Abstract

Household Income and Expenditure Survey (HIES) collects a wealth of information on HH income and expenditure, such as source of income by industry, HH expenditure on goods and services, and income and expenditure associated with subsistence production and consumption. In addition to this, HIES collects information on sectoral and thematic areas, such as education, health, labour force, primary activities, transport, information and communication, transfers and remittances, food expenditure (as a proxy for HH food consumption and nutrition analysis), and gender.

The Pacific Islands regionally standardized HIES instruments and procedures were adopted by the Government of Tokelau for the 2015/16 Tokelau HIES. These standards were designed to feed high-quality data to HIES data end users for:

1. deriving expenditure weights and other useful data for the revision of the consumer price index;
2. supplementing the data available for use in compiling official estimates of various components in the System of National Accounts;
3. supplementing the data available for production of the balance of payments; and
4. gathering information on poverty lines and the incidence of poverty in Tokelau.

The data allow for the production of useful indicators and information on the sectors covered in the survey, including providing data to inform indicators under the UN Sustainable Development Goals (SDGs). This report, the above listed outputs, and any thematic analyses of HIES data, collectively provide information to assist with social and economic planning and policy formation.

Geographic coverage

National coverage.

Analysis unit

Households and Individuals.

Universe

The universe of the 2015/16 Tokelau Household Income and Expenditure Survey (HIES) is all occupied households (HHs) in Tokelau. HHs are the sampling unit, defined as a group of people (related or not) who pool their money, cook and eat together. It is not the physical structure (dwelling) in which people live. The HH must have been living in Tokelau for a period of six months, or have had the intention to live in Tokelau for a period of twelve months in order to be included in the survey.

Household members covered in the survey include: -usual residents currently living in the HH; -usual residents who are temporarily away (e.g., for work or a holiday); -usual residents who are away for an extended period, but are financially dependent on, or supporting, the HH (e.g., students living in school dormitories outside Tokelau, or a provider working overseas who hasn't formed or joined another HH in the host country) and plan to return; -persons who frequently come and go from the HH, but consider the HH being interviewed as their main place of stay; -any person who lives with the HH and is employed (paid or in-kind) as a domestic worker and who shares accommodation and eats with the host HH; and -visitors currently living with the HH for a period of six months or more.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2015/16 Tokelau Household Income and Expenditure Survey (HIES) sampling approach was designed to generate reliable results at the national level. That is, the survey was not designed to produce reliable results at any lower level, such as for the three individual atolls. The reason for this is partly budgetary constraint, but also because the HIES will serve its primary objectives with a sample size that will provide reliable national aggregates.

The sampling frame used for the random selection of HHs was from December 2013, i.e. the HH listing updated in the 2013 Population Count.

The 2015/16 Tokelau HIES had a quota of 120 HHs. The sample covered all three populated atolls in Tokelau (Fakaofo, Nukunonu and Atafu) and the sample was evenly allocated between the three atoll clusters (i.e., 40 HHs per atoll surveyed over a ten-month period). The HHs within each cluster were randomly selected using a single-stage selection process.

In addition to the 120 selected HHs, 60 HHs (20 per cluster) were randomly selected as replacement HHs to ensure that the desired sample was met. The replacement HHs were only approached for interview in the case that one of the primarily selected HHs could not be interviewed.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for this Household Income and Expenditure Survey (HIES) are composed of a diary and 4 modules published in English and in Tokelauan. All English questionnaires and modules are provided as external resources.

Here is the list of the questionnaires for this 2015-2016 HIES: - Diary: week 1 an 2; - Module 1: Demographic information (Household listing, Demographic profile, Activities, Educational status, Communication status...); - Module 2: Household expenditure (Housing characteristics, Housing tenure expenditure, Utilities and communication, Land and home...etc); - Module 3: Individual expenditure (Education, Health, Clothing, Communication, Luxury items, Alcohonl & tobacco); - Module 4: Household and individual income (Wages and salary, Agricultural and forestry activities, Fishing gathering and hunting activities, livestock and aquaculture activities...etc).

Cleaning operations

All inconsistencies and missing values were corrected using a variety of methods: 1. Manual correction: verified on actual questionnaires (double check on the form, questionnaire notes, local knowledge, manual verifications) 2. Subjective: the answer is obvious and be deducted from other questions 3. Donor hot deck: the value is imputed based on similar characteristics from other HHs or individuals (see example below) 4. Donor median: the missing or outliers were imputed from similar items reported median value 5. Record deletion: the record was filled by mistake and had to be removed.

Several questions used the hotdeck method of imputation to impute missing and outlying values. This method can use one to three dimensions and is dependent on which section and module the question was placed. The process works by placing correct values in a coded matrix. For example in Tokelau the “Drink Alcohol” questions used a three dimension hotdeck to store in-range reported data. The constraining dimensions used are AGE, SEX and RELATIONSHIP questions and act as a key for the hotdeck. On the first pass the valid yes/no responses are place into this 3-dimension hotdeck. On the second pass the data in the matrix is updated one person at a time. If a “Drink Alcohol” question contained a missing response then the person's coded age, sex and relationship key is searched in the “valid” matrix. Once a key is found the result contained in the matrix is imputed for the missing value. The first preferred method to correct missing or outlying data is the manual correction (trying to obtain the real value, it could have been miss-keyed or reported incorrectly). If the manual correction was unsuccessful at correcting the values, a subjective approach was used, the next method would be the hotdeck, then the donor median and the last correction is the record deletion. The survey procedure and enumeration team structure allow for in-round data entry, which gives the field staff the opportunity to correct the data by manual review and by using the entry system-generated error messages. This process was designed to improve data quality. The data entry system used system-controlled entry, interactive coding and validity and consistency checks. Despite the validity and consistency checks put in place, the data still required cleaning. The cleaning was a two-stage process, which included manual cleaning while referencing the questionnaire, whereas the second stage involved computer-assisted code verification and, in some cases, imputation. Once the data were clean, verified and consistent, they were recoded to form a final aggregated database, consisting of: Person level record - characteristics of every (household) HH member, including activity and education profile; HH level record - characteristics of the dwelling and access to services; Final aggregated income - all HH income streams, by category and type; Final aggregated expenditure - all HH expenditure items, by category and type.

The cleaning was a two-stage process, which included manual cleaning while referencing the questionnaire, whereas the second stage involved computer-assisted code verification and, in some cases, imputation. Once the data were clean, verified and consistent, they were recoded to form a final aggregated database.

Response rate

Overall, 99% of the response rate objective was achieved.

Sampling error estimates

Refer to Appendix 2 of the Tokelau 2015/2016 Household Income and Expenditure Survey report attached as an external resource.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 25% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

Surveys related to the family budget are considered one of the most important surveys types carried out by the Department Of Statistics, since it provides data on household expenditure and income and their relationship with different indicators. Therefore, most of the countries undertake periodic surveys on household income and expenditures. The Department Of Statistics, since established, conducted a series of Expenditure and Income Surveys during the years 1966, 1980, 1986/1987, 1992, 1997, 2002/2003, 2006/2007, 2008/2009, 2010/2011 and because of continuous changes in spending patterns, income levels and prices, as well as in the population internal and external migration, it was necessary to update data for household income and expenditure over time. Hence, the need to implement the Household Expenditure and Income Survey for the year 2013 arises.

The survey was then conducted to achieve the following objectives: 1. Provide data on income and expenditure to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. 2. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index. 3. Provide the necessary data for the national accounts related to overall consumption and income of the household sector. 4. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty. 5. Identify consumer spending patterns prevailing in the society, and the impact of demographic, social and economic variables on those patterns. 6. Calculate the average annual income of the household and the individual, and identify the relationship between income and different socio-economic factors, such as profession and educational level of the head of the household and other indicators. 7. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it.

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

The General Census of Population and Housing in 2004 provided a detailed framework for housing and households for different administrative levels in the Kingdom. Where the Kingdom is administratively divided into 12 governorates, each governorate is composed of a number of districts, each district (Liwa) includes one or more sub-district (Qada). In each sub-district, there are a number of communities (cities and villages). Each community was divided into a number of blocks. Where in each block, the number of houses ranged between 60 and 100 houses. Nomads, persons living in collective dwellings such as hotels, hospitals and prison were excluded from the survey framework.

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 25% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

The Household Expenditure and Income survey sample, for the year 2013, was designed to serve the basic objectives of the survey through providing a relatively large sample in each sub-district to enable drawing a poverty map in Jordan. A two stage stratified cluster sampling technique was used. In the first stage, a cluster sample proportional to the size was uniformly selected, where the number of households in each cluster was considered the weight of the cluster. At the second stage, a sample of 10 households was selected from each cluster, in addition to another 5 households selected as a backup for the basic sample, using a systematic sampling technique. Those 5 households were sampled to be used during the first visit to the block in case the visit to the original household selected is not possible for any reason. For the purposes of this survey, each sub-district was considered a separate stratum to ensure the possibility of producing results on the sub-district level. In this respect, the survey framework adopted that provided by the General Census of Population and Housing Census in dividing the sample strata. To estimate the sample size, the coefficient of variation and the design effect of the expenditure variable provided in the Household Expenditure and Income Survey for the year 2010 was calculated for each sub-district. These results were used to estimate the sample size on the sub-district level so that the coefficient of variation for the expenditure variable in each sub-district is less than 10%, at a minimum, of the number of clusters in the same sub-district (8 clusters). This is to ensure adequate presentation of clusters in different administrative areas to enable drawing an indicative poverty map. It should be noted that in addition to the standard non response rate assumed, higher rates were expected in areas where poor households are concentrated in major cities. Therefore, those were taken into consideration during the sampling design phase, and a higher number of households were selected from those areas, aiming at well covering all regions where poverty spreads.

Mode of data collection

Face-to-face [f2f]

Research instrument

To reach the survey objectives, 3 forms have been developed. Those forms were finalized after being tested and reviewed by specialists taking into account making the data entry, and validation, process on the computer as simple as possible.

