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

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 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

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.

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 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

Analysis unit

• Household
• Person
• Expenditure Commodity

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] for questionnaires, self-enumeration for the diaries

Research instrument

The survey schedules adopted for the 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.

Cleaning operations

There were 3 phases to the editing process for the 2006 Nauru HIES which included: 1. Data Verification operations 2. Data Editing operations 3. Data Auditing operations

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.

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 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 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 information will be forgotten.

c) Intentional under-reporting for some items: For whatever reasons, a household may still participate in a survey but not be willing to provide accurate responses for some questions. Examples for a HIES include people not fully disclosing their total income, and intentionally under-reporting expenditures on items such as alcohol and tobacco.

d) Accidental under-reporting in the household diaries: Although the two diaries are left with the household for a period of two weeks, it is easy for the household to forget to enter all expenditures throughout this period - this problem most likely increases as the two

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

This data collection contains information gathered in the Survey of Income and Education (SIE) conducted in April-July 1976 by the Census Bureau for the United States Department of Health, Education, and Welfare (HEW). Although national estimates of the number of children in poverty were available each year from the Census Bureau's Current Population Survey (CPS), those estimates were not statistically reliable on a state-by-state basis. In enacting the Educational Amendments of 1974, Congress mandated that HEW conduct a survey to obtain reliable state-by-state data on the numbers of school-age children in local areas with family incomes below the federal poverty level. This was the statistic that determined the amount of grant a local educational agency was entitled to under Title 1, Elementary and Secondary Education Act of 1965. (Such funds were distributed by HEW's Office of Education.) The SIE was the survey created to fulfill that mandate. Its questions include those used in the Current Population Survey regarding current employment, past work experience, and income. Additional questions covering school enrollment, disability, health insurance, bilingualism, food stamp recipiency, assets, and housing costs enabled the study of the poverty concept and of program effectiveness in reaching target groups. Basic household information also was recorded, including tenure of unit (a determination of whether the occupants of the living quarters owned, rented, or occupied the unit without rent), type of unit, household language, and for each member of the household: age, sex, race, ethnicity, marital history, and education.

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.

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, 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.

Sampling deviation

Given the sample design, these weights will vary to some extent for the over-sampled governorates compared with the others. It is also important to calculate measures of sampling variability for key survey estimates.

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).

