukranian and Russian. However, the literacy assessment was done in Ukrainian only (due to budget constraints).

• The survey instruments were both piloted as part of the survey pretest.
• The adapted Background Questionnaires are provided in English as external resources. The Reading Literacy Assessment is protected by copyright and will not be published.

Country-specific questions on the Household Questionnaire result from a merge of STEP Ukraine survey with ULMS-2012 panel study.

Cleaning operations

STEP Data Management Process 1. Raw data is sent by the survey firm 2. The WB STEP team runs data checks on the Background Questionnaire data. - ETS runs data checks on the Reading Literacy Assessment data. - Comments and questions are sent back to the survey firm. 3. The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data. 4. The WB STEP team and ETS check the data files are clean. This might require additional iterations with the survey firm. 5. Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies. 6. ETS scales the Reading Literacy Assessment data. 7. The WB STEP team merges the Background Questionnaire data with the Reading Literacy Assessment data and computes derived variables.

Detailed information data processing in STEP surveys is provided in the 'Guidelines for STEP Data Entry Programs' document provided as an external resource. The template do-file used by the STEP team to check the raw background questionnaire data is provided as an external resource.

Response rate

An overall response rate of 60.4% was achieved in the Ukraine STEP Survey.

Sampling error estimates

A weighting documentation was prepared for each participating country and provides some information on sampling errors. All country weighting documentations are provided as an external resource.

Abstract

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

Geographic coverage

National coverage

Analysis unit

Households and individual household members

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

Sampling Frame

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

Sample Allocation and Selection

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

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

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

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

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

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

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

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

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

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

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

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

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

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

Cleaning operations

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

Response rate

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

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

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

Sampling error estimates

The sample design for the

Abstract

The GHS is a cross-sectional survey of 22,000 households throughout the country. The panel component (GHS-Panel) is now being applied to 5,000 households of the GHS and covers multiple agricultural activities. The focus of this panel component is to improve data from the agriculture sector and link this to other facets of household behavior and characteristics. The GHS-Panel drew heavily on the HNLSS and the NASS to create a new survey instrument and method to shed light on the role of agriculture in households’ economic wellbeing. The NBS implemented the first stage (Post Planting) of the first wave of the GHS-Panel in 2010. This panel is a subset of the full GHS (or GHS-Cross Section) that will be finished in 2011.) It is envisaged that the GHS-Panel will be carried out every two years while the GHS-Cross Section will be carried out annually.

The specific outputs and outcomes of the revised GHS with panel component are: - Development of an innovative model for collecting agricultural data in conjunction with household data; - Development of a model of inter-institutional collaboration between NBS and the FMA&RD and NFRA, inter alia, to ensure the relevance and use of the new GHS; - Building the capacity to generate a sustainable system for the production of accurate and timely information on agricultural households in Nigeria. - Comprehensive analysis of poverty indictors and socio-economic characteristics.

Geographic coverage

National, the survey covered all the 36 states and Federal Capital Territory (FCT).

Analysis unit

• Households
• Individuals
• Agricultural Plots

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The GHS-Panel (Post Planting 2010), like all household surveys in the country, is based on the Master Sample Frame, This Frame is based on the 2006 Housing and Population Census conducted by the National Population Commission (NpopC). The census includes approximately 662,000 enumeration areas (EAs) throughout the country. From the census, the Master Frame was constructed at the local government area (LGA). In 668 LGAs, 30 EAs were scientifically selected. The remaining six LGAs are found in FCT, Abuja. Forty EAs were scientifically selected in each of these 6 LGAs.. This gives a total of 23,280 EAs selected nationally. This is the Master Frame.

From the Master Frame a master sample frame, called the National Integrated Survey of Households 2007/2012 Master Sample Frame (NISH-MSF) was developed. The NISHMSF was constructed by pooling the LGAs in the Master Frame by state. Thereafter, a systematic sample of 200 EAs was selected with equal probability across all LGAs within the state. Furthermore, the NISH EAs in each state were divided into 20 replicates of 10 EAs each. However, the sample EAs for most national household surveys such as the GHS are based on a sub-sample of the NISH-MSF, selected as a combination of replicates from NISH-MSF frame. For the GHS-Panel, the sample is a subset of the EAs selected for the GHS.

Sample Framework The sample frame includes all thirty-six (36) states of the federation and Federal Capital Territory (FCT), Abuja. Both urban and rural areas were covered and in all, 500 clusters/EAs were canvassed and 5,000 households were interviewed. These samples were proportionally selected in the states such that different states have different samples.

Sample Selection The GHS Panel Survey used a two stage stratified sample selection process.

First Stage The Primary Sampling Units (PSUs) were the Enumeration Areas (EAs). These were selected based on probability proportional to size (PPS) of the total EAs in each state and FCT, Abuja and the total households listed in those EAs.

Second Stage The second stage involved the systematic selection of ten (10) households per EA. This involved obtaining the total number of households listed in a particular EA, and then calculating a Sampling Interval (S.I) by dividing the total households listed by ten (10). The next step is to generate a random start ‘r’ from the table of random numbers which stands as the 1st selection. The second selection is obtained by adding the sampling interval to the random start. For each of the next selections, the sampling interval was added to the value of the previous selection until the 10th selection is obtained. Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 HHs per EA are usually selected and give robust estimates.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey consisted of two household questionnaires and one community questionnaire. The first designated by ‘HOUSEHOLD QUESTIONNAIRE’ was administered to all households in the sample. The second questionnaire ‘AGRICULTURE QUESTIONNAIRE was administered to all households engaged in agriculture activities such as crop farming, livestock rearing and other agricultural and related activities. The third Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the community.

Cleaning operations

This survey used concurrent data entry approach. In this method, the fieldwork and data entry were handled by each team assigned to the state. Each team consisted of a field supervisor, 2-4 interviewers and a data entry operator. Immediately after the data were collected in the field by the interviewers and supervisors (the supervisors administered the community questionnaires and collected data on prices), the questionnaires were handed over to the supervisor to be checked and documented. At the end of each day of fieldwork, the questionnaires were then passed to the data entry operator for entry. After the questionnaires were entered, the data entry operator generated an error report which reported issues including out of range values and inconsistencies in the data. The supervisor then checked the report, determined what should be corrected, and decided if the field team needed to revisit the household to obtain additional information. The benefits of this method are that it allows one to: - Capture errors that might have been overlooked by a visual inspection only, - Identify errors early during the field work so that if any correction required a revisit to the household, it could be done while the team was still in the EA

The CSPro software was used to design the specialized data entry program that was used for the data entry of the questionnaires.

Abstract

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The first survey that covered all the country governorates was carried out in 1958/1959 followed by a long series of similar surveys. The current survey, HIECS 2012/2013, is the eleventh in this long series.

Starting 2008/2009, Household Income, Expenditure and Consumption Surveys were conducted each two years instead of five years. This would enable better tracking of the rapid changes in the level of the living standards of the Egyptian households.