(1) General Form/Questionnaire This form includes: - Housing characteristics such as geographic location variables, household area, building material predominant for external walls, type of tenure, monthly rent or lease, main source of water, lighting, heating and fuel cooking, sanitation type and water cycle, the number of rooms in the dwelling, in addition to providing ownership status of some home appliances and car. - Characteristics of household members: This form focused on the social characteristics of the family members such as relation to the head of the family, gender, age and educational status and marital status. It also included economic characteristics such as economic activity, and the main occupation, employment status, and the labor sector. To the additions of questions about individual continued to stay with the family, in order to update the information at the end of each of the four rounds of the survey. - Income section which included three parts · Family ownership of assets · Productive activities for the family · Current income sources

(2) Expenditure on food commodities form/Questionnaire This form indicates expenditure data on 17 consumption groups. Each group includes a number of food commodities, with the exception of the latter group, which was confined to some of the non-food goods and services because of their frequent spending pattern on daily basis like food commodities. For the purposes of the efficient use of results, expenditure data of the latter group was moved with the non-food commodities expenditure. The form also includes estimated amounts of own-produced food items and those received as gifts or in an in-kind form, as well as servants living with the family spending on themselves from their own wages to buy food.

(3) Expenditure on non-food commodities form/Questionnaire This form indicates expenditure data on 11 groups of non-food items, and 5 sets of spending on services, in addition to a group of consumption expenditure. It also includes an estimate of self-consumption, and non-food gifts or other items in an in-kind form received or sent by the household, as well as servants living with the family spending on themselves from their own wages to buy non-food items.

Cleaning operations

----> Raw Data

The data collection phase was then followed by the data processing stage accomplished through the following procedures: 1- Organizing forms/questionnaires A compatible archive system, with the nature of the subsequent operations, was used to classify the forms according to different round throughout the year. This is to effectively enable extracting the forms when required for processing. A registry was prepared to indicate different stages of the process of data checking, coding and entry till forms are back to the archive system. 2- Data office checking This phase is achieved concurrently with the data collection phase in the field, where questionnaires completed in the fieldwork are immediately sent to data office checking phase. 3- Data coding A team was trained to work on the data coding phase, which in this survey is only limited to education specialization, profession and economic activity. In this respect, international classifications were use, while for the rest of the questions, all coding were predefined

Abstract

The survey was conducted during December 2006, following an initial mini census listing exercise which was conducted about two months earlier in late September 2006. The objectives of the HIES were as follows: a) Provide information on income and expenditure distribution within the population; b) Provide income estimates of the household sector for the national accounts; c) Provide data for the re-base on the consumer price index; d) Provide data for the analysis of poverty and hardship.

Geographic coverage

National coverage: whole island was covered for the survey.

Analysis unit

• Household;
• Individual.

Universe

The survey covered all private households on the island of Nauru. When the survey was in the field, interviewers were further required to reduce the scope by removing those households which had not been residing in Nauru for the last 12 months and did not intend to stay in Nauru for the next 12 months. Persons living in special dwellings (Hospital, Prison, etc) were not included in the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size adopted for the survey was 500 households which allowed for expected sample loss, whilst still maintaining a suitable responding sample for the analysis.

Before the sample was selected, the population was stratified by constituency in order to assist with the logistical issues associated with the fieldwork. There were eight constituencies in total, along with "Location" which stretches across the districts of Denigamodu and Aiwo, forming nine strata in total. Although constituency level analysis was not a priority for the survey, sample sizes within each stratum were kept to a minimum of 40 households, to enable some basic forms of analysis at this level if required.

The sample selection procedure within each stratum was then to sort each household on the frame by household size (number of people), and then run a systematic skip through the list in order to achieve the desirable sample size.

Sampling deviation

No deviations from the sample design took place.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey schedules adopted for the Household Income and Expenditure Survey (HIES) included the following: · Expenditure questionnaire; · Income questionnaire; · Miscellaneous questionnaire; · Diary (x2).

Whilst a Household Control Form collecting basic demographics is also normally included with the survey, this wasn't required for this HIES as this activity took place for all households in the mini census.

Information collected in the four schedules covered the following: -Expenditure questionnaire: Covers basic details about the dwelling structure and its access to things like water and sanitation. It was also used as the vehicle to collect expenditure on major and infrequent expenditures incurred by the household. -Income questionnaire: Covers each of the main types of household income generated by the household such as wages and salaries, business income and income from subsistence activities. -Miscellaneous questionnaire: Covers topics relating to health access, labour force status and education. -Diary: Covers all day to day expenditures incurred by the household, consumption of items produced by the household such as fish and crops, and gifts both received and given by the household.

All questionnaires are provided as External Resources.

Cleaning operations

There were 3 phases to the editing process for the 2006 Household Income and Expenditure Survey (HIES) of Nauru which included: 1. Data Verification operations; 2. Data Editing operations; 3. Data Auditing operations.

The software used for data editting is CSPro 3.0. After each batch is completed the supervisor should check that all person details have been entered from the household listing form (HCF) and should review the income and expenditure questionnaires for each batch ensuring that all items have been entered correctly. Any omitted or incorrect items should be entered into the system. The supervisor is required to perform outlier checks (large or small values) on the batched diary data by calculating unit price (amount/quantity) and comparing prices for each item. This is to be conducted by loading the data into Excel files and sorting data by unit price for each item. Any changes to prices or quantities will be made on the batch file.

For more information on what each phase entailed go the document HIES Processing Instructions attached to this documentation.

Response rate

The survey response rates were a lot lower than expected, especially in some districts. The district of Aiwo, Uaboe and Denigomodu had the lowest response rates with 16.7%, 20.0% and 34.8% respectively. The area of Location was also extremely low with a responses rate of 32.2%. On a more positive note, the districts of Yaren, Ewa, Anabar, Ijuw and Anibare all had response rates at 80.0% or better.

The major contributing factor to the low response rates were households refusing to take part in the survey. The figures for responding above only include fully responding households, and given there were many partial responses, this also brought the values down. The other significant contributing factor to the low response rates was the interviewers not being able to make contact with the household during the survey period.

Unfortunately, not only do low response rates often increase the sampling error of the survey estimates, because the final sample is smaller, it will also introduce response bias into the final estimates. Response bias takes place when the households responding to the survey possess different characteristics to the households not responding, thus generating different results to what would have been achieved if all selected households responded. It is extremely difficult to measure the impact of the non-response bias, as little information is generally known about the non-responding households in the survey. For the Nauru 2006 HIES however, it was noted during the fieldwork that a higher proportion of the Chinese population residing in Nauru were more likely to not respond. Given it is expected their income and expenditure patterns would differ from the rest of the population, this would contribute to the magnitude of the bias.

Below is the list of all response rates by district: -Yaren: 80.5% -Boe: 70% -Aiwo: 16.7% -Buada: 62.5% -Denigomodu: 34.8% -Nibok: 68.4% -Uaboe: 20% -Baitsi: 47.8% -Ewa: 80% -Anetan: 76.5% -Anabar: 81.8% -Ijuw: 85.7% -Anibare: 80% -Meneng: 64.3% -Location: 32.2% -TOTAL: 54.4%

Sampling error estimates

To determine the impact of sampling error on the survey results, relative standard errors (RSEs) for key estimates were produced. When interpreting these results, one must remember that these figures don't include any of the non-sampling errors discussed in other sections of this documentation

To also provide a rough guide on how to interpret the RSEs provided in the main report, the following information can be used:

Category  Description
RSE < 5%  Estimate can be regarded as very reliable
5% < RSE < 10% Estimate can be regarded as good and usable
10% < RSE < 25% Estimate can be considered usable, with caution
RSE > 25%  Estimate should only be used with extreme caution

The actual RSEs for the key estimates can be found in Section 4.1 of the main report

As can be seen from these tables, the estimates for Total Income and Total Expenditure from the Household Income and Expenditure Survey (HIES) can be considered to be very good, from a sampling error perspective. The same can also be said for the Wage and Salary estimate in income and the Food estimate in expenditure, which make up a high proportion of each respective group.

Many of the other estimates should be used with caution, depending on the magnitude of their RSE. Some of these high RSEs are to be expected, due to the expected degree of variability for how households would report for these items. For example, with Business Income (RSE 56.8%), most households would report no business income as no household members undertook this activity, whereas other households would report large business incomes as it's their main source of income.

Data appraisal

Other than the non-response issues discussed in this documentation, other quality issues were identified which included: 1) Reporting errors Some of the different aspects contributing to the reporting errors generated from the survey, with some examples/explanations for each, include the following:

a) Misinterpretation of survey questions: A common mistake which takes place when conducting a survey is that the person responding to the questionnaire may interpret a question differently to the interviewer, who in turn may have interpreted the question differently to the people who designed the questionnaire. Some examples of this for a Household Income and Expenditure Survey (HIES) can include people providing answers in dollars and cents, instead of just dollars, or the reference/recall period for an “income” or “expenditure” is misunderstood. These errors can often see reported amounts out by a factor of 10 or even 100, which can have major impacts on final results.

b) Recall problems for the questionnaire information: The majority of questions in both of the income and expenditure questionnaires require the respondent to recall what took place over a 12 month period. As would be expected, people will often forget what took place up to 12 months ago so some

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

The main purpose of a HIES survey was to present high quality and representative national household data on income and expenditure in order to update Consumer Price Index (CPI), improve statistics on National Accounts and measure poverty within the country. These statistics are a requirement for evidence based policy-making in reducing poverty within the country and monitor progress in the national strategic plan "Te Kakeega 3".

The 2015-16 Household Income and Expenditure Survey (HIES) is the third HIES that was conducted by the Central Statistics Division since Tuvalu gained political independence in 1978. With great assitance from the Pacific Community (SPC) experts, the HIES was conducted over a period of 12 months in urban (Funafuti) and rural (4 outer islands) areas. From a total of 1,872 households on Tuvalu, an amount of 38 percent sample of all households in Tuvalu was selected to provide valid response.

Geographic coverage

National Coverage.

Analysis unit

Household and Individual.

Universe

The scope of the 2015/2016 Household Income and Expenditure Survey (HIES) was all occupied households in Tuvalu. Households are the sampling unit, defined as a group of people (related or not) who pool their money, and cook and eat together. It is not the physical structure (dwelling) in which people live. HIES covered all persons who were considered to be usual residents of private dwellings (must have been living in Tuvalu for a period of 12-months, or have intention to live in Tuvalu for a period of 12-months in order to be included in the survey). Usual residents who are temporary away are included as well (e.g., for work or a holiday).