The Household Market and Nonmarket Activities (HUS) project started as a joint research project between the Industrial Institute for Economic and Social Research (IUI) and Göteborg University in 1980. The ambition was to build a consistent longitudinal micro data base on the use of time, money and public services of households. The first main survey was carried out in 1984. In addition to a contact interview with the selected individuals, all designated individuals participated in a personal interview and two telephone interviews. All respondents were asked about their family background, education, marital status, labor market experience, and employment. In addition, questions about the household were asked of the head of household, concerning family composition, child care, health status, housing, possession of vacation homes, cars, boats and other consumption durables. At the end of the personal interview the household head had to fill out a questionnaire including questions about financing of current home, construction costs for building a house, house value and loans, imputation of property values and loans, additions/renovations 1983, maintenance and repairs, leasing, sale of previous home, assets and liabilities, and non-taxable benefits. All the respondents had to fill out a questionnaire including questions about tax-return information 1983, employment income, and taxes and support payments. Two telephone interviews were used primarily to collect data on the household´s time use and consumption expenditures. The 1986 HUS-survey included both a follow-up of the 1984 sample (panel study) and a supplementary sample. The 1986 sample included 1) all respondents participating in the 1984 survey, 2) the household heads, partners and third persons who should have participated in 1984 but did not (1984 nonresponse), 3) those individuals who started living together after the 1984 interview with an selected individual who participated or was supposed to participate in 1984, 4) members of the 1984 household born in 1966 or 1967. If entering a new household, for example because of leaving their parental home, the household head and his/her partner were also interviewed. Respondents participating in the 1984 survey were interviewed by telephone in 1986. Questions dealt with changes in family composition, housing, employment, wages and child care, and it was not only recorded whether a change had occurred, and what sort of change, but also when it occurred. The respondents also received a questionnaire by mail with questions mainly concerning income and assets. Respondents not participating in the earlier survey were interviewed in person and were asked approximately the same questions as in the 1984 personal interview. The 1988 HUS-survey was considerably smaller than the previous ones. It was addressed exclusively to participants in the 1986 survey, and consisted of a self-enumerated questionnaire with a nonrespondent follow-up by telephone. The questions dealt with changes in housing conditions, employment and household composition. The questionnaire also contained some questions on household income. In many respect the 1991 HUS-survey replicated the 1988 survey. The questions were basically the same in content and range, and the survey was conducted as a self-enamurated questionnaire sent out by mail. This time, however, in contrast to the 1988 survey, an attempt was made to include in the survey the new household members who had moved into sample households since 1986, as well as young people who turned 18 after the 1986 survey. Earlier respondents received a questionnaire by mail containing questions about their home, their primary occupation and weekly work hours since May 1988 (event-history data), earnings in 1989, 1990 and 1991, household composition and any changes in it that might have occurred since 1988, child care and some questions on income. New respondents were also asked about their education and labor-market experience. With respect to its design and question wording, the 1993 survey is a new version of the 1986 survey. The survey is made up of four parts: 1) the panel survey, which was addressed mainly to respondents in the 1991 survey, with certain additions; 2) the so-called supplementary survey, which focused on a new random sample of individuals; 3) the so-called nonresponse survey, which encompassed respondents who had participated in at least one of the earlier surveys but had since dropped out; 4) the time-use survey, which included the same sample of respondents as those in the panel and supplementary surveys. Individuals in the nonresponse group were not included in the time-use survey. Most of the questions in the first three surveys were the same, but certain questions sequences were targeted to the respondents in a specific survey. Thus certain retrospective questions were asked of the nonresponse group, while specific questions on social background, labor market experience etc. were addressed to new respondents. In the case of respondents who had already participated in the panel, a combined contact and main interview was conducted by telephone, after which a self-enumerated questionnaire was sent out to each respondent by mail. The panel sample also included young people in panel households who were born in 1973 or 1974 as well as certain new household members who had not previously been interviewed. These individuals, like new respondents, were not interviewed by telephone until they had been interviewed personally. Thus technically they were treated in the same manner as individuals in the supplementary sample. The new supplementary sample was first contacted by telephone and then given a fairly lengthy personal interview, at the conclusion of which each respondent was asked to fill out a written questionnaire. In this respect the survey design for the nonresponse sample was the same as for the supplementary sample. The nonresponse sample also included young people born in 1973 or 1974 as well as certain new household members. The time-use interviews were conducted by telephone. For each respondent two days were chosen at random from the period from February 15, 1993 to February 14, 1994 and the respondents were interviewed about their time use during those two days. If possible, the time-use interviews were preceded by the other parts of the survey, but this was not always feasible. In each household the household head and spouse/partner were interviewed, as well as an additional person in certain households. Questions regarding the household as a whole were asked of only one person in the household, preferably the household head. As in earlier surveys, data from the interviews was subsequently supplemented by registry data, but only for those respondents who had given their express consent. There is registry information for 75-80 percent of the sample. The telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; and cars and boats. The questionnaire was divided into twelve sections: sale of previous home; acquisition of current home; construction costs for building a home; house value and loans; repairs; insurance; home-related expenses; sale of previous home; assets; household income; taxes; and respondent income 1992. The 1996 telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; cars and boats; and environment. The questionnaire was divided into twelve sections: sale of previous home; acquisition of current home; construction costs for building a home; house value and loans; repairs; insurance; home-related expenses; sale of previous home; assets; household income; taxes; and respondent income 1995. The 1998 telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; cars and boats; and municipal service. The questionnaire was divided into nine sections: sale of previous home; house value and loans; insurance; home-related expenses; assets; household income; inheritances and gifts; black-market work; and respondent income 1997.