CAPMAS started in 2010/2011 to follow a panel sample of around 40% of the total household sample size. The current survey is the second one to follow a panel sample. This procedure will provide the necessary data to extract accurate indicators on the status of the society. The CAPMAS also is pleased to disseminate the results of this survey to policy makers, researchers and scholarly to help in policy making and conducting development related researches and studies

The survey main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To define average household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services. - To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index. - To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household. - To provide a time series of the most important data related to dominant standard of living from economic and social perspective. This will enable conducting comparisons based on the results of these time series. In addition to, the possibility of performing geographical comparisons.

Compared to previous surveys, the current survey experienced certain peculiarities, among which : 1) The total sample of the current survey (24.9 thousand households) is divided into two sections: a - A new sample of 16.1 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, ....... etc.

b - A panel sample of 2008/2009 survey data of around 8.8 thousand households were selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2) Some additional questions that showed to be important based on previous surveys results, were added to the survey questionnaire, such as: a - The extent of health services provided to monitor the level of services available in the Egyptian society. By collecting information on the in-kind transfers, the household received during the year; in order to monitor the assistance the household received from different sources government, association,..etc. b - Identifying the main outlet of fabrics, clothes and footwear to determine the level of living standards of the household.

3) Quality control procedures especially for fieldwork are increased, to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment.

Geographic coverage

National coverage, covering a sample of urban and rural areas in all the governorates.

Analysis unit

• Household/family
• Individual/person

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of HIECS 2012/2013 is a self-weighted two-stage stratified cluster sample, of around 24.9 households. The main elements of the sampling design are described in the following.

Sample Size The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 24863 households has been considered, and was distributed between urban and rural with the percentages of 45.4 % and 54.6, respectively. This sample is divided into two parts: a) A new sample of 16094 households selected from main enumeration areas. b) A panel sample of 8769 households (selected from HIECS 2010/2011 and the preceding survey in 2008/2009).

Cluster Size The cluster size in the previous survey has been decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, it has been decided to use a cluster size of only 8 households (In HIECS 2011/2012 a cluster size of 16 households was used). While the cluster size for the panel sample was 4 households.

Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2012 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources.

New Households Sample 1000 sample areas were selected across all governorates (urban/rural) using a proportional technique with the sample size. The number required for each governorate (urban/rural) was selected from the enumeration areas of the core sample using a systematic sampling technique.

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following: 1) Expenditure and Consumption Questionnaire. 2) Diary Questionnaire (Assisting questionnaire). 3) Income Questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention 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.
• Persons 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).

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 the 8th of May 2014 and ended on the 23rd of 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 CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The First Survey that covered all the country governorates was carried out in 1958/1959 followed by a long series of similar surveys. The current survey, HIECS 2015, is the twelfth in this long series. Starting 2008/2009, Household Income, Expenditure and Consumption Surveys were conducted each two years instead of five years. this would enable better tracking of the rapid changes in the level of the living standards of the Egyptian households.

CAPMAS started in 2010/2011 to follow a panel sample of around 40% of the total household sample size. The current survey is the second one to follow a panel sample. This procedure will provide the necessary data to extract accurate indicators on the status of the society. The CAPMAS also is pleased to disseminate the results of this survey to policy makers, researchers and scholarly to help in policy making and conducting development related researches and studies

The survey main objectives are:

• To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials.

• To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates.

• To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period.

• To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation.

• To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands.

• To define average household and per-capita income from different sources.

• To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey.

• To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas.

• To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure.

• To study the relationships between demographic, geographical, housing characteristics of households and their income.

• To provide data necessary for national accounts especially in compiling inputs and outputs tables.

• To identify consumers behavior changes among socio-economic groups in urban and rural areas.

• To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas.

• To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services.

• To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index.

• To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household.

• To provide a time series of the most important data related to dominant standard of living from economic and social perspective. This will enable conducting comparisons based on the results of these time series. In addition to, the possibility of performing geographical comparisons.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The sample of HIECS 2015 is a self-weighted two-stage stratified cluster sample. The main elements of the sampling design are described in the following.

1- Sample Size The sample size is around 25 thousand households. It was distributed between urban and rural with the percentages of 45% and 55%, respectively.

2- Cluster size The cluster size is 10 households in most governorates. It reached 20 households in Port-Said, Suez, Ismailiya, Damietta, Aswan and Frontier governorates, since the sample size in those governorates is smaller compared to others.

3- Sample allocation in different governorates 45% of the survey sample was allocated to urban areas (11260 households) and the other 55% was allocated to rural areas (13740 households). The sample was distributed on urban/rural areas in different governorates proportionally with the household size A sample size of a minimum of 1000 households was allocated to each governorate to ensure accuracy of poverty indicators. Therefore, the sample size was increased in Port-Said, Suez, Ismailiya, kafr el-Sheikh, Damietta, Bani Suef, Fayoum, Qena, Luxor and Aswan, by compensation from other governorates where the sample size exceeds a 1000 households. All Frontier governorates were considered as one governorate.

4- Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2010 and its size reached more than 1 million household selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources.

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following:

1- Expenditure and Consumption Questionnaire. 2- Assisting questionnaire. 3- Income Questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention of Labor Statisticians held in Geneva, 2003. - Using the recent Classification of Individual Consumption According to Purpose (COICOP). - Using more than one approach of expenditure measurement to serve many purposes of the survey.

A brief description of each questionnaire is given next:

----> 1- Expenditure and Consumption Questionnaire This questionnaire comprises 14 tables in addition to identification and geographic data of household on the cover page. The questionnaire is divided into two main sections.

Section one: Household schedule and other information, it includes: - Demographic characteristics and basic data for all household individuals consisting of 25 questions for every person. - Members of household who are currently working abroad. - The household ration card. - The main outlets that provide food and beverage. - Domestic and foreign tourism. - The housing conditions including 16 questions. - Household ownership of means of transportation, communication and domestic appliances. - Date of purchase, status at purchase, purchase value and

Abstract

Because of the importance of the household sector and due to it's large contribution to energy consumption in the Palestinian Territory, PCBS decided to conduct a special household energy survey to cover energy indicators in the household sector. To achieve this, a questionnaire was attached to the Labor Force Survey.

This survey aimed to provide data on energy consumption in the household and to provide data on energy consumption behavior in the society by type of energy.

The survey presents data on various energy households indicators in the Palestinian Territory, and presents statistical data on electricity and other fuel consumption for the household, using type of fuel by different activities (cooking, baking, conditioning, lighting, and water Heating).

Analysis unit

Households

Universe

The target population was all Palestinian households living in West Bank and Gaza.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The sampling frame consists of all the enumeration areas enumerated in 2007: each enumeration area consists of buildings and housing units with an average of around 124 households. These enumeration areas are used as primary sampling units (PSUs) in the first stage of the sampling selection.

Sample size The estimated sample size is 3,184 households.

Sampling Design: The sample of this survey is a part of the main sample of the Labor Force Survey (LFS), which is implemented quarterly (distributed over 13 weeks) by PCBS since 1995. This survey was attached to the LFS in the third quarter of 2013 and the sample comprised six weeks, from the eighth week to the thirteen week of the third round of the Labor Force Survey of 2013. The sample is two-stage stratified cluster sample:

First stage: selection of a stratified systematic random sample of 206 enumeration areas for the semi-round.

Second stage: selection of a random area sample of an average of 16 households from each enumeration area selected in the first stage.