Kind of data

Sample survey data [ssd]

Sampling procedure

Out of the total 1,872 households (HHs) listed in 2015, a sample 706 households which is 38 percent of the the total households were succesfully interviewed for a response rate of 98%.

SAMPLING FRAME: The 2010 (Household Income and Expenditure Survey (HIES) sample was spread over 12 months rounds - one each quarter - and the specifications of the final responding households are summarised below: Tuvalu urban: Selected households: 259 = 217 responded; Tuvalu rural: Selected households: 346 = 324 responded.

In 2010, 605 HHs were selected and 541 sufficiently responded. The 2010 HIES provided solid estimates for expenditure aggregates at the national level (sampling error for national expenditure estimate is 3.1%).

Similarly to the 2010 HIES, private occupied dwellings were the statistical unit for the 2015/2016 HIES. Institutions and vacant dwellings were removed from the sampling frame. Some areas in Tuvalu are very difficult to reach due to the cost of transportation and the remoteness of some islands, which is why they are excluded from the sample selection. The following table presents the distribution of the HHs according to their location (main island or outer islands in each domain) based on the 2012 Population and Housing Census: -Urban - Funafuti: 845 (48%); -Rural - Nanumea: 115 (7%); -Rural - Nanumaga: 116 (7%); -Rural - Niutao: 123 (7%); -Rural - Nui: 138 (8%); -Rural - Vaitupu: 226 (13%); -Rural - Nukufetau: 124 (%); -Rural - Nukulaelae: 67 (%); -Rural - Niulakita: 7 (%); -TOTAL: 1761 (100%).

The 2012 Population and Household Census (PHC) wsa used to select the island to interview, and then in each selected island the HH listing was updated for selection. For budget and logistics reasons the islands of Nui, Nukufetau, Nukulaelae and Niukalita were excluded from the sample selection. In total 19% of the HHs were excluded from the selection but this decision should not affect the HIES outputs as those 19% show similar profile as other HHs who live in the outer islands. This exclusion will be take into consideration in the sampling weight computation in order to cover 100% of the outer island HHs.

SAMPLE SELECTION AND SAMPLE SIZE: A simple random selection was used in each of the selected island (HHs were selected directly from the sampling frame). Based on the findings from the 2010 Tuvalu HIES, the sample in Funafuti has been increased and the one in rural remains stable. Within each rural selected atolls, the allocation of the sample size is proportional to its size (baed on the 2012 population census). The table below shows the number of HHs to survey: Urban - Funafuti: 384; Rural - Vaitupu: 126; Rural - Nanumea: 63; Rural - Niutao: 84; Rural - Nanumaga: 63; TUVALU: 720.

The expected sample size has been increased by one third (361 HHs) with the aim of pre-empting the non contacted HHs (refusals, absence….). The 2015/2016 HIES adopted the standardized HIES methodology and survey instruments for the Pacific Islands region. This approach, developed by the Pacific Community (SPC), has resulted in proven survey forms being used for data collection. It involves collection of data over a 12-month period to account for seasonal changes in income and expenditure patterns, and to keep the field team to a smaller and more qualified group. Their implementation had the objective of producing consistent and high quality data.

Sampling deviation

For budget and logistics reasons the islands of Nui, Nukufetau, Nukulaelae and Niukalita were excluded from the sample selection. In total 19% of the HHs were excluded from the selection but this decision should not affect the HIES outputs as those 19% show similar profile as other HHs who live in the outer islands. This exclusion will be take into consideration in the sampling weight computation in order to cover 100% of the outer island HHs.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey contain 4 modules and 2 Diaries (1 diary for each of the two weeks that a household was enumerated). The purpose of a Diary is to record all the daily expenses and incomes of a Household as shown by its topics below; - DIARY
The Diary module contains questions such as "What did your Household buy Today (Food and Non-Food Items)?", "Payments for Services made Today", "Food, Non-Food and Services Received for Free", "Home-Produced Items Today", "Overflow Sheet for Items Bought This Week", "Overflow Sheet for Services Paid for This Week", "Overflow Sheet for Items Received for Free this Week", and an "Overflow Sheet for Home-Produced Items This Week".

The 4 modules are detailed below; - MODULE 1 - DEMOGRAPHIC INFORMATION The module contains individual demograhic questions on their Demographic Profiles, Labour Force status (Activities), Education status, Health status, Communication status and questions on "Household members that have left the household". - MODULE 2 - HOUSEHOLD EXPENDITURE The module contains household expenditure questions the housing characteristics, Housing tenure expenditures, Utilities and Communication, Land, Household goods and assets, Vehicles and accessories, Private Travel details, Household services expenditures, Cash contributions, Provisions of Financial support, Household asset insurance and taxes and questions on Personal insurance. - MODULE 3 - INDIVIDUAL EXPENDITURE This module contains individual expenditure questions on Education, Health, Clothing, Communication, Luxury Items, Alcohol, Kava and Tobacco, and Deprivation questions. - MODULE 4 - HOUSEHOLD & INDIVIDUAL INCOME
This module contains household and individual questions on their income, on topics such as Wages and Salary, Agricultural and Forestry Activities, Fishing, Gathering and Hunting Activities, Livestock and Aquaculture Activities, Handicraft/Home-processed Food Activities, Income from Non-subsistence Business, Property income, transfer income & other Receipts, and Remmitances and other Cash gifts.

Depending on the information being collected, a recall period (ranging from the last 7 days to the last 12 months) is applied to various sections of the questionnaire. The forms were completed by face-to-face interview, usually with the HH head providing most of the information, with other household (HH) members being interviewed when necessary. The interviews took place over a 2-week period such that the HH diary, which is completed by the HH on a daily basis for 2 weeks, can be monitored while the module interviews take place. The HH diary collects information on the HH's daily expenditure on goods and services; and the harvest, capture, collection or slaughter of primary produce (fruit, vegetables and animals) by intended purpose (home consumption, sale or to give away). The income and expenditure data from the modules and the diary are concatenated (ensuring that double counting does not occur), annualised, and extrapolated to form the income and expenditure aggregates presented herein.

Cleaning operations

The survey procedure and enumeration team structure allowed for in-round data entry, which gives the field staff the opportunity to correct the data by manual review and by using the entry system-generated error messages. This process was designed to improve data quality. The data entry system used system-controlled entry, interactive coding and validity and consistency checks. Despite the validity and consistency checks put in place, the data still required cleaning. The cleaning was a 2-stage process, which included manual cleaning while referencing the questionnaire, whereas the second stage involved computer-assisted code verification and, in some cases, imputation. Once the data were clean, verified and consistent, they were recoded to form a final aggregated database, consisting of: 1. Person level record - characteristics of every HH member, including activity

Abstract

The main objective of the 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.

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

• Households
• 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. These 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

• Electronic Processing: This stage began by defining the electronic processing team, which consisted of a system analyst, programmers and data entry staff. Work of the system analyst and programmers began in parallel with the work of the survey staff; starting by designing the questionnaire in a form that facilitates and ensures accuracy of data entry, preparing the required programs, then testing them by using hypothetical data and finalizing them before data entry. A liaision officer was appointed to provide the entry division with office-processed questionnaires which were returned in the form of batches to the archive upon completing data entry process. As for data entry, the data analyst of the survey trained a group of data entry staff on already prepared programs and systems. A set of data entry editing rules for all fields of the questionnaires were compiled. It included checking the permitted range of the value and quantity of each entered field and ensuring consistency between value and quantity of the field, and the related values and quantities of fields related to it in other questionnaires. The consistency rules were applied directly during the entry on various questionnaire items. That is, to ensure that entered data were consistent with each other and logical on the one hand, and conformed to given instructions related to the questionnaires’ data on the other hand. After completing the data entry process, special lists of data were printed. They were edited to reassure the correct entry and rectification of errors (if any).

• Tabulation and Dissemination of Results: Upon finalization of all office and electronic processing operations, the actual survey results were tabulated using the ORACLE package. The results were checked by extracting similar reports using the SPSS package to ensure that the results are correct and free of errors. This required checking the formality and phrasing of the used titles and concepts, in addition to editing of all data in each table according to its details and consistency within the same table and with other tables. The final report was then prepared, containing detailed tabulations, as well as, the methodology of the survey.

Abstract

Survey based Harmonized Indicators (SHIP) files are harmonized data files from household surveys that are conducted by countries in Africa. To ensure the quality and transparency of the data, it is critical to document the procedures of compiling consumption aggregation and other indicators so that the results can be duplicated with ease. This process enables consistency and continuity that make temporal and cross-country comparisons consistent and more reliable.

Four harmonized data files are prepared for each survey to generate a set of harmonized variables that have the same variable names. Invariably, in each survey, questions are asked in a slightly different way, which poses challenges on consistent definition of harmonized variables. The harmonized household survey data present the best available variables with harmonized definitions, but not identical variables. The four harmonized data files are

a) Individual level file (Labor force indicators in a separate file): This file has information on basic characteristics of individuals such as age and sex, literacy, education, health, anthropometry and child survival. b) Labor force file: This file has information on labor force including employment/unemployment, earnings, sectors of employment, etc. c) Household level file: This file has information on household expenditure, household head characteristics (age and sex, level of education, employment), housing amenities, assets, and access to infrastructure and services. d) Household Expenditure file: This file has consumption/expenditure aggregates by consumption groups according to Purpose (COICOP) of Household Consumption of the UN.

Geographic coverage

National

Analysis unit

• Individual level for datasets with suffix _I and _L
• Household level for datasets with suffix _H and _E

Universe

The survey covered all de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The 1999/2000 Household Income, Consurnption, and Expendi.ture Survey covered both the urban and the sedentary rural parts of the country. The survey has not covered six zones in Somalia Region and two zones in Afar Region that are inhabited mainly by nomadic population. For the purpose of the survey, the country was divided into three categories . That is, the rural parts of the country and the urban areas that were divided into two broad categories taking into account sizes of their population. Category I: Rural parts of nine Regional States and two administrative regions were grouped in this category each of which were the survey dornains (reporting levels). These regions are Tigrai,Afar, Amhara, Oromia, Sornalia, Eenishangul-Gunuz, SNNP,Gambela, Flarari, Addis Ababa and Dire Dawa.