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 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.

This is a longitudinal survey designed to provide detailed information on the economic situation of households and persons in the United States. These data examine the distribution of income, wealth, and poverty in American society and gauge the effects of federal and state programs on the well-being of families and individuals. There are three basic elements contained in the survey. The first is a control card that records basic social and demographic characteristics for each person in a household, as well as changes in such characteristics over the course of the interviewing period. The second element is the core portion of the questionnaire, with questions repeated at each interview on labor force activity, types and amounts of income, participation in various cash and noncash benefit programs, attendance in postsecondary schools, private health insurance coverage, public or subsidized rental housing, low-income energy assistance, and school breakfast and lunch participation. The third element consists of topical modules, which are a series of supplemental questions asked during selected household visits. Topical modules include some core data to help link individuals to the core files. Topical module data for the 1992 Panel cover the following topics: Topical Module 1 -- welfare and other aid recipiency and employment, Topical Module 2 -- work disability, education and training, marital status, migration, and fertility histories, Topical Module 3 -- extended measures of well-being, including consumer durables, living conditions, and basic needs, Topical Module 4 -- assets and liabilities, retirement expectations and pension plan coverage, real estate, property, and vehicles, Topical Module 5 -- school enrollment and financing, Topical Module 6 -- work schedules, child care, support for nonhousehold members, functional limitations and disabilities, utilization of health care services, and home-based self-employment and size of firm, Topical Module 7 -- selected financial assets, medical expenses and work disability, real estate, shelter costs, dependent care, and vehicles, Topical Module 8 -- school enrollment and financing, Topical Module 9 -- work schedule, child care, child support agreements, child support, support for nonhousehold members, functional limitations and disability, utilization of health care, functional limitations and disability of children, health status and utilization of health care services, and utilization of health care services for children. Parts 26 and 27 are the Wave 5 and Wave 8 Topical Module Microdata Research Files obtained from the Census Bureau. These two topical module files include data on annual income, retirement accounts and taxes, and school enrollment and financing. These topical module files have not been edited nor imputed, although they have been topcoded or bottomcoded and recoded if necessary by the Census Bureau to avoid disclosure of individual respondents' identities. (Source: downloaded from ICPSR 7/13/10)

Comparable household income measures are crucial for most social science analyses of cross-national public opinion survey data. However, income questions in many cross-national surveys suffer from comparability and interpretability limitations that have not been adequately addressed by the existing literature. In this article, we examine the income measure in one major survey, the World Values Survey (WVS), arguing that a variety of problems arise when drawing inferences - descriptive or causal, individual or aggregate - using the standard 10-category measure. We then propose and implement a number of corrections to these potential biases and present a series of diagnostics that confirm the importance of our proposed corrections. We conclude by documenting some of the same challenges in the income measures used in other cross-national surveys. The accompanying data set can be merged with the WVS to make better use of the income measure.

Abstract

The Survey on Income and Living Conditions, introduced as part of the European Union harmonisation efforts, aims to produce data on income distribution, relative poverty by income, living conditions and social exclusion comparable with European Union member states. The study which uses a panel survey method is repeated every year and monitors sample of household members for four years. Every year, the study attempts to obtain two datasets: cross-sectional and panel.

The Income and Living Conditions Survey has been conducted to provide annual and regular cross-sectional data to answer questions such as:

• How equally is the income in the country distributed and how has it changed as compared to the previous years?
• How many poor people are there in the country and how do they distribute across regions? How has this situation changed as compared to the previous years?
• Who is poor? Has there been a change over time?
• How has this gap between the poor and the rich evolved over time?
• What kind of a change or transition occurs in the incomes of individuals and households? How does the direction of this change depends on characteristics and circumstances, does it decline or grow?
• How is the income distributed across sectors, types of income and household characteristics?
• How do people's living conditions change or improve over time?
• The study also aims to provide panel data to calculate indicators such as persistent income poverty and to measure net changes over time.