Sample strata The population was divided by: 1. Governorate (16 governorates) 2. Type of locality (urban, rural, refugee camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

The design of the questionnaire for the Household Energy Survey was based on the experiences of similar countries as well as on international standards and recommendations for the most important indicators, taking into account the special situation of the Palestinian Territory.

Cleaning operations

The data processing stage consisted of the following operations: - Editing and coding prior to data entry: all questionnaires were edited and coded in the office using the same instructions adopted for editing in the field. - Data entry: The household energy survey questionnaire was programmed onto handheld devices and data were entered directly using these devices in the West Bank. With regard to Jerusalem J1 and the Gaza Strip, data were entered into the computer in the offices in Ramallah and Gaza. At this stage, data were entered into the computer using a data entry template developed in Access. The data entry program was prepared to satisfy a number of requirements: · To prevent the duplication of questionnaires during data entry. · To apply checks on the integrity and consistency of entered data. · To handle errors in a user friendly manner. · The ability to transfer captured data to another format for data analysis using statistical analysis software such as SPSS.

Response rate

During fieldwork 3,184 families were visited in the Palestinian Territory. There are 2,692 complete questionnaires, which in percentage was about 85%.

Sampling error estimates

Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences are anticipated in comparison with the real values obtained through censuses. The variance was calculated for the most important indicators: the variance table is attached with the final report. There is no problem in the dissemination of results at national and regional level (North, Middle, South of West Bank, Gaza Strip) and by locality. However, the indicator of averages of household consumption for certain fuels by region show a high variance.

Non Sampling Errors The implementation of the survey encountered non-response where the household was not present at home during the field work visit and where the housing unit was vacant: these made up a high percentage of the non-response cases. The total non-response rate was 10.8%, which is very low when compared to the household surveys conducted by PCBS. The refusal rate was 3.3%, which is very low compared to the household surveys conducted by PCBS and may be attributed to the short and clear questionnaire.

The survey sample consisted of around 3,184 households, of which 2,692 households completed the interview: 1,757 households from the West Bank and 935 households in the Gaza Strip. Weights were modified to account for the non-response rate. The response rate in the West Bank was 86.8 % while in the Gaza Strip it was 94.3%.

Non-Response Cases

No. of cases non-response cases
2,692 Household completed 35 Household traveling 17 Unit does not exist 111 No one at home
102 Refused to cooperate
152 Vacant housing unit 5 No available information
70 Other
3,184 Total sample size

Response and non-response formulas:

Percentage of over coverage errors = Total cases of over coverage x 100% Number of cases in original sample = 5.3%

Non response rate = Total cases of non response x 100% Net Sample size = 10.8%

Net sample = Original sample - cases of over coverage Response rate = 100% - non-response rate = 89.2%

Treatment of non-response cases using weight adjustment

Where

the primary weight before adjustment for the household i g: adjustment group by ( governorate, locality type ). fg: weight adjustment factor for the group g. : Total weights in group g
cases : Total weights of over coverage : Total weights of response cases

We calculate fg for each group ,and final we obtain the final household weight () by using the following formula:

Comparability The data of the survey are comparable geographically and over time by comparing data from different geographical areas to data of previous surveys and the 2007 census.

Data quality assurance procedures Several procedures were undertaken to ensure appropriate quality control in the survey. Field workers were trained on the main skills prior to data collection, field visits were conducted to field workers to ensure the integrity of data collection, editing of questionnaires took place prior to data entry and a data entry application was used that prevents errors during the data entry process, then the data were reviewed. This was done to ensure that data were error free, while cleaning and inspection of anomalous values were carried out to ensure harmony between the different questions on the questionnaire.

Technical notes The following are important technical notes on the indicators presented in the results of the survey: · Some households were not present in their houses and could not be seen by interviewers. · Some households were not accurate in answering the questions in the questionnaire.
· Some errors occurred due to the way the questions were asked by interviewers. · Misunderstanding of the questions by the respondents. · Answering questions related to consumption based on estimations. · In all calculations related to gasoline, the average of all available types of gasoline was used. · In this survey, data were collected about the consumption of olive cake and coal in households, but due to lack of relevant data and fairly high variance, the data were grouped with others in the statistical tables. · The increase in consumption of electricity and the decrease in the consumption of the other types of fuel in the Gaza Strip reflected the Israeli siege imposed on the territory.

Data appraisal

The data of the survey is comparable geographically and over time by comparing the data between different geographical areas to data of previous surveys.

Abstract

The STEP (Skills Toward Employment and Productivity) Measurement program is the first ever initiative to generate internationally comparable data on skills available in developing countries. The program implements standardized surveys to gather information on the supply and distribution of skills and the demand for skills in labor market of low-income countries.

The uniquely-designed Household Survey includes modules that measure the cognitive skills (reading, writing and numeracy), socio-emotional skills (personality, behavior and preferences) and job-specific skills (subset of transversal skills with direct job relevance) of a representative sample of adults aged 15 to 64 living in urban areas, whether they work or not. The cognitive skills module also incorporates a direct assessment of reading literacy based on the Survey of Adults Skills instruments. Modules also gather information about family, health and language.

Geographic coverage

The cities that are covered are La Paz, El Alto, Cochabamba and Santa Cruz de la Sierra.

Analysis unit

The units of analysis are the individual respondents and households. A household roster is undertaken at the start of the survey and the individual respondent is randomly selected among all household members 15 to 64 years old. The random selection process was designed by the STEP team and compliance with the procedure is carefully monitored during fieldwork.

Universe

The STEP target population is the population 15-64 years old, living in urban areas, as defined by each country's statistical office. The following are excluded from the sample: - Residents of institutions (prisons, hospitals, etc.) - Residents of senior homes and hospices - Residents of other group dwellings such as college dormitories, halfway homes, workers' quarters, etc. - Persons living outside the country at the time of data collection

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified 3-stage sample design was implemented in Bolivia. The stratification variable is city-wealth category. There are 20 strata created by grouping the primary sample units (PSUs) into the 4 cities, i.e.,1- La Paz, 2-El Alto, 3-Cochabamba, 4-Santa Cruz de la Sierra, and 5 wealth categories, i.e., 1-Poorest, 2-Moderately Poor, 3-Middle Wealth, 4-Moderately Rich, 5-Rich.

The source of the sample frame of the first stage units is the 2001 National Census of Population and Housing carried out by the National Institute of Statistics. The primary sample unit (PSU) is a Census Sector. A sample of 218 PSUs was selected from the 10,304 PSUs on the sample frame. This sample of PSUs was comprised of 160 'initial' PSUs and 58 'reserve' PSUs. Of the 218 sampled PSUs, there were 169 activated PSUs consisting of 155 Initial Sampled PSUs and 14 Reserve sampled PSUs. Among the 160 'initial' PSUs, 5 PSUs were replaced due to security concerns; also, 14 reserve PSUs were activated to supplement the sample for initial PSUs where the target sample of 15 interviews was not achieved due to high levels of non-response; thus, only 169 PSUs were actually activated during data collection. The PSUs were grouped according to city-wealth strata, and within each city-wealth stratum PSUs were selected with probability proportional to size (PPS), where the measure of size was the number of households in a PSU.