Category II: All Regional capitals and five major urban centers of the country were grouped in this category. Each of the urban centers in this category was the survey domain (reporting level) for which separate survey results for rnajor survey characteristics were reported.

Category III: Urban centers in the country other than the urban centers in category II were grouped in this category and formed a single reporting level. Other than the reporting levels defined in category II and category III one additional domain, namely total urban (country level) can be constructed by eombining the basic domains defined in the two categories. All in all 35'basie rural and urban domains (reporting levels) were defined for the survey. In addition to the above urban and rural domains, survey results are to be reported at regional and eountry levels by aggregating the survey results for the conesponding urban and rural areas. Definition of the survey dornains was based on both technical and resource considerations. More specifically, sample size for the domains were determined to enable provision of major indicators with reasonable precision subject to the resources that were available for the survey.

Selection Scheme and Sample Size in Each Category CategoryI : A stratified two-stage sample design was used to select the sample in which the primary sampling units (PSUs) were EAs. Sample enumeration areas( EAs) from each domain were selected using systematic sampling that is probability proportional to the size being number of households obtained from the 1994 population and housing census.A total of 722 EAs were selected from the rural parts of the country. Within each sample EA a fresh list of households was prepared at the beginning of the survey's field work and for the administration of the survey questionnaire 12 households per sample EA for rural areas were systematically selected.

Category II: In this category also,a stratified two-stage sample design was used to select the sample. Here a strata constitutes all the "Regional State Capitals" and the five "Major Urban Centers" in the country and are grouped as a strata in this category. The primary sampling units (PSUs) are the EA's in the Regional State Capitals and the five Major Urban Centers and excludes the special EAs (non-conventional households). Sample enumeration areas( EAs) from each strata were selected using systematic sampling probability proportional to size, size being number of households obtained from the 1994 population and housing census. A total of 373 EAs were selected from this domain of study. Within each sample EAs a fresh list of households was prepared at the beginning of the survey's field work and for the administration of the questionnaire 16 household per sample EA were systematically selected-

Category III: Three-stage stratified sample design was adopted to select the sample from domains in category III. The PSUs were other urban centers selected using systematic sampling that is probability proportional to size; size being number of households obtained from the 1994 population and housing census. The secondary sampling units (SSUs) were EAs which were selected using systematic sampling that is probability proportional to size; size being number of households obtained from the 1994 population and housing census. A total of 169 sample EAs were selected from the sample of other urban centers and was determined by proportional allocation to their size of households from the 1994 census. Ultimately, 16 households within each of the sample EAs were selected systematically from a fresh list of households prepared at the beginning of the survey's fieldwork for the administration of the survey questionnaire.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Household Income, Consumption and Expenditure Survey questionnaire contains the following forms: - Form 1: Area Identification and Household Characteristics - Form 2A: Quantity and value of weekly consumption of food and drinks consumed at home and tobacco/including quantity purchased, own produced, obtained, etc for first and second week. - Form 2B: Quantity and value of weekly consumption of food and drinks consumed at home and tobacco/including quantity purchased, own produced, obtained, etc for third and fourth week . - Form 3A: All transaction (income, expenditure and consumption) for the first and second weeks except what is collected in Forms 2A and 2B - Form 3B: All transaction (income, expenditure and consumption) for the third and fourth weeks except what is collected in Forms 2A and 2B - Form 4: All transaction (expenditure and consumption) for last 6 months for Household expenditure on some selected item groups - Form 5: Cash income and receipts received by household and type of tenure. The survey questionnaire is provided as external resource.

Abstract

Survey based Harmonized Indicators (SHIP) files are harmonized data files from household surveys that are conducted by countries in Africa. To ensure the quality and transparency of the data, it is critical to document the procedures of compiling consumption aggregation and other indicators so that the results can be duplicated with ease. This process enables consistency and continuity that make temporal and cross-country comparisons consistent and more reliable.

Four harmonized data files are prepared for each survey to generate a set of harmonized variables that have the same variable names. Invariably, in each survey, questions are asked in a slightly different way, which poses challenges on consistent definition of harmonized variables. The harmonized household survey data present the best available variables with harmonized definitions, but not identical variables. The four harmonized data files are

a) Individual level file (Labor force indicators in a separate file): This file has information on basic characteristics of individuals such as age and sex, literacy, education, health, anthropometry and child survival. b) Labor force file: This file has information on labor force including employment/unemployment, earnings, sectors of employment, etc. c) Household level file: This file has information on household expenditure, household head characteristics (age and sex, level of education, employment), housing amenities, assets, and access to infrastructure and services. d) Household Expenditure file: This file has consumption/expenditure aggregates by consumption groups according to Purpose (COICOP) of Household Consumption of the UN.

Geographic coverage

National

Analysis unit

• Individual level for datasets with suffix _I and _L
• Household level for datasets with suffix _H and _E

Universe

The survey covered all de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The list of households obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration (EASE) was used as a frame to select EAs from the rural part of the country. On the other hand, the list consisting of households by EA, which was obtained from the 2004 Ethiopian Urban Economic Establishment Census, (EUEEC), was used as a frame in order to select sample enumeration areas for the urban HICE survey. A fresh list of households from each urban and rural EA was prepared at the beginning of the survey period. This list was, thus, used as a frame in order to select households from sample EAs.

Sample Design For the purpose of the survey the country was divided into three broad categories. That is; rural, major urban center and other urban center categories.

Category I: Rural: - This category consists of the rural areas of eight regional states and two administrative councils (Addis Ababa and Dire Dawa) of the country, except Gambella region. Each region was considered to be a domain (Reporting Level) for which major findings of the survey are reported. This category comprises 10 reporting levels. A stratified two-stage cluster sample design was used to select samples in which the primary sampling units (PSUs) were EAs. Twelve households per sample EA were selected as a Second Stage Sampling Unit (SSU) to which the survey questionnaire were administered.

Category II:- Major urban centers:- In this category all regional capitals (except Gambella region) and four additional urban centers having higher population sizes as compared to other urban centers were included. Each urban center in this category was considered as a reporting level. However, each sub-city of Addis Ababa was considered to be a domain (reporting levels). Since there is a high variation in the standards of living of the residents of these urban centers (that may have a significant impact on the final results of the survey), each urban center was further stratified into the following three sub-strata. Sub-stratum 1:- Households having a relatively high standards of living Sub-stratum 2:- Households having a relatively medium standards of living and Sub-stratum 3:- Households having a relatively low standards of living. The category has a total of 14 reporting levels. A stratified two-stage cluster sample design was also adopted in this instance. The primary sampling units were EAs of each urban center. Allocation of sample EAs of a reporting level among the above mentioned strata were accomplished in proportion to the number of EAs each stratum consists of. Sixteen households from each sample EA were inally selected as a Secondary Sampling Unit (SSU).

Category III: - Other urban centers: - Urban centers in the country other than those under category II were grouped into this category. Excluding Gambella region a domain of "other urban centers" is formed for each region. Consequently, 7 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category II. Hence, no domain was formed for these regions under this category. Unlike the above two categories a stratified three-stage cluster sample design was adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. Sixteen households from each EA were lastly selected at the third stage and the survey questionnaires administered for all of them.

Mode of data collection

Face-to-face [f2f]

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

The main purpose of the Household Income Expenditure Survey (HIES) 2016 was to offer high quality and nationwide representative household data that provided information on incomes and expenditure in order to update the Consumer Price Index (CPI), improve National Accounts statistics, provide agricultural data and measure poverty as well as other socio-economic indicators. These statistics were urgently required for evidence-based policy making and monitoring of implementation results supported by the Poverty Reduction Strategy (I & II), the AfT and the Liberia National Vision 2030. The survey was implemented by the Liberia Institute of Statistics and Geo-Information Services (LISGIS) over a 12-month period, starting from January 2016 and was completed in January 2017. LISGIS completed a total of 8,350 interviews, thus providing sufficient observations to make the data statistically significant at the county level. The data captured the effects of seasonality, making it the first of its kind in Liberia. Support for the survey was offered by the Government of Liberia, the World Bank, the European Union, the Swedish International Development Corporation Agency, the United States Agency for International Development and the African Development Bank. The objectives of the 2016 HIES were:

1. Update the Consumer Price Index (CPI): To obtain a new set of weights for the basket of goods and services that upgrade the Monrovia Consumer Price Index (MCPI) and the National Consumer Price Index (NCPI) and to revise the CPI basket of goods and services in Liberia to reflect the current consumption pattern of residence.
2. Improve National Accounts Statistics: To get information on annual household expenditure patterns in order to update the household component of the National Accounts.
3. Measure Poverty: To prepare robust poverty indices that enable the understanding of poverty dynamics across the country and of the factors influencing them.
4. Improve Agricultural Statistics: To obtain nationally representative and policy relevant agricultural statistics in order to undertake in-depth analysis of agricultural households.
5. Capture Socio-economic Impact of Ebola Virus Disease (EVD): To obtain a post-EVD dataset which allows for an in-depth analysis of the socioeconomic impact of EVD on households.
6. Benchmark Agenda for Transformation Indicators: To provide an update on selected socioeconomic indicators used to benchmark the government’s policies embedded within the Agenda for Transformation.
7. Develop Statistical Capacity: Emphasize capacity building and development of sustainable statistical systems through every stage of the project to produce accurate and timely information about Liberia.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The original sample design for the HIES exploited two-phased clustered sampling methods, encompassing a nationally representative sample of households in every quarter and was obtained using the 2008 National Housing and Population Census sampling frame. The procedures used for each sampling stage are as follows:
i. First stage
Selection of sample EAs. The sample EAs for the 2016 HIES were selected within each stratum systematically with Probability Proportional to Size from the ordered list of EAs in the sampling frame. They are selected separately for each county by urban/rural stratum. The measure of size for each EA was based on the number of households from the sampling frame of EAs based on the 2008 Liberia Census. Within each stratum the EAs were ordered geographically by district, clan and EA codes. This provided implicit geographic stratification of the sampling frame.

ii. Second stage
Selection of sample households within a sample EA. A random systematic sample of 10 households were selected from the listing for each sample EA. Using this type of table, the supervisor only has to look up the total number of households listed, and a specific systematic sample of households is identified in the corresponding row of the table.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were three questionnaires administered for this survey: 1. Household and Individual Questionnaire 2. Market Price Questionnaire 3. Agricultural Recall Questionnaire

Cleaning operations

The data entry clerk for each team, using data entry software called CSPro, entered data for each household in the field. For each household, an error report was generated on-site, which identified key problems with the data collected (outliers, incorrect entries, inconsistencies with skip patterns, basic filters for age and gender specific questions etc.). The Supervisor along with the Data Entry Clerk and the Enumerator that collected the data reviewed these errors. Callbacks were made to households if necessary to verify information and rectify the errors while in that EA.