The longitudinal database 2008-2011 is documented here.

Geographic coverage

All settlements within the borders of the Republic of Turkey have been included.

Universe

All household members living in households within the borders of the Republic of Turkey. However, the study excludes the population defined as institutional population living in hospices, elderly homes, prisons, military barracks, private hospitals and in childcare centres. Migrant population has also been excluded due to practical challenges.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling method: Stratified, multi-stage, clustered sampling.

Sampling unit: Household.

Sampling framework: Sampling framework has been derived from two sources:

1. For the settlements with municipal status; General Building Census conducted in 2000 by TurkStat and Numbering Study (conducted in 2000) Form Population 1 data have been used.
2. For the settlements without municipal status (Villages); data of General Population Census conducted in 2000 have been used to select the blocks which constituted the sampling unit of the first stage.

Selection of sample households: for the purposes of the study which used a two-staged sampling design; entire Turkey has been divided into blocks which covered 100 households each.

• At the first stage, blocks were selected as the first stage sampling unit
• At the second stage, households were selected from among the previously selected blocks as the final sampling unit. Prior to the selection of sample households, addresses at the blocks were updated through an "address screening study"

Sample size: Annual sampling size is 13,414 households in respect of the estimation, objectives and targeted variables of the study and in consideration of the attritions in the sample.

Substitution principle: Substitution has not been used as the sample size had been calculated by taking account of non-response.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

• Household registry form: The form filled at the beginning of the survey provides brief information on access to the address of the household, condition of the household and of the survey. Moreover, following the first field application, modalities are identified for filling in the monitoring forms if the households included in the panel survey move home.

• Personal registry form: These forms aim to identify basic demographic characteristics of the household members, changes that occur in the status of household membership of the individuals included in the panel survey, reasons for their leaving the household, the date of their departure etc. as well as individuals who join the household.

• Household and personal follow-up form: There is need for following up the households which have moved home and the sample individuals who have left the household to join or found another one. Household and personal follow-up forms are used to identify their new addresses and access their contact information.

• Household questionnaire: These forms attempt to collect information on the type of the occupied dwelling, status of ownership, information relating to the dwelling (number of rooms, the space actually used, heating system, dwelling facilities, goods owned etc), problems of the dwelling of the neighbourhood, status of indebtedness, rent payments, expenditures for the dwelling, the extent to which households are able to meet their general economic and basic needs and incomes earned at household level.

• Personal questionnaire: These forms attempt to collect information on education, health, employment and marital status of the household members aged 15 and over, as well as the dates of employment and incomes earned during the reference year.

Abstract

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

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

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

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

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

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

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

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

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

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

Geographic coverage

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

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

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

Sampling deviation

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

Mode of data collection

Face-to-face [f2f]

Research instrument

A

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

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.

Income data has been used extensively by researchers to better understand the economic well-being of Canadians. To meet the needs of these users, Statistics Canada has produced numerous cross-sectional public use microdata files (PUMFs). PUMFs for the Survey of Consumer Finance (SCF) were released until reference year 1997. With the end of the SCF, PUMFs for the Survey of Labour and Income Dynamics (SLID) were produced for reference years 1996 to 2011. The Canadian Income Survey (CIS) was introduced for the 2012 reference year. The CIS is a cross-sectional survey developed to provide information on the income and income sources of Canadians, with their individual and household characteristics. It is a short questionnaire which is asked of a sub-sample of respondents to the Labour Force Survey (LFS), gathering information on labour market activity, school attendance, support payments, child care expenses, inter-household transfers, personal income, food security and characteristics and costs of housing. The CIS content is supplemented with information from the LFS on individual and household characteristics (e.g. age, educational attainment, main job characteristics, and family type) and with tax data for income and income sources (Statistics Canada, 2021). The CIS PUMF is an anonymized microdata file that contains only a subset of variables that are available on the CIS master file. Various techniques have been employed to protect CIS respondents against the risk of disclosure.

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%