The second stage sample unit (SSU) is a household. The sampling objective was to obtain interviews at 15 households within each of the initial PSU sample, resulting in a final initial sample of 2,400 interviews. At the second stage of sample selection, 45 households were selected in each PSU using a systematic random method. The 45 households were randomly divided into 15 'Initial' households, and 30 'Reserve' households that were ranked according to the random sample selection order. Note: Due to higher than expected levels of non-response in some PSUs, additional households were sampled; thus, the final actual sample in some PSUs exceeded 45 households.

The third stage sample unit was an individual 15-64 years old (inclusive). The sampling objective was to select one individual with equal probability from each selected household.

Mode of data collection

Face-to-face [f2f]

Research instrument

The STEP survey instruments include:

• The background questionnaire developed by the World Bank (WB) STEP team
• Reading Literacy Assessment developed by Educational Testing Services (ETS).

All countries adapted and translated both instruments following the STEP technical standards: two independent translators adapted and translated the STEP background questionnaire and Reading Literacy Assessment, while reconciliation was carried out by a third translator.

The survey instruments were piloted as part of the survey pre-test.

The background questionnaire covers such topics as respondents' demographic characteristics, dwelling characteristics, education and training, health, employment, job skill requirements, personality, behavior and preferences, language and family background.

The background questionnaire, the structure of the Reading Literacy Assessment and Reading Literacy Data Codebook are provided in the document "Bolivia STEP Skills Measurement Survey Instruments", available in external resources.

Cleaning operations

STEP data management process:

1) Raw data is sent by the survey firm 2) The World Bank (WB) STEP team runs data checks on the background questionnaire data. Educational Testing Services (ETS) runs data checks on the Reading Literacy Assessment data. Comments and questions are sent back to the survey firm. 3) The survey firm reviews comments and questions. When a data entry error is identified, the survey firm corrects the data. 4) The WB STEP team and ETS check if the data files are clean. This might require additional iterations with the survey firm. 5) Once the data has been checked and cleaned, the WB STEP team computes the weights. Weights are computed by the STEP team to ensure consistency across sampling methodologies. 6) ETS scales the Reading Literacy Assessment data. 7) The WB STEP team merges the background questionnaire data with the Reading Literacy Assessment data and computes derived variables.

Detailed information on data processing in STEP surveys is provided in "STEP Guidelines for Data Processing" document, available in external resources. The template do-file used by the STEP team to check raw background questionnaire data is provided as an external resource, too.

Response rate

An overall response rate of 43% was achieved in the Bolivia STEP Survey. All non-response cases were documented (refusal/not found/no eligible household member, etc.) and accounted for during the weighting process. In such cases, a reserve household was activated to replace the initial household. Procedures are described in "Operation Manual" that is provided as an external resource.

Abstract

The 1997 Jordan Population and Family Health Survey (JPFHS) is a national sample survey carried out by the Department of Statistics (DOS) as part of its National Household Surveys Program (NHSP). The JPFHS was specifically aimed at providing information on fertility, family planning, and infant and child mortality. Information was also gathered on breastfeeding, on maternal and child health care and nutritional status, and on the characteristics of households and household members. The survey will provide policymakers and planners with important information for use in formulating informed programs and policies on reproductive behavior and health.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

SAMPLE DESIGN AND IMPLEMENTATION

The 1997 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, for urban and rural areas, for the three regions (each composed of a group of governorates), and for the three major governorates, Amman, Irbid, and Zarqa.

The 1997 JPFHS sample is a subsample of the master sample that was designed using the frame obtained from the 1994 Population and Housing Census. A two-stage sampling procedure was employed. First, primary sampling units (PSUs) were selected with probability proportional to the number of housing units in the PSU. A total of 300 PSUs were selected at this stage. In the second stage, in each selected PSU, occupied housing units were selected with probability inversely proportional to the number of housing units in the PSU. This design maintains a self-weighted sampling fraction within each governorate.

UPDATING OF SAMPLING FRAME

Prior to the main fieldwork, mapping operations were carried out and the sample units/blocks were selected and then identified and located in the field. The selected blocks were delineated and the outer boundaries were demarcated with special signs. During this process, the numbers on buildings and housing units were updated, listed and documented, along with the name of the owner/tenant of the unit or household and the name of the household head. These activities took place between January 7 and February 28, 1997.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face

Research instrument

The 1997 JPFHS used two questionnaires, one for the household interview and the other for eligible women. Both questionnaires were developed in English and then translated into Arabic. The household questionnaire was used to list all members of the sampled households, including usual residents as well as visitors. For each member of the household, basic demographic and social characteristics were recorded and women eligible for the individual interview were identified. The individual questionnaire was developed utilizing the experience gained from previous surveys, in particular the 1983 and 1990 Jordan Fertility and Family Health Surveys (JFFHS).

The 1997 JPFHS individual questionnaire consists of 10 sections: - Respondent’s background - Marriage - Reproduction (birth history) - Contraception - Pregnancy, breastfeeding, health and immunization - Fertility preferences - Husband’s background, woman’s work and residence - Knowledge of AIDS - Maternal mortality - Height and weight of children and mothers.

Cleaning operations

Fieldwork and data processing activities overlapped. After a week of data collection, and after field editing of questionnaires for completeness and consistency, the questionnaires for each cluster were packaged together and sent to the central office in Amman where they were registered and stored. Special teams were formed to carry out office editing and coding.

Data entry started after a week of office data processing. The process of data entry, editing, and cleaning was done by means of the ISSA (Integrated System for Survey Analysis) program DHS has developed especially for such surveys. The ISSA program allows data to be edited while being entered. Data entry was completed on November 14, 1997. A data processing specialist from Macro made a trip to Jordan in November and December 1997 to identify problems in data entry, editing, and cleaning, and to work on tabulations for both the preliminary and final report.

Response rate

A total of 7,924 occupied housing units were selected for the survey; from among those, 7,592 households were found. Of the occupied households, 7,335 (97 percent) were successfully interviewed. In those households, 5,765 eligible women were identified, and complete interviews were obtained with 5,548 of them (96 percent of all eligible women). Thus, the overall response rate of the 1997 JPFHS was 93 percent. The principal reason for nonresponse among the women was the failure of interviewers to find them at home despite repeated callbacks.

Note: See summarized response rates by place of residence in Table 1.1 of the survey report.

Sampling error estimates

The estimates from a sample survey are subject to two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the result of mistakes made in implementing data collection and data processing (such as failure to locate and interview the correct household, misunderstanding questions either by the interviewer or the respondent, and data entry errors). Although during the implementation of the 1997 JPFHS numerous efforts were made to minimize this type of error, nonsampling errors are not only impossible to avoid but also difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The respondents selected in the 1997 JPFHS constitute only one of many samples that could have been selected from the same population, given the same design and expected size. Each of those samples would have yielded results differing somewhat from the results of the sample actually selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, since the 1997 JDHS-II sample resulted from a multistage stratified design, formulae of higher complexity had to be used. The computer software used to calculate sampling errors for the 1997 JDHS-II was the ISSA Sampling Error Module, which uses the Taylor linearization method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics, such as fertility and mortality rates.

Note: See detailed estimate of sampling error calculation in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months

Note: See detailed tables in APPENDIX C of the survey report.