Once the data were collected in each EA, they were sent to LISGIS headquarters for further processing along with EA reports for each area visited. The HIES Technical committee converted the data into STATA and ran several consistency checks to manage overall data quality and prepared reports to identify key problems with the data set and called the field teams to update them about the same. Monthly reports were prepared by summarizing observations from data received from the field alongside statistics on data collection status to share with the field teams and LISGIS Management.

Abstract

The Household Income and Expenditure Survey 2000/01 (HIES) was carried out by the Tonga Statistics Department over a 12-month period, from October 2000 to September 2001. The survey collected detailed information on income and expenditure from more than 1,600 households. All adult members age 15 years and over of these households kept a detailed diary of daily expenditure over a two-week period.

The survey had three main objectives: • To provide updated information for the expenditure item weights for the CPI; • To provide some data for the components of National Accounts; and • To provide information on the nature and distribution of household income and expenditure for planners, policy makers, and the general public.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

In designing the sample for the survey, an initial simple allocation was made of 10 percent of all households in Tonga. This resulted in an initial sample of 1640 households, made up 1093 households for Tongatapu, 276 for Vava'u, 149 for Ha'apai, 83 for 'Eua, and 39 for the Niuas. To allow for seasonal effects, the survey was carried out over four rounds, covering a 12-month period. This meant that the sample size for each round was 410 households.

There were various stages to the selection process. Within each island division, the required sample was allocated to districts in proportion to their sizes. A sample of census blocks was then selected systematically within each district, using a sampling interval of 1 in 9. Within selected census blocks, the required size of sample was selected systematically from the list of all households.

Due to financial limitations, some of the small islands were not included in the survey at all, or only included in certain rounds. For example, the two main islands of the Niuas were only to be included in one round each. In the Ha'apai group, two of the islands (Foa and Ha'afeva) were only to be covered in two rounds, while three others (Ha'ano, 'Uiha and Nomuka) were only to be considered for one round.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two questionnaires (HIES-1 and HIES-2) were used to collect the data required for this survey:

HIES-1: Household income survey. This contained a cover sheet and three sections: - Section A: Household composition and characteristics. This section collected information on the general demographic characteristics of members of the household selected for the survey, including relationship to head of household, sex, age, marital status, number of days worked last week, main activity, employment status, educational attainment, occupation and industry.

• Section B: Value of output and payments for goods and services for the last 12 months. This section collected information on goods produced for sale in the local market or for export, and goods produced for home consumption. Information was collected separately for the following items: agricultural products; livestock; poultry and poultry products; fish and fish products; handicrafts; and rent for property.

• Section C: Sources of household income and receipts for the last 12 months This questionnaire collected information on the source and amount of income received by income earners, separately for cash and non-cash income.

HIES-2: Household expenditure survey. This booklet contained instructions for completing the diary, a listing of items that people might have bought, and four sections: - Section A: Daily expenditure during two weeks starting Saturday. There was a separate page for each day, and respondents were asked to give a description of each item obtained and the quantity. Alongside were three separate columns for recording the value of items that were paid for in cash, bought on credit, or where no cash was paid.

• Section B: Repairs on house during these two weeks. The value of all house repairs carried out over the two-week period was to be recorded here, unless it had already been recorded elsewhere in the diary. Again, there were three columns for cash, credit, and no cash paid.

• Section C: Rent for house If not already recorded elsewhere, this section was for recording the rent paid for the house, and the frequency of payment. In cases where a person lived in their own house, the person was asked to estimate the likely rental value if they had to rent the property.

• Section D: Other big payments during the last 12 months Any large payments (T$50 or more) made during the previous 12 months were to be recorded here. Examples were given of the types of payment to be recorded, and the layout was similar to that in Section A above.

Sampling error estimates

Sampling errors refer to those errors that are implicit in any sample survey, where only a portion of the population is covered. Non-sampling errors refer to all other types of error. These can arise at any stage of the survey process. Examples of activities that are likely to increase the level of non-sampling error are: failing to select a proper sample, poor questionnaire design, weak field supervision, inaccurate data entry, insufficient data editing, or failure to analyze or report on the data correctly. If a census of all the households in Tonga were carried out, there would be no sampling error (but probably increased non-sampling error).

Note: Detailed sampling error descriptions and standard error tables are available in the 2000-2001 HIES final report.

Abstract

A Household Income and Expenditure Survey (HIES) collects a wealth of information on household expenditure, income, own-account production and consumption. HIES also collects information on sectoral and thematic areas such as gender, education, health, labour, primary activities, transport, information and communication and cash transfers and remittances. The HIES data will be used to: · derive expenditure weights for the revision of the Consumer Price Index (CPI); · supplement the data available for use in compiling official estimates of various components in the System of National Accounts; and · gather information on welfare and food security in Palau. The data will inform indicators under the United Nations Sustainable Development Goals (SDGs) and guide social and economic policy.

Geographic coverage

National coverage.

Analysis unit

Households and individuals.

Universe

Household Income and Expenditure Survey (HIES) covered all persons who were considered to be usual residents of private dwellings as well as those living in barracks.

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2023/24 Palau Household Income and Expenditure Survey (HIES) questionnaire was developed in English language and it follows the Pacific Standard HIES questionnaire structure. It is administered on CAPI using Survey Solutions, and the diary is no longer part of the form. All transactions (food, non food, home production and gifts) are collected through different recall sections during the same visit. The traditional 14 days diary is no longer recommended in the region. This new method of implementing the HIES present some interesting and valuable advantages such as: cost saving, data quality, time reduction for data processing and reporting.

Below is a list of all modules in this questionnaire: -Household ID -Demographic characteristics -Education -Health -Functional difficulties -Communication -Alcohol -Other individual expenses -Labour force -Dwelling characteristics -Assets -Home maintenance -Vehicles -International trips -Domestic trips -Household services -Financial support -Other household expenditure -Ceremonies -Remittances -Food insecurity -Livestock -Agriculture -Fisheries -Hunting -Handicraft and home-processed food -Horticulture -Legal services

The survey questionnaire can be found in this documentation.

Cleaning operations

Data was edited and cleaned using the software Stata. Data cleaning was made manually and in close collaboration with the Statistics Office of Palau.

Response rate

Private households urban: 77,5% Private households rural: 81,2% Workers barracks urban: 76,1% Worker barracks rural: 80,8% Grand Total: 78,2%

Abstract

The purpose of this survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in the Republic of Palau. This information will be used to guide policy makers in framing socio-economic developmental policies and in initiating financial measures for improving economic conditions of the people.

Some more specific outputs from the survey are listed below: a) To obtain expenditure weights and other useful data for the revision of consumer price indices. b) To supplement the data available for use in compiling official estimates of household accounts in the systems of national accounts. c) To supply basic data needed for policy making in connection with social and economic planning d) To provide data for assessing the impact on household living conditions of existing or proposed economic and social measures, particularly changes in the structure of household expenditures and in household consumption e) To gather information on poverty lines and incidence of poverty throughout Palau.

Geographic coverage

• National

• Six geographical areas:

  Koror West Babeldaob Airai Peleliu East Babeldaob Kayangel/Angaur

Analysis unit

• Population and Household
• Region

Universe

All private households.

Households that had not been residing in Palau for the last 12 months and did not intend to stay in Palau for the next 12 months at the time of the survey, were still selected in the survey, but treated as out-of-scope.

Kind of data

Sample survey data [ssd]

Sampling procedure

A sample of 20 per cent was considered more than sufficient for Palau. An additional 10 per cent of sample was selected to allow for sample loss. As a result, a sample size of 1,041 households (20 per cent of 4,684, with a 10 per cent top-up) was considered suitable for the survey.

Six target areas were identified as sub-populations for which estimates would be desirable. These six areas, which also can be considered stratum were:

1) Koror 2) Airai 3) East Babeldaob 4) West Babeldaob 5) Peleliu 6) Kayangel/Angaur

To accommodate this requirement, the sample of 1,041 households needed to be distributed amongst each of these six strata in such a manner that the level of accuracy derived from each stratum would be roughly equal. The manner in which this is achieved is to over-sample (proportion wise) from the smaller strata to ensure they still have sufficient sample.

To make workloads even and manageable in the field for interviewers and supervisors, the final sample size was adjusted such that it was divisible by 15 within each stratum. The number 15 was chosen as it was considered a suitable number of dwellings for an interviewer to enumerate over a three week period.

Another modification to the sample was with Kayangel/ Angaur. Given the required sample for this area was derived to be 60 dwellings, and there are only 73 dwellings in these areas, it was decided to completely enumerate this stratum.

Although it would be desirable to cover all of Palau for this survey, due to cost and time constraints a couple of areas were excluded from the frame before the selections were made. The two areas removed from scope were:

1) Sonsorol 2) Tobi

The impact on final estimates is considered to be very small given the small populations on these two islands; 18 households on Sonsorol, and 10 households on Tobi. This accounts for less than 0.5 per cent of the population of Palau.