Abstract

The General Household Survey Panel, Farm Area Measurement Validation Study 2013 was conducted on a subsample of the GHS-Panel survey, it focused on the land area measurement component. The survey was motivated by observed differences between farmer estimates of plot area and GPS measurement in Nigeria and other countries with LSMS-ISA surveys. The study set out to validate GPS measurement and farmer self-reported estimates against the compass and rope measurement, commonly accepted as the gold standard method. The LSMS-ISA, an agriculture-focused project of the LSMS program, and the institutional collaborations on which it is built, provides an ideal platform to support methodological research. The broader LSMS-ISA research agenda is composed of seven primary components:

1. Land area measurement
2. Soil fertility
3. Water resources
4. Labour inputs
5. Skill measurement
6. Production of continuous and extended-harvest crops
7. Computer-assisted personal interviewing for agricultural data.

Four states were purposefully selected based on safety and past performance in area measurement (Benue, Osun, Oyo, and Kogi). The total number of plots measured and included in the validation study were 495, coming from a total of 202 households. The GHSP-FAMVS was carried out in 2013 by the Nigeria National Bureau of Statistics (NBS) in collaboration with The World Bank Living Standards Measurement Study (LSMS) team. Fieldwork began in March 2013 and lasted for approximately 3 weeks.

Geographic coverage

Regional

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The plot size plays a significant role in the accuracy of plot area measurement using the various methods, the validation sample was stratified on four plot size strata to ensure we could test the various methods on larger plots, which are much rarer. Four states were purposefully selected based on safety and past performance in area measurement (Benue, Osun, Oyo, and Kogi). Using the second wave of the GHS panel as the sample frame and the GPS measurement of the plot taken in the post-planting visit, every plot was assigned to some plot-size strata: · strata 1: <=1000 sq. meters · strata 2: 1000-2500 sq. meters · strata 3: 2500-5000sq. Meters · strata 4: >5000 sq. meters).

One hundred plots were then randomly selected from each stratum. This process yielded the selection of 400 plots (211 households). However, in order to maximize the sample at minimal added cost, we included all plots from the selected households, not only the plots that were selected in the first step (totalling 518 plots). From the 518 selected plots, 23 plots were unable to be measured (5 due to land disputes, 4 due to respondent refusal, 14 for other reasons). Therefore, the total number of plots measured and included in the farm area measurement validation study is 495, coming from a total of 202 households. Stratification by plot size in the validation sample results in the unequal probability of plot selection within households from the GHS-Wave 2 sample. Household-level sampling weights were calculated for the validation sample to make them representative of the same household population sampled in Wave 2. Refer to Annex I of the Basic Information Document for details on the construction of the sampling weights.

Mode of data collection

Face-to-face [f2f]

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

The HIECS 2010/2011 is the tenth Household Income, Expenditure and Consumption Survey that was carried out in 2010/2011, among a long series of similar surveys that started back in 1955.

The survey main objectives are: - To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials. - To measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands. - To define average household and per-capita income from different sources. - To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey. - To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas. - To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure. - To study the relationships between demographic, geographical, housing characteristics of households and their income. - To provide data necessary for national accounts especially in compiling inputs and outputs tables. - To identify consumers behavior changes among socio-economic groups in urban and rural areas. - To identify per capita food consumption and its main components of calories, proteins and fats according to its nutrition components and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to its sources, either from household production or not, in addition to household expenditure for non-food commodities and services. - To identify distribution of households according to the possession of some appliances and equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index. - To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household.

Compared to previous surveys, the current survey experienced certain peculiarities, among which : 1- The total sample of the current survey (26.5 thousand households) is divided into two sections: a- A new sample of 16.5 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, ....... etc. b- A panel sample with 2008/2009 survey data of around 10 thousand households was selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years. 2- The number of enumeration area segments is reduced from 2526 in the previous survey to 1000 segments for the new sample, with decreasing the number of households selected from each segment to be (16/18) households instead of (19/20) in the previous survey. 3- Some additional questions that showed to be important based on previous surveys results, were added, such as: a- Collect the expenditure data on education and health on the person level and not on the household level to enable assessing the real level of average expenditure on those services based on the number of beneficiaries. b- The extent of health services provided to monitor the level of services available in the Egyptian society. c- Smoking patterns and behaviors (tobacco types- consumption level- quantities purchased and their values). d- Counting the number of household members younger than 18 years of age registered in ration cards. e- Add more details to social security pensions data (for adults, children, scholarships, families of civilian martyrs due to military actions) to match new systems of social security. f- Duration of usage and current value of durable goods aiming at estimating the service cost of personal consumption, as in the case of imputed rents. 4- Quality control procedures especially for fieldwork, are increased, to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

Covering a sample of urban and rural areas in all the governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The sample of HIECS 2010/2011 is a self-weighted two-stage stratified cluster sample, of around 26500 households. The main elements of the sampling design are described in the following.

1- Sample Size
It has been deemed important to collect a smaller sample size (around 26.5 thousand households) compared to previous rounds due to the convergence in the time period over which the survey is conducted to be every two years instead of five years because of its importance. The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 26500 households has been considered, and was distributed between urban and rural with the percentages of 47.1 % and 52.9, respectively. This sample is divided into two parts: a- A new sample of 16.5 thousand households selected from main enumeration areas. b- A panel sample with 2008/2009 survey data of around 10 thousand households.

2- Cluster size
The cluster size in the previous survey has been decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, it has been decided to use a cluster size of only 16 households (that was increased to 18 households in urban governorates and Giza, in addition to urban areas in Helwan and 6th of October, to account for anticipated non-response in those governorates: in view of past experience indicating that non-response may almost be nil in rural governorates). While the cluster size for the panel sample was 4 households.

3- Core Sample The core sample is the master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2010 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources. New Households Sample 1000 sample areas were selected across

Abstract

Environmental statistics relating to households are an important instrument for making decisions, planning, and drawing up strategies for the environment. Due to the lack of data on this subject in Palestine, PCBS is building and developing a database on the environment in the household sector.

This survey is based on a household sample survey conducted during the period from 24 March 2015 to 31 May 2015. It provides basic statistics on various aspects of the environment, including water, solid waste, wastewater, noise, and air pollution. A special questionnaire was designed in accordance with United Nations standards and recommendations in the field of environmental statistics and adapted to Palestinian conditions.

This survey presents data on various environmental household indicators in Palestine and on water consumption for the household sector by water source, methods of solid waste disposal and their main components, the disposal of wastewater, and the existence of cesspits and water wells, in addition to exposure to noise and air pollution by source and time.

This report is divided into three chapters: the first chapter defines the main findings of the report. The second chapter explains the methodology of data collection and tabulation, in addition to details regarding data quality and estimates of data sources. The third chapter contains the concepts and definitions used in this report

Geographic coverage

It consists of all Palestinian households who are staying normally in Palestine during 2015.

Analysis unit

household

Universe

It consists of all Palestinian households who are staying normally in Palestine during 2015.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame

The sampling frame was based on master sample which was update in 2013-2014 for (Expenditure and Consumption Survey (PECS) and Multiple Indicator Cluster Survey (MICS)) surveys, and the frame consists from enumeration areas. These enumeration areas are used as primary sampling units (PSUs) in the first stage of the sampling selection.

Sampling Design: Two stage stratified cluster sample as following: First stage: selection of a PPS random sample of 370 enumeration areas. Second stage: A systematic random sample of 20 households from each enumeration area selected in the first stage. Sample strata: The population was divided by: 1- Governorate 2- Locality type (urban, rural, camps)

Sample Size: The sample size is 7,690 households for Palestine level, 6,609 households responded.

Mode of data collection

Face-to-face [f2f]

Research instrument

The environmental questionnaire was designed in accordance with similar international experiences and with international standards and recommendations for the most important indicators, taking into account the special situation of Palestine.

Cleaning operations

The data processing stage consisted of the following operations: Editing and coding prior to data entry: all questionnaires were edited and coded in the office using the same instructions adopted for editing in the field.

Data entry: The household Environmental survey questionnaire was programmed and the data were entered into the computer in the offices in Nablus, Hebron, Ramallah and Gaza. At this stage, data were entered into the computer using a data entry template developed in Access. The data entry program was prepared to satisfy a number of requirements: To prevent the duplication of questionnaires during data entry. To apply checks on the integrity and consistency of entered data. To handle errors in a user friendly manner. The ability to transfer captured data to another format for data analysis using statistical analysis software such as SPSS.

Response rate

7,690 households had been reached as a representative sample to Palestine, where the number of completed questionnaires amounted to 6,609 questionnaires of which 4,536 questionnaires were in West Bank and 2,073 questionnaires in Gaza Strip. Weights were amended at the level of design strata to modify effects of refusals rates and non response.

Response rate = 100% - the percentage of non-response. And equal to = 89.5%

Sampling error estimates

The concept of data quality covers many aspects, starting from the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are seven dimensions of statistical quality: relevance, accuracy, timeliness and punctuality, accessibility and clarity, comparability, coherence and completeness.

Accuracy

This includes many aspects of the survey, mainly statistical errors due to the use of a sample, and also non-statistical errors from workers and survey tools. It also includes the response rates in this survey and their effect on the assumptions. This section includes:

Sampling Errors: Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences are expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators and the variance table is attached with the final report. There is no problem with the dissemination of results on national and regional level (North, Middle, South West Bank, Gaza Strip) or by locality type.

Non Sampling Errors: The non-sampling errors are possible to occur at all phases of implementing the project, through data collection and entry which could be summarized as non-response errors, and responding errors (respondents), and interview errors (fieldworkers) and data-entry errors. To avoid errors and reduce the impact, it had been made ??great efforts through extensive training of fieldworkers on how to conduct interviews, things that ought to be followed during an interview, things that should be avoided, making some practical and theoretical exercises during training session, in addition to providing them with a manual booklet for fieldworkers which contained a private key questions of questionnaire, mechanism to fill questionnaire and methods of dealing with respondents to reduce refusal rates and providing correct and non-biased data, Also data entry staff were trained on the data entry program, which was tested before starting the data entry process.

As for office work, they had been trained for a special auditing of questionnaires and error detection, which greatly reduced rates of errors during field work. In order to reduce the percentage of errors during data entry, the program was designed to enter data so as not to allow any mistakes during the process and contained many of logical terms. This process led to disclosure of most of errors that had not been found in earlier phases of the work, where they were correcting all the errors that had been discovered.

After the completion of the aforesaid audits, data consistency was examined by computer using frequency and cross tables as turned out to be quite consistent, Errors impact was not detectable on data quality. This in turn gave a good impression of those in charge of the survey that we could rely on this data and extract reliable statistical and high significant indicators on the reality of corruption in Palestine.

Abstract

The main objective of the HEIS survey is to obtain detailed data on household expenditure and income, linked to various demographic and socio-economic variables, to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. Therefore, to achieve these goals, the sample had to be representative on the sub-district level. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality.

Data collected through the survey helped in achieving the following objectives: 1. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index 2. Study the consumer expenditure pattern prevailing in the society and the impact of demograohic and socio-economic variables on those patterns 3. Calculate the average annual income of the household and the individual, and assess the relationship between income and different economic and social factors, such as profession and educational level of the head of the household and other indicators 4. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it 5. Provide the necessary data for the national accounts related to overall consumption and income of the household sector 6. Provide the necessary income data to serve in calculating poverty indices and identifying the poor chracteristics as well as drawing poverty maps 7. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty

Geographic coverage

National

Analysis unit

• Household/families
• Individuals

Universe

The survey covered a national sample of households and all individuals permanently residing in surveyed households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2008 Household Expenditure and Income Survey sample was designed using two-stage cluster stratified sampling method. In the first stage, the primary sampling units (PSUs), the blocks, were drawn using probability proportionate to the size, through considering the number of households in each block to be the block size. The second stage included drawing the household sample (8 households from each PSU) using the systematic sampling method. Fourth substitute households from each PSU were drawn, using the systematic sampling method, to be used on the first visit to the block in case that any of the main sample households was not visited for any reason.

To estimate the sample size, the coefficient of variation and design effect in each subdistrict were calculated for the expenditure variable from data of the 2006 Household Expenditure and Income Survey. This results was used to estimate the sample size at sub-district level, provided that the coefficient of variation of the expenditure variable at the sub-district level did not exceed 10%, with a minimum number of clusters that should not be less than 6 at the district level, that is to ensure good clusters representation in the administrative areas to enable drawing poverty pockets.

It is worth mentioning that the expected non-response in addition to areas where poor families are concentrated in the major cities were taken into consideration in designing the sample. Therefore, a larger sample size was taken from these areas compared to other ones, in order to help in reaching the poverty pockets and covering them.

Mode of data collection

Face-to-face [f2f]

Research instrument

List of survey questionnaires: (1) General Form (2) Expenditure on food commodities Form (3) Expenditure on non-food commodities Form

Cleaning operations

Raw Data The design and implementation of this survey procedures were: 1. Sample design and selection 2. Design of forms/questionnaires, guidelines to assist in filling out the questionnaires, and preparing instruction manuals 3. Design the tables template to be used for the dissemination of the survey results 4. Preparation of the fieldwork phase including printing forms/questionnaires, instruction manuals, data collection instructions, data checking instructions and codebooks 5. Selection and training of survey staff to collect data and run required data checkings 6. Preparation and implementation of the pretest phase for the survey designed to test and develop forms/questionnaires, instructions and software programs required for data processing and production of survey results 7. Data collection 8. Data checking and coding 9. Data entry 10. Data cleaning using data validation programs 11. Data accuracy and consistency checks 12. Data tabulation and preliminary results 13. Preparation of the final report and dissemination of final results

Harmonized Data - The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets - The harmonization process started with cleaning all raw data files received from the Statistical Office - Cleaned data files were then all merged to produce one data file on the individual level containing all variables subject to harmonization - A country-specific program was generated for each dataset to generate/compute/recode/rename/format/label harmonized variables - A post-harmonization cleaning process was run on the data - Harmonized data was saved on the household as well as the individual level, in SPSS and converted to STATA format

Abstract

This data is from the first round of a unique, cross-country panel survey conducted in Pakistan by the Secure Livelihoods Research Consortium (SLRC). The Overseas Development Institute (ODI) is the lead organisation of SLRC. SLRC partners who participated in the survey were: the Centre for Poverty Analysis (CEPA) in Sri Lanka, Feinstein International Center (FIC, Tufts University), the Sustainable Development Policy Institute(SDPI) in Pakistan, Humanitarian Aid and Reconstruction, based at Wageningen University (WUR) in the Netherlands, the Nepal Centre for Contemporary Research (NCCR), and the Food and Agriculture Organization (FAO).