The sample of dwellings was selected independently within each stratum. A complete list of all dwellings identified during the recent census was used as a frame. The first task was to sort the dwellings within each stratum by two variables:

1) Hamlet (on Koror) and State (rest of Palau) 2) Household Size (number of persons)

Once the list had been sorted, systematic sampling was used to produce the sample of dwellings. A skip was produced by dividing the population size for each stratum by the required sample size (N/n). Having produced the skip, a random start was then generated between 0 and the skip to determine the starting point for the systematic sample.

For details please refer to the attached document entitled Documentation for Sample Selection.

Mode of data collection

Face-to-face [f2f] and Other [oth]

Research instrument

The survey schedules adopted for the HIES included the following: • Household Control Form • Expenditure Questionnaire • Income Questionnaire • Diary (x2)

Information collected in the four schedules covered the following:

Household Control Form: This form includes the following information: 1. Name 2. Sex 3. Date of Birth 4. Ethnicity 5. Marital Status 6. Educational Attainment 7. Activity Status 8. Literacy Status 9. Internet Usage

Income questionnaire: This questionnaire has 8 sections and includes the following information: 1. Working for Wage and / or Salary 2. Agriculture, livestock, fishing and other sales 3. Other Self Employed & Business Operations 4. Previous Jobs held in the last 12 months 5. Services Provided to Other Private Households 6. Receipts from Custom Occasions 7. Welfare Benefits/Allowances 8. Other Income, including Remittances

Expenditure Questionnaire: This questionnaire has 16 sections and includes the following information: 1. Dwelling characteristics 2. Dwelling tenure 3. Mortgages and loans for purchase of dwellings 4. Insurance policies 5. Construction of new dwellings 6. Major home improvements 7. Household operation 8. Transportation 9. Travel – Domestic & Overseas 10. Education, recreation, sport and culture 11. Loans 12. Credit Cards/ Charge accounts 13. Contribution to benefit schemes 14. Medical and health services 15. Customs Occasions 16. Miscellaneous payments 17. Agricultural Assets

Weekly Diary: This questionnaire has 4 sections and includes the following information: 1. Items Bought 2. Consumption of Items Produced by the Household 3. Gifts 4. Winnings from Betting, Raffles and Lotteries

For the household control form, expenditure questionnaire and income questionnaire, a face-to-face interview was conducted with the household to capture the information. For the two diaries, the first diary was left with the household for the first week, for the household to fill out. After the first week, the diary is picked up and the second week diary is dropped off to be filled out and picked up at the end of second week. Interviewers were required to contact each household every two to three days to make sure households were filling out their diaries appropriately.

Response rate

The overall response rate for Palau was 73%, which was a lower response rate than what was expected. The final response status for the 1,063 households selected in the HIES, 760 households fully responded to the survey, 28 partially responded (of which 16 could be included in the analysis) and 275 didn’t respond at all for various reasons.

For details please refer to section 4.2.1 NON-RESPONSE BIAS in the attached report entitled Republic of Palau Household Income and Expenditure Survey 2006.

Sampling error estimates

To determine the impact of sampling error on the survey results, relative standard errors (RSEs) for key estimates were produced.

The estimates for Total Income and Total Expenditure from the HIES can be considered to be very good, from a sampling error perspective. The same can also be said for the Wage and Salary estimate in income and the Food estimate in expenditure, which make up a high proportion of each respective group.

Some of the other estimates should be used with caution, depending on the magnitude of their RSE. Some of these high RSEs are to be expected, due to the expected degree of variability for how households would report for these items. For example, with Business Income (RSE 30.1%), most households would report no business income as no household members undertook this activity, whereas other households would report large business incomes as it’s their main source of income.

Relative Standard Errors for key estimates at the region level can be found in Appendix 2 of the survey report.

Data appraisal

Non-response bias

In was seen that 760 households fully responded to the survey, 28 partially responded (of which 16 could be included in the analysis) and 275 didn’t respond at all for various reasons. Despite the table indicating that the vast majority of nonresponses were “vacant/out-of-scope”, this was unlikely as the dwellings were occupied at the time of the census, only one year prior to the HIES. The assumption was therefore made that these households were more than likely mis-coded during the HIES collection, and would more likely have been a refusal or non-contact.

Abstract

South Africa's first Living Conditions Survey (LCS) was conducted by Statistics South Africa over a period of one year between 13 October 2014 and 25 October 2015. The main aim of this survey is to provide data that will contribute to a better understanding of living conditions and poverty in South Africa for monitoring levels of poverty over time. Data was collected from 27 527 households across the country. The survey used a combination of the diary and recall methods. Households were asked to record their daily acquisitions in diaries provided by Statistics SA for a period of a month. The survey also employed a household questionnaire to collect data on household expenditure, subjective poverty, and income.

Geographic coverage

The survey had national coverage.

Analysis unit

Households and individuals

Universe

The sample for the survey included all domestic households, holiday homes and all households in workers' residences, such as mining hostels and dormitories for workers, but excludes institutions such as hospitals, prisons, old-age homes, student hostels, and dormitories for scholars, boarding houses, hotels, lodges and guesthouses.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Living Conditions Survey 2014-2015 sample was based on the LCS 2008-2009 master sample of 3 080 PSUs. However, there were 40 PSUs with no DU sample, thus the sample of 30 818 DUs was selected from only 3 040 PSUs. Amongst the PSUs with no DU sample, 25 PSUs were non-respondent because 19 PSUs were not captured on the dwelling frame, and 6 PSUs had an insufficient DU count. The remaining 15 PSUs were vacant and therefore out-of-scope. Among the PSUs with a DU sample, 2 974 PSUs were respondent, 50 PSUs were non-respondent and 16 PSUs were out-of-scope. The scope of the Master Sample (MS) is national coverage of all households in South Africa. It was designed to cover all households living in private dwelling units and workers living in workers' quarters in the country.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Living Conditions Survey 2014-2015 used three data collection instruments, namely a household questionnaire, a weekly diary, and the summary questionnaire. The household questionnaire was a booklet of questions administered to respondents during the course of the survey month. The weekly diary was a booklet that was left with the responding household to track all acquisitions made by the household during the survey month. The household (after being trained by the Interviewer) was responsible for recording all their daily acquisitions, as well as information about where they purchased the item and the purpose of the item. A household completed a different diary for each of the four weeks of the survey month. Interviewers then assigned codes for the classification of individual consumption according to purpose (COICOP) to items recorded in the weekly diary, using a code list provided to them.

Data appraisal

Anthropometric data collected during the survey are not included in the dataset.

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

Extracted from the Field Work Instruction Manual NRU HIES 2013 (Attached):

1.2 Objectives

The purpose of the HIES survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in Nauru. This information will be used to guide policy makers in framing socio-economic developmental policies and in initiating financial measures for improving economic conditions of the people. Some more specific outputs from the survey are listed below: a) To obtain expenditure weights and other useful data for the revision of the consumer price index; b) To supplement the data available for use in compiling official estimates of household accounts in the systems of national accounts; c) To supply basic data needed for policy making in connection with social and economic planning; d) To provide data for assessing the impact on household living conditions of existing or proposed economic and social measures, particularly changes in the structure of household expenditures and in household consumption; e) To gather information on poverty lines and incidence of poverty throughout Nauru.

Geographic coverage

National coverage.

Analysis unit

• Households
• Individuals
• Expenditure items

Universe

The scope of the 2012-2013 Household Income Expenditure Survey (HIES) was all occupied households in Nauru. HIES covered all persons who were considered to be usual residents of private dwellings, usual residents who were away for a short amount of time and those away for a for a longer amount of time but still financially linked to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

-SAMPLE DESIGN: The sample was selected to be representative of the whole country of Nauru. Approximately 37 per cent of households were selected across Nauru, although not all responded to the survey - these details are provided in Section 4 of the Methodology Report (provided as External Resources). The sample fractions applied to each of the eight constituencies (plus Location) within Nauru were roughly the same, although they were slightly modified to create even workloads for interviewers. Whilst a 37 per cent sample seems exceptionally large for even a small country like Nauru, due to the large levels of non-response experienced in the 2006 HIES it was considered necessary. At the household level the survey is targeting All members of the Household; however, the main respondent will be the Household Head which could be either the Husband or spouse. If both are unavailable during the survey then any responsible adult will become the respondent. Additional information will also be sought from members of the household who are 15 years with respect to their economic activity and income earning activities.

The selection of the households was based on the 2011 Census of Population and Housing. The process for making the selections was to order the households within each constituency by size (number of persons in the household) and running a systematic skip through each constituency list to achieve the desirable sample size. Such a procedure should ensure each constituency is suitably represented as well as each household size type.

-SAMPLE SELECTION: Yaren: 40 (out of 105); Boe: 49 (out of 51); Aiwo: 81 (out of 84); Buada: 49 (out of 51); Ubenide: 101 (out of 104); Ewa/Anetan: 51 (out of 53); Anabar/Ijuw/Anibane: 51 (out of 53); Meneng: 86 (out of 89); Location (phosphate mining barracks): 116 (out of 120).

Mode of data collection

Face-to-face [f2f]

Research instrument

A Questionnaire consisting of four Modules and a Weekly Diary covering 2 weeks was used for Nauru Household Income and Expenditure Survey (HIES) 2013. Each Module covers distinct but connected portion of the Household.

The Modules are as follows:

• Module 1: Demographic Information (basic demographic information from each member of the household);
• Module 2: Household Expenditure;
• Module 3: Individual Expenditures;
• Module 4: Income
• Diary Week 1: Covering the first 7 Days (1 - 7)
• Diary Week 2: Covering the second 7 Days (8 - 14).

The questionnaires were published in English.

Cleaning operations

Data editing was done using the program: CSPro 5.1.

-DATA CLEANING PHASE 1: MANUAL CLEANING Although a heads-up interactive system was used in the processing of Household Income and Expenditure Survey (HIES) data, data errors are always inevitable. This can be contributed to a multitude of reasons and additional efforts must be made to have accurate data. Data cleaning Phase 1 was done in-country where access to original questionnaires allowed us to correct data by referencing source documents. Errors were identified using an edit specification program which checks keyed data for: • missing information • value specific ranges • data item relations • sequencing errors.

Steps were taken to ensure that missing items were not replaced with assumed values from those involved with data corrections. Data items such as these were addressed in Data Cleaning Phase 2.