This survey generated the first round of data on people's livelihoods, their access to and experience of basic services, and their views of governance actors. SLRC will attempt to re-interview the same respondents in 2015 to find out how the livelihoods and governance perceptions of people shift (or not) over time, and which factors may have contributed towards that change.

Geographic coverage

Pakistan: Swat and Lower Dir districts of Khyber Pakhtunkhwa (KP) Rural and urban

Analysis unit

Some questions are at the level of individuals in household (e.g. livelihood activities, education levels); other questions are at the household level (e.g. assets). A sizeable share of the questionnaire is devoted to perceptions based questions, which are at the individual (respondent) level.

Universe

Randomly selected households in purposely sampled sites (sampling procedure varied slightly by country).

Within a selected household, only one household members was interviewed about the household. Respondents were adults and we aimed to interview a fairly even share of men/ women. In some countries this was achieved, but in other countries the share of male respondents is substantially higher (e.g. Pakistan).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy was designed to select households that are relevant to the main research questions and as well as being of national relevance, while also being able to produce statistically significant conclusions at the study and village level. To meet these objectives, purposive and random sampling were combined at different stages of the sampling strategy. The first stages of the sampling process involved purposive sampling, with random sampling only utilized in the last stage of the process. Sampling locations were selected purposely (including districts and locations within districts), and then randomly households were selected within these locations. A rigorous sample is geared towards meeting the objectives of the research. The samples are not representative for the case study countries and cannot be used to represent the case study countries as a whole, nor for the districts. The samples are representative at the village level, with the exception of Uganda.

Sampling locations (sub-regions or districts, sub-districts and villages) were purposively selected, using criteria, such as levels of service provision or levels of conflict, in order to locate the specific groups of interest and to select geographical locations that are relevant to the broader SLRC research areas and of policy relevance at the national level. For instance, locations experienced high/ low levels of conflict and locations with high/ low provision of services were selected and locations that accounted for all possible combinations of selection criteria were included. Survey locations with different characteristics were chose, so that we could explore the relevance of conflict affectedness, access to services and variations in geography and livelihoods on our outcome variables. Depending on the administrative structure of the country, this process involved selecting a succession of sampling locations (at increasingly lower administrative units).

The survey did not attempt to achieve representativeness at the country /or district level, but it aimed for representativeness at the sub-district /or village level through random sampling (Households were randomly selected within villages so that the results are representative and statistically significant at the village level and so that a varied sample was captured. Households were randomly selected using a number of different tools, depending on data availability, such as random selection from vote registers (Nepal), construction of household listings (DRC) and a quasi-random household process that involved walking in a random direction for a random number of minutes (Uganda).

The samples are statistically significant at the survey level and village level (in all countries) and at the district level in Sri Lanka and sub-region level in Uganda. The sample size was calculated with the aim to achieve statistical significance at the study and village level, and to accommodate the available budget, logistical limitations, and to account for possible attrition between 2012-2015. In a number of countries estimated population data had to be used, as recent population data were not available.

The minimum overall sample size required to achieve significance at the study level, given population and average household size across districts, was calculated using a basic sample size calculator at a 95% confidence level and confidence interval of 5. The sample size at the village level was again calculated at the using a 95% confidence level and confidence interval of 5. . Finally, the sample was increased by 20% to account for possible attrition between 2012 and 2015, so that the sample size in 2015 is likely to be still statistically significant.

The overall sample required to achieve the sampling objectives in selected districts in each country ranged from 1,259 to 3,175 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

One questionnaire per country that includes household level, individual level and respondent level perceptions based questions.

The general structure and content of the questionnaire is similar across all five countries, with about 80% of questions similar, but tailored to the country-specific process. Country-specific surveys were tailored on the basis of a generic survey instrument that was developed by ODI specifically for this survey.

The questionnaires are published in English.

Cleaning operations

CSPro was used for data entries in most countries.

Data editing took place at a number of stages throughout the processing, including: • Office editing and coding • During data entry • Structure checking and completeness • Extensive secondary editing conducted by ODI

Response rate

The required sample sizes were achieved in all countries. Response rates were extremely high, ranging from 99%-100%.

Sampling error estimates

No further estimations of sampling error was conducted beyond the sampling design stage.

Data appraisal

Done on an ad hoc basis for some countries, but not consistently across all surveys and domains.

Abstract

The DPHS in Dar es Salaam was conducted in two rounds in November-December 2017 and in September 2018, with the objective to assess the role of poverty and other social factors in urban flooding in the city. The survey data collected in 2017 focused on exposure to frequent flooding, while the follow up survey in 2018, targeting the same households, focused on the impact of a flood event that happened in April 2018. During the follow up survey in 2018, additional households were also added to the sample. The data collected is representative at the city level and overrepresented in areas that are flood prone.

This project was a collaborative effort between Global Facility for Disaster Reduction and Recovery (GFDRR), the Tanzanian Urban Resilience Program (TURP), the Poverty Global Practice and Urban, Disaster Risk Management, Resilience and Land Global Practice (GPURL). Data collection was carried out by UDA Consulting under World Bank supervision.

Geographic coverage

Dar es Salaam, Tanzania.

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The selection of households in the survey design had two objectives. First, to select a sample that represents the population of Dar es Salaam and second, to interview enough people who had experienced floods to be able to detect patterns in their socio-economic characteristics.

The sample size was selected to confidently represent the population of Dar es Salaam given the income level and income distribution. Accordingly, a sample size of 105 EAs and 10 households per EA were selected using Probability Proportion to Size (PPS). In 2018, 28 EAs to the original sample as part of an additional round of data collection.

To capture enough households that had experienced floods, a flood risk stratum was designed using the Ramani Huria community flood map. EAs were categorized according to three flood risk strata, i.e., “no risk”, “low to medium risk” and “high risk”, depending on how much of the EA was covered by the flood layer in the map. This categorization of the city was used to oversample in high risk and low-to-medium risk areas by selecting more of those EAs compared to the population living there. Finally, all the selected households were randomly drawn within each EA using satellite imagery.

Sampling weights were calculated to compensate for the oversampling in high-risk areas. When applying the sample weights, the dataset is representative at the city level.

References:

ERMAN, A. E., TARIVERDI, M., OBOLENSKY, M. A. B., CHEN, X., VINCENT, R. C., MALGIOGLIO, S., & YOSHIDA, N. (2019). Wading out the storm: The role of poverty in exposure, vulnerability and resilience to floods in Dar Es Salaam. World Bank Policy Research Working Paper, (8976).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey questionnaire consists of 13 sections that were used to collect the survey data. See the attached questionnaire.