-DATA RECODING PHASE 1: SUB_RECORDS OF RELATED DATA ITEMS The objective of this phase was to combine similar data items in the questionnaire into 17 unique databases. The process involved identifying questions and sections in the questionnaire that were related either by subject area, classifications, and transaction types. The advantages of these databases are listed below: • Simplify data corrections - when the data is organised into liked data items, it makes for easier data corrections when implementing sub-routines to check for further data inconsistencies, outliers and code verifications. • Allow for area specific analysis - because the data is organised into similar subject areas, classifications and transaction types, the emerging databases then can be used independently or cross-referenced to other databases. • Simplify the creation of aggregated data - the overall intention of these sub-databases is to create four main databases used in the analysis of HIES data.

-DATA CLEANING PHASE 2: VALIDATION, IMPUTATION AND REMOVAL Before any data could be properly recoded into the main aggregated income and expenditure databases the information needed to be properly coded. After field collection this activity was very time consuming because each transaction needed to be verified for relevance and completeness. Activities in this process included: • deletion of households having inefficient amount of diary transactions or missing large amount of data • data item code validation and correction (e.g. COICOP, ISIC, and ISCO) • imputation of missing or invalid data items • deletion of transactions with insufficient data items.

-DATA RECODING PHASE 2: OUTPUT The final phase was to recode the sub-databases into the four main databases (Income, Expenditure, Person and House). The activities in this phase included quality control measures that checked for consistencies and balancing between: • categories, reference periods and transaction types • income and expenditure • sub-databases and aggregated databases.

Response rate

The HIES 2012/2013 survey response rates were a significant improvement on those achieved for the 2006 HIES, reaching levels more in line with what is considered acceptable. The national response rate of the survey was 74% (460 households responded out of the 624 that were selected).

Yaren: 55%; Boe: 76%; Aiwo: 72%; Buada: 88%; Ubenide: 68%; Ewa/Anetan: 92%; Anabar/Ijuw/Anibane: 77%; Meneng: 93%; Location (phosphate mining barracks): 56%.

Sampling error estimates

Many factors contribute to the magnitude of the non-sampling errors associated with survey results. Unfortunately, unlike the sampling error, it is difficult to measure the extent of the impact. In order to better understand the reason behind this, one only needs to look at the different types of non-sampling errors to appreciate why it is difficult to measure their impact. Some of the more significant non-sampling errors which are discussed in the Methodology Report (provided as External Resource): • Non response bias • Reporting errors • Data entry errors • Changing economy.

Abstract

The purpose of the HIES survey is to obtain information on the income, consumption pattern, incidence of poverty, and saving propensities for different groups of people in FSM. This information will be used to guide policy makers in framing socio-economic developmental policies and in initiating financial measures for improving economic conditions of the people. The 2005 FSM HIES asked income of all persons 15 years and over. It referred to income received during the calendar year 2004, and includes both cash and in-kind income. The survey has five primary objectives, namely to:

1) Rebase the FSM Consumer Price Index (CPI); 2) Provide data on the distribution of income and expenditures throughout the FSM; 3) Provide data for national accounts, particularly regarding income from home production activities and the consumption of goods and services derived form home production activities; 4) Provide nutritional information and food consumption patterns for the FSM families; and 5) Provide data for hardship study.

Geographic coverage

Entire Country

Four states of the FSM: Yap, Chuuk, Pohnpei, and Kosrae

Analysis unit

• Households
• Individuals
• Expenditure items

Universe

The survey universe covered all persons living in their place of usual residence at the time of the survey. Income data were collected from persons aged 15 years and over while expenditure data were obtained from all household members at a household level. Persons living in institutions, such as school dormitories, hospital wards, hostels, prisons, as well as those whose usual residence were somewhere else were excluded from the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2005 FSM Household Income and Expenditure Survey (HIES) used a sampling frame based on updated information on Enumeration Districts (ED) and household listing from the 2000 FSM Census. Based on this sampling frame, the four states of FSM were then classified as the domains of the survey. Each of the states was further divided into 3 strata, except for Kosrae which was not divided at all because it doesn't possess any outer islands and it has relatively good access to goods and services. The entire island was therefore classified under stratum 1. Each stratum was defined as follows:

1) State center and immediate surrounding areas:
- High 'living standard' and has immediate access to goods and services.

2) Areas surrounding state center (rest of main island):
- Medium 'living standard' and sometime limited access to goods and services

3) Outer islands:
- Low 'living standard' and rare access to goods and services.

Within each stratum, the HIES used a two-stage stratified sampling approach from which the sample was selected independently. First, enumeration districts (EDs) were drawn from each stratum using Proportion Probability to Size (PPS) sampling. Thus, the larger the ED size, the higher its probability of selection. About 69 EDs out of a total of 373 EDs were selected nationwide for the survey. Generally, one enumerator is assigned to each ED. Second, 20 households were systematically selected from an updated household listing for each of the selected EDs using a random start to come up with a total sample size of 1,380 households, or roughly 8.4 percent of all households in the state. Although it offered a fairly good representation of the total households in the nation, the final sample size showed a reduction of nearly 180 households from the 1,560 households, or 10 percent, initially selected for the survey.

Detailed information on the changes made to the sample size can be found in the next section under "Deviations from Sample Design."

Sampling deviation

The original plan to sample 1,560 households, or about 9.5 percent of all households in the nation was eventually reduced to 1,380 households, or about 8.4 percent of all households. The reduction of the sample size was due to fuel unavailability for transportation and uncertainty of field trip schedules to some of the selected outer islands. Dropping some of these islands from the sample was not expected to impact significantly on the accuracy of the survey results because independent weighting took place within each stratum, where islands were considered to be sufficiently homogenous.

Mode of data collection

Other [oth]

Research instrument

Questionaires and forms used for the 2005 FSM HIES consisted of 1) HIES Questionnaire and 2) Weekly Diaries. The HIES Questionnaire were provided to enumerators and should be filled out during the first visit to the household. Its main objective was to collect housing information, basic demographic information about members of the household, and general household expenditures over the previous year. On the other hand, the weekly diaries, was an attempt to record household expenditure on a daily basis over the course of a 2 week period. Both the HIES questionnaire and the weekly diary were developed and modeled after similar forms from the 1998 FSM HIES Survey and the 2004 Palau HIES Survey. Dr. Micheal Levin from the US Census Bureau, International Program Center (IPC), Ms. Brihmer Johnson of the FSM Division of Statistics and Mr. Glenn McKinlay, statistics advisor to FSM Division of Statistics, provided crucial inputs to the overall design of these forms. All questionnaires and diaries used during the HIES were printed in English so it was extremely important that field interviewers understand the instuctions and questions contained within. Testing of the questionnaire were carried out by FSM Division of Statistics staffs who conducted "real" interviews with certain households in their neighborhood as well as having their own household be interviewed by a different office staff. Specific sections for both the HIES questionnaire and the weekly diaries are outlined below:

I. HIES Questionnaire

1) General Household characteristics 2 ) Individual Person Characteristics 3) General Expenditure Listings - 12 Months Recall Period

II. 2 Week Daily Diaries

1) Daily Expenditure Diary - Day1 (Mon) thru Day7 (Sun) 2) Home Produced Items 3) Gifts Given Away 4) Gifts Received 5) Unusual Expenses for Special Events

Cleaning operations

Data editing of the 2005 FSM HIES data occurred over several instances during the data processing phase of the project and afterwards prior to putting together the final report. After a two weeks office review and call backs right after the enumeration phase, the initial phase of data editing took place on July 18, 2005 when the data processing phase of the survey commenced. Training for editing and coding took place on the same day along with the signing of contracts for 10 office clerks recruited to carry out this phase of the survey. As part of their contract, these individuals were also hired to key in the data at a later time. One of their primary responsibily was to match geographic ids for questionnaire with corresponding diaries and ensure consistencies and valid entries accordingly. No computer consistency edit checks were run against the data during the keying/verification process since the programs for these processes were not available at the time. All data quality checks and edits were done at the US Bureau of Census. Further edits were applied to the data during the data analysis and report writing process.

There were five types of checks performed: Structural check, Verification check, Consistency check, Macro Editing check, Data Quality assessment. Edit lists were also produced for health module, income and expenditure questionnaire which needed to be checked against the questionnaires. On the edit list, corrections of errors were made by crossing out incorrect or missing values and entering the correct values in red. Missing amounts that were also missing on the questionnaire will need to be estimated using estimates from questionnaires in the same Enumeration District (ED) batch. For the diaries, the batch files were concatenated for each state and exported to tab delimited files. These files were imported into Excel and the unit price for each item was calculated using quantities and weights where possible. Records for each item were then filtered out and check for outlier unit price values (both large and small values as well as missing values). Values for missing amounts were imputed from estimated using average prices from the items within the same ED.

The office operations manual used for editing and coding the questionnaires and diaries is provided under "Technical Documents/Data Processing Documents/Office Editing & Coding."

Response rate

Original Sample Size: 1,560 Households Original Sampling fraction 9.5%

Final Sample Size: 1,380 Households Final Sampling fraction 8.4%

The response rate for the final sample size of 1,380 households is 100 percent. The majority of households originally selected for the survey did respond to the survey. Households which have moved to other unselected areas or elsewhere and those who refused to respond were replaced with nearby households that were willing to participate in the survey.

Sampling error estimates

No sampling error analysis of the survey was calculated.

Data appraisal

The questionnaire design of the 2005 HIES vary from that of the 1998 HIES rendering comparison of the data to the 2005 HIES limited. However, when the data permits, comparisons were made.

Abstract

The Income and Expenditure Survey is conducted every five years in South Africa.The main purpose of the survey is to determine the average expenditure patterns of households in different areas of the country. This survey forms the basis for the determination of the "basket" of consumer goods and services used for the calculation of the Consumer Price Index.

Geographic coverage

The survey had national coverage.

Analysis unit

Households

Universe

The survey covered private dwellings, workers' hostels, residential hotels, and nurses' and doctors' quarters, but excluded hospitals and clinics, hotels and guest houses, prisons, schools and student hostels and old-age homes.