Cleaning operations

The following data editing was done for anonymization purpose: • Precise location data, such as GPS coordinates, were dropped • Personal information, such as name, citizenship and phone number were dropped • Information on from which region or country the respondent moved from before settling in current dwelling and where respondent was born was categorized into “in Dar es Salaam” and “outside Dar es Salaam” to protect privacy while preserving valuable data. District level information on origin was dropped. • Household size exceeding seven household members was categorized as “above 7 members” • Household member information for 7th member and above was dropped to avoid reconstruction of the household size variable.

For more information on the anonymization process, see the Technical Document.

Response rate

In the 2018 follow up interview, 419 were reached and interviewed out of the 1058 households in the original sample.

Abstract

The Integrated Household Income and Expenditure Survey with Living Standards Measurement Survey 2002-2003 is one of the biggest national surveys carried out in accordance with an international methodology with technical and financial support from the World Bank and United Nations Development Programme.

Background This survey was developed in response to provide the picture of the current situation of poverty in Mongolia in relation to social and economic indicators and contribute toward implementation and progress on National Millennium Development Goals articulated in the National Millennium Development Report and monitoring of the Economic Growth Support and Poverty Reduction Strategy, as well as toward developing and designing future policies and actions. Also, the survey enriched the national database on poverty and contributed in improving the professional capacity of experts and professionals of the National Statistical Office of Mongolia.

Purpose Since the onset of the transition to a market economy of Mongolia our country the need to study changes in people's living standards in relation to household members' demographic situation, their education, health, employment and household engagement in private enterprises has become extremely important. With that purpose and with the support of the World Bank and the United Nations Development Programme, the National Statistical Office of Mongolia conducted the Integrated Household Income and Expenditure Survey with Living Standards Measurement Survey-like features between 2002 and 2003. In conjunction with LSMS household interviews the NSO also collected a price and a community questionnaire in each selected soum. The latter collected information on the quality of infrastructure, and basic education and health services.

Main importance of the survey is to provide policy makers and decision makers with realistic information about poverty and will become a resource for experts and researchers who are interested in studying poverty as well as social and economic issues of Mongolia.

In July 2003 the Government of Mongolia completed the Economic Growth and Poverty Reduction Strategy Paper in which the Government gave high priority to the fight against poverty. As part of that commitment this paper is a study that intends to monitor poverty and understand its main causes in order to provide policy-makers with useful information to improve pro-poor policies.

Content The Integrated HIES with LSMS design has the peculiarity of being a sub-sample of a larger survey, namely the Household Income and Expenditure Survey 2002. Instead of administering an independent consumption module, the Integrated HIES with LSMS 2002-2003 depends on the HIES 2002 information on household consumption expenditure. This is why the survey is referred as Integrated HIES with LSMS 2002-2003. This survey is the only source of information of income-poverty, and the questionnaire is designed to provide poverty estimates and a set of useful social indicators that can monitor more in general human development, as well as more specific issues on key sectors, such as health, education, and energy. And, the price and social survey, in conjunction with LSMS household interviews, collected information on the quality of infrastructure, and basic education and health services of each selected soum.

HIES - food expenditure and consumption, non-food expenditure, other expense, income LSMS - general information, household roster, housing, education, employment, health, fertility, migration, agriculture, livestock, non-farm enterprises, other souces of income, savings and loans, remittances, durable goods, energy PRICE SURVEY - prices of household consumer goods and services SOCIAL SURVEY - population and households, economy and infrastructure, education, health, agriculture and livestock, and non-agricultural business

Survey results The final report of this survey has main results on key poverty indicators, used internationally, as they relate to various social sectors. Its annexes contain information regarding the consumption structure, poverty lines along with the methodology used, as well as some statistical indicators.

The main contributions of this survey report are: - new poverty estimates based on the latest available household survey, the Integrated HIES with LSMS 2002-2003 - the implementation of appropriate, and internationally accepted, methodologies in the calculation of poverty and its analysis (these methodologies may constitute a reference for the analysis of future surveys) - a 'poverty profile' that describes the main characteristics of poverty

The first section of the report provides information on the Mongolian economic background, and presents the basic poverty measures that are linked to the economic performance to offer an indication of what happened to poverty and inequality in recent years. A second section goes in much more detail in generating and describing the poverty profile, in particular looking at the geographical distribution of poverty, poverty and its correlation with household demographic characteristics, characteristics of the household head, employment, and assets. A final section looks at poverty and social sectors and investigates various aspects of education, health and safety nets. The report contains also a number of useful, but more technical appendixes with information about the HIES-LSMS 2002-2003 (sample design and data quality), on the methodology used to construct the basic welfare indicator, and set the poverty line, some sensitivity analysis, and additional statistical information.

Geographic coverage

The survey is nationally representative and covers the whole of Mongolia.

Analysis unit

• Household (defined as a group of persons who usually live and eat together)
• Household member (defined as members of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)
• Selected soums (for collecting prices of household consumer goods and services and information on quality of infrastructure, basic education, health services and so on)

Universe

The survey covered selected households and all members of the households (usual residents). And the price and social surveys covered all selected soums.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Integrated HIES with LSMS 2002-2003 households are a subset of the household interviewed for the HIES 2002. One third of the HIES 2002 households were contacted again and interviewed on the LSMS topics. The subset was equally distributed among the four quarters.

The HIES 2002, and consequently the Integrated HIES with LSMS 2002-2003, used the 2000 Census as sample frame. 1,248 enumerations areas were part of the sample, which is a two-stage stratified random sample. The strata, or domains of estimation, are four: Ulaanbaatar, Aimag capitals and small towns, Soum centres, and Countryside. At a first stage a number of Primary Sampling Units (PSUs) were selected from each stratum. In the selected PSUs enumerators listed all the households residing in the area, and in a second stage households were randomly selected from the list of households identified in that PSU (10 households were selected in urban areas and 8 households in rural areas).

It should be noted that non-response case of households once selected for the survey exerts unfavorable influence on the representativeness of the survey. Therefore an enumerator should take every step to avoid that. To obtain true and timely survey results a proper agreement should be reached with a selected household before a survey starts. One of the main reasons of non-response is that an enumerator doesn't meet with the household members who are able to give the required information. An enumerator should visit a household at least 3 times within the given period to take the questionnaire.

Another common reason is that a household refuses to participate in the survey. In this case an enumerator should explain the purpose of the survey again, explain that the private data will be kept strictly confidential according to the corresponding law. If necessary an enumerator can ask local statistical division or local administration for the help. However this practice is very seldom.

If there is no possibility to take the questionnaires from the selected households due to weather conditions or disasters, reserved households with numbers 11, 12, 13 respectively from the list provided by the NSO should replace the omitted ones. However the reasons of replacements are to be declared in detail on the form.

Sampling deviation

At the planning stage the time lag between the HIES and LSMS interviews was expected to be relatively short. However, for various reasons it is on average of about 9 months, and for some households more than one year. Households interviewed in the first and second quarter of 2002 were generally re-interviewed in March and April 2003, while households of the third and fourth quarter of 2002 were re-interviewed in May, June and July of 2003. The considerable time lag between HIES and LSMS interviews was the main responsible for a considerable loss of households in the LSMS sample, households that could not be easily relocated and therefore re-interviewed. Due also to some incomplete questionnaires, the number of households that were used for the final poverty analysis is 3,308.

Mode of data collection

Face-to-face [f2f]

Research instrument

A