Kind of data

Sample survey data

Sampling procedure

The sampling frame for the IES 2010/2011 was obtained from Statistics South Africa’s Master Sample (MS) based on the 2001 Population Census enumeration areas (EAs). The scope of the Master Sample (MS) is national coverage of all households in South Africa and the target population consists of all qualifying persons and households in the country. In summary, it has been designed to cover all households living in private dwelling units and workers living in workers’ quarters in the country. The IES 2010/2011 sample is based on an extended sample of 3 254 PSUs, which consists of the 3 080 PSUs in the Master Sample and a supplement of 174 urban PSUs selected from the PSU frame. The IES sample file contained 31 419 sampled dwelling units (DUs). The 31 419 sampled DUs consist of 31 007 DUs sampled from the 3 080 design PSUs in the Master Sample and 412 DUs from the supplemented 174 urban PSUs. In the case of multiple households at a sampled DU, all households in the DU were included.

Mode of data collection

Face-to-face [f2f]

Research instrument

There were four modules in the household questionnaire with eighteen subsections. The first module collected general household data and data on household members. Modules 2 to 4 collected data on consumption expenditure, household finances and income. The diary was a booklet in which the respondent recorded weekly expenditure data. A household completed a different diary for each week of the survey period.

Response rate

From the 31 419 dwelling units sampled across South Africa, 33 420 households were identified. Out of these, there was a sample realisation of 27 665 (82,8%) households, with the remaining 5 755 (17,2%) households being classified as out of scope.

Data appraisal

All continous household income and expenditure data collected during the Income and Expenditure Survey 2010-2011 are contained in the Total IES data file. The household data file contains only categorical variables. For example, expenditure data on electricity collected with the questions in sub-section 5.7 of the questionnaire will be found in the "Total_IES" data file under the COICOP codes 04511010, 04511110, 04404500. This is explained under "Data Organisation" on page 6 of the metadata record for the IES 2010 2011, which documents how the data files are organised and the variables in each data file.

The STAMINA study examined the nutritional risks of low-income peri-urban mothers, infants and young children, and households in Peru during the COVID-19 pandemic. The study was designed to capture information through three, repeated cross-sectional surveys at approximately 6 month intervals over an 18 month period, starting in December 2020. The surveys were carried out by telephone in November-December 2020, July-August 2021 and in February-April 2022. The third survey took place over a longer period to allow for a household visit after the telephone interview.The study areas were Manchay (Lima) and Huánuco district in the Andean highlands (~ 1900m above sea level).In each study area, we purposively selected the principal health centre and one subsidiary health centre. Peri-urban communities under the jurisdiction of these health centres were then selected to participate. Systematic random sampling was employed with quotas for IYC age (6-11, 12-17 and 18-23 months) to recruit a target sample size of 250 mother-infant pairs for each survey. .Data collected included: household socio-demographic characteristics; infant and young child feeding practices (IYCF), child and maternal qualitative 24-hour dietary recalls/7 day food frequency questionnaires, household food insecurity experience measured using the validated Food Insecurity Experience Scale (FIES) survey module (Cafiero, Viviani, & Nord, 2018), and maternal mental health.In addition, questions that assessed the impact of COVID-19 on households including changes in employment status, adaptations to finance, sources of financial support, household food insecurity experience as well as access to, and uptake of, well-child clinics and vaccination health services were included.This folder includes the dataset and dictionary of variables for survey 1 (English only).The survey questionnaire for survey 1 is available at 10.17028/rd.lboro.16825507.

Abstract

The Household Income and Expenditure Survey is a survey collecting data on income, consumption and expenditure patterns of households, in accordance with methodological principles of statistical enquiries, which are linked to demographic and socio-economic characteristics of households. A Household Income and expenditure Survey is the sole source of information on expenditure, consumption and income patterns of households, which is used to calculate poverty and income distribution indicators. It also serves as a statistical infrastructure for the compilation of the national basket of goods used to measure changes in price levels. Furthermore, it is used for updating of the national accounts.

The main objective of the NHIES 2009/2010 is to comprehensively describe the levels of living of Namibians using actual patterns of consumption and income, as well as a range of other socio-economic indicators based on collected data. This survey was designed to inform policy making at the international, national and regional levels within the context of the Fourth National Development Plan, in support of monitoring and evaluation of Vision 2030 and the Millennium Development Goals. The NHIES was designed to provide policy decision making with reliable estimates at regional levels as well as to meet rural - urban disaggregation requirements.

Geographic coverage

National Coverage

Analysis unit

Individuals and Households

Universe

Every week of the four weeks period of a survey round all persons in the household were asked if they spent at least 4 nights of the week in the household. Any person who spent at least 4 nights in the household was taken as having spent the whole week in the household. To qualify as a household member a person must have stayed in the household for at least two weeks out of four weeks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The targeted population of NHIES 2009/2010 was the private households of Namibia. The population living in institutions, such as hospitals, hostels, police barracks and prisons were not covered in the survey. However, private households residing within institutional settings were covered. The sample design for the survey was a stratified two-stage probability sample, where the first stage units were geographical areas designated as the Primary Sampling Units (PSUs) and the second stage units were the households. The PSUs were based on the 2001 Census EAs and the list of PSUs serves as the national sample frame. The urban part of the sample frame was updated to include the changes that take place due to rural to urban migration and the new developments in housing. The sample frame is stratified first by region followed by urban and rural areas within region. In urban areas further stratification is carried out by level of living which is based on geographic location and housing characteristics. The first stage units were selected from the sampling frame of PSUs and the second stage units were selected from a current list of households within each selected PSU, which was compiled just before the interviews.

PSUs were selected using probability proportional to size sampling coupled with the systematic sampling procedure where the size measure was the number of households within the PSU in the 2001 Population and Housing Census. The households were selected from the current list of households using systematic sampling procedure.

The sample size was designed to achieve reliable estimates at the region level and for urban and rural areas within each region. However the actual sample sizes in urban or rural areas within some of the regions may not satisfy the expected precision levels for certain characteristics. The final sample consists of 10 660 households in 533 PSUs. The selected PSUs were randomly allocated to the 13 survey rounds.

Sampling deviation

All the expected sample of 533 PSUs was covered. However a number of originally selected PSUs had to be substituted by new ones due to the following reasons.

Urban areas: Movement of people for resettlement in informal settlement areas from one place to another caused a selected PSU to be empty of households.

Rural areas: In addition to Caprivi region (where one constituency is generally flooded every year) Ohangwena and Oshana regions were badly affected from an unusual flood situation. Although this situation was generally addressed by interchanging the PSUs betweensurvey rounds still some PSUs were under water close to the end of the survey period. There were five empty PSUs in the urban areas of Hardap (1), Karas (3) and Omaheke (1) regions. Since these PSUs were found in the low strata within the urban areas of the relevant regions the substituting PSUs were selected from the same strata. The PSUs under water were also five in rural areas of Caprivi (1), Ohangwena (2) and Oshana (2) regions. Wherever possible the substituting PSUs were selected from the same constituency where the original PSU was selected. If not, the selection was carried out from the rural stratum of the particular region. One sampled PSU in urban area of Khomas region (Windhoek city) had grown so large that it had to be split into 7 PSUs. This was incorporated into the geographical information system (GIS) and one PSU out of the seven was selected for the survey. In one PSU in Erongo region only fourteen households were listed and one in Omusati region listed only eleven households. All these households were interviewed and no additional selection was done to cover for the loss in sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The instruments for data collection were as in the previous survey the questionnaires and manuals. Form I questionnaire collected demographic and socio-economic information of household members, such as: sex, age, education, employment status among others. It also collected information on household possessions like animals, land, housing, household goods, utilities, household income and expenditure, etc.

Form II or the Daily Record Book is a diary for recording daily household transactions. A book was administered to each sample household each week for four consecutive weeks (survey round). Households were asked to record transactions, item by item, for all expenditures and receipts, including incomes and gifts received or given out. Own produce items were also recorded. Prices of items from different outlets were also collected in both rural and urban areas. The price collection was needed to supplement information from areas where price collection for consumer price indices (CPI) does not currently take place.

Cleaning operations

The questionnaires received from the regions were registered and counterchecked at the survey head office. The data processing team consisted of Systems administrator, IT technician, Programmers, Statisticians and Data typists.

Data capturing

The data capturing process was undertakenin the following ways: Form 1 was scanned, interpreted and verified using the “Scan”, “Interpret” & “Verify” modules of the Eyes & Hands software respectively. Some basic checks were carried out to ensure that each PSU was valid and every household was unique. Invalid characters were removed. The scanned and verified data was converted into text files using the “Transfer” module of the Eyes & Hands. Finally, the data was transferred to a SQL database for further processing, using the “TranScan” application. The Daily Record Books (DRB or form 2) were manually entered after the scanned data had been transferred to the SQL database. The reason was to ensure that all DRBs were linked to the correct Form 1, i.e. each household’s Form 1 was linked to the corresponding Daily Record Book. In total, 10 645 questionnaires (Form 1), comprising around 500 questions each, were scanned and close to one million transactions from the Form 2 (DRBs) were manually captured.

Response rate

Household response rate: Total number of responding households and non-responding households and the reason for non-response are shown below. Non-contacts and incomplete forms, which were rejected due to a lot of missing data in the questionnaire, at 3.4 and 4.0 percent, respectively, formed the largest part of non-response. At the regional level Erongo, Khomas, and Kunene reported the lowest response rate and Caprivi and Kavango the highest. See page 17 of the report for a detailed breakdown of response rates by region.

Data appraisal

To be able to compare with the previous survey in 2003/2004 and to follow up the development of the country, methodology and definitions were kept the same. Comparisons between the surveys can be found in the different chapters in this report. Experiences from the previous survey gave valuable input to this one and the data collection was improved to avoid earlier experienced errors. Also, some additional questions in the questionnaire helped to confirm the accuracy of reported data. During the data cleaning process it turned out, that some households had difficulty to separate their household consumption from their business consumption when recording their daily transactions in DRB. This was in particular applicable for the guest farms, the number of which has shown a big increase during the past five years. All households with extreme high consumption were examined manually and business transactions were recorded and separated from private consumption.